Update Dockerfile

Dockerfile

@@ -1,27 +1,29 @@
-# Use an appropriate base image (you can adjust this as per your requirements)
-FROM python:3.10
+# Use NVIDIA CUDA base image with Ubuntu 22.04, CUDA 12.2, and cuDNN 8
+FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
 
-# Switch to root user
-USER root
+# Set Python to run in unbuffered mode for better logging
+ENV PYTHONUNBUFFERED=1
 
-# Install system dependencies
-RUN chmod 1777 /tmp \
-    && apt update -q && apt install -y ca-certificates wget libgl1 \
-    && wget -qO /tmp/cuda-keyring.deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb \
-    && dpkg -i /tmp/cuda-keyring.deb && apt update -q \
-    && apt install -y --no-install-recommends libcudnn8 libcublas-12-2
+# Install Python 3.10, pip, and system dependencies in a single layer
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3.10 \
+    python3-pip \
+    libgl1 \
+    && ln -s /usr/bin/python3.10 /usr/bin/python \
+    && rm -rf /var/lib/apt/lists/*
 
-# Copy the requirements.txt file into the container
-COPY requirements.txt requirements.txt
-
-# Install Python dependencies from requirements.txt
+# Copy and install Python requirements
+COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Copy the application code
-COPY main.py main.py
-COPY utils.py utils.py
-# Run Python script to check for errors before starting FastAPI
-RUN python main.py
+# Copy application code
+COPY main.py utils.py ./
+
+# Verify the application can be imported without errors
+RUN python -c "from main import app"
+
+# Expose the application port
+EXPOSE 7860
 
-# Start FastAPI server
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]
+# Start the FastAPI server
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]