Adding of custom Docker file and updating pip tools before installing

Dockerfile

@@ -0,0 +1,44 @@
+# Use a lightweight Python image with version 3.9
+FROM python:3.9-slim
+
+# Create a non-root user with UID 1000 as required by Hugging Face Spaces
+RUN useradd -m -u 1000 user
+
+# Set environment variables
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    PATH="/home/user/.local/bin:$PATH"
+
+# Install required system packages (including wget)
+RUN apt-get update && apt-get install -y wget && rm -rf /var/lib/apt/lists/*
+
+RUN apt-get update && apt-get install -y git
+RUN git config --global user.email "Mojmir@users.noreply.huggingface.co"
+# Switch to non-root user
+USER user
+
+# Set the working directory (root, since you don’t have an /app folder)
+WORKDIR /home/user
+
+# Copy requirements.txt before copying other files to utilize Docker cache
+COPY --chown=user requirements.txt .
+
+# pip update install tools
+run pip install -U pip setuptools wheel
+# Install required dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the project files to the container
+COPY --chown=user . .
+
+# RUN wget https://github.com/gitpod-io/openvscode-server/releases/download/openvscode-server-v1.86.2/openvscode-server-v1.86.2-linux-x64.tar.gz -O /tmp/openvscode-server.tar.gz && \
+#     tar -xzf /tmp/openvscode-server.tar.gz -C /opt && \
+#     rm /tmp/openvscode-server.tar.gz && \
+#     mv /opt/openvscode-server-v1.86.2-linux-x64 /opt/openvscode-server && \
+#     chown -R 1000:1000 /opt/openvscode-server
+
+# Expose the port Gradio runs on (7860)
+# EXPOSE 7860
+
+# Command to run the Gradio app
+CMD ["python", "app.py"]

app.py

@@ -4,6 +4,8 @@ import torch.nn as nn
 from torchvision import transforms
 from PIL import Image
 import time
+
+from concrete.fhe import Configuration
 from concrete.ml.torch.compile import compile_torch_model
 
 from custom_resnet import resnet18_custom  # Assuming custom_resnet.py is in the same directory
@@ -21,7 +23,6 @@ def load_model(model_path, device):
     model.eval()  # Set model to evaluation mode
     return model
 
-from concrete.fhe import Configuration
 
 def load_secure_model(model):
     print("Compiling secure model...")

requirements.txt

@@ -2,4 +2,4 @@ gradio
 torch
 torchvision
 Pillow
-concrete-ml
+concrete-ml==1.6.1