Update Dockerfile

Dockerfile

@@ -1,23 +1,26 @@
-# Use an official lightweight Python runtime as a parent image
+# Use an official Python runtime as a parent image
+# Using a slim version to keep the image size smaller
 FROM python:3.9-slim
 
-# Set the working directory inside the container
+# Set the working directory in the container
 WORKDIR /app
 
-# Copy the file that lists the dependencies to the working directory
+# Copy the requirements file into the container at /app
+# This is done first to leverage Docker's layer caching
 COPY requirements.txt .
 
-# Install the dependencies from requirements.txt
-# --no-cache-dir ensures the image is smaller
-RUN pip install --no-cache-dir -r requirements.txt
+# Install any needed packages specified in requirements.txt
+# Using --no-cache-dir to reduce image size
+# Specifying a CPU-only version of PyTorch to significantly reduce image size
+RUN pip install --no-cache-dir -r requirements.txt --index-url https://download.pytorch.org/whl/cpu
 
-# Copy all the other files from your local project folder (app.py, model.pkl)
-# into the container's working directory
+# Copy the rest of your application's code into the container
+# This includes app.py, your trained model (.pth), and the scaler (.pkl)
 COPY . .
 
-# Inform Docker that the container listens on port 8080 at runtime
+# Make port 8080 available to the world outside this container
 EXPOSE 8080
 
-# Define the command to run your application
-# This will execute "python app.py" when the container starts
-CMD ["python", "app.py"]
+# Define the command to run your app
+# This command runs when the container launches
+CMD ["python", "app.py"]