[Multi-User Part 5]: Add a production Docker file and use a gunicorn configuration with it (#514)

- Add a productionized setup for the Khoj server using `gunicorn` with multiple workers for handling requests
- Add a new Dockerfile meant for production config at `ghcr.io/khoj-ai/khoj:prod`; the existing Docker config should remain the same

prod.Dockerfile

@@ -0,0 +1,30 @@
+# Use Nvidia's latest Ubuntu 22.04 image as the base image
+FROM nvidia/cuda:12.2.0-devel-ubuntu22.04
+
+LABEL org.opencontainers.image.source https://github.com/khoj-ai/khoj
+
+# Install System Dependencies
+RUN apt update -y && apt -y install python3-pip git
+
+WORKDIR /app
+
+# Install Application
+COPY pyproject.toml .
+COPY README.md .
+RUN sed -i 's/dynamic = \["version"\]/version = "0.0.0"/' pyproject.toml && \
+    TMPDIR=/home/cache/ pip install --cache-dir=/home/cache/ -e .
+
+# Copy Source Code
+COPY . .
+
+RUN apt install vim -y
+
+# Set the PYTHONPATH environment variable in order for it to find the Django app.
+ENV PYTHONPATH=/app/src:$PYTHONPATH
+
+# Run the Application
+# There are more arguments required for the application to run,
+# but these should be passed in through the docker-compose.yml file.
+ARG PORT
+EXPOSE ${PORT}
+ENTRYPOINT [ "gunicorn", "-c", "gunicorn-config.py", "src.khoj.main:app" ]