Job Market project added

Docker-image-integration.md

@@ -141,3 +141,6 @@ The application included in this Docker image is built using the following depen
 - BeautifulSoup
 - Requests
 
+
+## References
+- [Docker for Machine Learning Engineers](https://www.realworldml.net/blog/docker-for-machine-learning-engineers?s=03)

Dockerfile

@@ -1,33 +1,44 @@
+# Layer 1
 # Use an official Python runtime as a parent image
 FROM python:3.10
 
+# Layer 2
 # Copy the current directory contents into the container at /app
 COPY requirements.txt /app/
 
+# Layer 3
 # Copy the requirements file to the working directory
 COPY requirements.txt .
 
+# Layer 4
 # Set the working directory in the container
 WORKDIR /app
 
+# Layer 5
 # Install any needed dependencies specified in requirements.txt
 RUN pip install --no-cache-dir -r requirements.txt
 
+# Layer 6
 # Copy the entire project directory into the container
-COPY . .
+COPY . /app/
 
+# Layer 7
 # Expose ports for FastAPI (8000), Elasticsearch (9200), and Kibana (5601)
 # Note: Exposing ports in a Dockerfile does not publish them to the host machine
 # This only serves as documentation for users of the image
 
+# Layer 8
 # 1. Expose port 8000 for FastApi to allow external access
 EXPOSE 8000
 
+# Layer 9
 # 2. Expose port 9200 for Elasticsearch to allow external access
 EXPOSE 9200
 
+# Layer 10
 # 3. Expose port 9200 for Kibana to allow external access
 EXPOSE 5601
 
+# Layer 11
 # Run script or command to start the application
-CMD ["python", "api.py"]
+ENTRYPOINT ["python", "api.py"]