A guide for setting up and getting started with the Entity Recognition and Linker part of the pipeline.
This subsection will guide you through both setting up to work on the repository, and how to get it all running on the server!
¶ Requirements
- Python3
- Uvicorn
- FastAPI
- SpaCy
- Wheel
- Setuptools
To get started developing on the code for this part of the pipeline, simply clone the repository to where you want using
git clone https://github.com/Knox-AAU/PreProcessingLayer_EntityRecognitionAndLinking ERAL
cd ERAL
After cloning the repository, you need to install the requirements. Make sure you have python3 and pip installed for this. You can install all the requirements using the following command:
pip install -r requirements.txt
To run Entity Recognizer and Linker, we use Uvicorn. Uvicorn works like node for python3. Simply run the following command to start the server:
uvicorn main:app
The server uses Docker and watchtower to maintain the up to date code on the github repository you can read more on this here.
Inside the Dockerfile in the repository, we have the following CMD specified for running the server:
CMD ["uvicorn", "main:app", "--host", "0.0.0.0". "--port", "3000"]
This CMD starts the uvicorn server but also adds the parameters host and port. This ensures that instead of the server running locally inside the Docker Container, it is ran using the public IP. That way, we are able to find the uvicorn server inside the KNOX server.
It is possible to get access to the uvicorn server running the Entity Recognition and Linking layer locally using SSH. This is done by forwarding the port the server is running on using the SSH. If the uvicorn server is ran on port 3000, you can access the server locally by doing the following SSH command:
SSH *AAU-MAIL*@knox-preproc01.srv.aau.dk -L 3000:localhost:3000
This forwards what is running on port 3000 on the KNOX server to your local machine. You should now be able to access the uvicorn server from your own browser at
http://localhost:3000.