📋 This guide will walk you through the installation process for the program. Please follow the steps below to ensure a successful installation.
Before proceeding with the installation, please make sure you have the following prerequisites:
- Access to a Linux terminal (Mac or Ubuntu) or a WSL on Windows
- Subscription to Rapidapi and the Linkedin Job search service: Rapidapi
Clone the repository to your local environment and create the virtual environment.
conda create --name jobhunter python=3.10
conda activate jobhunter
pip install .
To begin, we need to copy the .env-template
file into .env
so that the program can work properly. Use the following command to accomplish this:
cp .env-template .env
Next, open the .env
file in a text editor and add your Rapid API Key. This key is required for the program to function correctly. If you don't have a Rapid API Key, you can sign up for one here.
You can also add OpenAI API key to the .env
file to get GPT based resume similarity score. This is optional feature, and currently in development, and will be available in full version soon. You can sign up for OpenAI API here
To ensure that everything is set up correctly, run the following command to run the install all dependencies and run unit tests on the jobhunter:
make check
If there are no errors, then everything is working properly. If you encounter errors during installation, please make sure you have followed all the steps described above. If you can't fix the issue, open up an issue in this Github repo for triaging.
If you want to run your application locally, you can run the following command in the command line:
jobhunter
To create a Docker image, you need to run the appropriate Docker command on the Dockerfile. Make sure you have Docker installed on your system. If you don't have Docker installed, you can download it from the official website here.
sh run_docker.sh
ℹ️ NOTE: You can check the terminal to see the logs of the application when running.
That's it! You have successfully installed the program.
🌐 You should be able to access the application in your browser by clicking here.
You should see the UI like this:
If you encounter any issues during the installation process, please refer to the documentation or submit an issue to this repo.