This project automates the job application process using Google’s Gemini-2.0 and GitHub Actions. Taking a job description and your resume, the model provides suggestions for your resume, suggesting relevant points that best match the job.
With these suggestions, the model then helps in generating ideas and key content for a cover letter. The resulting resume and cover letter drafts are then saved as a .docx file for editing and personalization.
All generated content is stored in the hidden outputs directory, so you can revisit and track your job applications over time. Additionally, the system logs each interaction in a CSV file, providing a record of the jobs you've applied to with this automation.
This project takes 3 parameters within the inputs directory.
job_description.txtcontains the job opening's descriptionresume_template.txtthis is the template the model will follow when generating the resumeskillset.txtcontains key=value pairs matching the resume template representing all the possible skills the model will choose from to include in the resume
If you're on linux, to run locally:
bash execute_application.sh
If you're on windows run, to run locally:
.\execute_application.ps1
The .docx files will be written to outputs/<day_applied>/<company_name>-<job_title> and the csv file will be updated at outputs
- Google's Gemini 2.0 Flash model
- Python
- Shell
- Powershell
- GitHub Actions