An application tracking system (ATS) built using Google GEMINI Pro Vision API, which analyzes job descriptions and matches keywords to provided resumes in PDF format. The app outputs suggestions to improve the resume to better match the job description.
Table of Contents
- Create a GOOGLE_API_KEY
- Add it locally to a .env file
- Clone the repo
- Install dependencies
- Run python3 app.py
- Add a job description by copying and pasting it into the "Job Description" section.
- Upload a copy of your resume in PDF format.
- Click the "Submit" button.
- View the analysis results.
Access the application on Hugging Face: TrackHire - ATS Resume Analyzer
| Technology | Description |
|---|---|
| Terraform | an infrastructure as code tool that enables you to safely and predictably provision and manage infrastructure in any cloud. |
| Python | programming language |
| Streamlit | open-source Python framework for data scientists and AI/ML engineers to deliver interactive data apps |
| Docker | a platform designed to help developers build, share, and run container applications. |
| GitHub Actions | a continuous integration and continuous delivery (CI/CD) platform that allows you to automate your build, test, and deployment pipeline. |
| AWS (EKS,ECR) | cloud deployment |
| Google GEMINI Pro Vision API | gives you access to Gemini models created by Google DeepMind |
| Hugging Face | a service that develops computation tools for building applications using machine learning |
- Job Description Analysis:
- Analyzes job descriptions to extract keywords.
- Matches keywords to resumes in PDF format.
- Resume Improvement Suggestions:
- Provides suggestions to improve the resume for better alignment with the job description.
Utilized Terraform, Docker, GitHub Actions, AWS EC2, AWS ECR to create a complete CI/CD pipeline. The pipeline automates the deployment process, ensuring efficient and reliable updates to the application.
| Name | GitHub |
|---|---|
| Sandra Ashipala | GitHub |
