AI-powered ATS Resume Scanner built using Streamlit + Python + Google Gemini + AWS EC2.
Users can:
- Upload Resume PDF
- Paste Job Description (JD)
- Get ATS Match Score
- Resume Review
- Keyword Analysis
User
↓
Streamlit UI
↓
Resume PDF Processing
(pdf2image)
↓
Google Gemini AI
↓
ATS Review + Match Score
- AWS Account
- Ubuntu EC2 Instance
- Python 3.7+
- Google Gemini API Key
Create:
- Ubuntu Server 20.04 LTS
- Open Port:
- 22 (SSH)
- 8501 (Streamlit)
Connect:
ssh -i your-key.pem ubuntu@YOUR_PUBLIC_IPSwitch root:
sudo -iUpdate:
apt update && apt upgrade -yInstall Python:
apt install python3 python3-pip python3-venv -yVerify:
python3 --version
pip3 --versionInstall Git:
apt install git -yVerify:
git --versionInstall Poppler:
apt install poppler-utils -yVerify:
pdftoppm -vgit clone https://github.com/vikash93825/ATS-Multi-Cloud-AI-Project.git
cd ATS-Multi-Cloud-AI-ProjectCreate:
python3 -m venv venvActivate:
source venv/bin/activateExpected:
(venv)Upgrade pip:
pip install --upgrade pipInstall dependencies:
pip install -r requirements.txtInstall Gemini SDK:
pip install google-generativeai- Open Google AI Studio
- Create Project
- API Keys
- Create API Key
Copy key.
Create folder:
mkdir -p .streamlitOpen:
vi .streamlit/secrets.tomlAdd:
GOOGLE_API_KEY="YOUR_API_KEY"Save:
ESC
:wq
Start:
streamlit run app.py \
--server.port 8501 \
--server.enableCORS falseOutput:
Local URL:
http://localhost:8501
Network URL:
http://PUBLIC_IP:8501
Open:
http://YOUR_PUBLIC_IP:8501
ATS-Multi-Cloud-AI-Project/
│
├── app.py
├── requirements.txt
├── README.md
├── .streamlit/
│ └── secrets.toml
│
├── uploads/
├── assets/
├── utils/
└── venv/
✅ Resume Upload
✅ ATS Analysis
✅ Gemini Integration
✅ Match Score
✅ Resume Review
✅ Keywords Analysis
✅ AWS Deployment
sudo ufw allow 8501
sudo ufw reloadsudo apt install poppler-utilscat .streamlit/secrets.tomlExpected:
GOOGLE_API_KEY="YOUR_KEY"Vikash Kumar