https://github.com/dadvaiahpavan/ats-system
This AI-driven Applicant Tracking System (ATS) is a cutting-edge solution designed to revolutionize the recruitment process by providing intelligent resume analysis and matching capabilities.
https://github.com/dadvaiahpavan/ats-system
google-generativeai nltk pandas plotly python-docx scikit-learn spacy streamlit
Last synced: about 2 months ago
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This AI-driven Applicant Tracking System (ATS) is a cutting-edge solution designed to revolutionize the recruitment process by providing intelligent resume analysis and matching capabilities.
- Host: GitHub
- URL: https://github.com/dadvaiahpavan/ats-system
- Owner: DadvaiahPavan
- License: mit
- Created: 2024-12-13T09:08:19.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-12-17T15:18:13.000Z (5 months ago)
- Last Synced: 2025-02-08T12:29:54.173Z (3 months ago)
- Topics: google-generativeai, nltk, pandas, plotly, python-docx, scikit-learn, spacy, streamlit
- Language: C
- Homepage: https://next-gen-ai.streamlit.app/
- Size: 26.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🚀 AI-Powered Applicant Tracking System (ATS)
## 📝 Project Overview
This AI-driven Applicant Tracking System (ATS) is a cutting-edge solution designed to revolutionize the recruitment process by providing intelligent resume analysis and matching capabilities.
## Screenshots
## ✨ Key Features
### 1. Intelligent Resume Analysis
- Upload and analyze resumes in PDF and DOCX formats
- Extract and categorize skills
- Provide comprehensive resume feedback
### 2. Job Description Matching
- Compare resume content against job descriptions
- Generate detailed match scores
- Visualize skill compatibility
### 3. Multi-Resume Batch Processing
- Upload and analyze multiple resumes simultaneously
- Export results in CSV and Excel formats
- Instant skill and match score comparisons
## 🛠 Technologies Used
- **AI**: Google Gemini 1.5 Flash
- **Web Framework**: Streamlit
- **Data Processing**:
- Pandas
- PyMuPDF
- python-docx
- **Visualization**:
- Plotly
- Plotly Express
## 🔍 Detailed Functionality
### Resume Skills Extraction
- Categorizes skills into:
- Technical Skills
- Analytical Skills
- Soft Skills
### Match Score Calculation
- Advanced scoring mechanism considering:
- Skill weight system
- Experience level matching
- Education requirements
- Project experience analysis
### Visualization
- Interactive skill gap charts
- Percentage match gauge
- Detailed skill breakdown
## 🚀 Getting Started
### Prerequisites
- Python 3.8+
- Google Gemini API Key
### Installation
1. Clone the repository
```bash
git clone https://github.com/yourusername/ATS-System.git
cd ATS-System
```
2. Install dependencies
```bash
pip install -r requirements.txt
```
3. Set up Google Gemini API Key
- Create a `.streamlit/secrets.toml` file
- Add your API key:
```toml
GOOGLE_API_KEY = "your_api_key_here"
```
4. Run the application
```bash
streamlit run app.py
```
## 📋 Usage Instructions
1. Enter Job Description
2. Upload Resume(s)
3. Choose Analysis Type:
- Skills Extraction
- Percentage Match
- Batch Processing
## 🔒 Security Notes
- API keys managed via Streamlit secrets
- Secure file handling
- No local storage of sensitive information
## 🤝 Contributing
1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request
## 📄 License
[Specify your license here, e.g., MIT License]
## 🌟 Future Roadmap
- Enhanced AI matching algorithms
- More detailed skill taxonomy
- Support for more file formats
- Advanced reporting features
## 💡 Developed By
[Your Name/Organization]
---
**Note**: Ensure you have a valid Google Gemini API key to use this application.