https://github.com/inoles/resumeinsight
AI-powered resume screening tool
https://github.com/inoles/resumeinsight
numpy pandas pandas-python pdfminersix python resume resume-screening spacy spacy-nlp
Last synced: 20 days ago
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AI-powered resume screening tool
- Host: GitHub
- URL: https://github.com/inoles/resumeinsight
- Owner: iNoles
- License: gpl-3.0
- Created: 2025-02-15T19:20:57.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-11T02:00:06.000Z (about 1 year ago)
- Last Synced: 2025-05-12T19:07:37.203Z (about 1 year ago)
- Topics: numpy, pandas, pandas-python, pdfminersix, python, resume, resume-screening, spacy, spacy-nlp
- Language: Python
- Homepage:
- Size: 119 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ResumeInsight
ResumeInsight is a console-based and web-based AI resume screening tool that ranks resumes based on their relevance to a given job description. Using NLP, TF-IDF, and cosine similarity, this tool helps recruiters and hiring managers quickly identify the most relevant candidates.
## Features
- Parses resumes in PDF and DOCX formats
- Two Modes: Console & Web UI – Use via the terminal or a browser-based interface with Streamlit
- Extracts key information like skills, experience, and education
- Uses NLP to rank candidates based on job descriptions
- Provides insights into resume relevance
- Performance Optimization with Watchdog – Monitors file changes for efficient reloading
- Downloadable CSV Reports – Export ranked results for easy review
## Installation
1. Clone the repository:
```bash
git clone https://github.com/iNoles/ResumeInsight.git
cd ResumeInsight
```
2. Create a virtual environment and activate it:
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
### Run the Console Version
```bash
python main.py
```
### Run the Web App
```bash
streamlit run app.py
```
## Dependencies
- python-docx (for parsing DOCX files)
- pdfminer.six (for extracting text from PDFs)
- spacy (for NLP processing)
- numpy & pandas (for data handling)
- Streamlit – For interactive web-based UI
- Watchdog – For performance optimization and real-time file monitoring
## Contributing
1. Fork the repository
2. Create a new branch (```feature-branch```)
3. Commit your changes
4. Push to your fork
5. Submit a pull request