README.md

ATS Resume Scorer

An AI-powered tool to analyze resume-job description compatibility using ATS (Applicant Tracking System) scoring and skill matching.

🚀 Features

• PDF Resume Upload: Extract text from PDF resumes using pdfplumber
• Job Description Input: Paste job descriptions for comparison
• ATS Match Scoring: Calculate similarity score using TF-IDF vectorization and cosine similarity
• Skill Matching: Identify matched and missing skills from a predefined list
• Interactive UI: Clean Streamlit interface with progress bars and color-coded tags
• Error Handling: Graceful handling of invalid PDFs, empty inputs, and extraction failures

🛠️ Tech Stack

• Frontend/UI: Streamlit
• PDF Processing: pdfplumber
• NLP Processing: NLTK (tokenization, stopwords, lemmatization)
• Machine Learning: scikit-learn (TF-IDF, Cosine Similarity)
• Python: Core language

📁 Project Structure

ATS-Resume-Scorer/
├── app.py                 # Main Streamlit application
├── utils/
│   ├── text_extraction.py # PDF text extraction utilities
│   ├── preprocessing.py   # Text preprocessing (lowercase, punctuation, stopwords, lemmatization)
│   ├── scoring.py         # ATS score calculation using TF-IDF and cosine similarity
│   └── skill_matcher.py   # Skill matching against predefined list
├── data/
│   └── skills.txt         # Predefined list of skills for matching
├── requirements.txt       # Python dependencies
└── README.md             # Project documentation

🏃‍♂️ How to Run Locally

1. Clone or download the project:

   cd /path/to/your/workspace
   # Place the ATS-Resume-Scorer folder here
   

2. Install dependencies:

   cd ATS-Resume-Scorer
   pip install -r requirements.txt
   

3. Run the application:

   streamlit run app.py
   

4. Open your browser and go to http://localhost:8501

☁️ Deploy on Streamlit Cloud

1. Fork or upload to GitHub: Ensure all files are in a GitHub repository.

2. Go to Streamlit Cloud: Visit share.streamlit.io

3. Connect your GitHub repo: Select the repository containing this project.

4. Deploy: Choose app.py as the main file and click deploy.

5. Access your app: Once deployed, you'll get a public URL to access the application.

📝 Usage

1. Upload a PDF resume using the file uploader.
2. Paste the job description text in the text area.
3. Click "Analyze" to get:
   • ATS match score (0-100%)
   • Visual progress bar
   • Matched skills (green tags)
   • Missing skills (red tags)

🔧 Customization

• Skills List: Edit data/skills.txt to add or modify the predefined skills for matching.
• Preprocessing: Modify utils/preprocessing.py to adjust text cleaning steps.
• Scoring Algorithm: Enhance utils/scoring.py for more advanced similarity measures.

🤝 Contributing

Feel free to fork this project and submit pull requests for improvements!

📄 License

This project is open-source and available under the MIT License.