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📄 AI-Powered Resume Analyzer & Multi-Source Job Matcher

An AI-powered web app that:

  • Analyzes your uploaded resume (PDF)
  • Fetches live jobs from multiple sources
  • Matches the best job opportunities based on your skills and experience

Built using Streamlit, Python, Pandas, Sentence-Transformers, and Machine Learning for smart, semantic matching. [file:1][file:4]

🔥 Features

  • 📄 Upload your Resume (PDF)
  • 🧠 Automatic Resume Text Extraction (PDFMiner)
  • 🌎 Fetch Jobs from Multiple Sources
    • RemoteOK (API)
    • Microsoft Careers
    • AngelList / Wellfound [file:4]
  • 🤖 Smart Resume-to-Job Matching
    • Text preprocessing (HTML stripping, stopword removal, stemming)
    • Sentence-transformer embeddings (all-MiniLM-L6-v2)
    • Cosine similarity to rank best matches [file:4]
  • 🎯 Job Filters (in sidebar)
    • Only Remote Jobs
    • Only Microsoft Jobs
    • Only Startups (AngelList)
    • Filter by Tech Stack (e.g., Python, React) [file:2]
  • 🌗 Dark Mode UI with modern job cards (title, company, similarity score, Apply button) [file:2]

📥 Installation

  1. Clone the repository
git clone https://github.com/TR-3N/-AI-Powered-Resume-Analyzer-Multi-Source-Job-Matcher.git
cd -AI-Powered-Resume-Analyzer-Multi-Source-Job-Matcher
  1. Create & activate virtual environment (recommended)
python -m venv venv
# Windows (PowerShell)
venv\Scripts\activate
# macOS / Linux
# source venv/bin/activate
  1. Install dependencies
pip install -r requirements.txt

This installs Streamlit, Pandas, scikit-learn, pdfminer.six, BeautifulSoup, sentence-transformers, torch, and NLTK. [file:3][file:4]

  1. Download NLTK data (once)
python
>>> import nltk
>>> nltk.download('stopwords')
>>> exit()

🚀 Running the App

From the project folder (with venv active):

streamlit run app.py
  • This starts a local server (usually http://localhost:8501). [file:2]
  • In the browser:
    • Upload your resume (PDF).
    • The app extracts text, fetches jobs, matches them, and shows top job cards with similarity scores and “Apply Now” links. [file:2][file:4]

🛠 Project Structure

.
├── app.py          # Main Streamlit app (UI, filters, rendering)
├── utils.py        # Resume extraction, job fetching, matching logic
├── job_scraper.py  # Optional: scrape Indeed + insert into SQLite
├── database.py     # Optional: SQLAlchemy engine/table for jobs.db
├── init_db.py      # Optional: initialize jobs.db schema
├── jobs.csv        # Optional: sample/static jobs data
├── requirements.txt
└── README.md

[files:2][file:4][file:5][file:6][file:7]

✨ Future Improvements

  • Better salary estimation
  • Apply to jobs with a single click
  • AI-based resume improvement suggestions
  • Richer scraping of full job descriptions from Microsoft/AngelList pages

🤝 Contributing

Contributions are welcome!
Feel free to open an Issue or Pull Request.

📄 License

This project is licensed under the MIT License.


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