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📄 Resume AI Analyzer

An AI-powered resume analyzer built using FastAPI, LangChain, and DeepSeek via Ollama, designed to extract key resume information, match it with job descriptions, and provide ATS-like feedback to enhance your hiring potential.

🚀 Features

  • 🔍 Extracts text from PDF and DOCX resumes
  • 🤖 Uses deepseek-r1:7b-qwen-distill model (via Ollama)
  • 📊 Generates ATS score and personalized feedback
  • ✅ Highlights strengths, weaknesses, and keyword matching
  • 🧠 Conversational Q&A with LLM for detailed resume improvement
  • 🌐 Clean UI using HTML, CSS, and JavaScript

🛠️ Tech Stack

  • Backend: FastAPI, Python
  • AI/LLM: LangChain, DeepSeek via Ollama
  • Frontend: HTML5, CSS3, JavaScript, Jinja2
  • Parsing: PyPDF2, python-docx

📁 Folder Structure

Resume_AI_Analyzer/
├── main.py                  # FastAPI backend application
├── requirements.txt         # Python dependencies
├── README.md                # Project documentation
├── static/                  # Frontend static files
│   ├── css/
│   │   └── style.css
│   └── js/
│       └── script.js
├── templates/
│   └── index.html           # Jinja2 HTML template
├── uploaded_documents/      # Directory for uploaded resumes
└── .gitignore               # Git ignored files

🧪 Installation & Usage

1. Clone the Repository

git clone https://github.com/GoldSharon/Resume_AI_Analyzer.git
cd Resume_AI_Analyzer

2. Install Dependencies

Make sure you have Python 3.9+ installed.

pip install -r requirements.txt

3. Start Ollama with DeepSeek Model

Ensure Ollama is installed and the model is pulled:

ollama run deepseek-r1:7b-qwen-distill

4. Run the FastAPI Server

uvicorn main:app --reload

Then open your browser and navigate to: 👉 http://127.0.0.1:8000

📌 Example Use Case

  1. Upload your resume

  2. Optionally add a job description

  3. The AI analyzes and returns:

    • ATS Score
    • Strengths & Weaknesses
    • Feedback
    • Keyword Matching

You can interact with the AI chatbot to improve your resume further.

📄 Requirements

See requirements.txt. Key libraries include:

  • fastapi
  • uvicorn
  • PyPDF2
  • python-docx
  • langchain
  • langchain_ollama
  • pydantic

⚖️ License

MIT License © 2025 Gold Sharon R

👨‍💻 Author

Gold Sharon R B.Tech in Artificial Intelligence and Machine Learning St. Joseph’s College of Engineering, Chennai 📧 gold33sharon@gmail.com 🌐 GitHub Profile

🌟 Contribute

Feel free to fork this repository and open a pull request. Bug reports and feature suggestions are welcome!

🧠 Future Improvements

  • Add user authentication & login system
  • Save resume analysis history
  • Enhance LLM prompt tuning
  • Deploy to cloud (Render, Railway, Heroku)