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🚀 AI-Powered Resume Matcher & Optimizer

A smart resume enhancement tool that analyzes resumes, extracts skills, compares them with job descriptions, calculates match percentage, and gives improvement suggestions — powered by FastAPI, Streamlit, and Machine Learning.


🔍 What It Does

  • 🧠 Classifies resumes by job category using ML
  • 🧾 Extracts relevant skills from resumes & job descriptions
  • 🧮 Calculates match percentage (how well a resume fits a job)
  • ❌ Shows missing skills
  • 💡 Gives actionable suggestions to improve your resume
  • 📄 Accepts both text input and PDF uploads

⚙️ How It Works

  1. Resumes and job descriptions are input via text or file
  2. Text is preprocessed and compared using a custom skill matcher
  3. A match percentage is calculated based on skill overlap
  4. Suggestions are generated to improve the match
  5. Results are displayed in a beautiful Streamlit UI

📦 Technologies Used

Layer Tech
💻 Backend FastAPI (Python)
🤖 ML Model TF-IDF + Classifier (resume_classifier.pkl)
📊 Matching Logic Custom skill extractor & matcher
🎨 Frontend Streamlit
📄 File Processing PyMuPDF for PDF parsing
📚 Skills DB Hardcoded list (extensible to file/DB)

🛠️ Setup Instructions

1. Clone the repository

git clone https://github.com/yourusername/resumeparser.git

cd resumeparser

2. Create virtual environment and install dependencies

python -m venv .venv

venv\Scripts\Activate # on Windows

pip install -r requirements.txt

--

🚀 How to run the project

▶️ Start the Backend (FastAPI)

uvicorn app.main:app --reload

Runs on http://127.0.0.1:8000

🖼️ Start the Frontend (Streamlit UI) Open a new terminal:

streamlit run streamlit_ui/app.py

UI runs on http://localhost:8501


✨ Final Output

Once everything runs: Upload or paste a resume and job description Get:

✅ Match Percentage (with a progress bar)

🎯 Matched Skills

❌ Missing Skills

💡 Suggestions to Improve


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