Local ATS Resume Checker & Job Match Analyzer

A complete, production-quality ATS Resume Checker & Job Match Analyzer web application that runs 100% locally on your machine.

🔒 100% Local & Private: No API keys, no OpenAI, no Gemini, no Claude, no OpenRouter, or external LLM APIs required. All resume parsing, keyword extraction, and semantic matching run locally using open-source Python NLP libraries and local embedding models.

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🎯 Key Features

• 📄 Document Parsing: Supports PDF (PyMuPDF) and DOCX (python-docx) format parsing.
• 🔍 Hard & Soft Skill Extractor: Taxonomy-driven skill extractor with alias resolution and fuzzy string matching (RapidFuzz).
• 🧠 Local Semantic Similarity: Uses sentence-transformers (all-MiniLM-L6-v2) and scikit-learn cosine similarity to measure contextual alignment between resume experience and job descriptions.
• 🛡️ ATS Readability & Formatting Check: Scans for non-standard tables, text boxes, page count, word count, section header completeness, and formatting warnings.
• 📊 8-Factor Weighted Scoring:
  1. Exact Skill Match (25%)
  2. Semantic Context Match (25%)
  3. ATS Format Readability (15%)
  4. Hard Requirement Coverage (10%)
  5. Action Verb Density (10%)
  6. Bullet Point Quantification (5%)
  7. Section Completeness (5%)
  8. Phrase Repetition (5%)
• 🎨 Sleek Dark Blue Interface: Modern React frontend built with Vite, Tailwind CSS, Lucide icons, and Recharts visualization charts.

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🛠️ Tech Stack

Frontend

• Framework: React.js + Vite
• Styling: Tailwind CSS (Dark Blue Midnight Theme)
• Icons: Lucide React
• Charts: Recharts
• HTTP Client: Axios
• Notifications: React Hot Toast

Backend

• Framework: Python + FastAPI + Uvicorn
• Parsing: PyMuPDF (fitz), python-docx
• NLP & Text Processing: spaCy, RapidFuzz, Regular Expressions
• Semantic Embeddings: sentence-transformers (all-MiniLM-L6-v2), scikit-learn
• Validation: Pydantic v2

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🚀 Quick Start Guide

Prerequisites

• Node.js (v18+) & npm
• Python (v3.10+) & pip

1. Clone the Repository

git clone https://github.com/Kishore-Procode/Local_Resume_Checker.git
cd Local_Resume_Checker

2. Backend Setup

cd backend
python -m pip install -r requirements.txt
python -m uvicorn app.main:app --host 127.0.0.1 --port 8000 --reload

The FastAPI backend will be available at: http://127.0.0.1:8000 (Swagger API docs at http://127.0.0.1:8000/docs).

3. Frontend Setup

In a new terminal:

cd frontend
npm install
npm run dev

The Vite frontend will be available at: http://localhost:5173/

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🔒 Privacy Guarantee

All processing is performed locally on your device. No candidate data, resume text, or job descriptions are transmitted over the internet or saved to external servers.

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📜 License

MIT License. Free for personal and commercial use.