itslovepatel

Resume-ATS

# 🎯 ATS Resume Analyzer [](https://resume-ats-mu.vercel.app) [](https://resume-ats-backend.onrender.com/) [](https://github.com/itslovepatel/Resume-ATS) [](LICENSE) > **Free ATS Resume Checker** · AI-Powered Resume Scanner · No Signup Required · Instant ATS Score A modern, AI-powered **ATS (Applicant Tracking System) Resume Analyzer** that helps job seekers understand how their resume performs in automated screening systems. **Supports 25+ industries** including Software, Healthcare, Finance, Legal, Education, and more! 🔗 **[Try it Live →](https://resume-ats-mu.vercel.app/)** <!-- Project preview / OG image (also used for social shares) -->  ## 🔗 Deployments - Primary frontend (Vercel): https://resume-ats-mu.vercel.app - Alternate / vanity URL: https://ats.lovexog.me ## ✨ What It Does Upload your resume (PDF or DOCX) and get instant, comprehensive analysis: - See your ATS compatibility score (0-100) - Understand what's working and what needs improvement - Get AI-powered suggestions tailored to your industry - Download a detailed PDF report ## 🏭 Supported Industries (25+) | Technology | Business | Healthcare | Other | |------------|----------|------------|-------| | Software / IT | Marketing | Healthcare / Medical | Legal | | Data Science / AI | Finance / Banking | Pharmaceutical / Biotech | Education | | Cybersecurity | Sales | | Real Estate | | Design / UX | Human Resources | | Hospitality | | | Operations / Supply Chain | | Retail / E-commerce | | | Consulting | | Government | | | Project Management | | Non-Profit | ## 🚀 Features - **ATS Compatibility Score**: Get a comprehensive score (0-100) showing how well your resume will perform - **Candidate Profile Extraction**: Automatically extract name, email, phone, LinkedIn, and GitHub - **Domain Detection**: AI detects your primary job domain (IT, Data, Marketing, Finance, etc.) - **Skills Analysis**: Comprehensive breakdown of technical skills, frameworks, tools, and soft skills - **Projects Review**: Analyze project descriptions, technologies used, and impact statements - **Experience Analysis**: Evaluate work experience quality, action verbs usage, and metrics - **Issue Detection**: Identify formatting issues, missing sections, and ATS compatibility problems - **Smart Suggestions**: Get actionable recommendations to improve your ATS score - **PDF Report Download**: Download a professional PDF report of your analysis ## 🖨️ Local OCR Fallback (Scanned Resumes) Resume-ATS now includes a fully local OCR fallback to handle scanned or image-based PDFs. Key points: - The backend attempts standard PDF text extraction first (PyPDF). OCR runs only when extraction quality is poor (heuristics: text length < 800 chars, word count < 150, missing email or phone). - OCR uses Tesseract via `pytesseract` and `pdf2image` to convert pages at 300 DPI and preprocess images (grayscale, contrast, sharpening) before OCR. - Safety controls: max 5 OCR pages, 15s OCR timeout, never OCR DOCX, never store OCR images, never overwrite original PDFs. - Safety controls: max 5 OCR pages, 30s OCR timeout, never OCR DOCX, never store OCR images, never overwrite original PDFs. - API responses include `parsing_method` ("standard" | "ocr" | "ocr_unavailable") and `ocr_confidence` ("low" | "medium" | "high"). This makes Resume-ATS more robust for scanned resumes while keeping all processing local—no cloud OCR, no external APIs. ## 🛠️ Tech Stack ### Frontend - Next.js 14 - React 18 - TypeScript - Tailwind CSS - Framer Motion - Lucide React Icons ### Backend - Python 3.10+ - FastAPI - PyMuPDF (PDF parsing) - python-docx (DOCX parsing) ## 📦 Installation ### Prerequisites - Node.js 18+ - Python 3.10+ - pip ### Backend Setup 1. Navigate to the backend directory: ```bash cd backend ``` 2. Create a virtual environment: ```bash python -m venv venv ``` 3. Activate the virtual environment: - Windows: ```bash venv\Scripts\activate ``` - macOS/Linux: ```bash source venv/bin/activate ``` 4. Install dependencies: ```bash pip install -r requirements.txt ``` 5. Start the backend server: ```bash uvicorn app.main:app --reload --port 8000 ``` The API will be available at `http://localhost:8000` ### Frontend Setup 1. Navigate to the frontend directory: ```bash cd frontend ``` 2. Install dependencies: ```bash npm install ``` 3. Start the development server: ```bash npm run dev ``` The application will be available at `http://localhost:3000` ## 📁 Project Structure ``` Resume-ATS/ ├── backend/ │ ├── app/ │ │ ├── __init__.py │ │ ├── main.py # FastAPI application │ │ ├── models/ │ │ │ ├── __init__.py │ │ │ └── schemas.py # Pydantic models │ │ └── services/ │ │ ├── __init__.py │ │ ├── resume_parser.py # PDF/DOCX parsing │ │ ├── skill_extractor.py │ │ ├── domain_classifier.py │ │ └── ats_scorer.py # ATS scoring logic │ └── requirements.txt │ ├── frontend/ │ ├── src/ │ │ ├── app/ │ │ │ ├── globals.css │ │ │ ├── layout.tsx │ │ │ └── page.tsx │ │ ├── components/ │ │ │ ├── Header.tsx │ │ │ ├── Hero.tsx │ │ │ ├── HowItWorks.tsx │ │ │ ├── Features.tsx │ │ │ ├── UploadSection.tsx │ │ │ ├── LoadingOverlay.tsx │ │ │ ├── ResultsDashboard.tsx │ │ │ ├── Footer.tsx │ │ │ └── results/ │ │ │ ├── ScoreCircle.tsx │ │ │ ├── ScoreBreakdownCard.tsx │ │ │ ├── SkillsCard.tsx │ │ │ ├── ExperienceCard.tsx │ │ │ ├── ProjectsCard.tsx │ │ │ ├── KeywordsCard.tsx │ │ │ ├── IssuesCard.tsx │ │ │ └── SuggestionsCard.tsx │ │ └── types/ │ │ └── index.ts │ ├── package.json │ ├── tailwind.config.js │ └── next.config.js │ └── README.md ``` ## 🎯 ATS Scoring Logic The ATS score is calculated based on: | Factor | Weight | |--------|--------| | Keyword Relevance | 20% | | Section Completeness | 20% | | Formatting Score | 15% | | Skill Relevance | 20% | | Experience Clarity | 15% | | Project Impact | 10% | ### Score Categories: - **80-100**: Excellent - Resume is well-optimized for ATS - **60-79**: Good - Minor improvements needed - **40-59**: Needs Improvement - Significant optimization required - **0-39**: Poor - Major restructuring needed ## 📡 API Endpoints ### `POST /api/analyze` Analyze a resume file and return comprehensive ATS analysis. **Request:** - Content-Type: multipart/form-data - Body: file (PDF or DOCX, max 5MB) **Response:** ```json { "success": true, "candidate": { "name": "John Doe", "email": "[email protected]", "phone": "+1-555-123-4567", "location": "New York, NY" }, "ats_score": 85, "score_category": "Excellent", "domain": { "primary": "Software / IT", "confidence": 0.92 }, "skills": {...}, "experience": {...}, "projects": [...], "issues": [...], "suggestions": [...] } ``` ### `GET /health` Health check endpoint. ## 🔒 Security - Files are processed in memory and immediately deleted after analysis - No data is stored on the server - No user tracking or analytics - No signup required ## 🚧 Future Features - [ ] User authentication and resume history - [ ] Job description matching - [ ] AI-powered resume rewriting - [ ] Recruiter dashboard - [ ] Resume comparison - [ ] Industry-specific scoring ## 📄 License MIT License - feel free to use this project for personal or commercial purposes. ## 🤝 Contributing Contributions are welcome! Please feel free to submit a Pull Request. --- Built with ❤️ for job seekers everywhere