ResumeAI

AI-powered resume parser with skill extraction, ATS compatibility scoring, experience level detection, improvement suggestions, and job matching -- all using rule-based analysis (no external AI/LLM APIs required).

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Features

• Resume Parsing -- Extract name, email, phone, skills, experience, and education from plain text
• Section Extraction -- Detect Contact, Summary, Experience, Education, Skills, Certifications, Projects, and more
• Skill Extraction -- Match against 150+ skills across 6 categories using keyword matching
• ATS Scoring -- 0-100 compatibility score with detailed breakdown across 7 criteria
• Experience Level Detection -- Automatic classification as Entry / Mid / Senior / Lead
• Improvement Suggestions -- Actionable recommendations to strengthen your resume
• Job Matching -- Compare resume skills against job requirements with match percentage
• Match All Jobs -- Simultaneously match against all available positions, sorted by fit
• Analysis History -- Track all parsed resumes in a local SQLite database
• File Upload -- Drag-and-drop .txt file upload with progress visualization
• Professional UI -- Clean, responsive blue/white interface with animated score charts
• REST API -- Full JSON API for programmatic access

Screenshots

Upload & Parse	ATS Score	Job Matching
Paste or drag-drop resume	Animated score breakdown	Skill gap analysis

Tech Stack

Component	Technology	Version
Backend	Flask	3.0.0
Database	SQLite + SQLAlchemy	2.0.23
ORM Models	SQLAlchemy	2.0.23
Validation	Pydantic	2.5.2
Testing	pytest + coverage	7.4.3
Linting	flake8	6.1.0
Container	Docker + Compose	3.8
CI/CD	GitHub Actions	v4
Production	Gunicorn	21.2.0

Quick Start

Local Development

# Clone the repository
git clone https://github.com/ravikishan/ResumeAI.git
cd ResumeAI

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the application
python app.py

Open http://localhost:8005 in your browser.

Using start.sh

chmod +x start.sh
./start.sh

Docker

# Build and run
docker-compose up --build

# Or manually
docker build -t resumeai .
docker run -p 8005:8005 resumeai

API Endpoints

Method	Endpoint	Description
GET	/api/health	Health check
POST	/api/parse	Parse resume text (full analysis)
POST	/api/ats-score	Get ATS compatibility score only
POST	/api/match	Match resume against a specific job
POST	/api/match-all	Match resume against all jobs
GET	/api/resumes	List recently parsed resumes
GET	/api/resumes/:id	Get a specific resume analysis
GET	/api/jobs	List available job postings
GET	/api/sample	Get sample resume text
GET	/api/skills/categories	List skill categories and counts

Parse a Resume

curl -X POST http://localhost:8005/api/parse \
  -H "Content-Type: application/json" \
  -d '{"text": "John Doe\nSoftware Engineer\nEmail: john@example.com\n5 years of experience\nSkills: Python, Flask, AWS, Docker\nBachelor of Science in CS\nLeadership, Communication"}'

Response:

{
  "name": "John Doe",
  "email": "john@example.com",
  "phone": null,
  "sections": {},
  "skills": {
    "Programming": ["Python"],
    "Frameworks": ["Flask"],
    "Cloud": ["AWS", "Docker"]
  },
  "experience_years": 5.0,
  "experience_level": "Mid",
  "education": "Bachelor of Science",
  "ats_score": 62,
  "ats_breakdown": {
    "contact_email": 10,
    "contact_phone": 0,
    "skills_count": 8,
    "skill_diversity": 9,
    "education": 10,
    "experience": 15,
    "formatting": 10
  },
  "suggestions": [
    "Include a phone number for direct communication with hiring managers.",
    "Add a professional summary or objective at the top of your resume."
  ]
}

ATS Score

curl -X POST http://localhost:8005/api/ats-score \
  -H "Content-Type: application/json" \
  -d '{"text": "resume text here..."}'

Job Matching

curl -X POST http://localhost:8005/api/match \
  -H "Content-Type: application/json" \
  -d '{"resume_text": "...", "job_id": 1}'

Match All Jobs

curl -X POST http://localhost:8005/api/match-all \
  -H "Content-Type: application/json" \
  -d '{"resume_text": "..."}'

Skill Categories

ResumeAI recognizes skills across 6 categories with 150+ skills:

Category	Count	Examples
Programming	30	Python, Java, JavaScript, C++, Go, Rust, SQL
Frameworks	30	React, Angular, Vue.js, Flask, Django, Node.js
Cloud	30	AWS, Azure, GCP, Docker, Kubernetes, Terraform
Data	30	Pandas, NumPy, TensorFlow, PyTorch, Spark
Databases	19	PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch
Soft Skills	20	Leadership, Communication, Problem-solving

ATS Scoring Criteria

Criterion	Max Points	Description
Email present	10	Professional email address detected
Phone present	10	Phone number detected
Skills listed	20	Number of recognized skills (2 pts each)
Skill diversity	15	Skills across categories (3 pts each)
Education	15	Degree level (Bachelor=10, Master/PhD=15)
Experience	15	Years mentioned (2+=5, 5+=15)
Formatting & quality	15	Name, sections, action verbs, length
Total	100

Experience Level Detection

Level	Years
Entry	0 -- 2
Mid	3 -- 5
Senior	6 -- 10
Lead	11+

Architecture

ResumeAI/
├── app.py                 # Flask application factory
├── config.py              # Configuration class
├── models/
│   ├── database.py        # SQLAlchemy setup
│   └── schemas.py         # Resume, Skill, JobMatch models + Pydantic schemas
├── services/
│   ├── parser.py          # Section extraction, skill matching, suggestions
│   └── scorer.py          # ATS scoring, job matching engine
├── routes/
│   ├── api.py             # JSON API endpoints
│   └── views.py           # HTML view routes
├── templates/             # Jinja2 templates (6 pages)
├── static/
│   ├── css/style.css      # Professional blue/white theme
│   └── js/main.js         # Drag-drop, progress, charts, interactivity
├── tests/                 # 40+ pytest tests
├── seed_data/             # Sample resumes and job descriptions
├── Dockerfile             # Production container
├── docker-compose.yml     # Container orchestration
└── .github/workflows/     # CI pipeline (lint + test)

Testing

# Run all tests
python -m pytest tests/ -v

# With coverage report
python -m pytest tests/ -v --cov=. --cov-report=term-missing

# Run specific test file
python -m pytest tests/test_services.py -v

Development

# Install dev dependencies
pip install -r requirements.txt

# Run with debug mode
FLASK_DEBUG=1 python app.py

# Lint
flake8 . --max-line-length=120

# Verify syntax
python -c "import ast; [ast.parse(open(f).read()) for f in __import__('glob').glob('**/*.py', recursive=True)]"

Environment Variables

Variable	Default	Description
PORT	8005	Server port
SECRET_KEY	resumeai-secret-key...	Flask secret key
DATABASE_URL	sqlite:///instance/...	Database connection
FLASK_DEBUG	0	Debug mode (0 or 1)

License

MIT License -- see LICENSE for details.

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Built with Python and Flask | ravikishan