Project Overview
A sophisticated resume creation system that generates tailored, ATS-compliant resumes based on user inputs, enhanced by AI-driven content suggestions and optimizations.
Primary Features
🔍 AI-driven content creation based on professional information
🔑 Optimization for industry-specific keywords
✅ Assessment of ATS compatibility
📄 Various export formats available (PDF, DOCX, HTML)
🎯 Analysis of job description alignment
🎨 Over three customizable visual templates
💡 Intelligent content recommendations
🔄 Continuous feedback loop for improvements
Technical Details
🖥️ User-friendly, responsive interface
👀 Preview sections individually
🔒 Local data storage to ensure user privacy
📚 Detailed API documentation
🌍 Compatible across multiple browsers
Setup Guidelines
Prerequisites
Node.js (version 16 or later)
npm/yarn
Python (version 3.8 or later) for backend functions
API keys for any utilized AI services
Installation Steps
Clone the repository:
bash
git clone git clone https://github.com/Spado22/Fire4s-AI-Resume-Builder/edit/main/README.md
cd ai-resume-builder
Install dependencies for the frontend:
bash
cd frontend
npm install
Install dependencies for the backend:
bash
cd ../backend
pip install -r requirements.txt
Configure environment variables:
Create .env files in both the frontend and backend folders
Insert necessary API keys and settings
Launching the Application
Initiate the backend server:
bash
cd backend
python app.py
Initiate the frontend development server:
bash
cd ../frontend
npm start
Access the application at http://localhost:3000
Project Layout
text
ai-resume-builder/
├── backend/ # Backend server and API
├── frontend/ # React application
├── docs/ # Documentation
├── templates/ # Resume designs
└── samples/ # Example outputs
API Documentation
The application utilizes the following APIs:
OpenAI GPT for content generation
ATS compatibility assessment API
Job description analysis API
Refer to API_DOCS.md for extensive usage details and restrictions.
User Manual
For detailed instructions with visuals, refer to USER_GUIDE.md.
Technical Report
The three-page technical report contains:
Architectural choices and technology stack
API integration strategies
Template design methodology
Techniques for performance enhancement
Known issues and potential future improvements
Available in TECH_REPORT.md.
Team Members
[Oko Mwezo]
[Seeipati Sithole]
[Thokozani Maleka]
[Koketso Raphasha]
[Neo Mokoana]