📄 PerfectCV — AI-Powered CV Optimization System

PerfectCV is an intelligent platform that helps job seekers create ATS-friendly resumes by analyzing uploaded CVs, providing AI-powered recommendations, calculating ATS compatibility scores, and generating professionally optimized resumes automatically.

The project combines modern full-stack development with Large Language Models (LLMs) to streamline the resume optimization process and improve candidates' chances of passing Applicant Tracking Systems (ATS).

---

✨ Features

📑 Resume Analysis

• 📄 Automatic CV parsing and information extraction
• 🎯 ATS compatibility scoring (0–100)
• 📊 Detailed feedback on strengths and weaknesses
• 🧠 Skill, education, and experience detection

🤖 AI Features

• 💡 AI-powered resume improvement suggestions
• 💬 AI chatbot for CV advice and career guidance
• 📝 Professional resume rewriting using LLMs
• 🎯 Personalized career recommendations

📄 CV Generation

• 📥 Generate professionally formatted PDF resumes
• 🎨 Modern, ATS-friendly resume templates
• 🔄 Automatically populate templates using extracted data

🔐 User Management

• 👤 Secure user authentication
• 📁 Upload and manage multiple resumes
• ☁️ File storage using MongoDB GridFS

---

🛠️ Tech Stack

Layer	Technology
🌐 Frontend	React.js, Vite, Tailwind CSS, Axios
⚙️ Backend	FastAPI, Python
🗄️ Database	MongoDB Atlas, MongoDB GridFS
🤖 AI Integration	Google Gemini AI, Groq LLaMA 3.3
📄 Document Processing	PyPDF2, pdfplumber, Jinja2, xhtml2pdf
🔐 Authentication	JWT (JSON Web Tokens)

---

📁 Project Structure

perfectcv/
├── backend/
│   ├── app/
│   │   ├── api/
│   │   ├── services/
│   │   ├── models/
│   │   ├── database/
│   │   ├── utils/
│   │   └── ai/
│   ├── templates/
│   └── main.py
│
├── frontend/
│   └── src/
│       ├── components/
│       ├── pages/
│       ├── services/
│       ├── context/
│       └── assets/
│
├── screenshots/
├── README.md
└── requirements.txt

---

🚀 Getting Started

📋 Prerequisites

• Python 3.10+
• Node.js 18+
• MongoDB Atlas
• Google Gemini API Key
• Groq API Key

---

⚙️ Backend Setup

1️⃣ Clone the Repository

git clone https://github.com/your-username/perfectcv.git
cd perfectcv

2️⃣ Create a Virtual Environment

python -m venv venv

Activate it:

Windows

venv\Scripts\activate

Linux / macOS

source venv/bin/activate

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Configure Environment Variables

Create a .env file in the backend directory.

MONGODB_URI=your_mongodb_connection_string

JWT_SECRET=your_jwt_secret

GEMINI_API_KEY=your_gemini_api_key

GROQ_API_KEY=your_groq_api_key

⚠️ Never commit API keys or secrets to version control.

5️⃣ Run the Backend

uvicorn main:app --reload

Backend runs at:

http://localhost:8000

---

💻 Frontend Setup

Install Dependencies

cd frontend
npm install

Start Development Server

npm run dev

Frontend runs at:

http://localhost:5173

---

🔗 API Overview

Resource	Endpoint
🔑 Authentication	/api/auth/*
📄 Resume Upload	/api/upload
🤖 AI Analysis	/api/analyze
📊 ATS Score	/api/score
📥 CV Generation	/api/generate
💬 AI Chatbot	/api/chat

---

🌍 Environment Variables

Variable	Description
MONGODB_URI	MongoDB Atlas connection string
JWT_SECRET	JWT signing secret
GEMINI_API_KEY	Google Gemini API key
GROQ_API_KEY	Groq API key

---

🚀 Deployment

The application can be deployed using:

• ☁️ Vercel (Frontend)
• ⚙️ Render / Railway / VPS (Backend)
• 🗄️ MongoDB Atlas (Database)

---

🔒 Security

• 🔐 JWT-based authentication
• 📁 Secure file storage using MongoDB GridFS
• 🚫 Environment variables for API keys and secrets
• 🛡️ Input validation and request sanitization

---

🎓 Project Information

This project was developed as an academic group project to demonstrate the integration of Artificial Intelligence with modern full-stack web development. It focuses on helping job seekers optimize their resumes for Applicant Tracking Systems (ATS) using Large Language Models (LLMs), automated document processing, and intelligent career assistance.