📄 ResumeAnalyser

An AI-powered resume analysis and improvement tool built with React, Node.js, and the Google Gemini API.

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✨ Features

• 📤 Upload & Parse — Drag-and-drop your resume (PDF or DOCX), parsed entirely in memory with no disk writes
• 🤖 AI Analysis — Gemini 2.5 Flash scores your resume on ATS compatibility, readability, and keyword density
• 📊 Visual Dashboard — Animated score ring, keyword match bars, strengths, weaknesses, and actionable suggestions
• ✍️ AI Resume Rewrite — One-click to generate an improved version of your resume with all suggestions applied
• 🖊️ Edit Before Download — Review and edit the AI-rewritten resume in a modal before saving
• 📥 PDF Export — Download the final improved resume as a clean, multi-page PDF via jspdf

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🏗️ Project Architecture

ResumeAnalyser/
├── backend/                  # Node.js + Express API
│   ├── server.js             # Main server — routes, file parsing, AI calls
│   ├── package.json
│   ├── .env                  # API keys (never commit this)
│   └── .gitignore
│
└── frontend/                 # React + Vite SPA
    ├── public/
    ├── src/
    │   ├── pages/
    │   │   ├── Landing.jsx   # Home page with hero and feature highlights
    │   │   ├── Upload.jsx    # Drag-and-drop upload + live PDF preview
    │   │   └── Dashboard.jsx # Analysis results, score ring, edit/download
    │   ├── components/
    │   │   ├── Navbar.jsx    # Responsive navigation bar
    │   │   └── Footer.jsx    # Site footer
    │   ├── App.jsx           # React Router setup (/, /upload, /dashboard)
    │   ├── main.jsx          # React entry point
    │   └── index.css         # Global design tokens + Tailwind base
    ├── .env                  # VITE_API_BASE_URL (never commit this)
    ├── vite.config.js
    └── package.json

Data Flow

User uploads resume (PDF/DOCX)
        │
        ▼
[Frontend: Upload.jsx]
  POST /api/upload (multipart/form-data)
        │
        ▼
[Backend: server.js]
  1. Multer → reads file into memory buffer (no disk write)
  2. pdf-parse / mammoth → extracts raw text
  3. Gemini 2.5 Flash → returns structured JSON analysis
  4. Returns { sessionId, aiAnalysis } to frontend
        │
        ▼
[Frontend: Dashboard.jsx]
  Renders score, strengths/weaknesses, keyword bars
        │
        ▼ (on "Edit" or "Download Improved")
  POST /api/improve  (sends sessionId)
        │
        ▼
[Backend: server.js]
  1. Looks up resume text from in-memory cache (keyed by sessionId)
  2. Gemini 2.5 Flash → rewrites the resume
  3. Returns plain text
        │
        ▼
[Frontend] → user edits in modal → jsPDF generates downloadable PDF

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🛠️ Tech Stack

Layer	Technology
Frontend Framework	React 19 + Vite
Styling	Tailwind CSS v4 + Custom CSS tokens
Animations	Framer Motion
Icons	Lucide React + Google Material Symbols
PDF Export	jsPDF
Backend	Node.js + Express 5
File Parsing	pdf-parse (PDF), mammoth (DOCX)
File Uploads	Multer (memory storage)
AI	Google Gemini 2.5 Flash via @google/genai

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⚙️ Local Development

Prerequisites

• Node.js v18+
• A Google Gemini API key (free)

1. Clone the repo

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

2. Set up the Backend

cd backend
npm install

Create a .env file in the backend/ folder:

GEMINI_API_KEY=your_gemini_api_key_here
PORT=3000

Start the backend server:

npm start
# Server running at http://localhost:3000

3. Set up the Frontend

cd ../frontend
npm install

Create a .env file in the frontend/ folder:

VITE_API_BASE_URL=http://localhost:3000

Start the frontend dev server:

npm run dev
# App running at http://localhost:5173

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🚀 Deployment

Backend → Render (Free Tier)

1. Push your code to GitHub (ensure .env is not committed)
2. Go to render.com → New Web Service
3. Connect your GitHub repo and configure:

Setting	Value
Root Directory	backend
Build Command	npm install
Start Command	npm start
Instance Type	Free

4. Add Environment Variables in the Render dashboard:

Key	Value
GEMINI_API_KEY	your Gemini API key
PORT	3000

5. After deployment, copy your service URL (e.g., https://resumeanalyser-api.onrender.com)

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Frontend → Vercel (Free Tier)

1. Go to vercel.com → New Project
2. Connect your GitHub repo and configure:

Setting	Value
Root Directory	frontend
Framework Preset	Vite (auto-detected)

3. Add Environment Variables in the Vercel dashboard:

Key	Value
VITE_API_BASE_URL	your Render backend URL

4. Click Deploy ✅

💡 Note: Render's free tier spins down after 15 minutes of inactivity. The first request after idle may take ~30 seconds.

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📁 Key Environment Variables

backend/.env

GEMINI_API_KEY=       # Required — Google Gemini API key
PORT=3000             # Port the server listens on

frontend/.env

VITE_API_BASE_URL=    # Required — Full URL of your backend (no trailing slash)
                      # Local:      http://localhost:3000
                      # Production: https://your-app.onrender.com

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🔒 Security Notes

• Resume files are never written to disk — processed in-memory via Multer's memoryStorage()
• Extracted text is cached in-memory per session with a 30-minute auto-expiry
• API keys are loaded via dotenv and must be set as environment variables on the hosting platform — never hard-coded
• File type validation rejects anything other than .pdf, .doc, .docx
• 10 MB file size limit enforced by Multer

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📜 License

MIT