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AI Email Generator

Comprehensive, full-stack Software-as-a-Service (SaaS) application designed to automate and elevate professional correspondence.

Overview · Features · Architecture · Screenshots · Getting Started · Environment Variables · Documentation

Overview

AI Email Generator is a full-stack SaaS platform that helps users organize their emails, generate AI-assisted replies, and manage personalized correspondence using custom tones and personas.

The codebase is structured as a monorepo with two independently deployable services:

Component Technology Role
Frontend React 19, custom CSS SPA with login, dashboards, email generation interface, 3D premium styling, protected routes, and responsive design.
Backend Node.js 18+, Express REST API handling auth (JWT), session management, OpenAI integration, and password recovery.

Features

Core Generation

  • AI Replies — Context-aware, highly personalized email replies generated instantly by providing the incoming email context.
  • Customization — Configurable tone and persona presets that control how AI outputs are formatted and structured.

Dashboard and UI

  • Premium Aesthetics — 3D-styled user interface, glassmorphism, and a global dark/light theme toggle.
  • Rich Text Editing — Pre-send email formatting capabilities using React Quill integration.

Security and Quality

  • JWT Authentication — Secure account creation and session management using JSON Web Tokens and Bcrypt.js.
  • Password Recovery — Automated reset links sent securely via Nodemailer.

Architecture

The platform follows a decoupled client-server architecture:

Technology Stack

Layer Frontend Backend
Runtime / Framework React 19 Node.js, Express.js
Data / State React Context/Hooks MongoDB, Mongoose
Routing React Router DOM Express Router
UI / Styling Custom CSS (Premium 3D)
Rich Text React Quill
Icons Lucide React
HTTP / Auth Axios JWT, bcryptjs
AI Integration OpenAI API
Email Service Nodemailer

Screenshots

Login Page Dashboard
Login Page Dashboard
Profile Details
Profile Details

Repository Structure

AI email generator/
├── README.md
├── screenshots/              # Add your images here
├── Backend/
│   ├── controllers/          # HTTP handlers
│   ├── models/               # Mongoose schemas
│   ├── routes/               # Route definitions
│   ├── middleware/           # Auth and validation middleware
│   ├── .env                  # Backend configuration
│   └── index.js              # Application entry point
└── Frontend/
    ├── public/               # Static assets
    ├── src/
    │   ├── components/       # Layout, UI, and feature modules
    │   ├── pages/            # Route-level views
    │   ├── App.jsx           # Main React component
    │   └── index.css         # Global styles and 3D UI
    ├── .env                  # Frontend configuration
    └── package.json

Getting Started

Prerequisites

  • Node.js (v16.0.0 or higher recommended)
  • MongoDB (Local instance or MongoDB Atlas)
  • Active OpenAI API Key
  • SMTP Credentials (for password recovery emails)

1. Clone the Repository

git clone <repository_url>
cd "AI email generator"

2. Backend Setup

cd Backend
npm install

Create a .env file and fill in the required values (see the Environment Variables section below).

npm run dev

The API server starts on the port defined in .env (default is 5000).

3. Frontend Setup

cd ../Frontend
npm install

Create a .env file (if required) and configure your variables.

npm start

Open the provided local URL, typically http://localhost:3000.

Environment Variables

Backend (Backend/.env)

Variable Description
PORT Port the API server listens on (e.g., 5000)
MONGO_URI MongoDB connection string
JWT_SECRET Secret key for access token signing
OPENAI_API_KEY Your OpenAI API key
EMAIL_USER SMTP email address for password recovery
EMAIL_PASS SMTP email password or app password

Frontend (Frontend/.env) (Currently utilizes hardcoded proxy or direct calls to http://localhost:5000)

Documentation

Document Description
Backend/README.md Backend architecture and API reference
Frontend/README.md Frontend component structure and client configuration

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