DALL-E Clone

Overview

DALL-E Clone is a web application that leverages the power of the OpenAI API to generate imaginative images based on textual prompts. Users can create unique images through a user-friendly interface and share them with the community. This project is built using the MERN stack (MongoDB, Express, React, Node.js) and allows users to explore a collection of stunning and imaginative images generated by DALL-E AI.

Features

• Generate Images: Create imaginative images by providing textual prompts.
• Share with Community: Share the generated images with the DALL-E Clone community.
• Browse Image Collection: Explore a collection of visually stunning images.
• Search Functionality: Easily find specific posts using the search feature.
• Responsive Design: The application is designed to work seamlessly on various devices.

Architecture

Installation

1. Clone the repository:

• git clone https://github.com/kumaarbalbir/dalle.git

2. Navigate to the client and server directories and install dependencies:

   cd dalle/client
   npm install
   
   cd ../server
   npm install

3. Create a .env file in the server directory with the following environment variables:

   • MONGODB_URL: Your MongoDB connection URL.
   • OPENAI_API_KEY: Your OpenAI API key.
   • CLOUDINARY_CLOUD_NAME: Your Cloudinary cloud name.
   • CLOUDINARY_API_KEY: Your Cloudinary API key.
   • CLOUDINARY_API_SECRET: Your Cloudinary API secret.

4. Start the client and server:

   • In the client directory:

     npm run dev

   • In the server directory:

     npm start

5. Access the application in your web browser at http://localhost:3000 or provided localhost:@port (for client and server)

Usage

1. Visit the provided URL.

2. Generate Imaginative Images:

   • Provide a prompt for generating an image.
   • Click "Generate" to create the image.
   • Share your imaginative creations with the community.

3. Explore the Collection:

   • Browse through a collection of visually stunning images.

4. Search Posts:

   • Use the search bar to find posts by name or prompt.

Technologies Used

• MongoDB
• Express.js
• React
• Node.js
• OpenAI API
• Cloudinary
• Vite (for client development)
• Tailwind CSS

Acknowledgments

• Special thanks to the OpenAI team for providing access to the DALL-E API.
• Thanks to the open-source community for the libraries and tools used in this project.