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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

architecture-dalle

Installation

  1. Clone the repository:

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

    cd dalle/client
npm install

cd ../server
npm install

  2. 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.

  3. Start the client and server:

    • In the client directory:

      npm run dev

    • In the server directory:

      npm start

  4. 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.