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The application uses the Gemini AI model from Google for image generation and modification.\n\n## Features\n\n- **AI Image Generation**: Generate completely new images based on text prompts\n- **AI Image Modification**: Upload existing images and modify them using text prompts\n- **Cloud Storage**: All generated and modified images are stored in Cloudinary\n- **Responsive Design**: Works seamlessly across desktop and mobile devices\n\n## Project Structure\n\nThe project is structured into two main parts:\n\n### Frontend (Angular)\n\n- Built with Angular v20\n- Uses TailwindCSS for styling\n- Communicates with the backend API for image processing\n\n### Backend (Node.js)\n\n- Express.js server\n- MongoDB database for storing image metadata\n- Google Generative AI (Gemini) for image generation and modification\n- Cloudinary for image storage\n\n## Technologies Used\n\n- **Frontend**:\n  - Angular v20\n  - TailwindCSS\n  - RxJS\n  \n- **Backend**:\n  - Node.js\n  - Express.js\n  - MongoDB/Mongoose\n  - Google Generative AI (@google/genai)\n  - Cloudinary\n  - Multer for file handling\n\n## Getting Started\n\n### Prerequisites\n\n- Node.js (v14 or later)\n- MongoDB instance\n- Google Gemini API key\n- Cloudinary account\n\n### Installation\n\n1. Clone the repository\n\n   ```bash\n   git clone https://github.com/yourusername/ai-image-studio.git\n   cd ai-image-studio\n   ```\n\n2. Install frontend dependencies\n\n   ```bash\n   npm install\n   ```\n\n3. Install backend dependencies\n\n   ```bash\n   cd backend\n   npm install\n   ```\n\n4. Set up environment variables:\n   - Copy the `.example.env` to `.env` in the backend directory\n   - Fill in your credentials:\n\n     ```env\n     MONGO_URI=your_mongodb_connection_string\n     GEMINI_API_KEY=your_google_gemini_api_key\n     CLOUDINARY_CLOUD_NAME=your_cloudinary_cloud_name\n     CLOUDINARY_API_KEY=your_cloudinary_api_key\n     CLOUDINARY_API_SECRET=your_cloudinary_api_secret\n     PORT=5000\n     ```\n\n### Running the Application\n\n1. Start the backend server\n\n   ```bash\n   cd backend\n   npm run dev\n   ```\n\n2. Start the Angular frontend (in another terminal)\n\n   ```bash\n   cd ..  # Return to the project root\n   npm start\n   ```\n\n3. Open your browser at `http://localhost:4200`\n\n## API Endpoints\n\n- `POST /api/image/generate`: Generate an image from a text prompt\n- `POST /api/image/modify`: Modify an uploaded image using a text prompt\n- `GET /api/image/all`: Get all previously generated and modified images\n\n## Deployment\n\nThe application is deployed using Vercel:\n\n- Frontend: \u003chttps://ai-image-studio-app-app.vercel.app\u003e\n- Backend: \u003chttps://ai-image-studio-app-api.vercel.app\u003e\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\n## Author\n\nCreated by Manthan Ankolekar\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmanthanank%2Fai-image-studio-app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmanthanank%2Fai-image-studio-app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmanthanank%2Fai-image-studio-app/lists"}