CodeGenius is an AI-powered application that generates high-quality code from natural language descriptions. It supports multiple programming languages, provides live syntax validation, and offers debugging assistance.

• Contextual Intent Recognition: Understands your requirements in natural language
• Multi-Language Code Generation: Supports JavaScript, TypeScript, Python, Java, C#, Go, Ruby, and more
• Live Syntax & Semantic Validation: Checks your code for errors and suggests improvements
• Interactive Debugging Support: Helps troubleshoot issues in your code
• Version Control Integration: Track your code changes
• Code Snippet Library & Templates: Store reusable code snippets for quick access
• Automated Unit Test Generation: Creates tests for your code automatically
• Security & Compliance Checks: Identifies potential security vulnerabilities
• Customizable AI Agent Workflows: Configure how the AI generates your code

• Node.js 20.x or higher
• npm 9.x or higher
• Hugging Face API Key (for AI features)

1. Clone the repository:

   git clone https://github.com/yourusername/codegenius.git
   cd codegenius

2. Install dependencies:

   npm install

3. Set up environment variables: Create a .env file in the root directory with the following:

   HUGGINGFACE_API_TOKEN=your_huggingface_api_token
   

4. Start the development server:

   npm run dev

5. Open your browser and navigate to http://localhost:5000

To run the application in production mode:

npm run build
npm start

1. Install electron and electron-builder:

   npm install --save-dev electron electron-builder

2. Create an electron entry file (electron.js) in the root directory:

   const { app, BrowserWindow } = require('electron');
   const path = require('path');
   const express = require('express');
   const server = require('./server/index.js');
   
   let mainWindow;
   
   function createWindow() {
     mainWindow = new BrowserWindow({
       width: 1200,
       height: 800,
       webPreferences: {
         nodeIntegration: true,
         contextIsolation: false
       }
     });
   
     mainWindow.loadURL('http://localhost:5000');
     mainWindow.on('closed', () => mainWindow = null);
   }
   
   app.on('ready', createWindow);
   
   app.on('window-all-closed', () => {
     if (process.platform !== 'darwin') app.quit();
   });
   
   app.on('activate', () => {
     if (mainWindow === null) createWindow();
   });

3. Update your package.json with electron configuration:

   {
     "main": "electron.js",
     "scripts": {
       "electron": "electron .",
       "package-win": "electron-builder --win --x64"
     },
     "build": {
       "appId": "com.yourdomain.codegenius",
       "productName": "CodeGenius",
       "win": {
         "target": "nsis",
         "icon": "assets/icon.ico"
       }
     }
   }

4. Build the Windows installer:

   npm run package-win

   The installer will be available in the dist folder.

To package the application for Android, we'll use Capacitor:

1. Install Capacitor:

   npm install --save @capacitor/core @capacitor/android
   npm install --save-dev @capacitor/cli

2. Initialize Capacitor in your project:

   npx cap init CodeGenius com.yourdomain.codegenius --web-dir dist

3. Build your web application:

   npm run build

4. Add Android platform:

   npx cap add android

5. Update the Android configuration:

   npx cap copy android
   npx cap sync android

6. Open Android Studio to build and run:

   npx cap open android

7. In Android Studio:

   • Build -> Build Bundle(s) / APK(s) -> Build APK(s)
   • Or Build -> Generate Signed Bundle/APK for release version

POST /api/code/generate
Content-Type: application/json

{
  "prompt": "Create a function that calculates the Fibonacci sequence",
  "language": "javascript",
  "generateTests": true
}

POST /api/code/validate
Content-Type: application/json

{
  "code": "function example() { console.log('Hello') }",
  "language": "javascript"
}

POST /api/code/generate-tests
Content-Type: application/json

{
  "code": "function sum(a, b) { return a + b; }",
  "language": "javascript"
}

The application uses a client-server architecture:

• Frontend: React with TypeScript, using tailwind CSS and shadcn components for the UI
• Backend: Express.js server with Qdrant for storage
• AI Model: Hugging Face models for code generation, validation, and test generation

MIT

1. Fork the repository
2. Create your feature branch: git checkout -b feature/my-new-feature
3. Commit your changes: git commit -am 'Add some feature'
4. Push to the branch: git push origin feature/my-new-feature
5. Submit a pull request