Solina AI

Solina AI is an emotional support web application designed to provide users with a safe space to express their feelings and receive support through AI-driven chat interactions. The application features a user-friendly interface, emotional tracking, and access to resources for mental well-being.

Project Structure

The project is divided into two main parts: the frontend and the backend.

Frontend

The frontend is built using React and TypeScript, and it includes the following key components:

• Chat: A chat interface for users to interact with Solina AI.

  • ChatWindow.tsx: Main chat interface.
  • MessageBubble.tsx: Displays individual messages.
  • InputField.tsx: Input field for user messages.

• Emotion Tracker: Components for tracking and displaying emotions.

  • EmotionDisplay.tsx: Shows the user's current emotional state.
  • MoodSelector.tsx: Allows users to select and log their mood.

• Navigation: Navigation components for the application.

  • Navbar.tsx: Top navigation bar.
  • Sidebar.tsx: Sidebar for navigation.

• Common Components: Reusable components.

  • Button.tsx: Reusable button.
  • Card.tsx: Reusable card for content display.
  • Loading.tsx: Loading indicator.

• Pages: Main pages of the application.

  • Home.tsx: Home page.
  • Chat.tsx: Chat page.
  • MoodHistory.tsx: Displays mood history.
  • Resources.tsx: Links to emotional support resources.
  • Profile.tsx: User profile management.
  • Auth: Authentication pages.
    • Login.tsx: User login page.
    • Register.tsx: User registration page.

• Hooks: Custom hooks for managing state.

  • useAuth.ts: Authentication logic.
  • useChat.ts: Chat functionality.
  • useEmotions.ts: Emotional state tracking.

• Context: Context providers for global state management.

  • AuthContext.tsx: Authentication context.
  • ChatContext.tsx: Chat context.

• Services: API and emotion-related services.

  • api.ts: Axios instance configuration.
  • emotionService.ts: Functions for emotional data management.

• Utilities: Helper functions and types.

  • helpers.ts: Utility functions.
  • index.ts: Type definitions.

• Styles: Global styles for the application.

  • globals.css: Global CSS styles.

Backend

The backend is built using Node.js and TypeScript, and it includes the following key components:

• Controllers: Handle business logic for different routes.

  • authController.ts: User authentication.
  • chatController.ts: Chat functionality.
  • emotionController.ts: Emotional data management.
  • userController.ts: User profile management.

• Routes: Define API endpoints.

  • authRoutes.ts: Authentication routes.
  • chatRoutes.ts: Chat-related routes.
  • emotionRoutes.ts: Emotional data routes.
  • index.ts: Consolidated routes.

• Models: Database models for the application.

  • User.ts: User model.
  • Conversation.ts: Conversation model.
  • Message.ts: Message model.
  • EmotionLog.ts: Emotion log model.

• Middleware: Middleware functions for request handling.

  • auth.ts: JWT verification.
  • errorHandler.ts: Global error handling.

• Services: External service integrations.

  • aiService.ts: AI functionality integration.
  • emotionAnalysisService.ts: Emotion analysis logic.

• Config: Configuration files.

  • database.ts: Database connection management.

• Utilities: Helper functions and types.

  • helpers.ts: Utility functions.
  • index.ts: Type definitions.

Getting Started

To get started with the Solina AI application, follow these steps:

1. Clone the repository:

   git clone <repository-url>
   

2. Navigate to the project directory:

   cd solina-ai
   

3. Install dependencies for the frontend:

   cd client
   npm install
   

4. Install dependencies for the backend:

   cd ../server
   npm install
   

5. Set up environment variables:

   • Copy .env.example to .env and fill in the required values.

6. Start the development servers:

   • Frontend:

     cd client
     npm run dev
     

   • Backend:

     cd ../server
     npm run dev
     

7. Open your browser and navigate to http://localhost:3000 to access the application.

Contributing

Contributions are welcome! Please submit a pull request or open an issue for any suggestions or improvements.

License

This project is licensed under the MIT License. See the LICENSE file for more details.