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My Contribution

This mental health chatbot was developed as a collaborative software engineering project.
My responsibilities focused on the design, implementation, and validation of core system components, particularly those related to user interaction and chatbot functionality.

Key contributions include:

  • Design and implementation of chatbot conversation logic and response handling workflows
  • Development of mood tracking functionality and structured user input flows
  • Frontend implementation of the chat interface using component-based design principles
  • Integration of the frontend with chatbot APIs and backend services using RESTful communication
  • Implementation of input validation and basic error handling to improve system robustness
  • Testing, debugging, and refinement of chatbot responses and interaction flows

Project Setup (React + Vite)

The system is built using React with Vite to support a modern, efficient development workflow. Vite provides fast builds, Hot Module Replacement (HMR), and a streamlined configuration suitable for scalable web applications.

Tooling and Plugins

  • @vitejs/plugin-react for React support with Babel-based Fast Refresh
  • @vitejs/plugin-react-swc for improved performance using the SWC compiler

Development Considerations

  • Modular and reusable component architecture
  • Clear separation of concerns between UI components and API communication logic
  • Emphasis on maintainability, readability, and extensibility of the codebase

ESLint Configuration

For production-level development, the project structure supports extending the linting setup with TypeScript and type-aware rules. The official Vite React TypeScript template can be used to integrate:

  • TypeScript for static type checking
  • typescript-eslint for enhanced linting and code quality enforcement

About

A mental health support chatbot that provides conversational support, mood tracking, and mental wellness resources through a user-friendly web interface. Built as a software engineering coursework project.

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  • HTML 60.4%
  • JavaScript 37.9%
  • CSS 1.7%