A Next.js 14 web application that leverages Google's Gemini AI model to provide context-aware AI interactions through multiple specialized personalities. The application uses the gemini-2.0-flash
model for fast, efficient responses.
Each personality has unique characteristics and response patterns:
- Role: Advanced neural engine with 1.6T parameters
- Focus: Technical precision and authoritative responses
- Temperature: 0.4 (high precision)
- Style: Formal, technical, with quantum-processing references
- Role: Professional guide and information provider
- Focus: Clear, direct communication
- Temperature: 0.3 (highest precision)
- Style: Welcoming, straightforward, no theatrical elements
- Role: Apple-style technical advisor
- Focus: User experience and elegant solutions
- Temperature: 0.5 (balanced)
- Style: Minimalist, design-conscious communication
- Role: Programming mentor
- Focus: Code patterns and best practices
- Temperature: 0.7 (more creative)
- Style: Step-by-step explanations with practical examples
- Role: Mathematical concepts educator
- Focus: Rigorous mathematical explanations
- Temperature: 0.6 (moderately creative)
- Style: Formal proofs with LaTeX notation support
- Role: Machine learning researcher
- Focus: ML algorithms and architectures
- Temperature: 0.7 (more creative)
- Style: Technical deep-dives with visualizations
- Next.js 14.1.0 with TypeScript
- Google Generative AI (Gemini) integration
- Server-side and client-side rendering optimization
- Environment variable management for API keys
- Dark theme by default with Tailwind CSS
- shadcn/ui component library integration
- Real-time progress indicators
- Battery status monitoring
- Markdown rendering for formatted responses
- Responsive design with mobile support
- Client-side state management
- Optimized API response handling
- Progressive loading indicators
- Error boundary implementation
- ESLint configuration
- TypeScript strict mode
- Proper error handling and logging
- Development environment setup
Required environment variables:
NEXT_PUBLIC_GEMINI_API_KEY=your_api_key_here
- Clone the repository
- Install dependencies:
npm install
- Set up environment variables
- Run development server:
npm run dev
- Build for production:
npm run build
The application is configured for deployment on Vercel with:
- Automatic build optimization
- Static page generation where possible
- API routes for dynamic content
- Build cache management