TasteVibe

Discover your next favorite dining spot with AI-powered restaurant recommendations and personalized chat assistance, all in one place.

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Inspiration

We were inspired by the challenge of making restaurant discovery more intuitive and personalized. In a world of endless dining options, we wanted to create a solution that combines AI intelligence with user preferences to help people discover their perfect dining experience effortlessly.

What it does

TasteVibe is an AI-powered restaurant recommendation platform that:

  • Provides personalized restaurant suggestions based on location
  • Offers interactive chat for natural language queries
  • Displays rich restaurant details including ratings, cuisines, and more
  • Delivers real-time, streaming AI responses for a conversational experience

How we built it

  • Frontend: React.js with Tailwind CSS for a responsive UI
  • AI Integration: Google Gemini 2.5 Pro for natural language processing
  • APIs: Qloo Places API for restaurant data
  • State Management: React Hooks for efficient state management
  • Deployment: GitHub Pages for easy access

Challenges we ran into

  1. API Integration: Handling rate limits and data consistency across different locations
  2. Streaming Responses: Implementing smooth, real-time AI responses
  3. UI/UX: Creating an intuitive interface that works across all devices
  4. Error Handling: Managing API failures and edge cases gracefully

Accomplishments that we're proud of

  • Successfully integrated multiple APIs to create a seamless experience
  • Built a responsive, accessible UI with smooth animations
  • Implemented real-time chat with streaming responses
  • Created a system that provides genuinely useful recommendations

What we learned

  • Advanced state management in React applications
  • Handling streaming API responses
  • Building accessible web applications
  • Working with geolocation and mapping services
  • Implementing responsive design principles

What's next for TasteVibe

  • [ ] Add user authentication for saving preferences
  • [ ] Implement restaurant booking integration
  • [ ] Add food delivery service options
  • [ ] Expand to include user reviews and ratings
  • [ ] Develop a mobile app version
  • [ ] Add support for dietary restrictions and preferences
  • [ ] Implement a recommendation algorithm that learns from user interactions

Built With

  • eslint
  • github
  • google-gemini-2.5-pro
  • node.js
  • npm
  • qloo-places-api
  • react-hooks
  • react-icons
  • react.js
  • tailwind-css
  • vite
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