Certif-Eye 👀

• We have created an AI-powered platform dedicated to identifying and verifying the authenticity of restaurant reviews. On this website, users can:

  Check Review Authenticity - Input review text to get an authenticity score.

  Browse Restaurant Information - View ratings, reviews, and word clouds for specific restaurants.

  Analyze Review Trends - Understand overall restaurant ratings through visualized data.

👀 Feature Introduction

• Review Analysis:
  • Input review text for authenticity analysis
  • Display authenticity score for reviews
• Restaurant Information:
  • Show restaurant location, ratings, and reviews
  • Generate word clouds from reviews
  • Display restaurant's percentile ranking among all ratings
• Map Functionality:
  • Display restaurant locations
• Interface:
  • Responsive design
  • Intuitive user interface
• Automated Web Scraping:
  • Regularly collect new restaurant reviews from popular platforms
  • Update database with fresh review data
  • Ensure up-to-date analysis and trends

👀 Frameworks / Modules / Third-Party Packages Used

Frontend:

• React.js, Next.js
• UI components: shadcn-ui
• Map functionality: @vis.gl/react-google-maps

Backend:

• Flask API
• Machine Learning model: PyTorch
• Data processing: pandas, numpy
• Natural Language Processing: googletrans, wordcloud
• Web scraping: Beautiful Soup, Selenium

Development Tools:

• Code formatting and linting: eslint, prettier
• Type checking: typescript

👀 How to Install and Test on Localhost

1. Clone this repository:

   git clone https://github.com/guan404ming/certif-eye.git
   cd certif-eye
   

2. Set up environment variables in frontend:

   • cd frontend
   • Create a .env file in the frontend root
   • Add necessary environment variables (e.g., database URL, API keys, etc.)

3. Install and run the development servers:

   • Frontend:

     cd frontend
     bun install
     bun run next-dev
     

   • Backend:

     cd backend
     pip3 install -r requirements.txt
     python3 -m flask --app api/index run -p 5328
     

4. Open http://localhost:3000 with your browser to see the result.

👀 Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

👀 License

MIT