Flavor Match

Discover your next favorite dish with AI

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Problem:

Food enthusiasts and home cooks struggle to find similar dishes in indian Cuisne that match their taste preferences and dietary restrictions across different cuisines, leading to limited culinary exploration and repetitive meal choices.

Target users:

Primarily food enthusiasts, Restaurant owners, health-conscious individuals, and home cooks who want to explore similar dishes while maintaining their dietary preferences (vegetarian/non-vegetarian).

Solution Highlight:

FlavorMatch uses AWS Bedrock's Titan model to generate high-quality food images and Claude-3 for intelligent dish recommendations, helping users visualize and discover similar dishes while respecting their dietary preferences through vector similarity search.

🍽️ FlavorMatch

FlavorMatch is an AI-powered food recommendation system that helps users discover similar dishes based on ingredients, cuisine types, and dietary preferences. Using advanced natural language processing and image generation capabilities, it provides personalized food suggestions along with visually appealing representations of recommended dishes.

🌟 Features

  • Intelligent Food Matching: Utilizes sentence transformers and vector similarity search to find similar dishes
  • Dietary Preference Support: Handles both vegetarian and non-vegetarian preferences
  • AI-Generated Food Images: Creates high-quality food images using AWS Bedrock's Titan model
  • Smart Description Generation: Provides detailed dish descriptions using Claude-3 AI
  • Vector Search: Efficient similarity search using MongoDB Atlas vector search capabilities

AWS Bedrock Models

  • Ensure your AWS account has access to:
    • Claude-3 Sonnet model for text generation
    • Titan Image Generator for food images

🤝 Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository
  2. Create a new branch (git checkout -b feature/improvement)
  3. Make your changes
  4. Commit your changes (git commit -am 'Add new feature')
  5. Push to the branch (git push origin feature/improvement)
  6. Create a Pull Request

🙏 Acknowledgments

  • AWS Bedrock team for AI capabilities
  • MongoDB Atlas for vector search functionality
  • Sentence Transformers library
  • Flask community

📧 Contact

For questions or feedback, please open an issue on GitHub or contact aditya.kommu@gmail.com

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