flowchart TB
    subgraph "Registration & Authentication"
        register((User Registration)) --> verify{Verify Phone Number}
        verify --> authenticate[Authentication]
    end

    subgraph "Input Data"
        questionnaire(Questionnaire) --> categorize[User Categorization]
        tests(Medical Tests) --> categorize
    end

    subgraph "Data Processing"
        categorize --> score(Scored Food Options)
        score --> generate[Recommendation Generation]
    end

    subgraph "Output"
        generate --> recommendations(Food Recommendations)
    end

    subgraph "Interaction"
        userQueries(User Queries) --> recommendations
        feedback(Feedback Loop) --> generate
    end

    register --> authenticate
    questionnaire -.-> generate
    tests -.-> generate

The app, is a dietary management application designed to assist users in making informed food choices based on their individual nutritional needs and preferences. It utilizes a combination of user input, nutritional data, and personalized scoring algorithms to generate tailored recommendations for optimal health outcomes.

Authentication: Users phone numbers are verified to access the AI chat on Whatsapp.

1. User Categorization: Based on the questionnaire responses and medical test results, users are categorized into health groups.
2. Food Scoring: The app scores each food item in its database based on various factors such as nutritional content, sugar response, fat response, and gut response.
3. Recommendation Generation: Using the user's health group and dietary preferences, the app generates personalized food recommendations.

1. Scored Food Options: Users receive a list of scored food options, sorted based on their suitability for the user's health group and dietary preferences.
2. Food Recommendations: The app provides recommendations for food combinations that align with the user's health goals and preferences.

1. User Queries: Users can query the app for specific food items or meal recommendations tailored to their needs.
2. Feedback Loop: Users can provide feedback on recommended food items, helping to refine recommendations.

• Personalization: Tailored recommendations based on individual health profiles and dietary preferences.
• Scalability: The app can accommodate a growing user base while maintaining performance and accuracy.
• Feedback Mechanism: Continuous improvement through user feedback loops to enhance recommendation accuracy.
• Secure Authentication: Robust phone number-based authentication ensures user data security.