Smart Nutri Food Order

A smart food ordering platform with an AI-powered nutritionist assistant

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Table of Contents

1. About The Project
2. Built With
3. Architecture
4. Getting Started
   • Prerequisites
   • Installation
5. Usage

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About The Project

Smart Nutri Food Order is a web platform that allows users to browse restaurants and their menus, place food orders, and get personalized meal recommendations from an AI-powered nutritionist assistant.

The platform supports three types of users:

• Admin — manages the platform and adds restaurant managers
• Restaurant Manager — manages their restaurant's menu and dishes
• Customer — browses restaurants, places orders, and interacts with the smart assistant

Smart Nutritionist Assistant

The highlight of the platform is the AI nutritionist — a RAG-based model powered by OpenAI. Customers can describe their nutritional needs (calories, proteins, sugar limits, etc.) and the assistant recommends real dishes available on the platform. The knowledge base is enriched with local restaurant and food data (e.g. Novi Sad area), making recommendations contextually relevant.

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Built With

Backend

Frontend

AI

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Architecture

Backend — Clean Architecture

The backend is built using .NET following the Clean Architecture pattern, organized into clearly separated layers:

📦 Solution
 ┣ 📂 Domain
 ┣ 📂 Application
 ┣ 📂 Infrastructure
 ┗ 📂 Web (API)

This structure ensures that business logic is fully decoupled from infrastructure concerns, making the codebase testable, maintainable, and easy to extend.

Frontend — Single Page Application

The frontend is an Angular SPA that communicates with the backend via REST API. It provides a seamless, dynamic user experience without full page reloads.

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Getting Started

Prerequisites

• .NET SDK (version 8 or later)
• Node.js & npm
• Angular CLI
• OpenAI API key

Installation

1. Clone the repository

   git clone https://github.com/anasinik/smart-nutri-food-order.git
   cd smart-nutri-food-order

2. Backend setup

   cd backend/FoodOrderApi/src/FoodOrderApi.Web

   Configure your connection string and OpenAI key in appsettings.json:

   {
    "AzureOpenAI": {
      "Endpoint": "https://your-resource.openai.azure.com/",
      "ApiKey": "your_azure_openai_api_key",
      "ModelName": "gpt-4o",
      "Deployment": "gpt-4o",
      "EmbeddingDeployment": "text-embedding-3-large",
      "ApiVersion": "2025-01-01-preview"
    }
   }

   Run the API:

   dotnet run

3. Frontend setup

   cd frontend
   npm install
   ng serve

4. Open your browser at http://localhost:4200

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Usage

• Register or log in as a customer to browse restaurants and place orders
• Use the Smart Nutritionist chat to find meals that fit your dietary goals — just describe what you're looking for (e.g. "high protein, under 600 calories") and the assistant will suggest available dishes from real restaurants
• Admin users can manage restaurant managers through the admin panel
• Restaurant managers can add and update their menu items

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