DineBot

My project for the completion of my Node.js internship at Celebal Technologies 2025

• Website is live on : link

Note: Backend may not work because it is on free tier & only runs for 60 compute minutes/day.

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Sample Images (of the frontend:

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Instructions received for the project:

This handy restaurant bot simplifies your dining experience. It helps you find restaurants, browse menus, make reservations, and even place orders for delivery or pickup, all within a user-friendly chat interface.

• Restaurant Discovery: Search for restaurants by cuisine, location, price range, or specific keywords.
• Menu Exploration: Access digital menus with clear descriptions, pictures, and customer reviews.
• Reservation Management: Make reservations for your desired date and time, specifying any special requests.
• Ordering Made Easy: Place orders for delivery or pickup directly through the bot, adding or removing items with ease.
• Payment Integration: Securely pay for your order using a connected payment method within the chat interface.
• Order Tracking: Receive real-time updates on the status of your order, from confirmation to delivery (or pickup notification).
• Table Management: Manage your reservations and orders in one place, allowing for easy cancellations or modifications.
• Personalized Recommendations: Based on your past choices and preferences, the bot can suggest relevant restaurants and dishes.

Start the Project:

• Create .env in both frontend & backend workspaces

• After adding all the required details in the .env files

  • Backend :

    DB_HOST=db_host_name
    DB_USER=db_user_name
    DB_PASSWORD=_db_password
    DB_NAME=db_name
    DB_PORT=db_port_number
    BACKEND_PORT=port_number
    BASE_URL=backend_base_url
    JWT_SECRET=jwt_secret
    JWT_REFRESH_SECRET=jwt_refresh_secret
    AZURE_CLU_KEY=azure_clu_key
    AZURE_CLU_PROJECT_NAME=azure_clu_project_name
    AZURE_CLU_DEPLOYMENT_NAME=azure_clu_project_deployment_name
    AZURE_CLU_ENDPOINT=azure_clu_endpoint
    

  • Frontend :

    REACT_APP_AZURE_BACKEND_API=your_backend_api
    

• Run these on the terminal in the root directory of the project:

  npm install
  npm run dev:all
  

Technologies Used:

• Node.js
• Express.js
• React.js
• MySQL
• Microsoft Azure (conversation language understanding)
• REST APIs
• Microsoft Bot Emulator
• Postman (testing APIs)

Other Dependencies:

• Backend

  • azure/ai-language-conversations
  • bcrypt
  • body-parser
  • botbuilder
  • cookie-parser
  • cors
  • dotenv
  • express
  • express-rate-limit
  • express-slow-down
  • jsonwebtoken
  • mysql2
  • nodemon (dev dependency)

• Frontend

  • @testing-library/dom
  • @testing-library/jest-dom
  • @testing-library/react
  • @testing-library/user-event
  • lucide-react
  • react
  • react-dom
  • react-router-dom
  • react-scripts
  • web-vitals

TODO

• Core Setup & Tools

  • Install JavaScript dependencies (express, cors, botbuilder, bcrypt, nodemon)
  • Set up Bot Framework Emulator for local testing
  • Configure MySQL Database
  • Initialise Node.js Project
  • Connect Node.js to MySQL (using mysql2)
  • Basic User Authentication
  • User Auth using Bot
  • Persistent User Profile for each unique session
  • Make the bot conversationally stateful (creating a bias b/w each conversation thread from the intial indentified intent)

• Model Training

  • Setup Azure CLU service
  • Implement intents, entities, & training utterances
  • Train CLU model
  • Deploy CLU service
  • Integrate CLU service to bot

• Backend

  • Basic Security

    • Hashing & Salting
    • Rate Limiting
    • Delay spamming queries
    • Use parametrised SQL queries
    • Implement Intents
      • None (or FallbackIntent)
      • GeneralGreeting

  • Restaurant

    • Design MySQL relations (restaurants, locations, cuisines, reviews)
    • Implement basic restraunt discovery using user inputs
    • Implement all restraunt discovery (eg, "Show all restaurants")
    • Implement location based discovery using user input (eg, "Chinese food near me")
    • Restaurant search based on
      • Restaurant Name
      • Cuisine
      • Location or City
      • Price range
      • Rating
    • Implement Intents
      • SearchRestaurant

  • Menu

    • Create MySQL relations (menus, menu_items, item_images, item_reviews)
    • Display Menu description, image, price, user ratings
    • Implement Intents
      • ShowMenu

  • Reservation

    • Create MySQL relation (reservation)
    • Implement Intents
      • MakeReservation
      • CancelReservation
      • ModifyReservation
      • ShowReservations

  • Orders

    • Create MySQL relation (orders)
    • Implement Intents
      • CancelOrder
      • CheckOrderStatus

  • Cart

    • Implement memory for conversation
    • Implement Intents
      • AddToCart
      • RemoveFromCart
      • ViewCart
      • EditCart
      • ClearCart

  • Payment

    • Implement MySQL relation (payments)
    • Implement Intents
      • CheckPaymentStatus
      • PayOrder

  • Recommendations

    • Implement MySQL relation (user_behavior)
    • Track user's behavior
      • Menus viewed
      • Ordered items
    • Rule-based recommendation
    • Implement Intents
      • RecommendItem

• Frontend

  • Home: Home page of the application
  • NotFound: Fallack for undefined addresses
  • RestaurantBotCard: Selection of restaurant chatbot on home page
  • ChatHeader: Bot name, status indicator
  • ChatBubbles: Bubbles from either side's messages
  • ChatWindow: Chat container for messaging UI.
    • Implement up & down arrows to cycle through messages
  • Refresh Token funcitonality

• Deployment

  • Deploy CLU service to Azure Language Services
  • Deploy the bot to Azure Bot Services
  • Deploy frontend on Azure
  • Deploy backend on Azure
  • Deploy MySQL databse on Azure MySQL Flexible Server
  • Set up CD (Continuous Deployment) on Azure
  • Integrate them together