Many times I've been cooking and I've messed up somewhere, I couldn't find help instantly, so thats what inspired me for creating this webapp where people can share their experiences and find help instantly. We also added a gamification so that the users dont get bored.

What it does

You can Instantly find help via a video call you will be connected to professional chefs all over the world, with the forum functionality you can contribute to the website by sharing your experiences for which you may earn coins, every week the top contributors may get cool goodies :) , you can also search for various recipes, for each detailed description like calories, weight along with instructions and ingredients will be also displayed so the detailed insight is provided. And if you are bored or stuck on what to prepare, we randomly suggest a dish for you.

How I built it

(Assuming for Mom's Sphagetti) the tech and libraries we used are:

  1. Python
  2. HTML
  3. CSS
  4. JavaScript
  5. JQuery
  6. Random Dish API
  7. Recipes API
  8. Bootstrap
  9. Django
  10. VidyoConnector API
  11. WEBRTC
  12. Sqlite3
  13. Netlify
  14. Font Awesome Icons

Initially we brainstormed for the frontend and we finalised the design, then we starting jotting down all the requirements the funtional requirements and we started working on implementing all of them. At the end to make the experience a bit of fun, we added gamification and random suggestor. Finally we prepared a website in javascript, html, css called vidyo connector and hosted on netlify.

Challenges I ran into

Implementing the leaderboard and the gamification aspects of the website and also the video chat was a bit tricky.

Accomplishments that I'm proud of

I've never implemented Gamification in any of my projects, this is the most proudest thing and developer can get i.e. making user experience hell lot of fun.

What I learned

How to increase the UserExperience, Important tricks to retain users. How to implement gamification aspects.

What's next for Help-Me-Mom

Store their experiences and suggest the next best option for preparing dish, Machine learning model to recognize the dish with Image

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