khuda-lagche

Project Overview

This project aims to develop a web application that provides personalized recipe recommendations. It uses a combination of Next.js with TypeScript for the frontend, FastAPI for the backend, and AWS services including DynamoDB for database management and Amplify for frontend hosting.

Key Technologies

• Frontend: Next.js with TypeScript
• Backend: FastAPI
• Database: AWS DynamoDB
• Hosting: AWS Amplify for the frontend, AWS Elastic Beanstalk for the backend
• Machine Learning: Python (Scikit-Learn, TensorFlow, or PyTorch)
• Authentication: AWS Cognito

Getting Started

Prerequisites

• Node.js and npm
• Python 3.x
• AWS Account
• AWS CLI

Setting Up the Project

1. Clone the repository

   git clone https://github.com/thetajwar2003/khuda-lagche.git
   cd khuda-lagche

2. Install dependencies

   Frontend:

   cd frontend
   npm install

   Backend:

   cd backend
   pip install -r requirements.txt

3. Configure AWS

   Set up AWS credentials and configure the AWS CLI with your account.

4. Set up DynamoDB

   Create the necessary tables in DynamoDB.

5. Environment Variables

   Set up the required environment variables for both frontend and backend.

Running the Application

1. Start the Frontend

   cd frontend
   npm run dev

2. Start the Backend

   cd backend
   uvicorn main:app --reload

Features

Frontend

• User account management
• Recipe searching and browsing
• Recipe rating and saving
• Responsive UI

Backend

• RESTful API for user and recipe management
• Recipe recommendation engine
• Secure user data handling

Machine Learning

• Personalized recipe recommendations
• Continuous learning and adaptation

Deployment

• Frontend: Deploy on AWS Amplify
• Backend: Host on AWS Elastic Beanstalk