Roamify Extension

Roaming Redefined: Changing the Way the World Travels

Welcome to the official repository of Roamify Chrome Extension. This repository contains the code and documentation for our innovative approach to providing personalized travel recommendations using a chrome extension.

Table of Contents

• Introduction
• Directory Structure
• Extension Objectives
• Citing This Work
• Acknowledgements

Introduction

Roamify aims to revolutionize the travel experience by leveraging the power of machine learning to provide personalized recommendations through a google chrome extension.

Directory Structure

Extension/
│
├── backend
│   ├── app
│   │   ├── routes
│   │   │   └── process.py
│   │   ├── utils
│   │   │   ├── bert_processing.py
│   │   │   ├── llama_processing.py
│   │   │   ├── nlp_process.py
│   │   │   ├── llama_processing.py
│   │   │   ├── pipeline_processing.py
│   │   │   ├── setup_pytorch_environment.py
│   │   │   ├── t5_processing.py
│   │   │   └── test.py
│   │   ├── __init__.py
│   │   └── config.py
│   ├── .env
│   ├── Dockerfile
│   ├── requirements.txt
│   └── run.py
│
├── src
│   ├── assets
│   │   └── <icon>.svg
│   ├── scripts
│   │   ├── airport_dict.json
│   │   ├── background.js
│   │   ├── destination.js
│   │   ├── iata-icao-2.csv
│   │   ├── itinerary.js
│   │   ├── popup.js
│   │   ├── splash.js
│   │   └── transition.js
│   ├── styles
│   │   ├── itinerary.css
│   │   └── panel.css
│   ├── destination.html
│   ├── itinerary.html
│   ├── manifest.json
│   ├── options.html
│   └── panel.html
│
├── .gitignore
├── LICENSE
├── README.md
└── requirements.txt

Extension Objectives

1. User-Friendly and Minimal Design: Ensure the extension is easy to use for individuals of all age groups by maintaining a clean and intuitive interface.
2. Simplified Itinerary Creation: Provide features that make it easier for users to create and manage travel itineraries with minimal effort.
3. Real-Time Data Scraping: Enable the extension to directly scrape data from the current Google tab to generate detailed and relevant itineraries.

Citing This Work

If you use our work in your research or project, please cite it as follows:

@inproceedings{roamifyredefined2024,
  title={Roamify: Roaming Redefined},
  author={Vikranth Udandarao, Harsh Mistry, Muthuraj Vairamuthu, Noel Tiju, Armaan Singh, and Dhruv Kumar},
  year={2024},
  organization={IIIT Delhi, Computer Science Engineering Dept}
}

Acknowledgements

We would like to thank our academic institution, IIIT Delhi, and our guide, Dr. Dhruv Kumar for their support and contributions to this research.

For more information on our research and publications, please visit our Roamify Machine Learning repository.