Rootski - Full codebase for rootski.io (without the data)

Overview

breakdown-svg

📣 Welcome to the Rootski codebase!

This is the codebase for the application running at rootski.io.

🗒 Note: You can find information and training on the architecture, ticket board, development practices, and how to contribute on our knowledge base.

Rootski is a full-stack application for studying the Russian language by learning roots.

Rootski uses an A.I. algorithm called a "transformer" to break Russian words into roots. Rootski enriches the word breakdowns with data such as definitions, grammar information, related words, and examples and then displays this information to users for them to study.

How is the Rootski project run? (Hint, get involved here 😃 )

Rootski is developed by volunteers!

We use Rootski as a platform to learn and mentor anyone with an interest in frontend/backend development, developing data science models, data engineering, MLOps, DevOps, UX, and running a business. Although the code is open-source, the license for reuse and redistribution is tightly restricted.

The premise for building Rootski "in the open" is this: possibly the best ways to learn to write production-ready, high quality software is to

  1. explore other high-quality software that is already written
  2. develop an application meant to support a large number of users
  3. work with experienced mentors

For better or worse, it's hard to find code for large software systems built to be hosted in the cloud and used by a large number of customers. This is because virtually all apps that fit this description... are proprietary 🤣 . That makes (1) hard.

(2) can be inaccessible due to the amount of time it takes to write well-written software systems without a team (or mentorship). If you're only interested in a sub-part of engineering, or if you are a beginner, it can be infeasible to build an entire production system on your own. Think of this as working on a personal project... with a bunch of other fun people working on it with you.

Contributors

Onboarded and contributed features :D

  • Eric Riddoch - Been working on Rootski for 3 years and counting!
  • Ryan Gardner - Helping with all of the legal/business aspects and dabbling in development

Friends

Completed a lot of the Rootski onboarding and chat with us in our Slack workspace about miscellanious code questions, careers, advice, etc.

  • Isaac Robbins - Learning and building experience in MLOps and DevOps!
  • Colin Varney - Full-stack python guy. Is working his first full-time software job!
  • Fazleem Baig - MLOps guy. Quite experienced with Python and learning about AWS. Working for an AI startup in Canada.
  • Ayse (Aysha) Arslan - Learning about all things MLOps. Working her first MLE/MLOps job!
  • Sebastian Sanchez - Learning about frontend development.
  • Yashwanth (Yash) Kumar - Finishing up the Georgia Tech online masters in CS.






The Technical Stuff

How to deploy an entire Rootski environment from scratch

Going through this, you'll notice that there are several one-time, manual steps. This is common even for teams with a heavily automated infrastructure-as-code workflow, particularly when it comes to the creation of users and storing of credentials.

Once these steps are complete, all subsequent interactions with our Rootski infrastructure can be done using our infrastructure as code and other automation tools.

1. Create an AWS account and user

  1. Create an IAM user with programmatic access
  2. Install the AWS CLI
  3. Run aws configure --profile rootski and copy the credentials from step (1). Set the region to us-west-2.

🗒 Note: this IAM user will need sufficient permissions to create and access the infrastructure that will be discussed below. This includes creating several types of infrastructure using CloudFormation.

2. Create an SSH key pair

  1. In the AWS console, go to EC2 and create an SSH key pair named rootski.
  2. Download the key pair.
  3. Save the key pair somewhere you won't forget. If the pair isn't already named, I like to rename them and store them at ~/.ssh/rootski/rootski.id_rsa (private key) and ~/.ssh/rootski/rootski.id_rsa.pub (public key).
  4. Create a new GitHub account for a "Machine User". Copy/paste the contents of rootski.id_rsa.pub into any boxes you have to to make this work :D this "machine user" is now authorized to clone the rootski repository!

3. Create several parameters in AWS SSM Parameter Store

Parameter Description
/rootski/ssh/private_key The contents of the private key needed to clone the rootski repository.
/rootski/prod/database_config A stringified JSON object with database connection information (see below)
{
    "postgres_user": "rootski-db-user",
    "postgres_password": "rootski-db-pass",
    "postgres_host": "database.rootski.io",
    "postgres_port": "5432",
    "postgres_db": "rootski-db-database-name"
}

4. Purchase a domain name that happens to be rootski.io

You know, the domain name rootski.io is hard coded in a few places throughout the Rootski infrastructure. It felt wasteful to parameterize this everywhere since... it's unlikely that we will ever change our domain name.

If we ever have a need for this, we can revisit it :D

5. Create an ACM TLS certificate verified with the DNS challenge for *.rootski.io

You'll need to do this in the AWS console. This certificate will allow us to access rootski.io and all of its subdomains over HTTPS. You'll need the ARN of this certificate for a later step.

4. Create the rootski infrastructure

Before running these commands, copy/paste the ARN of the *.rootski.io ACM certificate into the appropriate place in infrastructure/iac/cloudformation/front-end/static-website.yml.

# create the S3 bucket and Route53 hosted zone for hosting the React application as a static site
...

# create the AWS Cognito user pool
...

# create the AWS Lightsail instance with the backend database (simultaneously deploys the database)
...

# deploy the API Gateway and Lambda function
...

5. Deploy the frontend site

make deploy-frontend

DONE!

Owner
Eric
In modern Applied Mathematics, we specialize in algorithms. I'm a data scientist with a strong background in algorithm design and software development.
Eric
XLNet: Generalized Autoregressive Pretraining for Language Understanding

Introduction XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective.

Zihang Dai 6k Jan 07, 2023
An easier way to build neural search on the cloud

An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g

Jina AI 17.1k Jan 09, 2023
Paradigm Shift in NLP - "Paradigm Shift in Natural Language Processing".

Paradigm Shift in NLP Welcome to the webpage for "Paradigm Shift in Natural Language Processing". Some resources of the paper are constantly maintaine

Tianxiang Sun 41 Dec 30, 2022
Code for the Python code smells video on the ArjanCodes channel.

7 Python code smells This repository contains the code for the Python code smells video on the ArjanCodes channel (watch the video here). The example

55 Dec 29, 2022
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Hugging Face 15k Jan 02, 2023
"Investigating the Limitations of Transformers with Simple Arithmetic Tasks", 2021

transformers-arithmetic This repository contains the code to reproduce the experiments from the paper: Nogueira, Jiang, Lin "Investigating the Limitat

Castorini 33 Nov 16, 2022
Extract city and country mentions from Text like GeoText without regex, but FlashText, a Aho-Corasick implementation.

flashgeotext ⚡ 🌍 Extract and count countries and cities (+their synonyms) from text, like GeoText on steroids using FlashText, a Aho-Corasick impleme

Ben 57 Dec 16, 2022
Modular and extensible speech recognition library leveraging pytorch-lightning and hydra.

Lightning ASR Modular and extensible speech recognition library leveraging pytorch-lightning and hydra What is Lightning ASR • Installation • Get Star

Soohwan Kim 40 Sep 19, 2022
A python script that will use hydra to get user and password to login to ssh, ftp, and telnet

Hydra-Auto-Hack A python script that will use hydra to get user and password to login to ssh, ftp, and telnet Project Description This python script w

2 Jan 16, 2022
DaCy: The State of the Art Danish NLP pipeline using SpaCy

DaCy: A SpaCy NLP Pipeline for Danish DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Ar

Kenneth Enevoldsen 71 Jan 06, 2023
jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese.

jel: Japanese Entity Linker jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese. Usage Currently, link and question methods

izuna385 10 Jan 06, 2023
Russian words synonyms and antonyms

ru_synonyms Russian words synonyms and antonyms. Install pip install git+https://github.com/ahmados/rusynonyms.git Usage from ru_synonyms import Anto

sumekenov 7 Dec 14, 2022
customer care chatbot made with Rasa Open Source.

Customer Care Bot Customer care bot for ecomm company which can solve faq and chitchat with users, can contact directly to team. 🛠 Features Basic E-c

Dishant Gandhi 23 Oct 27, 2022
Pytorch version of BERT-whitening

BERT-whitening This is the Pytorch implementation of "Whitening Sentence Representations for Better Semantics and Faster Retrieval". BERT-whitening is

Weijie Liu 255 Dec 27, 2022
COVID-19 Chatbot with Rasa 2.0: open source conversational AI

COVID-19 chatbot implementation with Rasa open source 2.0, conversational AI framework.

Aazim Parwaz 1 Dec 23, 2022
Few-shot Natural Language Generation for Task-Oriented Dialog

Few-shot Natural Language Generation for Task-Oriented Dialog This repository contains the dataset, source code and trained model for the following pa

172 Dec 13, 2022
Honor's thesis project analyzing whether the GPT-2 model can more effectively generate free-verse or structured poetry.

gpt2-poetry The following code is for my senior honor's thesis project, under the guidance of Dr. Keith Holyoak at the University of California, Los A

Ashley Kim 2 Jan 09, 2022
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing

Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar

Phil Wang 32 Oct 14, 2022
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge

Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge This is an implementation of the paper,

Mutian He 19 Oct 14, 2022
A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.

A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to ach

Keon Lee 237 Jan 02, 2023