Aiyush Gupta


I Remade Github Copilot - PyOoshi Browser Based Alternative

I Remade Github Copilot - PyOoshi Browser Based Alternative

Built in <6 hours, demonstrating the power of open-source AI models built on GPT-J-6B with a beautiful GUI

Aiyush Gupta's photo
Aiyush Gupta
·Aug 10, 2021·

7 min read

Play this article

Hello 👋

Its’ finally here 🎉, I’m incredibly excited to announce my first web-dev project – PyOoshi. PyOoshi came after a week of hard work learning HTML, CSS and JS from scratch leading to my first project. After trial and error, organisation and lots of SO I came to my final project✨️

After learning about Github Copilot and its' closed source soon to be paid nature, I attempted to create my own free version in less than 6 hours. Here goes...

In the spirit of open-source, I've released my project on Github under the GNU V3 license. If you would like to make a change then feel free to do so and create a pull request, thanks.



I will be the first to admit it, learning a new language (never mind Stack) can be daunting, especially when you don’t know where to start. With this in mind, I attempted to solve 2 problems at once 1. Learn a new stack 2. Create an educational tool to help people learn a new programming language.

Although the project doesn’t yet work perfectly (I need to add more context to my model) it demonstrates perfectly what you can create in the same week of starting Web Dev 🚀

That's Progress Gif

Introducing PyOoshi ✨️

PyOoshi is a powerful, experimental and easy-to-use code generation toy project that successfully generates beautiful code just by inputting some general prompt. Whilst this project was created in <6 hours it is fully functional and I thought the best way to demonstrate what is possible with a little dedication. It can handle simple prompts such as “make a password generator” or “covert Celsius to Fahrenheit” but struggles with more ambiguous and general tasks.

Inspiration 👀

After getting access to GPT-3 last year, I was fascinated by the tasks it could complete and how rapid and accurate its’ output was. Ever since, I have been waiting for ‘Open’-AI to release an open-source version or someone to recreate it. Along came GPT-J-6B, read my blog post about it here. %[ ]

Combined with a few google searches, I knew it was possible so it was my turn to give it a crack. There was one small problem though, I had never touched HTML, CSS or JS beyond the classic inspect-element to change my score on online HTML5 games.

How to Use?

Visit PyOoshi , you will see the UI (created using Tailwind – which I love), you can ignore the options at the top for now and you can enter something like Divide A by B and store it in result and then click on the go button. You will see the web-page load, it may take up to 60 seconds if under heavy load. At the moment, it works better on Desktop than mobile since I am having issues with the responsiveness (which works on localhost) but not upon deployment.


Prompt Guide

Showing, not just telling, is the secret to a good prompt. Even people familiar with machine learning accustomed to chatbots and single-purpose text models can get confused by this. The API’s power is its adaptability. The key to unlocking this adaptability is in learning how to show it what you want. The API tries to guess what you want from the prompt. If type the words “Give me a list of numbers,” the AI (GPT-J-6B), wouldn’t automatically assume that you’re asking for a list of numbers. You could just as easily be asking the API to continue a conversation where the first words are “Give me a list of numbers and ensure they are miltiples of 2.” If the API only assumed that you wanted a list of numbers it wouldn’t be as good at classification or code generation TL;DR Keep It Simple

Keep It Simple

Examples: Divide A by B and store it in result Generate the sine values from 0 to 1. Convert input from Celcius to Farenheit Perform a google search of what the user wants and print the top result Print what part of the day is going on right now Make a password generator

Output Once the output has been generated, you will see it in the green output box. Note, if your output has tonnes of random text at the bottom of it, or cuts of randomly then carry on reading to learn about setting max-tokens, temperature and max-probability

Token Recommended max amount of tokens is 2048, this is the maximum output length in characters including spaces.

Temperature Controls how random the model is, recommended setting > 1.0 A higher temperature means more creativity and a low temperature means less changes will be made when completing the prompt. The value must be a float.

Probability An alternative method to setting the creativity if the temperature is set then probability must equal 1, vice-vera.

Built With:


Planning, Coding, Deploying 🏗️

  • Planning All I needed was a piece of paper and a pen, I quickly sketched out a rough wireframe and looked at the pre-existing components of DaisyUI and built it around that. Since it was all input and buttons, I could be quite flexible in the layout. I built it using a mobile-first approach, however, this stopped working on deployment and my responsive aspects aren’t happening. If anyone knows why this is happening then please reach out.

  • Coding I had spent 5 days learning HTML, CSS and JS by following an array of tutorials on YouTube. Now, I was ready to get started.

Building with Tailwind I had two options, to use the CDN or the CLI. Since the CDN is much heavier than the CLI and lacked some important features for this project, I decided to use the CLI. However, to setup the CDN just add this to your head.

<link href=^2/dist/tailwind.min.css
  1. To use the CLI, you should create a project structure
└── Project/
    ├── css/
    │   └── tailwind.css
    └── index.html

2. You should populate css/tailwind.css with  

@tailwind base; /* Entry Point Directive */
@tailwind components; 
@tailwind utilities;

This is the entry point directive

3. npx tailwindcss-cli build -i css/tailwind.css -o build/tailwind.css This processes your css into a build directory .

npm init -y npm install -D tailwindcss postcss autoprefixer vite Install the required libraries, vite provides us with a server to see our changes in real time.

4. To reflect the installation of vite I adjusted the package.json with a new script.

  "name": "TailwindLabsCSS",
  "version": "1.0.0",
  "description": "",
  "main": "index.js",
  "scripts": {
    "dev": "vite" // Change here
  "keywords": [],
  "author": "",
  "license": "ISC",
  "devDependencies": {
    "autoprefixer": "^10.3.1",
    "postcss": "^8.3.6",
    "tailwindcss": "^2.2.7",
    "vite": "^2.4.4"

5. Generate the configuration file, this is where we can install plugins etc… npx tailwindcss init -p

  1. npm i daisyui The daisyUI library provides a great way to rapidly prototype designs.

  2. Lastly, link the CSS file in your index.html in the root project directory.

  3. Start the Vite development server using npm run dev

Since I had setup tailwind after familiarising myself with the documentation & framework, I started to code out the frontend.

Once I had finished with the frontend it looked like this (with a different colour theme applied):

Connecting the frontend to Python

Connecting to python was a challenge at first since I had no idea how to use tailwind with Flask, luckily I found this:


Soon enough, I had created my API and by using post and get methods on my @app.route I could quickly access form fields by their names with maxTokens = int(request.form.get('maxTokens')), this was some repetition after this and adding authentication to ensure valid responses. Ie. maxTokens = 2048 if maxTokens<2048 else maxTokens.

Deploying 🚀

I have a hacker account so I quickly reproduced my steps on and within 5 minutes of tinkering and realisation that I could use a custom subdomain of I quickly got the site up and running. Although this is in very early stages, if you would like to help develop this then just reach out on LinkedIn / GitHub . Overall, this is my first frontend project and I am quite proud of it.


Wrapping it up🎁

Thanks 👏👏👏 for reading until the end, I am happy with my project overall and I wouldn’t have been able to do it without all the great content-creators out there. If you have further feedback / enhancements then please comment them down below.

In the spirit of open-source, I've released my project on Github under the Common Clause license. If you would like to make a change then feel free to do so and create a pull request, thanks.

Did you find this article valuable?

Support Aiyush Gupta by becoming a sponsor. Any amount is appreciated!

Learn more about Hashnode Sponsors
Share this