Python API Coding Sample

This is a code sample for prospective employers demonstrating my ability to develop a basic python-based api which leverages a large language model (in this case, GPT-4) to generate small code functions which can be run without knowing anything about the code inside them.

Examples

Example API request:

POST http://localhost:8000/api/task/create
Body:

{   
    "desired_action": "given a dataset containing a bunch of text, extract the most important topics from each text",  
    "task_type": "passthrough"  
}  

On successful response, a folder with a UUID will be generated under ./user_tasks/<the_uuid>. That folder will contain a function.py file which accomplishes the task you described, and a metadata.json file describing the function, its required parameters, and how it is meant to be run.

Video of me building this

I hope this video demonstrates a few things:

1. How I can use TDD (Test Driven Development) to write software. With the exception of a few functions, I wrote the tests first, and iterated on the code until the tests passed.
2. How I can build new software efficiently by going from experimentation (failing/learning fast) to implementation in a highly iterative manner.

Overview

This is a sample of a Python API that can be used to create and run Python tasks. It uses OpenAI's GPT-4 API to generate Python code from natural language descriptions of tasks.

Due to privacy concerns, I cannot share the full repo. This repo is a subset of the full repo, and is meant to demonstrate my coding style and ability to work with Python and APIs.

Context

• This code was completed in 9 hours over 4 days.
• This is an example of my POC code, meaning it was designed to be fast to iterate upon, and not to be production ready.
• The backend, or task_service section is ready to be deployed as an AWS lambda function, or run as a local api.
• What I would do to make this production ready:
  • Standardize the API request validation and response format
  • Add API security using a securely generated token (JWT)
  • Use a formatting library like Black, and a linting library like Flake8
  • Abstract logical code away from the API requests
  • Reorganize the code / tests to follow a standard pattern
  • Make more comprehensive types
  • Add tests for the API itself
  • Add more testing around edge cases and exceptions
  • Add a CI/CD pipeline

API

A set of endpoints for creating python tasks + metainfo about those tasks using natural language, as well as running those tasks.

API Requirements

• Python 3.11

Setup API

From a clean Python environment with pip installed:
pip install -r task_service/requirements-dev.txt
cp .example.env ./.env

Add your Open AI key to the .env

Run API

cd task_service
python app.py

Run Tests

pytest task_service
Note: some tests cost money as some of them call the acutal OpenAi API for completions. They don't use the most expensive models though.

Client

Does nothing except display a test button right now.

Client Requirements

• NPM 9.6
• Node v20.0

Run Client

cd client
npm install
npm run dev-client
Open a new terminal
npm run start-tool-service