My spirit animal while working on these projects 💕
Ever since ChatGPT’s meteoric launch, I’ve been spending a lot of time working on two open source projects:
My goal with this post is to share some stories and insights from building these two projects, with a focus on understanding how the ChatGPT twitter bot has been used by real people over the past two months.
I’m also publishing a data set containing all of the ChatGPT Twitter interactions in a simple JSON format. While this represents a tiny fraction of the massive usage that OpenAI has seen with ChatGPT so far, it is my hope that this data set will prove useful as a publicly available, statistically significant sample of common conversations between real users and ChatGPT.
I’ll start by sharing a story about the ups & downs of hacking on top of ChatGPT to build the twitter bot, and then we’ll look at some data-based analytics and insights.
Let’s dlve in 💪
OpenAI released ChatGPT released on Nov 30, 2022.
Like many of you, it was a wake-up call that made realize just how far the AI field has come. I was so inspired by it’s potential that I ended up coding almost non-stop for the next 48 hours. I released the first version of the chatgpt npm package on Dec 2nd, 2022.
The project immediately gained traction with other devs who were also inspired, with the repo reaching the top of GitHub trending a few days later.
The chatgpt package was a fairly straightforward wrapper around the unofficial REST API that the official chat.openai.com webapp was using under the hood. OpenAI didn’t put too many safeguards in place, so reverse engineering their unofficial API was mostly a matter of opening up Chrome devtools and looking through the network tab.
Example devtools API call of a POST to the https://chat.openai.com/backend-api/conversation endpoint, which returns a response that uses server-side events to pass incremental results to the client. The ChatGPT webapp’s UI displays these incremental results to mimic the bot “typing.”