Code Clinic | Building Custom GPT Assistants: A Step-by-Step Tutorial

Remember the PhoneSaber app?

So OpenAI launches their Langchain/Autogen competitor and it’s a low/no-code galore. Seems like everyone and their mother are jumping on the Assistants as Conversations train.

What I find interesting about this new GPT-based product though, is the possibility to get it published and gain access to a pool of potentially 100 million paying users including Enterprise.

Especially Enterprise.

So I, like thousands of other hopefuls. have spent the last 48 hours since the announcement thinking deeply about how to build the one assistant that rules them all and makes a Billion dollars. How do you make a Billion dollars? Understand the problem that you are trying to solve where genAI is the perfect, never-seen-before solution.

Always think along the lines of

I want to have a conversation with… Documents | APIs | Experts | Schedulers to solve really painful tasks that I am currently doing in a different (slower, lower quality, more expensive) way and I would pay money to have the agent do it for me.

But so far I haven’t come up with anything smart yet.

Maybe, just maybe, this whole thing starts to suffer from a solution looking for a problem. Just pondering that though…

So what we always do, and is always the wrong approach, when facing the situation of a solution looking for a problem…

We are building product!

In this case, we will be developing an assistant that specializes in knowledge retrieval and consumes a document to answer questions and questions about the rules of the lovely game of Poker. Then we will use it in the Assistant Playground and if we are happy, we will publish it to the GPT Store (or not).

Let’s start.

The script is actually quite straightforward and begins with the simple import of the OpenAI package and the definition of the client.