OpenAI ChatGPT APIs

We keep hearing that chatbots are complicated. They don’t have to be. OpenAI gives us APIs that make the heavy lifting simple. We just need to know which calls to make, and when.

Starting with chat completions

The main tool is the Chat Completions API. Think of it as the part where we say something, and she answers. We send a list of messages (user, assistant, system). She reads the whole thread, then decides the next reply. That’s all.

It’s cleaner than older text generation APIs. Instead of a long, messy prompt, we structure the conversation as turns. Our code is easier to read, and our chatbot behaves more predictably.

Making the call

A call looks like one JSON object. Model, messages, and maybe temperature if we want her a bit more playful. That’s it. Send it to the endpoint, and she sends back her words.

We can log both sides of the exchange. That way our chatbot feels consistent, because every new call includes the history we’ve saved. Otherwise she forgets.

Adding rules with system messages

If we want her polite, terse, or full of jokes, we say so up front in the system message. She usually follows it. Not always, but close enough. Think of it like stage directions before the dialogue starts.

Chaining behavior

One completion call is fine for hello-world. Real chatbots need more. We may chain calls: first for intent detection, second for an actual answer. Or swap models—fast one for routine stuff, slower one for thoughtful answers. It’s just more API calls, stitched together.

A coder’s thought

We came here expecting a tangle of AI magic. We found a few API calls, some JSON, and a chatbot that talks back. Feels almost like cheating.