Function calling in four acts. A simple but complete soup-to-nuts example of function calling with the OpenAI API.

example.js

import { OpenAI } from "openai";
const openai = new OpenAI();

// 1.) Define an array of functions the model could decide to call
const tools = [{
  type: "function",
  function: {
    name: "generate_horoscope",
    parameters: { type: "object", properties: { sign: { type: "string" } } }
  }
}];

// 2.) Prompt the model, providing an array of available functions in the
// "tools" param (tools can theoretically have other items than just functions)
const messages = [
  { role: "user", content: "I'm a virgo, what's my horoscope for today?" },
];

const response1 = await openai.chat.completions.create({
    model: "gpt-4o",
    messages,
    tools,
});

// 3.) If the model decides to call a function, parse function input from JSON
// and execute logic to implement the function however you need to.
const toolCall = response1.choices[0].message.tool_calls[0];
const args = JSON.parse(toolCall.function.arguments);

// Return a function call message to pass back in to the model
function generateHoroscope(fnArgs) {
  return {
    role: "tool",
    tool_call_id: toolCall.id,
    content: JSON.stringify({
      horoscope: `Oh, you're a ${fnArgs.sign}? Eventually you're gonna die.`
    })
  };
}

const functionResponse = generateHoroscope(args);


// 4.) Generate another response from the model, including both the assistant
// message from the first API response, and your new generated message from
// the function call. Now the model has all the data it needs to respond to the
// original prompt!
messages.push(response1.choices[0].message);
messages.push(functionResponse);

const response2 = await openai.chat.completions.create({
  model: "gpt-4o",
  messages,
  tools,
});

console.log(response2.choices[0].message.content);