🚀☕ Developers, Turbocharge Your Projects with Function Calling in GPT-4

GPT-4, OpenAI's latest language model, introduced a game-changing feature: function calling last week.

I didn’t understand a lot of the explanations people gave on youtube so I took a look into the original blog post from OpenAI and I’ll share what I learned here - with coffee themed analogies as always to simplify complex topics.

I’ll talk about how it will elevate your development work and provide business ideas that could possibly be the caffeine kick your creativity needs today. Let's dive into the best parts and practical examples of this exciting capability. ☕️👨‍💻

👨‍💻 GPT-4 Function Calling: Implications

Before Function Calling was introduced, GPTs were like baristas who could write down your coffee order or answer any questions you had about coffee - but they wouldn’t actually make your coffee.

But now, with Function Calling, interacting with the GPT-4 API, the barista will not only write down your order but also brew the exact coffee you want.

🎯 Real World Results: You can now ask GPT-4 to draft an email, it used to give you a text draft - a time saver no doubt. But now, it can actually send that email or save it as a draft in your inbox so you can review it before sending. And that’s just one tiny example of the limitless possibilities. The gist is, developers can now be much faster and do a lot more now.

🔑 Understanding Function Calling in GPT-4

Picture this:

1. 🏢 A customer strolls into your coffee shop (your program).

2. 📜 They scan the menu on your app filled with delicious options (the defined functions in your code).

3. 📝 They order a double espresso, but with a twist. It’s two shots of espresso, 30 ml each, served in a small cup at 67°C with whipped cream (the arguments).

4. 🤖 The barista (the OpenAI API) understands your request and gets to work.

5. ☕️ Your coffee order (the output of your function call) comes back just as you wanted it (in JSON format), which is a format that machines (like our coffee-ordering system) can easily understand.
   
   This JSON output might look something like this:

   {
     "size": "small",
     "type": "double espresso",
     "temperature": 67,
     "shots": 2,
     "topping": "whipped cream"
   }

🎖️ TLDR; For your business, this means that your apps can now accurately & efficiently capture and execute natural text commands. It significantly reduces misunderstandings and streamlines operations. A bit like using a ChatGPT plugin.