Hello people! I hope you're all doing well and staying curious. Today, we're going to dive into a fascinating new feature from OpenAI, the function calling capability of their updated GPT-4 and GBT-3.5 models. It's like having a Swiss Army knife in your AI toolbox, and I can't wait to show you how it works.
In a recent video by James Briggs, he does a fantastic job of explaining and demonstrating this new feature. If you haven't seen it yet, I highly recommend giving it a watch here. But for those of you who prefer reading, or just want a quick recap, let's break it down.
Function calling in GPT-4 and GBT-3.5 is like having a conversation with your AI model about Python functions. You describe a function to the model, ask it a question, and if the model determines that the question requires one of the functions you've described, it will return the parameters needed to use that function. It's like the tool usage in Lang Chain, but directly within the OpenAI API. It's a powerful feature that can simplify and lighten your code.
In the video, Briggs demonstrates this by creating a function that builds a web page for a product. He uses GPT-4 to generate a title and marketing copy for the product, which is then incorporated into the HTML code of the page. But he doesn't stop there. He also uses an image generation model from Hugging Face Diffusers to generate an image for the product page, demonstrating how you can combine different models and functions to create a more comprehensive result.
The video is a great example of how AI can be used to automate tasks and generate creative content. But more than that, it shows how the new function calling feature in GPT-4 and GBT-3.5 can be used to create more complex and interactive AI applications.
Now, I know what you're thinking. "This sounds great, Scott, but how can I use this in my own projects?" Well, the good news is that implementing this feature is straightforward. You'll need an OpenAI API key, which you can get from the OpenAI platform, and you'll need to be using a CUDA-enabled GPU for the image generation part of the demonstration.
Once you have those, it's just a matter of describing your functions to the model and then using the chat completions API to ask the model questions. The model will then return the parameters needed to use the functions you've described. It's a powerful tool that can help you create more interactive and dynamic AI applications.
The function calling feature in GPT-4 and GBT-3.5 is a powerful tool that can help you create more interactive and dynamic AI applications. It's like having a Swiss Army knife in your AI toolbox, and I can't wait to see what you all create with it.
As always, stay curious, keep learning, and I'll see you in the next post. Until then, happy coding!
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