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Hands-On Introduction to Open AI Function Calling
Data Science   Latest   Machine Learning

Hands-On Introduction to Open AI Function Calling

Last Updated on June 10, 2024 by Editorial Team

Author(s): Youssef Hosni

Originally published on Towards AI.

Hands-On Introduction to Open AI Function Calling

A few months ago, OpenAI introduced a new capability to its API, enhancing its most recent models to accept additional parameters for function calling. These models are now fine-tuned to determine when it’s relevant to call one of these functions. In this article, we’ll explore how to use this feature effectively, along with tips and tricks for optimal results.

We’ll use the OpenAI SDK to demonstrate this new capability, imagining a function we find valuable to provide to the language model. We’ll delve into what makes a function “interesting” and discuss various use cases for this new parameter.

Setting Up Working EnvironmentDefining a FunctionPassing Function Definitions to the Language ModelProcessing Responses from the Language ModelHandling Non-Function-Related MessagesForcing Function Calls with ParametersIntegrating Function Results into Language Model ResponsesToken Usage and LimitationsConclusion and Next Steps

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