Master Function Calling in Azure OpenAI

Master Function Calling in Azure OpenAI

Table of Contents

1. Introduction
2. How Function Calling Works
3. Understanding the Invocation Process
4. Passing User Input to Azure OpenAI Service
5. Determining the Function to Invoke
6. Invoking Functions in the Application
7. Handling Natural Language Outputs
8. Injecting Functions into the System
9. Managing Function Tokens and Costs
10. Official Documentation and API Version
11. Running Example Code in Python
12. Configuring Function Calls
13. Exploring Function Call Parameters
14. Conclusion

How Function Calling Works in Azure OpenAI Service

Function calling in Azure OpenAI service provides a way for an AI-integrated application to Interact with and leverage the capabilities of the OpenAI APIs. This article explores the process of function calling and how it enables applications to seamlessly invoke specific functions Based on user input.

Introduction

In an AI-integrated application that utilizes Azure OpenAI service, function calling plays a vital role in enabling the application to respond to user requests and perform specific actions. While the term "function calling" might imply that Azure OpenAI is directly invoking functions, it actually works differently.

How Function Calling Works

When a user interacts with the application through natural language, the application itself cannot understand and process the input. To overcome this, the user input is passed to the Azure OpenAI service, which acts as a language model and provides a response back to the application.

Understanding the Invocation Process

To determine which function to invoke, Azure OpenAI service analyzes the user input and compares it with predefined functions and their descriptions. Based on this analysis, the service identifies the appropriate function and provides the necessary details to the application for invocation.

Passing User Input to Azure OpenAI Service

To enable function calling, the application sends the user input, along with the necessary Context, to the Azure OpenAI service. This input is processed by the language model, which identifies the function to invoke and provides the required information back to the application.

Determining the Function to Invoke

Azure OpenAI service acts as a facilitator, directing the application on which function to invoke based on the user input. It does not directly invoke the function, but instead informs the application about the function to use.

Invoking Functions in the Application

Once the application receives the function information from Azure OpenAI service, it can proceed with invoking the specified function. The application should have the corresponding function implemented to ensure compatibility with the information provided.

Handling Natural Language Outputs

In cases where the invoked function generates a natural language output, the application can utilize Azure OpenAI service again to convert the function response into a natural language format. This allows the application to present the output to the user in a human-readable manner.

Injecting Functions into the System

When defining the functions for the application, they are included in the system message to facilitate the function calling process. The more functions included, the higher the token usage and associated costs. Therefore, careful consideration should be given to the number of functions included.

Managing Function Tokens and Costs

It's important to note that the inclusion of functions in the system message affects token usage and costs. As the functions are passed along with the input, they contribute to the token count. The more functions defined, the greater the token usage and associated costs.

Official Documentation and API Version

Function calling in Azure OpenAI service is still in the preview stage. The latest versions of GPT-3.5 Turbo and GPT-4 have been fine-tuned to support this functionality. The official documentation provides detailed insights into defining functions and utilizing the OpenAI service to enable function calling.

Running Example Code in Python

To demonstrate the function calling functionality, an example code snippet is provided in the official documentation. This example showcases how to define functions, pass user input, and receive the function information from Azure OpenAI service. Python is used to illustrate the process, but other programming languages can be used as well.

Configuring Function Calls

The configuration of function calls can be customized according to application requirements. Azure OpenAI service provides options to specify function call parameters, such as determining whether the function call is set to auto or explicitly passing the function call object.

Exploring Function Call Parameters

Azure OpenAI service offers parameters to control the behavior of function calls. The configuration options include setting the function call to auto or explicitly defining the function call object. These parameters influence how the service responds to user input and determines the appropriate function to invoke.

Conclusion

Function calling in Azure OpenAI service is a powerful feature that enables AI-integrated applications to leverage the capabilities of the OpenAI APIs. By understanding the process of function calling, developers can design applications that seamlessly respond to user input and invoke the necessary functions to fulfill user requests.

Highlights

• Function calling in Azure OpenAI service allows AI-integrated applications to seamlessly invoke specific functions based on user input.
• Azure OpenAI service acts as a facilitator, informing the application about which function to invoke based on natural language inputs.
• Functions are defined within the application and included in the system message to facilitate the function calling process.
• Inclusion of functions in the system message affects token usage and associated costs.
• The official documentation provides detailed information on how to define functions and utilize the OpenAI service for function calling.
• Example code in Python is available to demonstrate the function calling functionality.
• Function call parameters can be configured to customize the behavior of function calls in the application.

FAQ

Q: Can an AI-integrated application invoke multiple functions in a single user interaction? A: Yes, an application can invoke multiple functions in response to a single user interaction. Azure OpenAI service analyzes the user input and determines which functions should be invoked based on the context.

Q: Are there any limitations on the number of functions that can be defined in an application? A: While there is no predefined limit on the number of functions that can be defined in an application, it's important to consider token usage and associated costs. Including a large number of functions may increase token usage, resulting in higher costs.

Q: Can function calling be used with programming languages other than Python? A: Yes, function calling can be utilized with programming languages other than Python. The example provided in the documentation is written in Python, but the concept can be applied to other supported programming languages as well.

Q: Does Azure OpenAI service directly invoke the functions defined in the application? A: No, Azure OpenAI service only informs the application about the function to invoke based on the user input. It is the responsibility of the application to implement and invoke the corresponding function.