免费教程：GPT实例讲解新特性Function Calling

Table of Contents

1. Introduction
2. GPT3.5 Update: Adding a 16K Version
3. GPT3.5 Update: Model Reduction
4. New Functions in GPT3.5 Update
5. Principle and Significance of the New Function
6. Official Example of Using the New Function
7. Practical Example of Using the New Function
8. Function Calling Feature in GPT
9. Implementation of GPT Function in Local Workflows
10. Examples of Using Function Calling in GPT
11. Automating Functions with Function Calling
12. Conclusion

Introduction

In this article, we will explore the latest update from OpenAI on GPT3.5, which includes the addition of a 16K version with longer Context and new functions that can be called in the API. We will Delve into the principle and significance of these new functions and provide both official and practical examples on how to use them. We will also discuss the function calling feature in GPT and its implementation in local workflows. By the end of this article, You will have a clear understanding of the capabilities and possibilities of utilizing function calling in GPT.

GPT3.5 Update: Adding a 16K Version

The latest update on GPT3.5 brings a new 16K version with longer context. This means that users can now input more extensive text to generate responses with improved context understanding. While this update comes at a higher cost compared to previous versions, it offers enhanced capabilities for generating high-quality content.

GPT3.5 Update: Model Reduction

Another significant aspect of the GPT3.5 update is the reduction in model size. Although it still remains more expensive than Claude, the cost has been significantly reduced. This reduction in model size allows for more efficient usage while maintaining comparable performance.

New Functions in GPT3.5 Update

One of the most exciting developments in the GPT3.5 update is the addition of new functions that can be called in the API. These functions act as an intermediary between users and third-party software, leveraging GPT's natural language understanding ability to convert unstructured data into structured data. Users can now extract specific parameters from ambiguous natural language and pass them to third-party interfaces, significantly enhancing the user experience.

Principle and Significance of the New Function

The new function added in GPT3.5 update brings significant improvements in user interaction and customization. By injecting a plug-in that remains invisible to the user, key information can be extracted from the user's language and automatically converted into parameters required to execute the third-party interface. This concept is exemplified in the implementation of the GPT plug-in store, where essential information is extracted to improve the user experience. The introduction of the function calling feature in GPT further extends this mechanism to the developer side, allowing for seamless integration of GPT capabilities into their own products and workflows.

Official Example of Using the New Function

To illustrate the functionality and usage of the new function, OpenAI provides an official example. This example demonstrates how to implement a function to obtain the Current weather. By providing a function name, description, and necessary parameters, developers can easily describe the function to GPT. During a conversation with the user, GPT can then identify the need to trigger the function and extract Relevant information through further Prompts. This example showcases the simplicity and effectiveness of utilizing the new function calling feature in GPT.

Practical Example of Using the New Function

In addition to the official example, we can also explore practical use cases of the new function calling feature in GPT. For instance, we can leverage this feature to implement functions that enable local song ordering and playing movies. By creating a function to obtain the keyword of the song name and matching it with the available MP3 files, users can use GPT to play the closest matching song. Similarly, a function can be implemented to play local movies Based on user requests. These practical examples highlight the versatility and customization options provided by function calling in GPT.

Function Calling Feature in GPT

The function calling feature in GPT enables developers to seamlessly integrate GPT's capabilities into their own products or workflows. With the ability to define functions, describe them to GPT, and call them based on user prompts, developers can leverage GPT's natural language understanding to automate various tasks and enhance user experiences. The implementation of function calling drastically simplifies the integration of GPT into applications, making it a powerful tool even for large-Scale enterprise-level applications.

Implementation of GPT Function in Local Workflows

With the introduction of function calling in GPT, developers can now implement GPT functions in local workflows instead of relying solely on the plug-in store. By providing function names, descriptions, and necessary parameters, developers can describe the functions to GPT and initiate requests based on user prompts. This local implementation offers more flexibility and control over the usage of GPT's capabilities, opening doors for various applications and customization options.

Examples of Using Function Calling in GPT

The possibilities of utilizing function calling in GPT are vast and extend beyond the provided examples. Developers can explore fully automated examples locally, encapsulating operations on the operating system into functions controlled by human language. From ordering songs to controlling wearable devices, function calling enables developers to unleash the full potential of GPT's language capabilities. Additionally, the integration of third-party service providers can further expand the range of functions and possibilities available.

Automating Functions with Function Calling

By leveraging the new function calling feature in GPT, developers can automate various tasks by defining functions and describing them to GPT. From generating query statements based on user questions to implementing fully automated functions, GPT's natural language understanding can be harnessed to Create powerful, personalized experiences. With GPT's ability to interpret user prompts and extract specific parameters, developers can build applications that are intuitive and responsive to user requirements.

Conclusion

The addition of the function calling feature in GPT3.5 update brings significant advancements in user interaction and customization. By enabling the integration of GPT's capabilities into local workflows and products, developers can create highly tailored experiences for users. The examples provided and the flexibility of function calling showcase the immense potential of leveraging GPT's natural language understanding. With the right implementation, developers can unlock opportunities and create innovative applications that leverage the power of GPT to enhance user experiences and improve productivity.

Highlights

• The GPT3.5 update introduces a 16K version with longer context and reduced model size, offering improved capabilities at a lower cost.
• New functions in GPT3.5 allow for seamless integration with third-party interfaces, improving the user experience.
• The function calling feature in GPT enables developers to implement GPT functions in local workflows, enhancing customization possibilities.
• Official and practical examples illustrate the simplicity and effectiveness of using the new function calling feature in GPT.
• GPT's natural language understanding and parameter extraction capabilities make it possible to automate functions and create personalized experiences.
• Function calling opens doors for extensive applications, including controlling operating systems and integrating with third-party service providers.

FAQ

Q: How can developers implement GPT functions in their own workflows? A: Developers can describe functions to GPT by providing function names, descriptions, and necessary parameters. These functions can then be called based on user prompts to automate various tasks.

Q: Can GPT generate parameters for functions automatically? A: Yes, GPT can automatically generate query statements based on user questions, which can be used as parameters for functions.

Q: Is there a limit to the number of functions that can be implemented with function calling in GPT? A: There is no limit to the number of functions that can be implemented. Developers can add multiple functions to address different requirements and use cases.

Q: Can function calling be used in large-scale enterprise-level applications? A: Yes, function calling is designed to be scalable and can be used in large-scale enterprise-level applications without any issues.

Q: Can function calling be combined with other service providers' interfaces? A: Yes, developers have the option to call interfaces from other service providers instead of implementing functions themselves, allowing for expanded functionality and possibilities.