Unlock the Power of GPT-3 with Function Calling

Table of Contents:

1. Introduction
2. What is Function Calling?
3. How Function Calling Works
4. Basic Use Cases of Function Calling
5. Creating a .ENV File and API Key Setup
6. Importing Libraries and Loading API Keys
7. Defining Function Descriptions
8. Writing the Get Stock Movers Function
9. Writing the Get Stock News Function
10. Writing the Add Stocks News to Airtable Function
11. Using Function Calling with GPT-3
12. Writing the Ask Function Calling Function
13. Connecting Function Calling with Airtable
14. Controlling Lights with Function Calling
15. Conclusion

Introduction

In a groundbreaking announcement, OpenAI has introduced a new feature called function calling to their GPT-3 technology. With function calling, GPT-3 goes beyond generating text and gains access to a wide range of API endpoints, enabling it to perform tasks such as sending emails, retrieving real-time data, and controlling smart devices. This article explores the concept of function calling and provides a step-by-step guide on how to use it effectively.

What is Function Calling?

Function calling allows GPT-3 to utilize various tools and functions by giving it access to a wide range of APIs. By selecting the most suitable tools autonomously, GPT-3 can output responses in a structured JSON format, which can be understood by machines and triggers the desired functions. Function calling enables developers to unlock their imagination and leverage the power of AI to make their applications ten times more powerful.

How Function Calling Works

When using function calling, developers define a list of function descriptions, each containing the name, parameters, and properties of the function. GPT-3 receives this list as the available tools it can use. Based on the query or prompt, GPT-3 makes decisions on which functions to call and with what arguments. By passing responses back to GPT-3, developers can Create a feedback loop where GPT-3 continuously calls different functions until the task is complete.

Basic Use Cases of Function Calling

One basic use case of function calling is to allow GPT-3 to access various APIs and retrieve Relevant data. For example, a developer can use a finance data API to get stocks with the biggest price movement, then use a news API to summarize the latest news about those stocks. These pieces of information can be added to a database, such as an Airtable, for further analysis and tracking.

Creating a .ENV File and API Key Setup

When using function calling, it is essential to create a .env file and store API keys securely. The .env file will store OpenAI, Airtable, and other API keys necessary for the application. These API keys need to be loaded into the application using appropriate libraries to ensure smooth integration with the APIs.

Importing Libraries and Loading API Keys

To start using function calling, developers need to import the necessary libraries and load the API keys from the .env file. These libraries will provide the necessary functions and methods to Interact with the APIs effectively.

Defining Function Descriptions

Developers need to define the function descriptions that will be passed to GPT-3 as the available tools. Each function description should specify the name, parameters, and properties of the function. Clear definitions of the function structure and required properties enable GPT-3 to make accurate decisions on which functions to call.

Writing the Get Stock Movers Function

To retrieve stocks with the biggest price movement, developers can write a function called "get_stock_movers". This function can utilize a finance data API to get the required data. The function should accept necessary parameters, such as the API key, and return the list of stocks with significant price movement.

Writing the Get Stock News Function

To retrieve the latest news about a stock, developers can write a function called "get_stock_news". This function can utilize a news API and requires the stock's performance ID as a parameter. The function should return a list of news articles related to the stock.

Writing the Add Stocks News to Airtable Function

To add the stock information and news to an Airtable database, developers can write a function called "add_stock_news_to_airtable". This function requires the stock name, price movement, and news summary as parameters. Using the Airtable API, the function should create a new Record in the designated table containing the provided information.

Using Function Calling with GPT-3

To utilize function calling with GPT-3, developers need to make API calls to OpenAI. By specifying the function descriptions, the model (GPT-3 for June 13 in this case), and the message with the user query or prompt, GPT-3 can intelligently choose which functions to call. The responses from GPT-3 will contain the generated content, including function calls and arguments.

Writing the Ask Function Calling Function

To handle the function calls and execute the corresponding functions, developers should write a function called "ask_function_calling". This function receives the response from GPT-3 and extracts the function name and arguments. Using conditional statements, the function can execute the appropriate functions based on the function name and arguments.

Connecting Function Calling with Airtable

To connect function calling with Airtable, developers need to include the necessary API keys and import the Airtable library. By defining a function to add stock news to Airtable, developers can pass the required information from the function call response and create new records in the Airtable database.

Controlling Lights with Function Calling

Another exciting use case of function calling is to give GPT-3 access to external devices, such as smart lights. Using the appropriate APIs and libraries, developers can create a function to control lights based on the state (on or off) provided in the function call. This allows AI-powered applications to interact with the physical world effectively.

Conclusion

Function calling is a powerful feature introduced by OpenAI that enhances the capabilities of GPT-3. By providing access to various APIs and functions, developers can unlock new possibilities and create applications that are ten times more powerful. This article provided a step-by-step guide on how to use function calling, covering the setup, defining functions, and integrating with existing APIs. With function calling, developers can create intelligent AI applications that can perform complex tasks and interact with external systems effectively.

Highlights

• OpenAI introduces function calling to GPT-3, allowing access to APIs and functions.
• Function calling enables AI apps to perform tasks beyond text generation.
• Developers define function descriptions to guide GPT-3 in calling the right functions.
• Use cases include data retrieval, analysis, and control of external devices.
• Integration with APIs such as finance data and news services enhances functionality.
• Function calling creates a feedback loop between GPT-3 and functions until task completion.
• Airtable integration enables seamless database operations.
• Controlling smart devices, like lights, adds physical interaction to AI applications.
• Function calling makes AI apps 10 times more powerful and versatile.
• Sample code and further experimentation opportunities are available on GitHub.

FAQ

Q: Can GPT-3 call any function? A: GPT-3 can call functions as long as they are defined within the available function descriptions. Developers define what functions GPT-3 can call and the required parameters.

Q: Can GPT-3 handle multiple function calls in a single query? A: Yes, GPT-3 can handle multiple function calls in a single query. Developers define the sequence of function calls and GPT-3 executes them accordingly.

Q: Are there any limitations to function calling? A: Function calling has some limitations, such as call duration and resource usage. It is important to optimize function calls to ensure efficient and effective usage of resources.

Q: Can GPT-3 access APIs that require authentication? A: Yes, GPT-3 can access APIs that require authentication. Developers need to include the necessary API keys and follow the authentication process specified by the API provider.

Q: How does function calling enhance AI applications? A: Function calling adds functionality, automation, and real-time data retrieval to AI applications. It enables AI apps to perform complex tasks and interact with external systems effectively.

Q: Can GPT-3 handle errors or exceptions during function calling? A: Yes, GPT-3 can handle errors or exceptions during function calling. Developers can include error handling mechanisms in their functions and provide appropriate responses to GPT-3.

Q: What other applications can benefit from function calling? A: Function calling is versatile and can benefit various applications, including finance, data analysis, news summarization, smart home automation, and more. The possibilities are virtually limitless.

Q: Can GPT-3 learn and improve its function calling capabilities? A: GPT-3 cannot inherently learn or improve its function calling capabilities. However, developers can refine function definitions and optimize the application to enhance GPT-3's performance.

Q: Is function calling available in all languages? A: Function calling is language-agnostic and can be implemented in any programming language that supports API integration. Developers need to provide the necessary code and libraries to enable function calling.

Q: Are there any security considerations when using function calling? A: Security considerations include proper handling of API keys, data encryption, and access control. Developers should follow best practices for secure API integration and prevent unauthorized access to systems and data.