OpenAI has announced a groundbreaking feature - Function Calling in GPT (Generative Pre-trained Transformer) models. This game-changer has expanded the horizons for GPT beyond generating text; it can now send emails, access an array of APIs, and control home devices like lights. This step-by-step auto-gpt tutorial will guide you on utilizing this incredible functionality.
What is Function Calling?
Function Calling enables GPT to access a variety of tools and functions. It essentially acts as an autonomous agent that selects the most suitable tools to accomplish the given task. It also provides an output response in a structured JSON format, facilitating smooth communication with machines.
This new feature has made AI apps 10 times more powerful, unlocking the potential to create more innovative applications.
Implementing Function Calling
Let's dive into a basic use case - granting GPT access to different APIs. For example, Rapid API, a valuable platform for GPT apps, provides data from sports, finance, movies, science, and more. We'll examine a complex task where GPT summarizes the latest news about the stock with the largest price movement of the day and archives the information in an Airtable.
Setup: Create a .env file and add your API keys for OpenAI, Airtable, and Rapid API. Then, in the app.py, import various libraries and load the API keys.
Create Function Descriptions List: This list contains the functions that GPT can use. Each function must have a name, description, and parameters defined. Properties should also be well-structured, indicating what kind of information GPT should generate. If certain properties are required, add the required parameter.
Writing the Functions: Create functions that return the required data based on the API calls. You can use the requests library in Python for this.
Handling Function Calls: Write a function that extracts the name of the function from the AI's response and handles the function call. Based on the name, it will trigger the appropriate function to fetch data.
Return Information Back to GPT: It's crucial to return the information back to GPT so it can decide the next step. If the finished reason is "function_call", GPT will decide what the next step should be and continue running until the finished reason becomes "stop".
GPT Access to Airtable: Provide GPT with access to your Airtable. Use the Airtable API Python package to create a function that adds items into the Airtable very easily. Include this function in your function call handler.
GPT Control Over Home Devices: For example, if you use Lifx lights, generate an API token from your Lifx account and create a function in your Python script to turn the lights on or off based on GPT’s instruction. Add this function to your function description list and function call handler.
This GPT functioning calling tutorial provides a taste of how much more powerful your AI applications can become. Function Calling enables GPT to interact with the outside world and make informed decisions autonomously. It's no-code, making it user-friendly and accessible. Start experimenting with OpenAI, LangFlow, and LangChain to unlock the immense potential of your AI applications.