Use Cases for Function Calling

Function calling transforms AI from a simple information provider into an active partner that can interact with the real world by connecting to external systems.

What is LLM Function Calling

LLM function calling allows models like those from OpenAI to call external functions, enabling them to fetch data or perform actions beyond their training data. For example, a user might ask for the current weather, and the LLM calls a weather API to retrieve and include the data in its response.

Why is This Useful

This capability makes LLMs more dynamic, allowing them to:

• Access real-time or proprietary data.
• Automate tasks like sending notifications or updating databases.
• Create intelligent agents that combine data retrieval and actions for complex tasks.

Why Function Calling Matters

Without function calling, AI responses remain static and limited. Function calling adds dynamic, real-time capabilities, enhancing AI's usefulness by allowing it to gather, act on, and deliver current, personalized information.

Function Calling Categories

Here are three categories of function calling:

1. Data Collection

Data collection is when the AI gathers and stores information from user interactions. This is perfect for tasks like collecting leads, managing customer feedback, or integrating with CRM tools.

Examples:

• Lead Generation: Capturing customer details (name, email) directly into a CRM system like Salesforce or Zoho.
• Feedback Forms: Logging user feedback into platforms such as Airtable or Notion.
• Support Tickets: Collecting user-reported issues and automatically creating support tickets.

These typically involve sending data through POST requests.

2. Triggering an Action

Action triggering allows the AI to perform real-world tasks on your behalf, such as sending notifications or managing appointments.

Examples:

• Sending Messages: Automatically sending emails or SMS via services like SendGrid or Twilio.
• Scheduling Appointments: Using Google Calendar to arrange meetings or events.
• Managing Infrastructure: Automatically deploying servers or restarting services via DevOps APIs.

Here, the AI acts as an active agent that completes tasks for you.

3. Information Retrieval

Information retrieval helps the AI access external, real-time data to provide accurate responses.

Examples:

• Checking Order Status: Quickly fetching the latest status from an e-commerce database.
• Current Weather & News: Getting real-time data from services like OpenWeatherMap or news feeds.
• Knowledge Database Access: Retrieving information like product details or FAQs from internal databases.

These mostly involve using GET requests to pull data.

Practical Use Cases by Industry and Role

Here's a summary of some real-world function calling scenarios:

This table illustrates how broadly function calling can support practical, everyday tasks across various industries.