Azure AI Agent Function Calling: Connect Your Agent to APIs with Terraform 🔌

An Azure AI agent without tools is just a chatbot. Function calling gives your agent the ability to invoke your code when it needs real data or actions. Here's how to define functions, handle tool calls, and wire up the infrastructure with Terraform. In the previous post, we deployed an Azure AI agent that can reason and hold multi-turn conversations. But it can only generate text from what the model already knows. Ask it for a live exchange rate or your account balance, and it either hallucinates or admits it doesn't know. Function calling changes that. You define functions with descriptions and parameters. When the agent determines it needs data or an action, it returns a structured function call request. Your code executes the function and sends the result back. The agent then uses that real data to generate its response. The model decides what to call; your code does the work. 🎯 🏗️ How Function Calling Works User: "What's the exchange rate from USD to EUR?" ↓ Agent reads function