Function Calling

Function calling bridges the gap between AI language understanding and real-world action. Instead of just generating text, the model can decide to call a function — search the web, query a database, send an email, execute code — by outputting a structured JSON object that the system then executes.

The mechanism works through tool definitions: you describe available functions (name, parameters, descriptions) in the system prompt. When the model determines a function call would help, it generates a structured call instead of plain text. The system executes the function and returns the result to the model, which then continues its reasoning.

Function calling is what transforms a chatbot into an agent. Without it, an LLM can only talk about actions. With it, the LLM can take actions — reading files, writing code, deploying applications, sending notifications. At Agentik {OS}, function calling is how our agents interact with the real world. Each agent has access to dozens of tools specific to its role: development agents call code execution tools, marketing agents call analytics APIs, design agents call image generation services. The tools make the agents operational.