Tool Calling, Explained: How AI Agents Decide What to Do Next

Tool calling enables an AI agent to interact with the external world by deciding which functions or APIs to use in response to a user's request. The Large Language Model does not execute the function itself but returns a structured response indicating the specific tool and arguments to be used by the application code. This code then executes the function, feeds the result back to the model, and the model uses this new information to generate a final, context-aware answer. The article demonstrates this process with a Python example using a weather API and shows how a model can intelligently select the correct tool from multiple options based on the user's query.