How to Build An AI Agent with Function Calling and GPT-5

AI agents extend the capabilities of large language models (LLMs) by allowing them to interact with external tools and environments to solve complex tasks. An agent's basic structure consists of an LLM as its "brain" for reasoning and planning, and tools that perform actions like web searches or calendar access. Function calling is the key technique that connects the LLM to these external tools by using a schema to define when and how a specific function should be used. The content provides a step-by-step Python tutorial for building a web search agent, utilizing an LLM, the Tavily search API, and a defined tool schema to handle queries requiring up-to-date information.