LLM agents often operate with information limited to their training data, lacking direct means to access current data or execute actions in external systems. External Application Programming Interfaces (APIs) offer a structured bridge, allowing these agents to interact with a wide array of services and data sources. This chapter provides in-depth guidance on how to effectively wrap external APIs, transforming them into usable and reliable tools for your LLM agents.

You will learn key techniques for this integration, including establishing secure authentication and authorization for API access. We will cover methods for parsing various API response formats and appropriately structuring data for LLM consumption. The chapter also addresses operational necessities like managing API rate limits and implementing effective retry mechanisms. A significant focus will be on enabling the LLM to map natural language requests to specific API calls, and subsequently, on how to process and summarize API data concisely for the agent. Security considerations specific to API tool integration will be discussed throughout. You'll also have the opportunity to apply these concepts by wrapping a public API as a functional LLM tool.