Overview of actions and the stop and parse approach. Formats JSON/CODE.
The design of the interface through which an agent uses tools can affect the agent’s performance. For example, a search tool that returns results ordered by relevance may be more helpful to an AI agent than one that returns results ordered by frequency. The interface should be designed to be clear and concise, so that the agent can easily understand how to use the tools. It should also be designed to be flexible, so that the agent can use the tools in different ways depending on the task at hand.
Here are some examples of how interface design can affect an AI agent’s performance:
The use of tools is considered a form of “acting” by an AI agent in an environment. Agents can generate special tokens to invoke tool calls. This “acting” can be guided by “reasoning,” which allows the agent to plan and re-plan based on the information gained from the tool. For example, an agent might use a search engine to find information and then use a calculator to perform calculations based on that information. The agent may revise its plan based on the result of the calculation and return the retrieved information. This kind of reasoning-based tool use is the cornerstone of agents, and we will explore it in more detail in the coming sections.
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