The CoAgents framework indeed employs an innovative multi-intelligentsia collaborative architecture with a core consisting of three parts: base agent, execution agent and observation agent. The base agent is responsible for transforming user intent into executable tool instructions, the execution agent focuses on specific tool or API invocation operations, and the observation agent extracts valuable information from the returned data. This division of labor and collaboration mechanism forms a complete feedback loop, and when an error occurs during execution, the system is able to make iterative adjustments and self-corrections based on environmental feedback, thus significantly improving the accuracy and efficiency of the tools used in the large language model.
This answer comes from the articleCoAgents: a framework for learning to use tools through multi-intelligence collaborationThe
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