CoAgents breaks through the limitations of traditional LLM through an innovative multi-intelligence collaboration mechanism. It breaks down the process of tool use into three specialized segments: theBasic AgentGenerate precise instructions, byexecuting agentTool handling, and then theObservation AgentsParsing results. This division of labor achieves three key improvements: 1) avoiding ambiguous or non-executable instructions from a single LLM; 2) execution agents can specialize in optimizing the technical details of API calls; and 3) observation agents can accurately extract key information from structured data. What's more, the system forms a closed-loop feedback when an execution error occurs, and each agent can automatically adjust its strategy based on the environmental feedback, an iterative learning capability that enables the framework to continuously optimize the effectiveness of tool usage.
This answer comes from the articleCoAgents: a framework for learning to use tools through multi-intelligence collaborationThe
English 
简体中文 
日本語 
Deutsch 
Português do Brasil