Unverified50% confidenceFactExact time
The key difference between an Agent and an ordinary LLM application lies in tool calling (Tool/Function Calling): the model outputs the function to be called and its parameters in an agreed format, and the program executes it and passes the result back to the model to continue reasoning.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
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Unverified现代LLM Agent的核心逻辑可归结为一个循环：接收目标、调用LLM、解析输出、执行工具、重复迭代78% similarUnverifiedThe fundamental difference between Agentic workflows and traditional single LLM calls lies in the closed loop of multi-step reasoning and tool invocation.78% similarVerifiedAn Agent's Action capability relies on standardized interfaces such as Function Calling or Tool Use to convert the model's text output into executable API calls.78% similarVerifiedThe technical essence of Agent-type tools is an LLM-based autonomous decision-making loop, i.e., the ReAct framework (Reasoning → Action → Observation → Re-reasoning).77% similarVerifiedAgents use the Tool Calling mechanism to allow models to output calling intent in a structured JSON format, with external programs executing the actual operations and feeding results back to the model.77% similar
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