LLMs don't execute functions directly; frameworks manage tool calls

This article clarifies that Large Language Models (LLMs) do not directly execute functions. Instead, they generate structured output that represents a request to call a function. The application or an agent framework then interprets this request, validates the arguments, and executes the actual function. The result is then returned to the LLM to continue the interaction loop. This process applies across various programming languages, not just Python, and is fundamental to how agent frameworks like LangChain and PydanticAI enable LLMs to interact with external tools. AI

IMPACT Clarifies the execution flow for LLM tool usage, impacting how developers build agentic applications.

RANK_REASON Article explains the technical mechanism of LLM function calling, clarifying a common misconception.

Read on dev.to — LLM tag →

• C.
• LangChain
• langgraph
• PydanticAI
• Python
• Rust
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