Expired50% confidenceFactExact time
Function Calling is currently the standard interface method supported by mainstream LLMs for tool invocation.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/10/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/8/2026(expired)
Sources
AI Agent Learning Path for Beginners: From Theory to Real-World Practice
bilibiliAgent开发7/9/2026
Related Claims
UnverifiedTool Calling (Function Calling) allows an LLM to dynamically invoke external APIs, database queries, and code execution tools during the reasoning process79% similarPartially VerifiedRecent versions of LLM have added tool-calling (tool-calling/function-calling) functionality.78% similarUnverifiedFunction Calling has three major advantages: strictly parseable output format, support for parallel tool calls, and dynamic capability expansion.73% similarUnverifiedUnder the LangChain framework, defining a tool only requires writing a regular function with a description and a @tool decorator, and its description is serialized into a Function Calling format understandable by large language models.72% similarUnverifiedThe new version introduces llm.user() and llm.assistant() builder functions, supporting the passing of complete conversation history via a messages=[] array.72% similar
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