Models
Function Calling
A model capability where the LLM outputs structured JSON describing which function to call and with what arguments, rather than plain text.
In depth
A model capability where the LLM outputs structured JSON describing which function to call and with what arguments, rather than plain text. This lets AI applications reliably trigger actions like database queries, API calls, or tool use based on natural language input.
Example
This lets AI applications reliably trigger actions like database queries, API calls, or tool use based on natural language input.
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FAQ
Common questions
What is Function Calling?
A model capability where the LLM outputs structured JSON describing which function to call and with what arguments, rather than plain text.
Why does Function Calling matter for AI developers?
Function Calling sits in the Models part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Function Calling?
Developers Digest publishes tutorials and videos that cover Models topics including Function Calling. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Models
Interleaved Thinking
A Claude capability that lets the model think between tool calls within a single assistant turn, reasoning about each tool result before deciding what to do next.
Models
Adaptive Thinking
A Claude feature where the model decides how much to reason based on task difficulty rather than a fixed thinking budget.
Models
Tree of Thoughts
A prompting framework that has a language model explore several intermediate reasoning steps ("thoughts") as branches of a tree instead of one linear chain.
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