Function Calling
An LLM capability where the model decides to call a defined function with structured arguments, enabling reliable tool use in production systems.
· Reviewed by senior engineers
Function calling (also called tool use) is the LLM capability that lets the model produce a structured request to call a specific function rather than answering in free text. You give the model a list of functions with names, descriptions and JSON Schema for the arguments. When the model decides one applies, it returns a function name and the arguments to pass; your code executes and returns the result; the model uses the result to produce the final answer.
This is what makes reliable agents and integrations possible. Without function calling, hooking an LLM to a database, API or external tool requires fragile regex parsing of free text — which breaks on the model's next quirky output. With it, you get a typed, parsable interface that scales to dozens of tools without losing coherence.
The nuances matter. Function descriptions are prompts — clear, unambiguous, with worked examples — not documentation. Argument schemas should constrain values where possible (enums, formats) so the model can't invent invalid inputs. Parallel function calling, where supported, lets the model fan out across independent calls in one turn, dramatically cutting latency.
Devinsta builds function-calling integrations as the default pattern for any LLM feature that touches your systems. The boilerplate is small; the reliability gain is enormous.