Function Calling
Structured model outputs that invoke predefined functions/tools with typed arguments, enabling safe actions and structured data extraction.
Function calling lets models return structured tool invocations instead of free-form text. Tools define schemas; the model fills arguments to perform actions or fetch data.
Teams use function calling to connect LLMs to APIs, databases, and business logic—routing tasks like lookups, calculations, and updates through controlled handlers.
In workflows, it reduces hallucinations, enforces structure, and keeps actions auditable. Proper schema design and validation make agent runs safer and easier to debug.
Frequently Asked Questions
How do I design function schemas?
Keep arguments typed and minimal, use enums where possible, and include descriptions/examples. Avoid overly broad free-text fields.
How do I prevent unsafe actions?
Whitelist functions, validate arguments, enforce RBAC, and add business-rule guardrails. Keep side effects idempotent when possible.
What if the model picks the wrong function?
Use clear names/descriptions, add disambiguating instructions, and log/model feedback. Consider routing layers or classification before tool choice.
How do I debug function calling?
Log chosen function, arguments, validation results, and handler output. Store traces for replay and improvement.
Can I chain multiple function calls?
Yes—allow iterative calls with context carryover. Cap iterations and validate each step to avoid loops.
How do I handle validation failures?
Return structured errors and, if safe, let the model repair arguments. Otherwise route to human review or fail-safe paths.
Does function calling reduce hallucinations?
It reduces free-form outputs by forcing structured calls, but you still need validation and guardrails to prevent bad arguments.
What about cost and latency?
Tool calls add latency. Keep tools fast, batch where possible, and choose models that handle function calling efficiently.
How do I secure function calls?
Authenticate handlers, enforce least privilege, and limit exposed capabilities. Mask secrets and avoid echoing sensitive data in prompts.
Agentic AI
An AI approach where models autonomously plan next steps, choose tools, and iterate toward an objective within guardrails.
Agentic Workflow
A sequence where an AI agent plans, executes tool calls, evaluates results, and loops until success criteria are met.
Agent Handoff
A pattern where one AI agent passes context and state to another specialized agent to keep multi-step automation modular.
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