What problem does it solve?
It helps you register LLM tools and display rich, tool-specific user interfaces so tool calls feel first-class and—when needed—can involve humans directly.
Core Features & Use Cases
- Tool registration for AI calls: Define tool names, input schemas, and execution logic for backend or browser-only execution.
- Custom tool UI rendering: Render tool call states (running/complete/incomplete/requires-action) with
makeAssistantToolUI.
- Human-in-the-loop interactions: Pause tool execution for confirmation or user input using
requires-action and submitResult.
- Reference-driven implementation: Use the included guidance to implement
makeAssistantTool, makeAssistantToolUI, and interactive patterns consistently.
Quick Start
Register a backend or frontend tool named exactly as the UI expects, then wire the UI component inside AssistantRuntimeProvider and render the tool call output based on its status value.