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Max Korp
bec1fd0811
The A2UI React renderer (packages/a2ui-renderer/src/react-renderer/a2ui-react/A2uiSurface.tsx:152)
always begins rendering at the component with id="root":
export const A2uiSurface: React.FC<{...}> = ({ surface }) => {
// The root component always has ID 'root' and base path '/'
return <DeferredChild surface={surface} id="root" basePath="/" />;
};
If no component has that ID, DeferredChild falls through to its loading-
shimmer placeholder, so the surface silently renders as an empty ~30px
rectangle regardless of how many other components are on the surface.
The generation guidelines shipped to the sub-LLM (in @copilotkit/shared
and copilotkit sdk-python) never stated this requirement. Fixed-schema
demos hard-code a component with id="root" in their JSON and work; dynamic
demos relied on the LLM guessing, which it sometimes did and sometimes
didn't. The failure mode is particularly nasty: no error, no warning,
just a loading spinner that never resolves.
Adds the requirement to COMPONENT ID RULES in both the TS and Python
guideline strings. Both strings are injected into the sub-LLM's context
by A2UICatalogContext (packages/react-core) and
copilotkit.a2ui.a2ui_prompt() respectively, so every A2UI-enabled app
picks it up automatically — no per-demo change needed.
Stacked on #4216, which restores the same instruction to the
langgraph-python-threads demo's tool docstring (belt-and-braces until
consumers update their shared package version).
CopilotKit - Shared
✨ Why CopilotKit?
- Minutes to integrate - Get started quickly with our CLI
- Framework agnostic - Works with React, Next.js, AGUI and more
- Production-ready UI - Use customizable components or build with headless UI
- Built-in security - Prompt injection protection
- Open source - Full transparency and community-driven
🧑💻 Real life use cases
Deploy deeply-integrated AI assistants & agents that work alongside your users inside your applications.
🖥️ Code Samples
Drop in these building blocks and tailor them to your needs.
Build with Headless APIs and Pre-Built Components
// Headless UI with full control
const { visibleMessages, appendMessage, setMessages, ... } = useCopilotChat();
// Pre-built components with deep customization options (CSS + pass custom sub-components)
<CopilotPopup
instructions={"You are assisting the user as best as you can. Answer in the best way possible given the data you have."}
labels={{ title: "Popup Assistant", initial: "Need any help?" }}
/>
// Frontend actions + generative UI, with full streaming support
useCopilotAction({
name: "appendToSpreadsheet",
description: "Append rows to the current spreadsheet",
parameters: [
{ name: "rows", type: "object[]", attributes: [{ name: "cells", type: "object[]", attributes: [{ name: "value", type: "string" }] }] }
],
render: ({ status, args }) => <Spreadsheet data={canonicalSpreadsheetData(args.rows)} />,
handler: ({ rows }) => setSpreadsheet({ ...spreadsheet, rows: [...spreadsheet.rows, ...canonicalSpreadsheetData(rows)] }),
});
Integrate In-App CoAgents with LangGraph
// Share state between app and agent
const { agentState } = useCoAgent({
name: "basic_agent",
initialState: { input: "NYC" }
});
// agentic generative UI
useCoAgentStateRender({
name: "basic_agent",
render: ({ state }) => <WeatherDisplay {...state.final_response} />,
});
// Human in the Loop (Approval)
useCopilotAction({
name: "email_tool",
parameters: [
{
name: "email_draft",
type: "string",
description: "The email content",
required: true,
},
],
renderAndWaitForResponse: ({ args, status, respond }) => {
return (
<EmailConfirmation
emailContent={args.email_draft || ""}
isExecuting={status === "executing"}
onCancel={() => respond?.({ approved: false })}
onSend={() =>
respond?.({
approved: true,
metadata: { sentAt: new Date().toISOString() },
})
}
/>
);
},
});
// intermediate agent state streaming (supports both LangGraph.js + LangGraph python)
const modifiedConfig = copilotKitCustomizeConfig(config, {
emitIntermediateState: [
{
stateKey: "outline",
tool: "set_outline",
toolArgument: "outline",
},
],
});
const response = await ChatOpenAI({ model: "gpt-4o" }).invoke(
messages,
modifiedConfig,
);
🏆 Featured Examples
Documentation
To get started with CopilotKit, please check out the documentation.