mirror of
https://github.com/CopilotKit/CopilotKit.git
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Tyler Slaton
0e787632a3
Pressing Stop mid-stream against a CopilotRuntime + HttpAgent proxy aborts the upstream agent, which emits a live RUN_ERROR while a text message is still open. finalizeRunEvents then appended a trailing TEXT_MESSAGE_END *after* that RUN_ERROR. Because the runners stream finalization events after everything the agent already emitted, the closer landed past the terminal and the AG-UI verifier rejected it with "the run has already errored with 'RUN_ERROR'. No further events can be sent." — crashing the chat. finalizeRunEvents (in @copilotkit/shared, consumed by the in-memory, intelligence, and sqlite runners) now returns early and appends nothing when the stream already contains a terminal event (RUN_FINISHED or RUN_ERROR): any message or tool call still open is closed by the terminal on the client. The abrupt-end path (no terminal -> close open streams + synthesize a terminal) is unchanged. Tests: - finalize-events.test.ts: terminal-present appends nothing (both RUN_FINISHED and RUN_ERROR) + a named #5812 case. - in-memory-runner.test.ts: end-to-end mid-stream-stop regression that asserts no events follow RUN_ERROR and the stream passes AG-UI verifyEvents (the verifier the browser runs). - intelligence-runner.test.ts: corrected an assertion that had encoded the buggy post-terminal TEXT_MESSAGE_END. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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.