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https://github.com/CopilotKit/CopilotKit.git
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de9d46d1df
Bring the agent skills in line with the shipped v2 API so their examples install, compile, and connect. Extends #5345 (which migrated the copilotkit-setup SKILL.md body) to the rest of the skills. - Imports: drop the nonexistent @copilotkit/react and @copilotkit/agent packages and the bare @copilotkit/runtime/express subpath; use @copilotkit/react-core/v2 and @copilotkit/runtime/v2 (+ /v2/express), and createCopilotHonoHandler / createCopilotExpressHandler rather than the deprecated createCopilotEndpoint aliases. - Provider: CopilotKit from @copilotkit/react-core/v2 with useSingleEndpoint={false} on multi-route setups (the v1-compat bridge defaults to single transport and would 404 a multi-route backend). - Routes: v2 catch-all Hono handler exporting GET/POST/PATCH/DELETE via handle() from hono/vercel, replacing the v1 copilotRuntimeNextJSAppRouterEndpoint + ExperimentalEmptyAdapter. - Integrations: per-framework agent classes matched to the shipped examples (LangGraphAgent/LangGraphHttpAgent from @copilotkit/runtime/ langgraph, CrewAIAgent, MastraAgent, LlamaIndexAgent, HttpAgent from @ag-ui/client; Agno via HttpAgent, not @ag-ui/agno). - Hooks/props: correct useAgent, useThreads, useRenderTool, identifyUser, and the chat-component props (defaultOpen, onSubmitMessage, the headless CopilotChatView render prop). Validated across review rounds and a build test against the published @copilotkit/*@1.60.0 packages (tsc passes, every /v2 subpath resolves). Regenerated the skills/runtime and skills/react-core mirrors.
CopilotKit - React Core
✨ 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.