Files
Benjamin Taylor 28437b1612 feat(web-components): expose drawer width + mobile breakpoint (ENT-1035)
Surface the CopilotThreadsDrawer's own structural values so host layouts
stop hand-copying `320px` / `768px`:

- New `layout-constants.ts` (single source of truth): DRAWER_DEFAULT_WIDTH,
  DRAWER_DEFAULT_WIDTH_PX, MOBILE_BREAKPOINT_PX, MOBILE_MAX_WIDTH_PX,
  MOBILE_MAX_WIDTH_QUERY. Exported from the barrel and from a PURE
  `./threads-drawer/layout-constants` subpath (importing it never evaluates
  the Lit element, so it is SSR-safe).
- Ship `./threads-drawer/layout.css`: a `:root --cpk-drawer-width` default
  plus `copilotkit-threads-layout` / `copilotkit-threads-main` helper classes
  that reserve the drawer column and collapse it on mobile off the same width
  and breakpoint the element uses. Copied into dist via a build:css step.
- The element and its shadow styles now read the constants. This also fixes
  the 767/768 seam (ENT-1037 item 1): the element flipped to mobile overlay at
  `max-width: 768px` while the react/vue coordination layers used
  `max-width: 767px`, so at exactly 768px the drawer went modal with no
  on-screen launcher. The element now uses 767px like everything else.
- react-core (Provider, ModalHeader, ChatInput) and vue (is-mobile-viewport,
  ChatInput) key their mobile split off the shared MOBILE_MAX_WIDTH_QUERY.
- Parity test asserts layout.css and the element stay in sync with the
  constants; attw excludes the CSS entrypoint.
2026-07-02 12:14:11 -05:00
..
2026-04-10 23:38:59 +00:00
2026-07-01 17:07:44 +00:00
…

CopilotKit - React Core

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✨ 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
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🧑‍💻 Real life use cases

Deploy deeply-integrated AI assistants & agents that work alongside your users inside your applications.

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🖥️ 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,
);

Documentation

To get started with CopilotKit, please check out the documentation.