![CopilotKit](/statics/github-mark.png)
CopilotKit
React UI + elegant infrastructure for AI Copilots, in-app AI agents, AI chatbots, and AI-powered Textareas 🪁
Stars: 16220
![screenshot](/screenshots_githubs/CopilotKit-CopilotKit.jpg)
CopilotKit is an open-source framework for building, deploying, and operating fully custom AI Copilots, including in-app AI chatbots, AI agents, and AI Textareas. It provides a set of components and entry points that allow developers to easily integrate AI capabilities into their applications. CopilotKit is designed to be flexible and extensible, so developers can tailor it to their specific needs. It supports a variety of use cases, including providing app-aware AI chatbots that can interact with the application state and take action, drop-in replacements for textareas with AI-assisted text generation, and in-app agents that can access real-time application context and take action within the application.
README:
Get started in minutes - check out the quickstart documentation.
// 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 RAG
useCopilotReadable({
description: "The current user's colleagues",
value: colleagues,
});
// knowledge-base integration
useCopilotKnowledgebase(myCustomKnowledgeBase)
// ---
// 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)] }),
});
// ---
// structured autocomplete for anything
const { suggestions } = useCopilotStructuredAutocompletion(
{
instructions: `Autocomplete or modify spreadsheet rows based on the inferred user intent.`,
value: { rows: spreadsheet.rows.map((row) => ({ cells: row })) },
enabled: !!activeCell && !spreadsheetIsEmpty,
},
[activeCell, spreadsheet]
);
// 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 }) => (
<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);
Thanks for your interest in contributing to CopilotKit! 💜
We value all contributions, whether it's through code, documentation, creating demo apps, or just spreading the word.
Here are a few useful resources to help you get started:
-
For code contributions, CONTRIBUTING.md.
-
For documentation-related contributions, check out the documentation contributions guide.
-
Want to contribute but not sure how? Join our Discord and we'll help you out!
💡 NOTE: All contributions must be submitted via a pull request and be reviewed by our team. This ensures all contributions are of high quality and align with the project's goals.
You are invited to join our community on Discord and chat with our team and other community members.
This repository's source code is available under the MIT License.
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