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React UI + elegant infrastructure for AI Copilots, in-app AI agents, AI chatbots, and AI-powered Textareas πŸͺ

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CopilotKit Logo

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





214 (1)

Demos (click to clone / run)

πŸ“Š Spreadsheets + Copilot

Spreadsheet Demo

View Demo Repository β†’

A powerful spreadsheet assistant that helps users analyze data, create formulas, and generate insights through natural language interaction.

🏦 Banking Assistant (SaaS Copilot)

View Demo Repository β†’

An AI-powered banking interface that helps users manage transactions, analyze spending patterns, and get personalized financial advice.

✈️ [Tutorial] Agent-Native Travel Planner (ANA)

View Tutorial β†’

Interactive travel planning assistant that helps users discover destinations, create itineraries, and manage trip details with natural language.

πŸ” [Tutorial] Agent-Native Research Canvas (ANA)

View Demo Repository β†’

An intelligent research assistant that helps users analyze academic papers, synthesize information across multiple sources, and generate comprehensive research summaries through natural language interaction.

Getting Started

Get started in minutes - check out the quickstart documentation.

Code Samples

// 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]
);

Code Samples (CoAgents: in-app LangGraph Agents)

// 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);

Contributing

Thanks for your interest in contributing to CopilotKit! πŸ’œ

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:

πŸ’‘ 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.

Get in touch

You are invited to join our community on Discord and chat with our team and other community members.

License

This repository's source code is available under the MIT License.

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