Markus Ecker 40205f3900 fix(deps): resolve @ag-ui peers to the renamed build, not the old canary
The lockfile installed TWO incompatible copies of the protocol: the PR-2350
preview carrying `subagentRunId`, and the old `0.0.59-canary.1785518626.0`
carrying `subagentId`. Any subagent-attributed event passing through a package
bound to the canary copy lost its attribution silently -- the registry would read
a field the stream no longer emits, so every lookup returned undefined with no
error. Reported in review of the rename commit.

The cause is peer auto-install, which took a while to find. `pnpm.overrides`
governs DECLARED dependencies. `@ag-ui/langgraph`, `@ag-ui/a2a` and
`@ag-ui/mcp-apps-middleware` declare `@ag-ui/core` / `@ag-ui/client` as PEERS,
and four workspace packages depended on them without declaring those peers
themselves -- so pnpm auto-installed the peers straight from the registry,
resolving to the canary and bypassing the overrides. That is why the overrides
looked ignored: they were never consulted for those edges.

Fixed the conventional way, by declaring the peers so they resolve from the graph
instead of being fetched:

- `packages/sdk-js` -- @ag-ui/core, @ag-ui/client
- `examples/v2/angular/demo-server` -- @ag-ui/core, @ag-ui/client
- `examples/showcases/generative-ui-playground` -- @ag-ui/core
- `examples/v2/vue/demo` -- @ag-ui/client (it declared mcp-apps-middleware but no
  client, which was the last remaining edge)

Result: zero references to the canary in the lockfile, and exactly ONE
@ag-ui/core installed -- the renamed preview. Verified by deleting the stale
store directories and reinstalling from the committed lockfile alone: they are
not recreated, so nothing can reach the old copy.

Things that did NOT work, recorded so they are not retried: plain install,
`--force`, `pnpm dedupe`, `>`-scoped overrides (`@ag-ui/a2a>@ag-ui/core`),
version-specific overrides, and deleting the lockfile to regenerate from scratch
-- which reproduced it byte-identically, since the resolution was correct given
the package.json files rather than stale.

These four declarations are TEMPORARY, like the overrides they support, and come
out with them when @ag-ui publishes the rename.

Verified: @copilotkit/core, react-core and sdk-js typecheck; react-core 1424
tests and vue 1071 tests pass.
2026-08-10 15:10:17 +02:00
2026-04-07 12:29:28 +02:00
2026-06-18 14:54:25 -07:00
2026-06-18 14:54:25 -07:00
2023-06-30 16:46:26 -07:00
2026-06-23 20:52:56 -07:00
2026-06-23 20:52:56 -07:00
2026-07-06 14:24:16 -07:00

FavIcon

CopilotKit

Build agent-native applications — on any framework, on any surface.

Generative UI, shared state, and human-in-the-loop workflows for React, Angular, Vue, React Native — and beyond the browser.

CopilotKit



What is CopilotKit

CopilotKit is a best-in-class SDK for building full-stack agentic applications, Generative UI, and chat applications.

What started as a React library is now a multi-platform agentic framework: the same agent can power your web app, your mobile app, and your team's Slack workspace.

We are the company behind the AG-UI Protocol - adopted by Google, LangChain, AWS, Microsoft, Mastra, PydanticAI, and more!

Quick Start

Up and running in under five minutes. All you need is an LLM key (OpenAI, Anthropic, Gemini, etc.).

npx copilotkit@latest create

Agent Skills

CopilotKit ships agent skills that teach your coding agent (Claude Code, Codex, Cursor, Gemini, and others) how to set up, build with, integrate, debug, and upgrade CopilotKit.

Install them into any project directory:

npx copilotkit@latest skills install

Run it again any time to refresh to the latest skills.

Bring Your App to Life

https://github.com/user-attachments/assets/72b7b4f3-b6e7-460c-a932-5746fe3c8db3

Add AI to your app in 1 minute

Features:

  • Chat UI A fully customizable chat interface that supports message streaming, tool calls, and agent responses.
  • Backend Tool Rendering Enables agents to call backend tools that return UI components rendered directly in the client.
  • Generative UI Allows agents to generate and update UI components dynamically at runtime based on user intent and agent state.
  • Shared State A synchronized state layer that both agents and UI components can read from and write to in real time.
  • Human-in-the-Loop Lets agents pause execution to request user input, confirmation, or edits before continuing.
  • Self-Learning (early access) Agents that continuously improve from user feedback via in-context reinforcement learning (CLHF).

🧩 Works With Your Stack

One agent backend. Every frontend.

Platform Status Get Started
⚛️ React / Next.js GA Quickstart
🅰️ Angular Supported Source Code - Quickstart coming soon
💚 Vue Supported Source Code - Quickstart coming soon
📱 React Native Supported Quickstart
💬 Slack / MS Teams / Discord / Google Chat 🟡 Beta Request early access

Your agent logic stays the same — AG-UI handles the wire protocol, CopilotKit handles the UI layer for each framework.

💬 Beyond the Browser: Slack & Microsoft Teams (Discord, Google Chat coming soon...)

Your agents can run and generate Generative UI beyond the web app (Learn more).

CopilotKit now lets you deploy the same agent to the places your users already work:

  • Slack Agents as first-class Slack apps: threads, tool calls, and human-in-the-loop approvals right in the channel.
  • Microsoft Teams Bring agentic workflows to the enterprise, where your org already lives.

🔒 Early access: We're onboarding teams now.

👉 Request early access →

🧠 Self-Learning Agents

Improve your product by learning over time.

With Continuous Learning from Human Feedback (CLHF), part of the CopilotKit Intelligence Platform, agents improve with every interaction:

  • In-context reinforcement learning Agents automatically improve from user interactions, no model fine-tuning required.
  • Automatic prompt augmentation Agent behavior adapts based on recent interactions and outcomes.
  • Per-user adaptation Agents learn individual preferences and get better for each user over time.
  • Threads & persistence Full interaction history — generative UI, human-in-the-loop, shared state — captured across sessions.

Available via CopilotKit Cloud or self-hosted.

🔒 Early access: We're onboarding teams now.

👉 Request early access →

https://github.com/user-attachments/assets/7372b27b-8def-40fb-a11d-1f6585f556ad

What this gives you:

  • CopilotKit installed Core packages are fully set up in your app
  • Provider configured Context, state, and hooks ready to use
  • Agent <> UI connected Agents can stream actions and render UI immediately
  • Deployment-ready Your app is ready to deploy

Complete getting started guide →

How it works:

CopilotKit connects your UI, agents, and tools into a single interaction loop.

CopilotKit Diagram — Motion x2 6 sec version

This enables:

  • Agents that ask users for input
  • Tools that render UI
  • Stateful workflows across steps and sessions
  • One agent, deployed across web, mobile, and chat platforms

useAgent Hook

The useAgent hook sits directly on AG-UI, giving you full programmatic control over the agent connection.

// Programmatically access and control your agents
const { agent } = useAgent({ agentId: "my_agent" });

// Render and update your agent's state
return <div>
  <h1>{agent.state.city}</h1>
  <button onClick={() => agent.setState({ city: "NYC" })}>
    Set City
  </button>
</div>

Check out the useAgent docs to learn more.

https://github.com/user-attachments/assets/67928406-8abc-49a1-a851-98018b52174f

Generative UI

Generative UI is a core CopilotKit pattern that allows agents to dynamically render UI as part of their workflow.

https://github.com/user-attachments/assets/3cfacac0-4ffd-457a-96f9-d7951e4ab7b6

Compare the Three Types

image

Explore:

Generative UI educational repo →

🖥️ AG-UI: The AgentUser Interaction Protocol

Connect agent workflows to user-facing apps, with deep partnerships and 1st-party integrations across the agentic stack—including LangChain, CrewAI, Mastra, PydanticAI, and more.

AG-UI


npx create-ag-ui-app my-agent-app
Learn more in the AG-UI README →

🤝 Community

Have questions or need help?

Join our Discord →
Read the Docs →
Try the Enterprise Intelligence Platform →

Stay up to date with our latest releases!

Follow us on LinkedIn →
Follow us on X →

🙋🏽‍♂️ Contributing

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:

📄 License

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

S
Description
copilotkit-debug: Use when diagnosing CopilotKit issues -- runtime connectivity failures, agent not responding, streaming errors, tool execution problems, transcription…; copilotkit-develop: Use when building AI-powered features with CopilotKit v2 -- adding chat interfaces, registering frontend tools, sharing application context with agents,…; copilotkit-agui: Use when building custom agent backends, implementing the AG-UI protocol, debugging streaming issues, or understanding how agents commun…
Readme MIT 924 MiB
Languages
TypeScript 78.7%
MDX 6.6%
Python 6.4%
C# 1.7%
CSS 1.3%
Other 5.3%