Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

One hook connects any Agent to your frontend Then layer on chat UI, threads, generative UI, voice transcription, tool calls, state sync, HITL, and any AI feature. We make it easy for devs to build fullstack agentic apps. Everything here is built with CopilotKit 👇

20,568 görüntüleme • 5 ay önce •via X (Twitter)

7 Yorum

CopilotKit🪁 profil fotoğrafı
CopilotKit🪁5 ay önce

Entirely open source.

CopilotKit🪁 profil fotoğrafı
CopilotKit🪁5 ay önce

Tools for Devs building with CopilotKit: 1. CopilotKit MCP Server gives coding agents (Cursor, Claude etc.) structured access to docs, code, and examples so that they can generate accurate code, give your AI agents a UI, and help you implement features correctly 2. Inspector built-in debugging tool that gives you full visibility into what's happening between your frontend and agents in real time 3. VS Code Extension Live preview your CopilotKit render hooks, A2UI catalog components, and AG-UI event stream — without leaving VS Code 3. Debug Mode single flag, structured logging across the full stack 4. AIMock mock your entire agentic stack (LLMs, MCP tools, A2A agents) from one config file for testing and more...

Sani Ai Tech profil fotoğrafı
Sani Ai Tech5 ay önce

One hook for fullstack agentic apps is dev superpower right there

Alice The Ai Expert profil fotoğrafı
Alice The Ai Expert5 ay önce

This makes agentic apps way easier to ship

Aaliya profil fotoğrafı
Aaliya5 ay önce

Nice concept. Making agent integration this simple can really speed up building full-stack AI apps.

Sharon Riley profil fotoğrafı
Sharon Riley5 ay önce

That "one hook" simplicity is a game-changer for dev speed, but how does it handle complex state sync when multiple tools are calling at once?

Karl Ju profil fotoğrafı
Karl Ju5 ay önce

Is it true that the react support is for nextjs only?

Benzer Videolar

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

Santiago

17,438 görüntüleme • 4 ay önce