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✨AG-UI has been taking off! The Agent-User Interaction Protocol, allows you to bring AI agents into Frontend Apps. Excited to announce BIG updates & adoption by LlamaIndex 🦙 ,Agno, Google ADK, AWS & more! + New Building Experience🧑‍💻 npx create-ag-ui-app How it works & more 👇

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CopilotKit🪁

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70,572 görüntüleme • 1 yıl önce •via X (Twitter)

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AG-UI Launched one month ago with day-0 support for LangGraph, CrewAI, Mastra and AG2 - it has since taken off with both users & integrations! Today we're excited to welcome @llama_index & @AgnoAgi into AG-UI🎉 AG-UI fills a major gap in the Agent ecosystem, making it dead simple for builders to bring compatible Agents into Frontend clients. In the protocol landscape; MCP; Agents to tools A2A; Agents to agents AG-UI; Agents to users, via Frontends We first developed AG-UI as an in-house protocol for CopilotKit integrations, but we have since factored it into a generalized and powerful open protocol...

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Here's how it works: AG-UI compatible frameworks emit events (20 types of events) as they are running, to update state or UI, send messages or tool calls, etc AG-UI compatible clients, listen to these events, and represent them in the Frontend. This includes UI, shared state, and deep human-in-the-loop. It is highly extendable by design. AG-UI is a bridge. Connect to that bridge and you will automatically get framework <> client compatibility

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To get started with AG-UI, you can either: 🧑‍💻Create an AG-UI application via: npx create-ag-ui-app 🤝To integrate with AG-UI (for new clients & frameworks) Go to and check out the integration guides. Star the repo⭐️ We are only one month in, and just getting started!

Bonnie profil fotoğrafı
Bonnie1 yıl önce

@llama_index @AgnoAgi This is awesome.

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Uli 🪁1 yıl önce

@llama_index @AgnoAgi Amazing job on all the new integrations. AG-UI 📈

Avi Chawla profil fotoğrafı
Avi Chawla1 yıl önce

@llama_index @AgnoAgi Been waiting for the LlamaIndex integration. Great work solving a key problem using AG-UI 🙌

Benzer Videolar

Microsoft 🤝 AG-UI Protocol Microsoft Agent Framework is now AG-UI compatible! 🎉 Connect your MS Agent Framework .NET agents into fullstack applications with Python coming soon 👀 MS Agent Framework takes care of the agentic backend, AG-UI connects your agents to the frontend. Features include: - Chat UI - Generative UI - State synchronization - Human-in-the-loop - Frontend Tool Calls All the building blocks you need to take your agents from the backend and into a fullstack agentic application. Available in React & Angular via CopilotKit, and Rust, Kotlin, Rust, Java and .NET via community SDKs Big shoutout to the Microsoft & CopilotKit teams, who shipped this highly requested integration at breakneck speeds. More coming soon 👀 🙏 Javier Nelson, Joonseok Oh, Daniel Roth, Evan Mattson, Tyler Slaton, Brandon McConnell, Markus Ecker Read more about our collaboration: Get started: Check out the Dojo:
1:13

Microsoft 🤝 AG-UI Protocol Microsoft Agent Framework is now AG-UI compatible! 🎉 Connect your MS Agent Framework .NET agents into fullstack applications with Python coming soon 👀 MS Agent Framework takes care of the agentic backend, AG-UI connects your agents to the frontend. Features include: - Chat UI - Generative UI - State synchronization - Human-in-the-loop - Frontend Tool Calls All the building blocks you need to take your agents from the backend and into a fullstack agentic application. Available in React & Angular via CopilotKit, and Rust, Kotlin, Rust, Java and .NET via community SDKs Big shoutout to the Microsoft & CopilotKit teams, who shipped this highly requested integration at breakneck speeds. More coming soon 👀 🙏 Javier Nelson, Joonseok Oh, Daniel Roth, Evan Mattson, Tyler Slaton, Brandon McConnell, Markus Ecker Read more about our collaboration: Get started: Check out the Dojo:

CopilotKit🪁

40,513 görüntüleme • 7 ay önce

create-llama is now also the easiest way to get started with multi-agents using LlamaIndex 🦙 v0.2 adds multi-agents using LlamaIndex Workflows. Create a multi-agent chat UI like the one below in a single command line! 🖥️ $ npx create-llama 📄
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create-llama is now also the easiest way to get started with multi-agents using LlamaIndex 🦙 v0.2 adds multi-agents using LlamaIndex Workflows. Create a multi-agent chat UI like the one below in a single command line! 🖥️ $ npx create-llama 📄

Marcus Schiesser

48,338 görüntüleme • 1 yıl önce

We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.
0:33

We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.

Pratham

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INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!! Grok 3 generated the code for an AI agent that manages your Gmail - send, reply, and draft effortlessly Here's how it works: - Connect with your Gmail using Composio - Use Lovable to build an extremely cool frontend for the Agent - Agentic workflow with LlamaIndex Built with Composio Lovable LlamaIndex 🦙 To connect your agents with more tools like Gmail, use
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INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!! Grok 3 generated the code for an AI agent that manages your Gmail - send, reply, and draft effortlessly Here's how it works: - Connect with your Gmail using Composio - Use Lovable to build an extremely cool frontend for the Agent - Agentic workflow with LlamaIndex Built with Composio Lovable LlamaIndex 🦙 To connect your agents with more tools like Gmail, use

Karan Vaidya

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1 command to build, deploy &amp; scale AI Agents! xpander is your plug-and-play Backend-as-a-Service for agents—manages memory, tools, multi-user states, events, guardrails, and more. Works with LlamaIndex, Langchain, CrewAI, Google ADK—you name it. 100% open-source.
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1 command to build, deploy &amp; scale AI Agents! xpander is your plug-and-play Backend-as-a-Service for agents—manages memory, tools, multi-user states, events, guardrails, and more. Works with LlamaIndex, Langchain, CrewAI, Google ADK—you name it. 100% open-source.

Akshay 🚀

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All UI will become AI This is THE article you'll need give your agents a frontend. Agent-user collaboration is the future, see below 👇
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All UI will become AI This is THE article you'll need give your agents a frontend. Agent-user collaboration is the future, see below 👇

Atai Barkai

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🆕 Major upgrades to Google AI Studio: - More intuitive prompting UI - New Starter Apps to use, fork, and share - Native code editing to customize and create your own AND MORE. Start building in Blog for details:
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🆕 Major upgrades to Google AI Studio: - More intuitive prompting UI - New Starter Apps to use, fork, and share - Native code editing to customize and create your own AND MORE. Start building in Blog for details:

Google AI Developers

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Your AI stack just stopped being closed. 🔓 TanStack AI now speaks AG-UI client-to-server. - The same client hits any AG-UI server. - Any AG-UI client hits a TanStack server. Zero breaking changes. Migration guide in the tweet below 👇
0:30

Your AI stack just stopped being closed. 🔓 TanStack AI now speaks AG-UI client-to-server. - The same client hits any AG-UI server. - Any AG-UI client hits a TanStack server. Zero breaking changes. Migration guide in the tweet below 👇

TANSTACK

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Introducing the new AI first vibe coding experience in Google AI Studio! Built to take you from prompt to production with Gemini, and optimized for AI app creation. Start building AI apps for free : ) More updates and features to come!
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Introducing the new AI first vibe coding experience in Google AI Studio! Built to take you from prompt to production with Gemini, and optimized for AI app creation. Start building AI apps for free : ) More updates and features to come!

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🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5
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🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5

AshutoshShrivastava

130,227 görüntüleme • 1 yıl önce

Anthropic's in trouble, again! They spent years building what's now fully open-source. What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box. For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response. Every major AI product tried to replicate it. But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shipped natively with LangGraph, CrewAI, or Google ADK. So teams started building an owned version that required engineering the entire interface layer from scratch. Most teams, however, just settled for shipping the agent as a backend API in a chat box since rendering the UI is only one piece of it. To actually make it work, the interface layer also needed real-time streaming, state kept in sync between agent and UI, conversations that persist across sessions, and reconnection when a user refreshes mid-run. CopilotKit🪁 is now the only open-source framework that actually lets you build your own full-stack Claude-like apps. It decouples the agent from the interface, talking over AG-UI (an open protocol for agent-to-user communication). Being a standard protocol, the frontend never needs to know whether it is talking to a LangGraph or a CrewAI agent. You can change the backend anytime and the UI will never notice. In practice, CopilotKit's interface layer gives several pre-implemented React building blocks that wire the agent directly into the app, like: - generative UI, so the agent renders real components instead of text - chat windows, sidebars, and popups, or a fully headless setup - shared state, so the agent and app stay in sync - human-in-the-loop approvals, where the agent waits before acting - persistent threads that store the whole session, including the agent-user interactions and generated UI, not just text And because that full history is captured, those interactions can feed a self-learning layer that also improves the agent from real usage over time. The interface layer that Anthropic spent years engineering in-house is now literally available to any developer/team. CopilotKit is open-source with 30k+ GitHub stars, and AG-UI, the protocol underneath, is already supported across every major agent framework: LangGraph, CrewAI, Mastra, Google ADK, and more. CopilotKit GitHub repo → (don't forget to star it ⭐ ) If you want to go deeper, I found a detailed breakdown by Shubham Saboo recently on the three Generative UI patterns, with implementation. Read it below.
0:23

Anthropic's in trouble, again! They spent years building what's now fully open-source. What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box. For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response. Every major AI product tried to replicate it. But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shipped natively with LangGraph, CrewAI, or Google ADK. So teams started building an owned version that required engineering the entire interface layer from scratch. Most teams, however, just settled for shipping the agent as a backend API in a chat box since rendering the UI is only one piece of it. To actually make it work, the interface layer also needed real-time streaming, state kept in sync between agent and UI, conversations that persist across sessions, and reconnection when a user refreshes mid-run. CopilotKit🪁 is now the only open-source framework that actually lets you build your own full-stack Claude-like apps. It decouples the agent from the interface, talking over AG-UI (an open protocol for agent-to-user communication). Being a standard protocol, the frontend never needs to know whether it is talking to a LangGraph or a CrewAI agent. You can change the backend anytime and the UI will never notice. In practice, CopilotKit's interface layer gives several pre-implemented React building blocks that wire the agent directly into the app, like: - generative UI, so the agent renders real components instead of text - chat windows, sidebars, and popups, or a fully headless setup - shared state, so the agent and app stay in sync - human-in-the-loop approvals, where the agent waits before acting - persistent threads that store the whole session, including the agent-user interactions and generated UI, not just text And because that full history is captured, those interactions can feed a self-learning layer that also improves the agent from real usage over time. The interface layer that Anthropic spent years engineering in-house is now literally available to any developer/team. CopilotKit is open-source with 30k+ GitHub stars, and AG-UI, the protocol underneath, is already supported across every major agent framework: LangGraph, CrewAI, Mastra, Google ADK, and more. CopilotKit GitHub repo → (don't forget to star it ⭐ ) If you want to go deeper, I found a detailed breakdown by Shubham Saboo recently on the three Generative UI patterns, with implementation. Read it below.

Avi Chawla

449,707 görüntüleme • 14 gün önce

Excited to announce the newest Webflow app we've been building 🔥 Miyagi: An AI app for Webflow made up of 3 powerful agents: • Design Agent: Automate tasks in the Webflow Designer • Code Agent: Vibe code in Webflow • CMS Agent: Bulk edit and create content in the CMS Take a look at some more info & examples below 👇🧵
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Excited to announce the newest Webflow app we've been building 🔥 Miyagi: An AI app for Webflow made up of 3 powerful agents: • Design Agent: Automate tasks in the Webflow Designer • Code Agent: Vibe code in Webflow • CMS Agent: Bulk edit and create content in the CMS Take a look at some more info & examples below 👇🧵

Bradford Huber

12,388 görüntüleme • 11 ay önce

Generative UI will be the next big shift in AI. Where your product UI is dynamically generated, based on user intent and context. If you are a developer building AI apps, you need to hear this out:
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Generative UI will be the next big shift in AI. Where your product UI is dynamically generated, based on user intent and context. If you are a developer building AI apps, you need to hear this out:

Pratham

119,196 görüntüleme • 7 ay önce

Introducing the Developer’s Guide to AI Agent Protocols. Stop writing custom integration glue for every tool, API, and frontend. We used Google Agent Development Kit to build a B2B agent that handles the full stack using 6 open standards: MCP, A2A, UCP, AP2, A2UI, and AG-UI The future of agents is interoperable. Read the full technical guide here:
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Introducing the Developer’s Guide to AI Agent Protocols. Stop writing custom integration glue for every tool, API, and frontend. We used Google Agent Development Kit to build a B2B agent that handles the full stack using 6 open standards: MCP, A2A, UCP, AP2, A2UI, and AG-UI The future of agents is interoperable. Read the full technical guide here:

Google for Developers

116,371 görüntüleme • 3 ay önce

Don't just learn how to build AI agents. Instead, learn how to build full-stack AI agents that actually work inside apps. Today, we have reliable tools to create decent agentic workflows. Yet, the main challenge is transitioning them from local setups to user-facing apps. Here are some key factors to consider: - How do you embed a seamless UI? - How do you enable user control when necessary? - How do you unify the agent’s state and actions with the app? This is where I would like to introduce CoAgents by CopilotKit🪁, they offer all the essential building blocks for full-stack agentic apps. The best part, they're completely open-source with an MIT Licence ✨ (link to their GitHub repo in the next tweet) The latest updates to CoAgents include: ↳ Human-in-the-loop: Real-time human approvals. ↳ LangGraph integration: Supports LG Studio, Platform, and self-hosted. ↳ Agentic UI: Agents generate UI components dynamically. ↳ Predictive state updates: Preview upcoming changes. ↳ Enhanced documentation: Clear, step-by-step guidance. The video below showcases a full-stack Travel Planner app built in 20 minutes using CoAgents. Impressive, right? Big thanks to CopilotKit for partnering on today's post and showing what's possible with their powerful Agent-development framework.
1:11

Don't just learn how to build AI agents. Instead, learn how to build full-stack AI agents that actually work inside apps. Today, we have reliable tools to create decent agentic workflows. Yet, the main challenge is transitioning them from local setups to user-facing apps. Here are some key factors to consider: - How do you embed a seamless UI? - How do you enable user control when necessary? - How do you unify the agent’s state and actions with the app? This is where I would like to introduce CoAgents by CopilotKit🪁, they offer all the essential building blocks for full-stack agentic apps. The best part, they're completely open-source with an MIT Licence ✨ (link to their GitHub repo in the next tweet) The latest updates to CoAgents include: ↳ Human-in-the-loop: Real-time human approvals. ↳ LangGraph integration: Supports LG Studio, Platform, and self-hosted. ↳ Agentic UI: Agents generate UI components dynamically. ↳ Predictive state updates: Preview upcoming changes. ↳ Enhanced documentation: Clear, step-by-step guidance. The video below showcases a full-stack Travel Planner app built in 20 minutes using CoAgents. Impressive, right? Big thanks to CopilotKit for partnering on today's post and showing what's possible with their powerful Agent-development framework.

Akshay 🚀

90,819 görüntüleme • 1 yıl önce

New generative UI experiences in the Google Gemini and AI Mode in Search use Gemini 3’s multimodal understanding capabilities to make entire user interfaces for you from scratch — dynamically delivering what you need in a visual and interactive way. Google Research software engineer Yaniv Leviathan shares more about the process of building generative UI (hint: so much fun that the team couldn't stop playing with it) and how he's been using it so far.
1:53

New generative UI experiences in the Google Gemini and AI Mode in Search use Gemini 3’s multimodal understanding capabilities to make entire user interfaces for you from scratch — dynamically delivering what you need in a visual and interactive way. Google Research software engineer Yaniv Leviathan shares more about the process of building generative UI (hint: so much fun that the team couldn't stop playing with it) and how he's been using it so far.

Google

138,435 görüntüleme • 6 ay önce

MAI-UI by Tongyi Lab—a family of foundation GUI agents. It natively integrates MCP tool use, agent user interaction, device–cloud collaboration, and online RL, establishing state-of-the-art results in general GUI grounding and mobile GUI navigation. Follow us for more updates!
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MAI-UI by Tongyi Lab—a family of foundation GUI agents. It natively integrates MCP tool use, agent user interaction, device–cloud collaboration, and online RL, establishing state-of-the-art results in general GUI grounding and mobile GUI navigation. Follow us for more updates!

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