A2UI Launched: Full CopilotKit support at launch!

A2UI Launched: CopilotKit has partnered with Google to deliver full support in both CopilotKit and AG-UI!

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  • Overview
  • Integrations
  • API Reference
  • Copilot Cloud
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  • Getting Started
  • Introduction to CopilotKit
  • LLM Quickstart
  • Agent Quickstart
  • Vibe Coding MCP
  • What's New
  • CopilotKit Features
  • Agentic Chat UI
  • Copilot Suggestions
  • Human in the Loop (HITL)
  • Generative UI
  • Frontend Actions
  • Backend Actions
  • Shared State
  • Premium Features
  • CopilotKit Premium
  • Fully Headless UI
  • Observability
  • Inspector
  • Agentic Protocols
  • Agentic Protocols
  • AG-UI (Agents<->Users)
  • MCP (Agents<->Tools)
  • A2A (Agents<->Agents)
  • Generative UI Specs
  • Generative UI Specs
  • A2UI
  • Open-JSON-UI
  • MCP-UI
  • Learning
  • Tutorial: AI Todo App
  • Tutorial: AI Travel App
  • Video: Research Canvas
  • Cookbook: State Machine
  • Troubleshooting
  • Error Debugging
  • Error Observability Connectors
  • Common Copilot Issues
  • Migrate to 1.10.X
  • Migrate to 1.8.2
  • Other
  • Integrations
  • ADK
  • A2A
  • Microsoft Agent Framework
  • AWS Strands
  • Direct to LLM
  • LangGraph
  • AutoGen2
  • Agno
  • CrewAI Crews
  • CrewAI Flows
  • LlamaIndex
  • Mastra
  • Open Agent Spec
  • Pydantic AI

Agentic Chat UI

Create intelligent chat interfaces powered by AI agents that can execute tools and maintain context.

What is Agentic Chat UI?

Agentic Chat UI is an intelligent chat interface that goes beyond simple text exchange. It's powered by AI agents that can execute tools, maintain context, access application state, and provide interactive experiences within the chat interface itself.

Unlike traditional chatbots that only respond with text, agentic chat interfaces can execute functions, display rich content, and create collaborative experiences between users and AI agents.

Choose your Integration

Agentic Chat UI can be implemented with any agentic backend, with each integration providing different approaches for creating intelligent, action-oriented chat experiences.

Choose your integration to see specific implementation guides and examples.

ADK
Microsoft Agent Framework
AWS Strands
LangGraph
AG2
Agno
CrewAI Crews
CrewAI Flows
LlamaIndex
Mastra
Open Agent Spec
Pydantic AI
ADK
Microsoft Agent Framework
AWS Strands
LangGraph
AG2
Agno
CrewAI Crews
CrewAI Flows
LlamaIndex
Mastra
Open Agent Spec
Pydantic AI

Key Features

Agent-Powered Responses

Messages are generated by intelligent agents that understand context and can execute appropriate tools.

Interactive Message Components

Chat messages can contain buttons, forms, visualizations, and other interactive elements.

Real-time State Updates

Chat interface updates in real-time as agents process information and modify application state.

Tool Execution

Agents can execute both frontend and backend tools directly from chat interactions.

Context Persistence

Conversation context and agent state persist across sessions and interactions.

Multi-modal Communication

Support for text, images, files, and custom interactive components within the chat.

When to Use Agentic Chat UI

Consider Agentic Chat UI when you want to:

  • Provide natural language interfaces for complex applications
  • Enable task completion through conversational interactions
  • Create collaborative experiences between users and AI
  • Simplify complex workflows with guided conversations
  • Offer contextual help that understands current application state
  • Build engaging user experiences that go beyond traditional forms and menus
  • Provide accessible interfaces that work well for users of all technical levels
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On this page

What is Agentic Chat UI?
Choose your Integration
Key Features
Agent-Powered Responses
Interactive Message Components
Real-time State Updates
Tool Execution
Context Persistence
Multi-modal Communication
When to Use Agentic Chat UI