New open source AI protocol! A lightweight protocol for AI Agent to interact with the front end, making it easy to build interactive AI applications!
AG-UI protocol: A new era of interaction between AI Agent and front-end, making AI application development simpler and more efficient.
Core content:
1. The birth background and core value of AG-UI protocol
2. The core functions and technical highlights of AG-UI protocol
3. Online Demo and SDK access guide of AG-UI protocol
The rise of AI Agents has led to a surge in demand for front-end interaction, but in traditional development, connecting the Agent backend and frontend requires a lot of customized code, which is inefficient.
After MCP (Model Context Protocol) and A2A (Agent-to-Agent Communication Protocol), the AI Agent ecosystem is moving towards a more complete direction: the AG-UI protocol was born, designed specifically for the communication and interaction between Agents and front-end applications.
It allows you to quickly access AI assistants, AI customer service, smart question-and-answer UI, etc. on web pages, apps, or embedded devices, without having to reinvent the wheel for each application or worrying about interaction logic.
AG-UI completes the AI protocol stack and focuses on bridging the Agent and the user front end. It uses event-driven design, defines 16 standard events, supports SSE/WebSocket/Webhook transmission, and is compatible with frameworks such as LangGraph and CrewAI.
It is equivalent to plugging an AI "brain" into your front end, without the need to bind to a specific model or framework, and a set of protocols can handle all interaction needs.
Core Features
• Streaming communication support : built-in SSE, WebSocket, Webhook channels, support streaming message generation • Two-way state synchronization : Agent state and front-end state are synchronized in real time to adapt to UI updates • 16 types of standard events : unified definition of event types such as user input, AI response, control information, UI operation, etc. • Structured messages and UI controls : support generative UI, card-style replies, tool triggers and other advanced interactions • Multi-Agent & Component Integration : Can be expanded into a multi-agent interaction container, working with MCP and A2A protocols
AG-UI uses HTTP/SSE reference implementation to support fast integration of the front-end and Agent back-end.
Online Demo: https://agui-demo.vercel.app
It provides front-end TypeScript and back-end Python SDKs that can be seamlessly integrated into existing code.
front end:
npm install @ag-ui/core
npm install @ag-ui/clientPython import method:
from ag_ui.core import TextMessageContentEvent, EventType
from ag_ui.encoder import EventEncoder
# Create an event
event = TextMessageContentEvent(
type =EventType.TEXT_MESSAGE_CONTENT,
message_id= "msg_123" ,
delta= "Hello, world!"
)
# Initialize the encoder
encoder = EventEncoder()
# Encode the event
encoded_event = encoder.encode(event)
print (encoded_event)
# Output: data: {"type":"TEXT_MESSAGE_CONTENT","messageId":"msg_123","delta":"Hello, world!"}\n\nCore modules:
• RunAgentInput: Input parameters for running the agent • Message: User assistant communication and tool usage • Context: contextual information provided to the agent • Tool: defines functions that the agent can call • State: Agent state management
Detailed usage documentation:https://docs.ag-ui.com/introduction
Last words
AG-UI provides a unified front-end communication language for LLM Agent, making "human-computer interaction" truly intelligent and standardized.
It solves the fragmentation problem of Agent→front-end interaction, allowing us to quickly build rich and diverse AI application interfaces like building blocks!
It also provides TypeScript and Python SDKs to facilitate developers to integrate into existing front-end applications.
If you want to use AG-UI to build an AI customer service system or LLM tool collaboration platform, you can easily achieve it with its help.
