🚀 Have you ever heard about AG-UI?
Imagine an interface where AI agents and humans collaborate in real time, with state sharing, continuous streaming, and direct integration between the frontend and agents.
The AG-UI architecture offers:
🔄 Bidirectional communication based on events: UIs and agents exchange messages, tool calls, state status, and lifecycle signals through lightweight and efficient JSON events (such as STATE_SNAPSHOT and STATE_DELTA).
🔗Shared state synchronization: Frontend and agents maintain a common state, updated incrementally (deltas) or fully (snapshots), enabling smooth and context-rich collaboration.
⚡Dynamic agent creation and frontend integration: Agents can call interface-defined tools, request human approvals, delegate tasks between agents, and much more, all with transparency and control.
🧩Interchangeable components and flexible backend: Use CopilotKit React components with any AG-UI–compatible backend (OpenAI, LangGraph, PydanticAI, etc.), without being locked into a single provider.
💡 With this frontend agent support, I created a platform to explore these features: EditAI👉 https://lnkd.in/dfHDNUiR
With EditAI you can create documents and edit them with the help of a chat assistant: it can search the web, write content, and provide intelligent suggestions.
Some applied features include:
🔮Predictive State Updates: allows the user to decide whether new suggested content should be accepted as an official edit of the document.
🤝CoAgents: share states between document generation and user display, including the progress of web searches and other agent tasks, presented in a user-friendly way.
In addition, EditAI allows:
📂 Creating multiple files within each project
🗂️ Organizing them into folders
📝 Rich text editing support
The platform is currently in demo version, open for use and feedback collection. https://lnkd.in/dfHDNUiR 🚀
If you want to dive deeper into AG-UI:
Beginners can start with Pydantic with this doc: https://lnkd.in/d9-QAd3r.
More advanced users can explore LangChain documentation.
For the frontend, CopilotKit provides excellent resources for integration with today’s major frameworks, doc: https://lnkd.in/dMrMT4G9