state-rendering.mdx

title	State Rendering
icon	lucide/Bot
description	Render the state of your agent with custom UI components.

What is this?

AG2 agents can maintain state across a session through ContextVariables. CopilotKit can render this state in your application with custom UI components, which we call Agentic Generative UI.

CopilotKit consumes AG-UI protocol events streamed by AG2 over /chat. See the AG2 AG-UI integration docs.

When should I use this?

Rendering the state of your agent in the UI is useful when you want to provide the user with feedback about the overall state of a session. A great example of this is a situation where a user and an agent are working together to solve a problem. The agent can store a draft in its state which is then rendered in the UI.

Implementation

### Run and connect your agent Start your AG2 backend with AG-UI streaming enabled on `/chat`. ### Set up your agent with state

Create your AG2 agent with `ContextVariables` and emit `StateSnapshotEvent` updates:

```python title="agent.py"
from typing import Annotated

from ag_ui.core import EventType, StateSnapshotEvent
from fastapi import FastAPI, Header
from fastapi.responses import StreamingResponse
from pydantic import BaseModel, Field
from autogen import ConversableAgent, LLMConfig
from autogen.agentchat import ContextVariables
from autogen.ag_ui import AGUIStream, RunAgentInput


class Search(BaseModel):
    query: str
    done: bool


class AgentState(BaseModel):
    searches: list[Search] = Field(default_factory=list)


def read_state(context: ContextVariables) -> AgentState:
    raw_state = context.get("agent_state", {"searches": []})
    return AgentState.model_validate(raw_state)


def write_state(context: ContextVariables, state: AgentState) -> StateSnapshotEvent:
    snapshot = state.model_dump()
    context["agent_state"] = snapshot
    return StateSnapshotEvent(type=EventType.STATE_SNAPSHOT, snapshot=snapshot)


agent = ConversableAgent(
    name="assistant",
    system_message=(
        "You are a helpful assistant for storing searches. "
        "Use `add_search` once per query, then call `run_searches`."
    ),
    llm_config=LLMConfig({"model": "gpt-5.4-mini"}),
    human_input_mode="NEVER",
)


@agent.register_for_llm(description="Add a search to the state.")
def add_search(
    context: ContextVariables,
    new_query: Annotated[str, "The query to add to state"],
) -> StateSnapshotEvent:
    state = read_state(context)
    state.searches.append(Search(query=new_query, done=False))
    return write_state(context, state)


@agent.register_for_llm(description="Run the queued searches and mark them done.")
def run_searches(context: ContextVariables) -> StateSnapshotEvent:
    state = read_state(context)
    for search in state.searches:
        search.done = True
    return write_state(context, state)


agent.register_for_execution(name="add_search")(add_search)
agent.register_for_execution(name="run_searches")(run_searches)

stream = AGUIStream(agent)
app = FastAPI()


@app.post("/chat")
async def run_agent(
    message: RunAgentInput,
    accept: str | None = Header(None),
):
    return StreamingResponse(
        stream.dispatch(message, accept=accept),
        media_type=accept or "text/event-stream",
    )
```

### Render state of the agent in the chat Now we can utilize `useAgent` with a `render` function to render the state of our agent **in the chat**.

```tsx title="app/page.tsx"
// ...
import { useAgent } from "@copilotkit/react-core/v2";
// ...

// Define the state of the agent, should match the state streamed by your AG2 backend.
type AgentState = {
  searches: {
    query: string;
    done: boolean;
  }[];
};

function YourMainContent() {
  // ...

  // [!code highlight:13]
  // styles omitted for brevity
  useAgent({
    agentId: "my_agent",
    render: ({ state }) => (
      <div>
        {state.searches?.map((search, index) => (
          <div key={index}>
            {search.done ? "✅" : "❌"} {search.query}{search.done ? "" : "..."}
          </div>
        ))}
      </div>
    ),
  });

  // ...

  return <div>...</div>;
}
```

<Callout type="warn" title="Important">
  The `name` parameter must exactly match the agent name you defined in your CopilotRuntime configuration (e.g., `my_agent` from the quickstart).
</Callout>

### Render state outside of the chat You can also render the state of your agent **outside of the chat**. This is useful when you want to render the state of your agent anywhere other than the chat.

```tsx title="app/page.tsx"
import { useAgent } from "@copilotkit/react-core/v2"; // [!code highlight]
// ...

// Define the state of the agent, should match the state streamed by your AG2 backend.
type AgentState = {
  searches: {
    query: string;
    done: boolean;
  }[];
};

function YourMainContent() {
  // ...

  // [!code highlight:3]
  const { agent } = useAgent({
    agentId: "my_agent", // MUST match the agent name in CopilotRuntime
  })

  // ...

  return (
    <div>
      {/* ... */}
      <div className="flex flex-col gap-2 mt-4">
        {/* [!code highlight:5] */}
        {agent.state.searches?.map((search, index) => (
          <div key={index} className="flex flex-row">
            {search.done ? "✅" : "❌"} {search.query}
          </div>
        ))}
      </div>
    </div>
  )
}
```

<Callout type="warn" title="Important">
  The `agentId` parameter must exactly match the agent name you defined in your CopilotRuntime configuration (e.g., `my_agent` from the quickstart).
</Callout>

### Give it a try

You've now created a component that will render the agent's state in the chat.

<video
  src="https://cdn.copilotkit.ai/docs/copilotkit/images/coagents/agentic-generative-ui.mp4"
  className="rounded-lg shadow-xl"
  loop
  playsInline
  controls
  autoPlay
  muted
/>