Reading agent state - Copilotkit

<Callout type="info"> This example demonstrates reading from shared state in the [CopilotKit Feature Viewer](https://feature-viewer.copilotkit.ai/pydantic-ai/feature/shared_state). </Callout>

What is this?

You can easily use the realtime agent state not only in the chat UI, but also in the native application UX.

When should I use this?

You can use this when you want to provide the user with feedback about your agent's state. As your agent's state updates, you can reflect these updates natively in your application.

Implementation

<Steps> <Step> ### Run and connect your agent <RunAndConnect /> </Step> <Step> ### Define the Agent State

Create your Pydantic AI agent with a stateful structure. Here's a complete example that tracks language:

```python title="agent.py"
from textwrap import dedent

from pydantic import BaseModel
from pydantic_ai import Agent, RunContext
from pydantic_ai.ag_ui import StateDeps


class AgentState(BaseModel):
    """State for the agent."""
    language: str = "english"


agent = Agent("openai:gpt-5.4-mini", deps_type=StateDeps[AgentState])


@agent.instructions()
async def language_instructions(ctx: RunContext[StateDeps[AgentState]]) -> str:
    """Instructions for the language tracking agent.

    Args:
        ctx: The run context containing language state information.

    Returns:
        Instructions string for the language tracking agent.
    """
    return dedent(
        f"""
        You are a helpful assistant for tracking the language.

        IMPORTANT:
        - ALWAYS use the lower case for the language
        - ALWAYS response in the current language: {ctx.deps.state.language}
        """
    )


app = agent.to_ag_ui(deps=StateDeps(AgentState()))

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)
```

</Step> <Step> ### Use the `useAgent` Hook With your agent connected and running all that is left is to call the `useAgent` hook, pass the agent's name, and optionally provide an initial state.

```tsx title="ui/app/page.tsx"

// Define the agent state type, should match the actual state of your agent
type AgentState = {
  language: "english" | "spanish";
}

function YourMainContent() {
  // [!code highlight:4]
  const { agent } = useAgent({
    agentId: "my_agent",
    initialState: { language: "english" }  // optionally provide an initial state
  });

  // ...

  return (
    // style excluded for brevity
    <div>
      <h1>Your main content</h1>
      <p>Language: {agent.state?.language}</p>
    </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>

<Callout type="info">
  The `agent.state` in `useAgent` is reactive and will automatically update when the agent's state changes.
</Callout>

</Step> <Step> ### Give it a try! As the agent state updates, your `state` variable will automatically update with it! In this case, you'll see the language set to "english" as that's the initial state we set. </Step> </Steps>

Rendering agent state in the chat

You can also render the agent's state in the chat UI. This is useful for informing the user about the agent's state in a more in-context way. To do this, you can use the useAgent hook with a render function.

tsx

// Define the agent state type, should match the actual state of your agent
type AgentState = {
  language: "english" | "spanish";
};

function YourMainContent() {
  // ...
  // [!code highlight:7]
  useAgent({
    agentId: "my_agent",
    render: ({ state }) => {
      if (!state.language) return null;
      return <div>Language: {state.language}</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> <Callout type="info"> The `agent.state` in `useAgent` is reactive and will automatically update when the agent's state changes. </Callout>

Intermediately Stream and Render Agent State

By default, the Pydantic AI Agent state will only update between Pydantic AI Agent node transitions -- which means state updates will be discontinuous and delayed.