Reading agent state
Read the realtime agent state in your native application.
This example demonstrates reading from shared state in the CopilotKit Feature Viewer.
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#
Run and connect your agent#
You'll need to run your agent and connect it to CopilotKit before proceeding. If you haven't done so already, you can follow the instructions in the Getting Started guide.
If you don't already have an agent, you can use the coagent starter as a starting point as this guide uses it as a starting point.
Define the Agent State#
Decide which parts of agent state you want to reflect in the UI and allow updating from the UI.
public class AgentStateSnapshot
{
public string Language { get; set; } = "english";
}from __future__ import annotations
import os
import uvicorn
from agent_framework import Agent, tool, SupportsChatGetResponse
from agent_framework.openai import OpenAIChatClient
from agent_framework.ag_ui import add_agent_framework_fastapi_endpoint
from agent_framework.ag_ui import AgentFrameworkAgent
from dotenv import load_dotenv
from fastapi import FastAPI
from typing import Annotated
from pydantic import BaseModel, Field
load_dotenv()
class SearchItem(BaseModel):
query: str
done: bool
STATE_SCHEMA: dict[str, object] = {
"language": {
"type": "string",
"enum": ["english", "spanish"],
"description": "Preferred language.",
}
}
PREDICT_STATE_CONFIG: dict[str, dict[str, str]] = {
"language": {"tool": "update_language", "tool_argument": "language"}
}
@tool
def update_language(
language: Annotated[str, Field(description="Preferred language: 'english' or 'spanish'")],
) -> str:
normalized = (language or "").strip().lower()
if normalized not in ("english", "spanish"):
return "Language unchanged. Use 'english' or 'spanish'."
return f"Language updated to {normalized}."
def _build_chat_client():
if os.getenv("AZURE_OPENAI_ENDPOINT"):
return OpenAIChatClient(
model=os.getenv("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", "gpt-4o-mini"),
api_key=os.getenv("AZURE_OPENAI_API_KEY"),
azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
)
if os.getenv("OPENAI_API_KEY"):
return OpenAIChatClient(
model=os.getenv("OPENAI_CHAT_MODEL_ID", "gpt-4o-mini"),
api_key=os.getenv("OPENAI_API_KEY"),
)
raise RuntimeError(
"Set either AZURE_OPENAI_ENDPOINT + AZURE_OPENAI_API_KEY, or OPENAI_API_KEY."
)
def create_agent(chat_client: SupportsChatGetResponse) -> AgentFrameworkAgent:
base_agent = Agent(
name="sample_agent",
instructions="You are a helpful assistant.",
client=chat_client,
tools=[update_language],
)
return AgentFrameworkAgent(
agent=base_agent,
name="CopilotKitMicrosoftAgentFrameworkAgent",
description="Assistant that tracks a simple language state.",
state_schema=STATE_SCHEMA,
predict_state_config=PREDICT_STATE_CONFIG,
require_confirmation=False,
)
chat_client = _build_chat_client()
agent = create_agent(chat_client)
app = FastAPI(title="Microsoft Agent Framework - Quickstart")
add_agent_framework_fastapi_endpoint(app=app, agent=agent, path="/")
if __name__ == "__main__":
uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)type AgentState = {
language: "english" | "spanish";
}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.
// Define the agent state type, should match the actual state of your agent
type AgentState = {
language: "english" | "spanish";
}
function YourMainContent() {
const { agent } = useAgent({
agentId: "sample_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>
);
}The agent.state in useAgent is reactive and will automatically update when the agent's state changes.
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.
Pictured above is the agent starter with the implementation section applied!
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.
// Define the agent state type, should match the actual state of your agent
type AgentState = {
language: "english" | "spanish";
};
function YourMainContent() {
// ...
useAgent({
agentId: "sample_agent",
render: ({ state }) => {
if (!state.language) return null;
return <div>Language: {state.language}</div>;
},
});
// ...
}The agent.state in useAgent is reactive and will automatically update when
the agent's state changes.
Advanced: Emitting Intermediate State#
By default, agent state updates arrive at natural checkpoints during agent execution. For more granular, real-time updates during long-running operations, you can emit state snapshots from within your agent logic. Consult the Microsoft Agent Framework documentation for patterns on streaming custom state events during execution.
