ChatKit

agent-framework-chatkit converts OpenAI ChatKit thread items into Agent Framework messages and converts streamed agent updates back into ChatKit events. Use it when you want a ChatKit frontend with an Agent Framework Python backend.

The integration provides:

• ThreadItemConverter for converting ChatKit thread items and attachments.
• stream_agent_response() for converting streamed agent updates to ChatKit events.
• simple_to_agent_input() for the default message-conversion path.

Prerequisites

• Python 3.10 or later.
• A backend web framework such as FastAPI.
• Node.js for the ChatKit frontend.
• A ChatKit domain key for a production frontend domain.

Install the package

pip install agent-framework-chatkit --pre

Create a ChatKit server

Subclass ChatKitServer, create the Agent Framework agent, and configure a converter for thread items and attachments.

class WeatherChatKitServer(ChatKitServer[dict[str, Any]]):
    """ChatKit server implementation using Agent Framework.

    This server integrates Agent Framework agents with ChatKit's server protocol,
    providing weather information with interactive widgets and time queries through Azure OpenAI.
    """

    def __init__(self, data_store: SQLiteStore, attachment_store: FileBasedAttachmentStore):
        super().__init__(data_store, attachment_store)

        logger.info("Initializing WeatherChatKitServer")

        # Create Agent Framework agent with Azure OpenAI
        # For authentication, run `az login` command in terminal
        try:
            self.weather_agent = Agent(
                client=FoundryChatClient(credential=AzureCliCredential()),
                instructions=(
                    "You are a helpful weather assistant with image analysis capabilities. "
                    "You can provide weather information for any location, tell the current time, "
                    "and analyze images that users upload. Be friendly and informative in your responses.\n\n"
                    "If a user asks to see a list of cities or wants to choose from available cities, "
                    "use the show_city_selector tool to display an interactive city selector.\n\n"
                    "When users upload images, you will automatically receive them and can analyze their content. "
                    "Describe what you see in detail and be helpful in answering questions about the images."
                ),
                tools=[get_weather, get_time, show_city_selector],
            )
            logger.info("Weather agent initialized successfully with Azure OpenAI")
        except Exception as e:
            logger.error(f"Failed to initialize weather agent: {e}")
            raise

        # Create ThreadItemConverter with attachment data fetcher
        self.converter = ThreadItemConverter(
            attachment_data_fetcher=self._fetch_attachment_data,
        )

Convert and stream responses

Load the thread history, convert it to Agent Framework messages, run the agent in streaming mode, and yield ChatKit events.

async def respond(
    self,
    thread: ThreadMetadata,
    input_user_message: UserMessageItem | None,
    context: dict[str, Any],
) -> AsyncIterator[ThreadStreamEvent]:
    """Handle incoming user messages and generate responses.

    This method converts ChatKit messages to Agent Framework format using ThreadItemConverter,
    runs the agent, converts the response back to ChatKit events using stream_agent_response,
    and creates interactive weather widgets when weather data is queried.
    """
    from agent_framework import FunctionResultContent

    if input_user_message is None:
        logger.debug("Received None user message, skipping")
        return

    logger.info(f"Processing message for thread: {thread.id}")

    try:
        # Track weather data and city selector flag for this request
        weather_data: WeatherData | None = None
        show_city_selector = False

        # Load full thread history from the store
        thread_items_page = await self.store.load_thread_items(
            thread_id=thread.id,
            after=None,
            limit=1000,
            order="asc",
            context=context,
        )
        thread_items = thread_items_page.data

        # Convert ALL thread items to Agent Framework ChatMessages using ThreadItemConverter
        # This ensures the agent has the full conversation context
        agent_messages = await self.converter.to_agent_input(thread_items)

        if not agent_messages:
            logger.warning("No messages after conversion")
            return

        logger.info(f"Running agent with {len(agent_messages)} message(s)")

        # Run the Agent Framework agent with streaming
        agent_stream = self.weather_agent.run(agent_messages, stream=True)

        # Create an intercepting stream that extracts function results while passing through updates
        async def intercept_stream() -> AsyncIterator[AgentResponseUpdate]:
            nonlocal weather_data, show_city_selector
            async for update in agent_stream:
                # Check for function results in the update
                if update.contents:
                    for content in update.contents:
                        if isinstance(content, FunctionResultContent):
                            result = content.result

                            # Check if it's a WeatherResponse (string subclass with weather_data attribute)
                            if isinstance(result, str) and hasattr(result, "weather_data"):
                                extracted_data = getattr(result, "weather_data", None)
                                if isinstance(extracted_data, WeatherData):
                                    weather_data = extracted_data
                                    logger.info(f"Weather data extracted: {weather_data.location}")
                            # Check if it's the city selector marker
                            elif isinstance(result, str) and result == "__SHOW_CITY_SELECTOR__":
                                show_city_selector = True
                                logger.info("City selector flag detected")
                yield update

        # Stream updates as ChatKit events with interception
        async for event in stream_agent_response(
            intercept_stream(),
            thread_id=thread.id,
        ):
            yield event

The complete sample also demonstrates SQLite-backed threads, file uploads, attachment storage, actions, and interactive widgets.

Warning

The ChatKit frontend is loaded from OpenAI's CDN and makes outbound requests to OpenAI domains. It can't currently be self-hosted and isn't suitable for air-gapped environments.

Next steps

DevUI