This package provides an integration layer between Microsoft Agent Framework and OpenAI ChatKit (Python). Specifically, it mirrors the Agent SDK integration, and provides the following helpers:
stream_agent_response: A helper to convert a streamedAgentRunResponseUpdatefrom a Microsoft Agent Framework agent that implementsAgentProtocolto ChatKit events.ThreadItemConverter: A extendable helper class to convert ChatKit thread items toChatMessageobjects that can be consumed by an Agent Framework agent.simple_to_agent_input: A helper function that uses the default implementation ofThreadItemConverterto convert a ChatKit thread to a list ofChatMessage, useful for getting started quickly.
pip install agent-framework-chatkit --preThis will install agent-framework-core and openai-chatkit as dependencies.
Here's a minimal example showing how to integrate Agent Framework with ChatKit:
from collections.abc import AsyncIterator
from typing import Any
from azure.identity import AzureCliCredential
from fastapi import FastAPI, Request
from fastapi.responses import Response, StreamingResponse
from agent_framework import ChatAgent
from agent_framework.azure import AzureOpenAIChatClient
from agent_framework.chatkit import simple_to_agent_input, stream_agent_response
from chatkit.server import ChatKitServer
from chatkit.types import ThreadMetadata, UserMessageItem, ThreadStreamEvent
# You'll need to implement a Store - see the sample for a SQLiteStore implementation
from your_store import YourStore # type: ignore[import-not-found] # Replace with your Store implementation
# Define your agent with tools
agent = ChatAgent(
chat_client=AzureOpenAIChatClient(credential=AzureCliCredential()),
instructions="You are a helpful assistant.",
tools=[], # Add your tools here
)
# Create a ChatKit server that uses your agent
class MyChatKitServer(ChatKitServer[dict[str, Any]]):
async def respond(
self,
thread: ThreadMetadata,
input_user_message: UserMessageItem | None,
context: dict[str, Any],
) -> AsyncIterator[ThreadStreamEvent]:
if input_user_message is None:
return
# Convert ChatKit message to Agent Framework format
agent_messages = await simple_to_agent_input(input_user_message)
# Run the agent and stream responses
response_stream = agent.run_stream(agent_messages)
# Convert agent responses back to ChatKit events
async for event in stream_agent_response(response_stream, thread.id):
yield event
# Set up FastAPI endpoint
app = FastAPI()
chatkit_server = MyChatKitServer(YourStore()) # type: ignore[misc]
@app.post("/chatkit")
async def chatkit_endpoint(request: Request):
result = await chatkit_server.process(await request.body(), {"request": request})
if hasattr(result, '__aiter__'): # Streaming
return StreamingResponse(result, media_type="text/event-stream") # type: ignore[arg-type]
else: # Non-streaming
return Response(content=result.json, media_type="application/json") # type: ignore[union-attr]For a complete end-to-end example with a full frontend, see the weather agent sample.