Pre-release
This release is a pre-release and may not be stable for production use.
Agent Framework and ChatKit Integration
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.
Installation
pip install agent-framework-chatkit --pre
This will install agent-framework-core and openai-chatkit as dependencies.
Example Usage
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.
5 maintainers
Metadata
5 maintainers
Release files for agent-framework-chatkit 1.0.0b251111
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