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* [BREAKING] Rename ChatAgent -> Agent, ChatMessage -> Message, ChatClientProtocol -> SupportsChatGetResponse Simplify the public API by removing redundant 'Chat' prefix from core types: - ChatAgent -> Agent - RawChatAgent -> RawAgent - ChatMessage -> Message - ChatClientProtocol -> SupportsChatGetResponse Also renamed internal WorkflowMessage (was Message in _runner_context) to avoid collision. No backward compatibility aliases - this is a clean breaking change. * [BREAKING] Rename Agent chat_client parameter to client * Fix rebase issues: WorkflowMessage references and broken markdown links * Fix formatting and lint issues from code quality checks * Fix import ordering in workflow sample files * fixed rebase * Fix test failures: use WorkflowMessage and A2AMessage after ChatMessage→Message rename - Replace Message(data=..., source_id=...) with WorkflowMessage(...) in workflow tests - Fix isinstance check in A2A agent to use A2AMessage instead of Message - Fix import in test_workflow_observability.py (Message→WorkflowMessage) * Fix lint, fmt, and sample errors after ChatMessage→Message rename - Auto-fix 70+ ruff lint issues across samples (ChatMessage→Message refs) - Fix HostedVectorStoreContent→Content.from_hosted_vector_store in file search sample - Fix _normalize_messages→normalize_messages in custom agent sample - Fix context.terminate→raise MiddlewareTermination in middleware samples - Fix with_update_hook→with_transform_hook in override middleware sample - Add TOptions_co import back to custom_chat_client sample - Add noqa for FastAPI File() default in chatkit sample - Fix B023 loop variable capture in weather agent sample * fix: update Agent constructor calls from chat_client to client in declaration-only tool tests * fix: add register_cleanup to devui lazy-loading proxy and type stub * fixed tests and updated new pieces * fix agui typevar * fix merge errors * fix merge conflicts * fiux merge * Remove unused links --------- Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
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Agent Framework AG-UI Integration
AG-UI protocol integration for Agent Framework, enabling seamless integration with AG-UI's web interface and streaming protocol.
Installation
pip install agent-framework-ag-ui
Quick Start
Server (Host an AI Agent)
from fastapi import FastAPI
from agent_framework import Agent
from agent_framework.azure import AzureOpenAIChatClient
from agent_framework.ag_ui import add_agent_framework_fastapi_endpoint
# Create your agent
agent = Agent(
name="my_agent",
instructions="You are a helpful assistant.",
client=AzureOpenAIChatClient(
endpoint="https://your-resource.openai.azure.com/",
deployment_name="gpt-4o-mini",
api_key="your-api-key",
),
)
# Create FastAPI app and add AG-UI endpoint
app = FastAPI()
add_agent_framework_fastapi_endpoint(app, agent, "/")
# Run with: uvicorn main:app --reload
Client (Connect to an AG-UI Server)
import asyncio
from agent_framework.ag_ui import AGUIChatClient
async def main():
async with AGUIChatClient(endpoint="http://localhost:8000/") as client:
# Stream responses
async for update in client.get_response("Hello!", stream=True):
for content in update.contents:
if content.type == "text" and content.text:
print(content.text, end="", flush=True)
print()
asyncio.run(main())
The AGUIChatClient supports:
- Streaming and non-streaming responses
- Hybrid tool execution (client-side + server-side tools)
- Automatic thread management for conversation continuity
- Integration with
Agentfor client-side history management
Documentation
- Getting Started Tutorial - Step-by-step guide to building AG-UI servers and clients
- Server setup with FastAPI
- Client examples using
AGUIChatClient - Hybrid tool execution (client-side + server-side)
- Thread management and conversation continuity
- Examples - Complete examples for AG-UI features
Features
This integration supports all 7 AG-UI features:
- Agentic Chat: Basic streaming chat with tool calling support
- Backend Tool Rendering: Tools executed on backend with results streamed to client
- Human in the Loop: Function approval requests for user confirmation before tool execution
- Agentic Generative UI: Async tools for long-running operations with progress updates
- Tool-based Generative UI: Custom UI components rendered on frontend based on tool calls
- Shared State: Bidirectional state sync between client and server
- Predictive State Updates: Stream tool arguments as optimistic state updates during execution
Security: Authentication & Authorization
The AG-UI endpoint does not enforce authentication by default. For production deployments, you should add authentication using FastAPI's dependency injection system via the dependencies parameter.
API Key Authentication Example
import os
from fastapi import Depends, FastAPI, HTTPException, Security
from fastapi.security import APIKeyHeader
from agent_framework import Agent
from agent_framework.ag_ui import add_agent_framework_fastapi_endpoint
# Configure API key authentication
API_KEY_HEADER = APIKeyHeader(name="X-API-Key", auto_error=False)
EXPECTED_API_KEY = os.environ.get("AG_UI_API_KEY")
async def verify_api_key(api_key: str | None = Security(API_KEY_HEADER)) -> None:
"""Verify the API key provided in the request header."""
if not api_key or api_key != EXPECTED_API_KEY:
raise HTTPException(status_code=401, detail="Invalid or missing API key")
# Create agent and app
agent = Agent(name="my_agent", instructions="...", client=...)
app = FastAPI()
# Register endpoint WITH authentication
add_agent_framework_fastapi_endpoint(
app,
agent,
"/",
dependencies=[Depends(verify_api_key)], # Authentication enforced here
)
Other Authentication Options
The dependencies parameter accepts any FastAPI dependency, enabling integration with:
- OAuth 2.0 / OpenID Connect - Use
fastapi.security.OAuth2PasswordBearer - JWT Tokens - Validate tokens with libraries like
python-jose - Azure AD / Entra ID - Use
azure-identityfor Microsoft identity platform - Rate Limiting - Add request throttling dependencies
- Custom Authentication - Implement your organization's auth requirements
For a complete authentication example, see getting_started/server.py.
Architecture
The package uses a clean, orchestrator-based architecture:
- AgentFrameworkAgent: Lightweight wrapper that delegates to orchestrators
- Orchestrators: Handle different execution flows (default, human-in-the-loop, etc.)
- Confirmation Strategies: Domain-specific confirmation messages (extensible)
- AgentFrameworkEventBridge: Converts Agent Framework events to AG-UI events
- Message Adapters: Bidirectional conversion between AG-UI and Agent Framework message formats
- FastAPI Endpoint: Streaming HTTP endpoint with Server-Sent Events (SSE)
Next Steps
- New to AG-UI? Start with the Getting Started Tutorial
- Want to see examples? Check out the Examples for AG-UI features
License
MIT