Python: Update workflow orchestration samples to use AzureOpenAIResponsesClient (#4285)

* Update workflow orchestration samples to use AzureOpenAIResponsesClient

* Fix broken link

python/samples/03-workflows/orchestrations/handoff_simple.py

@@ -1,6 +1,7 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import asyncio
+import os
 from typing import Annotated, cast
 
 from agent_framework import (
@@ -11,7 +12,7 @@ from agent_framework import (
     WorkflowRunState,
     tool,
 )
-from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.azure import AzureOpenAIResponsesClient
 from agent_framework.orchestrations import HandoffAgentUserRequest, HandoffBuilder
 from azure.identity import AzureCliCredential
 from dotenv import load_dotenv
@@ -25,8 +26,9 @@ A handoff workflow defines a pattern that assembles agents in a mesh topology, a
 them to transfer control to each other based on the conversation context.
 
 Prerequisites:
-    - `az login` (Azure CLI authentication)
-    - Environment variables configured for AzureOpenAIChatClient (AZURE_OPENAI_ENDPOINT, etc.)
+    - AZURE_AI_PROJECT_ENDPOINT must be your Azure AI Foundry Agent Service (V2) project endpoint.
+    - Azure OpenAI configured for AzureOpenAIResponsesClient with required environment variables.
+    - Authentication via azure-identity. Use AzureCliCredential and run `az login` before executing the sample.
 
 Key Concepts:
     - Auto-registered handoff tools: HandoffBuilder automatically creates handoff tools
@@ -58,11 +60,11 @@ def process_return(order_number: Annotated[str, "Order number to process return
     return f"Return initiated successfully for order {order_number}. You will receive return instructions via email."
 
 
-def create_agents(client: AzureOpenAIChatClient) -> tuple[Agent, Agent, Agent, Agent]:
+def create_agents(client: AzureOpenAIResponsesClient) -> tuple[Agent, Agent, Agent, Agent]:
     """Create and configure the triage and specialist agents.
 
     Args:
-        client: The AzureOpenAIChatClient to use for creating agents.
+        client: The AzureOpenAIResponsesClient to use for creating agents.
 
     Returns:
         Tuple of (triage_agent, refund_agent, order_agent, return_agent)
@@ -192,8 +194,12 @@ async def main() -> None:
     the demo reproducible and testable. In a production application, you would
     replace the scripted_responses with actual user input collection.
     """
-    # Initialize the Azure OpenAI chat client
-    client = AzureOpenAIChatClient(credential=AzureCliCredential())
+    # Initialize the Azure OpenAI Responses client
+    client = AzureOpenAIResponsesClient(
+        project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+        deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        credential=AzureCliCredential(),
+    )
 
     # Create all agents: triage + specialists
     triage, refund, order, support = create_agents(client)