Python: Properly configure structured outputs based on new options dict (#3213)

* Properly configure structured outputs based on new options dict

* Fix mypy

python/samples/getting_started/workflows/agents/workflow_as_agent_reflection_pattern.py

@@ -100,7 +100,7 @@ class Reviewer(Executor):
         messages.append(ChatMessage(role=Role.USER, text="Please review the agent's responses."))
 
         print("Reviewer: Sending review request to LLM...")
-        response = await self._chat_client.get_response(messages=messages, response_format=_Response)
+        response = await self._chat_client.get_response(messages=messages, options={"response_format": _Response})
 
         parsed = _Response.model_validate_json(response.messages[-1].text)
 

python/samples/getting_started/workflows/control-flow/edge_condition.py

@@ -138,7 +138,7 @@ def create_spam_detector_agent() -> ChatAgent:
             "Include the original email content in email_content."
         ),
         name="spam_detection_agent",
-        response_format=DetectionResult,
+        default_options={"response_format": DetectionResult},
     )
 
 
@@ -152,7 +152,7 @@ def create_email_assistant_agent() -> ChatAgent:
             "Return JSON with a single field 'response' containing the drafted reply."
         ),
         name="email_assistant_agent",
-        response_format=EmailResponse,
+        default_options={"response_format": EmailResponse},
     )
 
 

python/samples/getting_started/workflows/control-flow/multi_selection_edge_group.py

@@ -190,7 +190,7 @@ def create_email_analysis_agent() -> ChatAgent:
             "and 'reason' (string)."
         ),
         name="email_analysis_agent",
-        response_format=AnalysisResultAgent,
+        default_options={"response_format": AnalysisResultAgent},
     )
 
 
@@ -199,7 +199,7 @@ def create_email_assistant_agent() -> ChatAgent:
     return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
         instructions=("You are an email assistant that helps users draft responses to emails with professionalism."),
         name="email_assistant_agent",
-        response_format=EmailResponse,
+        default_options={"response_format": EmailResponse},
     )
 
 
@@ -208,7 +208,7 @@ def create_email_summary_agent() -> ChatAgent:
     return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
         instructions=("You are an assistant that helps users summarize emails."),
         name="email_summary_agent",
-        response_format=EmailSummaryModel,
+        default_options={"response_format": EmailSummaryModel},
     )
 
 
@@ -243,7 +243,8 @@ async def main() -> None:
     )
 
     workflow = (
-        workflow_builder.set_start_executor("store_email")
+        workflow_builder
+        .set_start_executor("store_email")
         .add_edge("store_email", "email_analysis_agent")
         .add_edge("email_analysis_agent", "to_analysis_result")
         .add_multi_selection_edge_group(

python/samples/getting_started/workflows/control-flow/switch_case_edge_group.py

@@ -162,7 +162,7 @@ def create_spam_detection_agent() -> ChatAgent:
             "and 'reason' (string)."
         ),
         name="spam_detection_agent",
-        response_format=DetectionResultAgent,
+        default_options={"response_format": DetectionResultAgent},
     )
 
 
@@ -171,7 +171,7 @@ def create_email_assistant_agent() -> ChatAgent:
     return AzureOpenAIChatClient(credential=AzureCliCredential()).create_agent(
         instructions=("You are an email assistant that helps users draft responses to emails with professionalism."),
         name="email_assistant_agent",
-        response_format=EmailResponse,
+        default_options={"response_format": EmailResponse},
     )
 
 

python/samples/getting_started/workflows/declarative/customer_support/main.py

@@ -171,28 +171,28 @@ async def main() -> None:
     self_service_agent = chat_client.create_agent(
         name="SelfServiceAgent",
         instructions=SELF_SERVICE_INSTRUCTIONS,
-        response_format=SelfServiceResponse,
+        default_options={"response_format": SelfServiceResponse},
     )
 
     ticketing_agent = chat_client.create_agent(
         name="TicketingAgent",
         instructions=TICKETING_INSTRUCTIONS,
         tools=plugin.get_functions(),
-        response_format=TicketingResponse,
+        default_options={"response_format": TicketingResponse},
     )
 
     routing_agent = chat_client.create_agent(
         name="TicketRoutingAgent",
         instructions=TICKET_ROUTING_INSTRUCTIONS,
         tools=[plugin.get_ticket],
-        response_format=RoutingResponse,
+        default_options={"response_format": RoutingResponse},
     )
 
     windows_support_agent = chat_client.create_agent(
         name="WindowsSupportAgent",
         instructions=WINDOWS_SUPPORT_INSTRUCTIONS,
         tools=[plugin.get_ticket],
-        response_format=SupportResponse,
+        default_options={"response_format": SupportResponse},
     )
 
     resolution_agent = chat_client.create_agent(
@@ -205,7 +205,7 @@ async def main() -> None:
         name="TicketEscalationAgent",
         instructions=ESCALATION_INSTRUCTIONS,
         tools=[plugin.get_ticket, plugin.send_notification],
-        response_format=EscalationResponse,
+        default_options={"response_format": EscalationResponse},
     )
 
     # Agent registry for lookup

python/samples/getting_started/workflows/declarative/deep_research/main.py

@@ -139,7 +139,7 @@ async def main() -> None:
     manager_agent = chat_client.create_agent(
         name="ManagerAgent",
         instructions=MANAGER_INSTRUCTIONS,
-        response_format=ManagerResponse,
+        default_options={"response_format": ManagerResponse},
     )
 
     summary_agent = chat_client.create_agent(

python/samples/getting_started/workflows/human-in-the-loop/guessing_game_with_human_input.py

@@ -154,7 +154,7 @@ def create_guessing_agent() -> ChatAgent:
             "No explanations or additional text."
         ),
         # response_format enforces that the model produces JSON compatible with GuessOutput.
-        response_format=GuessOutput,
+        default_options={"response_format": GuessOutput},
     )
 
 

python/samples/getting_started/workflows/state-management/shared_states_with_agents.py

@@ -162,7 +162,7 @@ def create_spam_detection_agent() -> ChatAgent:
             "You are a spam detection assistant that identifies spam emails. "
             "Always return JSON with fields is_spam (bool) and reason (string)."
         ),
-        response_format=DetectionResultAgent,
+        default_options={"response_format": DetectionResultAgent},
         # response_format enforces structured JSON from each agent.
         name="spam_detection_agent",
     )
@@ -176,7 +176,7 @@ def create_email_assistant_agent() -> ChatAgent:
             "Return JSON with a single field 'response' containing the drafted reply."
         ),
         # response_format enforces structured JSON from each agent.
-        response_format=EmailResponse,
+        default_options={"response_format": EmailResponse},
         name="email_assistant_agent",
     )