renamed all (#3207)

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

@@ -208,7 +208,7 @@ async def conclude_workflow(
     ctx: WorkflowContext[Never, str],
 ) -> None:
     """Conclude the workflow by yielding the final email response."""
-    await ctx.yield_output(email_response.agent_run_response.text)
+    await ctx.yield_output(email_response.agent_response.text)
 
 
 def create_email_writer_agent() -> ChatAgent:

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

@@ -64,7 +64,7 @@ async def aggregate_with_synthesis(results: list[AgentExecutorResponse]) -> Any:
 
     for r in results:
         try:
-            messages = getattr(r.agent_run_response, "messages", [])
+            messages = getattr(r.agent_response, "messages", [])
             final_text = messages[-1].text if messages and hasattr(messages[-1], "text") else "(no content)"
             expert_sections.append(f"{getattr(r, 'executor_id', 'analyst')}:\n{final_text}")
 
@@ -161,7 +161,7 @@ async def main() -> None:
                     print("\n" + "-" * 40)
                     print("INPUT REQUESTED")
                     print(
-                        f"Agent {event.source_executor_id} just responded with: '{event.data.agent_run_response.text}'. "
+                        f"Agent {event.source_executor_id} just responded with: '{event.data.agent_response.text}'. "
                         "Please provide your feedback."
                     )
                     print("-" * 40)

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

@@ -27,7 +27,7 @@ import asyncio
 from agent_framework import (
     AgentExecutorResponse,
     AgentRequestInfoResponse,
-    AgentRunResponse,
+    AgentResponse,
     AgentRunUpdateEvent,
     ChatMessage,
     GroupChatBuilder,
@@ -138,8 +138,8 @@ async def main() -> None:
                     print(f"About to call agent: {event.source_executor_id}")
                     print("-" * 40)
                     print("Conversation context:")
-                    agent_run_response: AgentRunResponse = event.data.agent_run_response
-                    messages: list[ChatMessage] = agent_run_response.messages
+                    agent_response: AgentResponse = event.data.agent_response
+                    messages: list[ChatMessage] = agent_response.messages
                     recent: list[ChatMessage] = messages[-3:] if len(messages) > 3 else messages  # type: ignore
                     for msg in recent:
                         name = msg.author_name or "unknown"

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

@@ -103,7 +103,7 @@ class TurnManager(Executor):
         2) Request info with a HumanFeedbackRequest as the payload.
         """
         # Parse structured model output
-        text = result.agent_run_response.text
+        text = result.agent_response.text
         last_guess = GuessOutput.model_validate_json(text).guess
 
         # Craft a precise human prompt that defines higher and lower relative to the agent's guess.

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

@@ -96,7 +96,7 @@ async def main() -> None:
                     print("\n" + "-" * 40)
                     print("REQUEST INFO: INPUT REQUESTED")
                     print(
-                        f"Agent {event.source_executor_id} just responded with: '{event.data.agent_run_response.text}'. "
+                        f"Agent {event.source_executor_id} just responded with: '{event.data.agent_response.text}'. "
                         "Please provide your feedback."
                     )
                     print("-" * 40)