renamed all (#3207)

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

@@ -85,7 +85,7 @@ def get_condition(expected_result: bool):
         try:
             # Prefer parsing a structured DetectionResult from the agent JSON text.
             # Using model_validate_json ensures type safety and raises if the shape is wrong.
-            detection = DetectionResult.model_validate_json(message.agent_run_response.text)
+            detection = DetectionResult.model_validate_json(message.agent_response.text)
             # Route only when the spam flag matches the expected path.
             return detection.is_spam == expected_result
         except Exception:
@@ -99,14 +99,14 @@ def get_condition(expected_result: bool):
 @executor(id="send_email")
 async def handle_email_response(response: AgentExecutorResponse, ctx: WorkflowContext[Never, str]) -> None:
     # Downstream of the email assistant. Parse a validated EmailResponse and yield the workflow output.
-    email_response = EmailResponse.model_validate_json(response.agent_run_response.text)
+    email_response = EmailResponse.model_validate_json(response.agent_response.text)
     await ctx.yield_output(f"Email sent:\n{email_response.response}")
 
 
 @executor(id="handle_spam")
 async def handle_spam_classifier_response(response: AgentExecutorResponse, ctx: WorkflowContext[Never, str]) -> None:
     # Spam path. Confirm the DetectionResult and yield the workflow output. Guard against accidental non spam input.
-    detection = DetectionResult.model_validate_json(response.agent_run_response.text)
+    detection = DetectionResult.model_validate_json(response.agent_response.text)
     if detection.is_spam:
         await ctx.yield_output(f"Email marked as spam: {detection.reason}")
     else:
@@ -123,7 +123,7 @@ async def to_email_assistant_request(
     Extracts DetectionResult.email_content and forwards it as a user message.
     """
     # Bridge executor. Converts a structured DetectionResult into a ChatMessage and forwards it as a new request.
-    detection = DetectionResult.model_validate_json(response.agent_run_response.text)
+    detection = DetectionResult.model_validate_json(response.agent_response.text)
     user_msg = ChatMessage(Role.USER, text=detection.email_content)
     await ctx.send_message(AgentExecutorRequest(messages=[user_msg], should_respond=True))
 

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

@@ -98,7 +98,7 @@ async def store_email(email_text: str, ctx: WorkflowContext[AgentExecutorRequest
 
 @executor(id="to_analysis_result")
 async def to_analysis_result(response: AgentExecutorResponse, ctx: WorkflowContext[AnalysisResult]) -> None:
-    parsed = AnalysisResultAgent.model_validate_json(response.agent_run_response.text)
+    parsed = AnalysisResultAgent.model_validate_json(response.agent_response.text)
     email_id: str = await ctx.get_shared_state(CURRENT_EMAIL_ID_KEY)
     email: Email = await ctx.get_shared_state(f"{EMAIL_STATE_PREFIX}{email_id}")
     await ctx.send_message(
@@ -125,7 +125,7 @@ async def submit_to_email_assistant(analysis: AnalysisResult, ctx: WorkflowConte
 
 @executor(id="finalize_and_send")
 async def finalize_and_send(response: AgentExecutorResponse, ctx: WorkflowContext[Never, str]) -> None:
-    parsed = EmailResponse.model_validate_json(response.agent_run_response.text)
+    parsed = EmailResponse.model_validate_json(response.agent_response.text)
     await ctx.yield_output(f"Email sent: {parsed.response}")
 
 
@@ -140,7 +140,7 @@ async def summarize_email(analysis: AnalysisResult, ctx: WorkflowContext[AgentEx
 
 @executor(id="merge_summary")
 async def merge_summary(response: AgentExecutorResponse, ctx: WorkflowContext[AnalysisResult]) -> None:
-    summary = EmailSummaryModel.model_validate_json(response.agent_run_response.text)
+    summary = EmailSummaryModel.model_validate_json(response.agent_response.text)
     email_id: str = await ctx.get_shared_state(CURRENT_EMAIL_ID_KEY)
     email: Email = await ctx.get_shared_state(f"{EMAIL_STATE_PREFIX}{email_id}")
     # Build an AnalysisResult mirroring to_analysis_result but with summary

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

@@ -106,7 +106,7 @@ class ParseJudgeResponse(Executor):
 
     @handler
     async def parse(self, response: AgentExecutorResponse, ctx: WorkflowContext[NumberSignal]) -> None:
-        text = response.agent_run_response.text.strip().upper()
+        text = response.agent_response.text.strip().upper()
         if "MATCHED" in text:
             await ctx.send_message(NumberSignal.MATCHED)
         elif "ABOVE" in text and "BELOW" not in text:

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

@@ -106,7 +106,7 @@ async def store_email(email_text: str, ctx: WorkflowContext[AgentExecutorRequest
 @executor(id="to_detection_result")
 async def to_detection_result(response: AgentExecutorResponse, ctx: WorkflowContext[DetectionResult]) -> None:
     # Parse the detector JSON into a typed model. Attach the current email id for downstream lookups.
-    parsed = DetectionResultAgent.model_validate_json(response.agent_run_response.text)
+    parsed = DetectionResultAgent.model_validate_json(response.agent_response.text)
     email_id: str = await ctx.get_shared_state(CURRENT_EMAIL_ID_KEY)
     await ctx.send_message(DetectionResult(spam_decision=parsed.spam_decision, reason=parsed.reason, email_id=email_id))
 
@@ -127,7 +127,7 @@ async def submit_to_email_assistant(detection: DetectionResult, ctx: WorkflowCon
 @executor(id="finalize_and_send")
 async def finalize_and_send(response: AgentExecutorResponse, ctx: WorkflowContext[Never, str]) -> None:
     # Terminal step for the drafting branch. Yield the email response as output.
-    parsed = EmailResponse.model_validate_json(response.agent_run_response.text)
+    parsed = EmailResponse.model_validate_json(response.agent_response.text)
     await ctx.yield_output(f"Email sent: {parsed.response}")