Merge branch 'main' into python-middleware

dotnet/Directory.Packages.props

@@ -82,7 +82,7 @@
     <!-- MCP -->
     <PackageVersion Include="ModelContextProtocol" Version="0.3.0-preview.4" />
     <!-- Inference SDKs -->
-    <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.9.1" />
+    <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.9.2" />
     <PackageVersion Include="OllamaSharp" Version="5.4.4" />
     <!-- Identity -->
     <PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.77.0" />

dotnet/agent-framework-dotnet.slnx

@@ -33,6 +33,7 @@
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Agent_With_CustomImplementation.csproj" />
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_Ollama/Agent_With_Ollama.csproj" />
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_ONNX/Agent_With_ONNX.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/Agent_With_OpenAIAssistants.csproj" />
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIChatCompletion/Agent_With_OpenAIChatCompletion.csproj" />
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIResponses/Agent_With_OpenAIResponses.csproj" />
   </Folder>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/Agent_With_OpenAIAssistants.csproj

@@ -0,0 +1,16 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/Program.cs

@@ -0,0 +1,42 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with OpenAI Assistants as the backend.
+
+// WARNING: The Assistants API is deprecated and will be shut down.
+// For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration
+
+#pragma warning disable OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+
+using System;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var apiKey = Environment.GetEnvironmentVariable("OPENAI_APIKEY") ?? throw new InvalidOperationException("OPENAI_APIKEY is not set.");
+var mmodel = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+// Get a client to create/retrieve server side agents with.
+var assistantClient = new OpenAIClient(apiKey).GetAssistantClient();
+
+// You can create a server side assistant with the OpenAI SDK.
+var createResult = await assistantClient.CreateAssistantAsync(mmodel, new() { Name = JokerName, Instructions = JokerInstructions });
+
+// You can retrieve an already created server side assistant as an AIAgent.
+AIAgent agent1 = await assistantClient.GetAIAgentAsync(createResult.Value.Id);
+
+// You can also create a server side assistant and return it as an AIAgent directly.
+AIAgent agent2 = await assistantClient.CreateAIAgentAsync(
+    model: mmodel,
+    name: JokerName,
+    instructions: JokerInstructions);
+
+// You can invoke the agent like any other AIAgent.
+AgentThread thread = agent1.GetNewThread();
+Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Cleanup for sample purposes.
+await assistantClient.DeleteThreadAsync(thread.ConversationId);
+await assistantClient.DeleteAssistantAsync(agent1.Id);
+await assistantClient.DeleteAssistantAsync(agent2.Id);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/README.md

@@ -0,0 +1,16 @@
+# Prerequisites
+
+WARNING: The Assistants API is deprecated and will be shut down.
+For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- OpenAI API key
+
+Set the following environment variables:
+
+```powershell
+$env:OPENAI_APIKEY="*****" # Replace with your OpenAI API key
+$env:OPENAI_MODEL="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```

dotnet/samples/GettingStarted/AgentProviders/README.md

@@ -21,6 +21,7 @@ See the README.md for each sample for the prerequisites for that sample.
 |[Creating an AIAgent with a custom implementation](./Agent_With_CustomImplementation/)|This sample demonstrates how to create an AIAgent with a custom implementation|
 |[Creating an AIAgent with Ollama](./Agent_With_Ollama/)|This sample demonstrates how to create an AIAgent using Ollama as the underlying inference service|
 |[Creating an AIAgent with ONNX](./Agent_With_ONNX/)|This sample demonstrates how to create an AIAgent using ONNX as the underlying inference service|
+|[Creating an AIAgent with OpenAI Assistants](./Agent_With_OpenAIAssistants/)|This sample demonstrates how to create an AIAgent using OpenAI Assistants as the underlying inference service.</br>WARNING: The Assistants API is deprecated and will be shut down. For more information see the OpenAI documentation: https://platform.openai.com/docs/assistants/migration|
 |[Creating an AIAgent with OpenAI ChatCompletion](./Agent_With_OpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using OpenAI ChatCompletion as the underlying inference service|
 |[Creating an AIAgent with OpenAI Responses](./Agent_With_OpenAIResponses/)|This sample demonstrates how to create an AIAgent using OpenAI Responses as the underlying inference service|
 

dotnet/samples/GettingStarted/Workflows/Declarative/Program.cs

@@ -33,7 +33,16 @@ internal sealed class Program
 {
     public static async Task Main(string[] args)
     {
-        Program program = new(args);
+        string? workflowFile = ParseWorkflowFile(args);
+        if (workflowFile is null)
+        {
+            Notify("\nUsage: DeclarativeWorkflow <workflow-file> [<input>]");
+            return;
+        }
+
+        string? workflowInput = ParseWorkflowInput(args);
+
+        Program program = new(workflowFile, workflowInput);
         await program.ExecuteAsync();
     }
 
@@ -103,7 +112,6 @@ internal sealed class Program
         return DeclarativeWorkflowBuilder.Build<string>(this.WorkflowFile, options);
     }
 
-    private const string DefaultWorkflow = "HelloWorld.yaml";
     private const string ConfigKeyFoundryEndpoint = "FOUNDRY_PROJECT_ENDPOINT";
 
     private static Dictionary<string, string> NameCache { get; } = [];
@@ -116,10 +124,10 @@ internal sealed class Program
     private IConfiguration Configuration { get; }
     private CheckpointInfo? LastCheckpoint { get; set; }
 
-    private Program(string[] args)
+    private Program(string workflowFile, string? workflowInput)
     {
-        this.WorkflowFile = ParseWorkflowFile(args);
-        this.WorkflowInput = ParseWorkflowInput(args);
+        this.WorkflowFile = workflowFile;
+        this.WorkflowInput = workflowInput;
 
         this.Configuration = InitializeConfig();
 
@@ -270,9 +278,13 @@ internal sealed class Program
         return new InputResponse(userInput);
     }
 
-    private static string ParseWorkflowFile(string[] args)
+    private static string? ParseWorkflowFile(string[] args)
     {
-        string workflowFile = args.FirstOrDefault() ?? DefaultWorkflow;
+        string? workflowFile = args.FirstOrDefault();
+        if (string.IsNullOrWhiteSpace(workflowFile))
+        {
+            return null;
+        }
 
         if (!File.Exists(workflowFile) && !Path.IsPathFullyQualified(workflowFile))
         {

dotnet/src/Microsoft.Extensions.AI.Agents.OpenAI/Extensions/AssistantClientResultExtensions.cs

@@ -25,7 +25,7 @@ public static class AssistantExtensions
             throw new ArgumentNullException(nameof(assistantClientResult));
         }
 
-        return AsAIAgent(assistantClientResult, assistantClient, chatOptions);
+        return AsAIAgent(assistantClientResult.Value, assistantClient, chatOptions);
     }
 
     /// <summary>

python/packages/main/agent_framework/_workflow/__init__.py

@@ -31,12 +31,14 @@ from ._events import (
     ExecutorCompletedEvent,
     ExecutorEvent,
     ExecutorFailedEvent,
-    ExecutorInvokeEvent,
+    ExecutorInvokedEvent,
     RequestInfoEvent,
     WorkflowCompletedEvent,
     WorkflowErrorDetails,
     WorkflowEvent,
+    WorkflowEventSource,
     WorkflowFailedEvent,
+    WorkflowLifecycleEvent,
     WorkflowRunState,
     WorkflowStartedEvent,
     WorkflowStatusEvent,
@@ -118,7 +120,7 @@ __all__ = [
     "ExecutorCompletedEvent",
     "ExecutorEvent",
     "ExecutorFailedEvent",
-    "ExecutorInvokeEvent",
+    "ExecutorInvokedEvent",
     "FanInEdgeGroup",
     "FanOutEdgeGroup",
     "FileCheckpointStorage",
@@ -172,8 +174,10 @@ __all__ = [
     "WorkflowContext",
     "WorkflowErrorDetails",
     "WorkflowEvent",
+    "WorkflowEventSource",
     "WorkflowExecutor",
     "WorkflowFailedEvent",
+    "WorkflowLifecycleEvent",
     "WorkflowRunResult",
     "WorkflowRunState",
     "WorkflowStartedEvent",

python/packages/main/agent_framework/_workflow/__init__.pyi

@@ -27,12 +27,14 @@ from ._events import (
     ExecutorCompletedEvent,
     ExecutorEvent,
     ExecutorFailedEvent,
-    ExecutorInvokeEvent,
+    ExecutorInvokedEvent,
     RequestInfoEvent,
     WorkflowCompletedEvent,
     WorkflowErrorDetails,
     WorkflowEvent,
+    WorkflowEventSource,
     WorkflowFailedEvent,
+    WorkflowLifecycleEvent,
     WorkflowRunState,
     WorkflowStartedEvent,
     WorkflowStatusEvent,
@@ -114,7 +116,7 @@ __all__ = [
     "ExecutorCompletedEvent",
     "ExecutorEvent",
     "ExecutorFailedEvent",
-    "ExecutorInvokeEvent",
+    "ExecutorInvokedEvent",
     "FanInEdgeGroup",
     "FanOutEdgeGroup",
     "FileCheckpointStorage",
@@ -168,8 +170,10 @@ __all__ = [
     "WorkflowContext",
     "WorkflowErrorDetails",
     "WorkflowEvent",
+    "WorkflowEventSource",
     "WorkflowExecutor",
     "WorkflowFailedEvent",
+    "WorkflowLifecycleEvent",
     "WorkflowRunResult",
     "WorkflowRunState",
     "WorkflowStartedEvent",

python/packages/main/agent_framework/_workflow/_events.py

@@ -1,9 +1,12 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import traceback as _traceback
+from collections.abc import Iterator
+from contextlib import contextmanager
+from contextvars import ContextVar
 from dataclasses import dataclass
 from enum import Enum
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, TypeAlias
 
 from agent_framework import AgentRunResponse, AgentRunResponseUpdate
 
@@ -11,32 +14,70 @@ if TYPE_CHECKING:
     from ._executor import RequestInfoMessage
 
 
+class WorkflowEventSource(str, Enum):
+    """Identifies whether a workflow event came from the framework or an executor.
+
+    Use `FRAMEWORK` for events emitted by built-in orchestration paths—even when the
+    code that raises them lives in runner-related modules—and `EXECUTOR` for events
+    surfaced by developer-provided executor implementations.
+    """
+
+    FRAMEWORK = "FRAMEWORK"  # Framework-owned orchestration, regardless of module location
+    EXECUTOR = "EXECUTOR"  # User-supplied executor code and callbacks
+
+
+_event_origin_context: ContextVar[WorkflowEventSource] = ContextVar(
+    "workflow_event_origin", default=WorkflowEventSource.EXECUTOR
+)
+
+
+def _current_event_origin() -> WorkflowEventSource:
+    """Return the origin to associate with newly created workflow events."""
+    return _event_origin_context.get()
+
+
+@contextmanager
+def _framework_event_origin() -> Iterator[None]:  # pyright: ignore[reportUnusedFunction]
+    """Temporarily mark subsequently created events as originating from the framework (internal)."""
+    token = _event_origin_context.set(WorkflowEventSource.FRAMEWORK)
+    try:
+        yield
+    finally:
+        _event_origin_context.reset(token)
+
+
 class WorkflowEvent:
     """Base class for workflow events."""
 
     def __init__(self, data: Any | None = None):
         """Initialize the workflow event with optional data."""
         self.data = data
+        self.origin = _current_event_origin()
 
     def __repr__(self) -> str:
         """Return a string representation of the workflow event."""
-        return f"{self.__class__.__name__}(data={self.data if self.data is not None else 'None'})"
+        data_repr = self.data if self.data is not None else "None"
+        return f"{self.__class__.__name__}(origin={self.origin}, data={data_repr})"
 
 
 class WorkflowStartedEvent(WorkflowEvent):
-    """Event triggered when a workflow starts."""
+    """Built-in lifecycle event emitted when a workflow run begins."""
 
     ...
 
 
 class WorkflowCompletedEvent(WorkflowEvent):
-    """Event triggered when a workflow completes."""
+    """Built-in lifecycle event emitted when a workflow run completes successfully.
+
+    Unlike the framework-only `WorkflowLifecycleEvent` union, this event can be
+    emitted by developer-provided executors to return final workflow output.
+    """
 
     ...
 
 
 class WorkflowWarningEvent(WorkflowEvent):
-    """Event triggered when a warning occurs in the workflow."""
+    """Executor-origin event signaling a warning surfaced by user code."""
 
     def __init__(self, data: str):
         """Initialize the workflow warning event with optional data and warning message."""
@@ -44,11 +85,11 @@ class WorkflowWarningEvent(WorkflowEvent):
 
     def __repr__(self) -> str:
         """Return a string representation of the workflow warning event."""
-        return f"{self.__class__.__name__}(message={self.data})"
+        return f"{self.__class__.__name__}(message={self.data}, origin={self.origin})"
 
 
 class WorkflowErrorEvent(WorkflowEvent):
-    """Event triggered when an error occurs in the workflow."""
+    """Executor-origin event signaling an error surfaced by user code."""
 
     def __init__(self, data: Exception):
         """Initialize the workflow error event with optional data and error message."""
@@ -56,7 +97,7 @@ class WorkflowErrorEvent(WorkflowEvent):
 
     def __repr__(self) -> str:
         """Return a string representation of the workflow error event."""
-        return f"{self.__class__.__name__}(exception={self.data})"
+        return f"{self.__class__.__name__}(exception={self.data}, origin={self.origin})"
 
 
 class WorkflowRunState(str, Enum):
@@ -108,14 +149,24 @@ class WorkflowRunState(str, Enum):
 
 
 class WorkflowStatusEvent(WorkflowEvent):
-    """Event indicating a transition in the workflow run state."""
+    """Built-in lifecycle event emitted for workflow run state transitions."""
 
-    def __init__(self, state: WorkflowRunState, data: Any | None = None):
+    def __init__(
+        self,
+        state: WorkflowRunState,
+        data: Any | None = None,
+    ):
+        """Initialize the workflow status event with a new state and optional data.
+
+        Args:
+            state: The new state of the workflow run.
+            data: Optional additional data associated with the state change.
+        """
         super().__init__(data)
         self.state = state
 
     def __repr__(self) -> str:  # pragma: no cover - representation only
-        return f"{self.__class__.__name__}(state={self.state}, data={self.data!r})"
+        return f"{self.__class__.__name__}(state={self.state}, data={self.data!r}, origin={self.origin})"
 
 
 @dataclass
@@ -151,14 +202,18 @@ class WorkflowErrorDetails:
 
 
 class WorkflowFailedEvent(WorkflowEvent):
-    """Terminal failure event for a workflow run."""
+    """Built-in lifecycle event emitted when a workflow run terminates with an error."""
 
-    def __init__(self, details: WorkflowErrorDetails, data: Any | None = None):
+    def __init__(
+        self,
+        details: WorkflowErrorDetails,
+        data: Any | None = None,
+    ):
         super().__init__(data)
         self.details = details
 
     def __repr__(self) -> str:  # pragma: no cover - representation only
-        return f"{self.__class__.__name__}(details={self.details}, data={self.data!r})"
+        return f"{self.__class__.__name__}(details={self.details}, data={self.data!r}, origin={self.origin})"
 
 
 class RequestInfoEvent(WorkflowEvent):
@@ -208,12 +263,12 @@ class ExecutorEvent(WorkflowEvent):
         return f"{self.__class__.__name__}(executor_id={self.executor_id}, data={self.data})"
 
 
-class ExecutorInvokeEvent(ExecutorEvent):
+class ExecutorInvokedEvent(ExecutorEvent):
     """Event triggered when an executor handler is invoked."""
 
     def __repr__(self) -> str:
         """Return a string representation of the executor handler invoke event."""
-        return f"{self.__class__.__name__}(executor_id={self.executor_id})"
+        return f"{self.__class__.__name__}(executor_id={self.executor_id}, data={self.data})"
 
 
 class ExecutorCompletedEvent(ExecutorEvent):
@@ -221,13 +276,17 @@ class ExecutorCompletedEvent(ExecutorEvent):
 
     def __repr__(self) -> str:
         """Return a string representation of the executor handler complete event."""
-        return f"{self.__class__.__name__}(executor_id={self.executor_id})"
+        return f"{self.__class__.__name__}(executor_id={self.executor_id}, data={self.data})"
 
 
 class ExecutorFailedEvent(ExecutorEvent):
     """Event triggered when an executor handler raises an error."""
 
-    def __init__(self, executor_id: str, details: WorkflowErrorDetails):
+    def __init__(
+        self,
+        executor_id: str,
+        details: WorkflowErrorDetails,
+    ):
         super().__init__(executor_id, details)
         self.details = details
 
@@ -257,3 +316,6 @@ class AgentRunEvent(ExecutorEvent):
     def __repr__(self) -> str:
         """Return a string representation of the agent run event."""
         return f"{self.__class__.__name__}(executor_id={self.executor_id}, data={self.data})"
+
+
+WorkflowLifecycleEvent: TypeAlias = WorkflowStartedEvent | WorkflowStatusEvent | WorkflowFailedEvent

python/packages/main/agent_framework/_workflow/_executor.py

@@ -21,8 +21,9 @@ from ._events import (
     AgentRunEvent,
     AgentRunUpdateEvent,
     ExecutorCompletedEvent,
-    ExecutorInvokeEvent,
+    ExecutorInvokedEvent,
     RequestInfoEvent,
+    _framework_event_origin,  # pyright: ignore[reportPrivateUsage]
 )
 from ._typing_utils import is_instance_of
 from ._workflow_context import WorkflowContext
@@ -102,16 +103,22 @@ class Executor(AFBaseModel):
             # Lazy registration for SubWorkflowRequestInfo if we have interceptors
             if self._request_interceptors and message.__class__.__name__ == "SubWorkflowRequestInfo":
                 # Directly handle SubWorkflowRequestInfo
-                await context.add_event(ExecutorInvokeEvent(self.id))
+                with _framework_event_origin():
+                    invoke_event = ExecutorInvokedEvent(self.id)
+                await context.add_event(invoke_event)
                 try:
                     await self._handle_sub_workflow_request(message, context)
                 except Exception as exc:
                     # Surface structured executor failure before propagating
                     from ._events import ExecutorFailedEvent, WorkflowErrorDetails
 
-                    await context.add_event(ExecutorFailedEvent(self.id, WorkflowErrorDetails.from_exception(exc)))
+                    with _framework_event_origin():
+                        failure_event = ExecutorFailedEvent(self.id, WorkflowErrorDetails.from_exception(exc))
+                    await context.add_event(failure_event)
                     raise
-                await context.add_event(ExecutorCompletedEvent(self.id))
+                with _framework_event_origin():
+                    completed_event = ExecutorCompletedEvent(self.id)
+                await context.add_event(completed_event)
                 return
 
             handler: Callable[[Any, WorkflowContext[Any]], Any] | None = None
@@ -122,16 +129,22 @@ class Executor(AFBaseModel):
 
             if handler is None:
                 raise RuntimeError(f"Executor {self.__class__.__name__} cannot handle message of type {type(message)}.")
-            await context.add_event(ExecutorInvokeEvent(self.id))
+            with _framework_event_origin():
+                invoke_event = ExecutorInvokedEvent(self.id)
+            await context.add_event(invoke_event)
             try:
                 await handler(message, context)
             except Exception as exc:
                 # Surface structured executor failure before propagating
                 from ._events import ExecutorFailedEvent, WorkflowErrorDetails
 
-                await context.add_event(ExecutorFailedEvent(self.id, WorkflowErrorDetails.from_exception(exc)))
+                with _framework_event_origin():
+                    failure_event = ExecutorFailedEvent(self.id, WorkflowErrorDetails.from_exception(exc))
+                await context.add_event(failure_event)
                 raise
-            await context.add_event(ExecutorCompletedEvent(self.id))
+            with _framework_event_origin():
+                completed_event = ExecutorCompletedEvent(self.id)
+            await context.add_event(completed_event)
 
     def _discover_handlers(self) -> None:
         """Discover message handlers and request interceptors in the executor class."""

python/packages/main/agent_framework/_workflow/_runner.py

@@ -11,7 +11,7 @@ if TYPE_CHECKING:
 
 from ._edge import EdgeGroup
 from ._edge_runner import EdgeRunner, create_edge_runner
-from ._events import WorkflowCompletedEvent, WorkflowEvent
+from ._events import WorkflowCompletedEvent, WorkflowEvent, _framework_event_origin
 from ._executor import Executor
 from ._runner_context import Message, RunnerContext
 from ._shared_state import SharedState
@@ -280,7 +280,9 @@ class Runner:
                         if isinstance(message.data, AgentExecutorResponse):
                             final_messages = message.data.agent_run_response.messages
                             final_text = final_messages[-1].text if final_messages else "(no content)"
-                            await self._ctx.add_event(WorkflowCompletedEvent(final_text))
+                            with _framework_event_origin():
+                                completion_event = WorkflowCompletedEvent(final_text)
+                            await self._ctx.add_event(completion_event)
                             continue  # Terminal handled
                     except Exception as exc:  # pragma: no cover - defensive
                         logger.debug("Suppressed exception during terminal message type check: %s", exc)
@@ -301,7 +303,9 @@ class Runner:
                             # Emit a single completion event with final text (best-effort extraction)
                             final_messages = message.data.agent_run_response.messages
                             final_text = final_messages[-1].text if final_messages else "(no content)"
-                            await self._ctx.add_event(WorkflowCompletedEvent(final_text))
+                            with _framework_event_origin():
+                                completion_event = WorkflowCompletedEvent(final_text)
+                            await self._ctx.add_event(completion_event)
                             continue
                     except Exception as exc:  # pragma: no cover
                         logger.debug("Terminal completion emission failed: %s", exc)

python/packages/main/agent_framework/_workflow/_workflow.py

@@ -5,7 +5,7 @@ import logging
 import sys
 import uuid
 from collections.abc import AsyncIterable, Awaitable, Callable, Sequence
-from typing import Any, cast
+from typing import Any
 
 from pydantic import Field
 
@@ -35,6 +35,7 @@ from ._events import (
     WorkflowRunState,
     WorkflowStartedEvent,
     WorkflowStatusEvent,
+    _framework_event_origin,
 )
 from ._executor import AgentExecutor, Executor, RequestInfoExecutor
 from ._runner import Runner
@@ -52,14 +53,6 @@ else:
 logger = logging.getLogger(__name__)
 
 
-def _default_edge_groups() -> list[EdgeGroup]:
-    return []
-
-
-def _default_executors() -> dict[str, Executor]:
-    return {}
-
-
 class WorkflowRunResult(list[WorkflowEvent]):
     """A list of events generated during the workflow execution in non-streaming mode.
 
@@ -125,10 +118,10 @@ class Workflow(AFBaseModel):
     """
 
     edge_groups: list[EdgeGroup] = Field(
-        default_factory=_default_edge_groups, description="List of edge groups that define the workflow edges"
+        default_factory=list, description="List of edge groups that define the workflow edges"
     )
     executors: dict[str, Executor] = Field(
-        default_factory=_default_executors, description="Dictionary mapping executor IDs to Executor instances"
+        default_factory=dict, description="Dictionary mapping executor IDs to Executor instances"
     )
     start_executor_id: str = Field(min_length=1, description="The ID of the starting executor for the workflow")
     max_iterations: int = Field(
@@ -190,20 +183,21 @@ class Workflow(AFBaseModel):
 
         # Ensure WorkflowExecutor instances have their workflow field serialized
         if "executors" in data:
-            executors_data = cast(dict[str, Any], data["executors"])
-            executor_map: dict[str, Executor] = self.executors
+            executors_data = data["executors"]
             for executor_id, executor_data in executors_data.items():
                 # Check if this is a WorkflowExecutor that might be missing its workflow field
-                if isinstance(executor_data, dict):
-                    executor_dict = cast(dict[str, Any], executor_data)
-                    if executor_dict.get("type") == "WorkflowExecutor" and "workflow" not in executor_dict:
-                        # Get the original executor object and serialize its workflow
-                        original_executor = executor_map.get(executor_id)
-                        if original_executor is not None and hasattr(original_executor, "workflow"):
-                            from ._executor import WorkflowExecutor
+                if (
+                    isinstance(executor_data, dict)
+                    and executor_data.get("type") == "WorkflowExecutor"
+                    and "workflow" not in executor_data
+                ):
+                    # Get the original executor object and serialize its workflow
+                    original_executor = self.executors.get(executor_id)
+                    if original_executor and hasattr(original_executor, "workflow"):
+                        from ._executor import WorkflowExecutor
 
-                            if isinstance(original_executor, WorkflowExecutor):
-                                executor_dict["workflow"] = original_executor.workflow.model_dump(**kwargs)
+                        if isinstance(original_executor, WorkflowExecutor):
+                            executor_data["workflow"] = original_executor.workflow.model_dump(**kwargs)
 
         return data
 
@@ -252,8 +246,12 @@ class Workflow(AFBaseModel):
                 # Add workflow started event (telemetry + surface state to consumers)
                 workflow_tracer.add_workflow_event("workflow.started")
                 # Emit explicit start/status events to the stream
-                yield WorkflowStartedEvent()
-                yield WorkflowStatusEvent(WorkflowRunState.IN_PROGRESS)
+                with _framework_event_origin():
+                    started = WorkflowStartedEvent()
+                yield started
+                with _framework_event_origin():
+                    in_progress = WorkflowStatusEvent(WorkflowRunState.IN_PROGRESS)
+                yield in_progress
 
                 # Reset context for a new run if supported
                 if reset_context:
@@ -274,22 +272,34 @@ class Workflow(AFBaseModel):
 
                     if isinstance(event, RequestInfoEvent) and not emitted_in_progress_pending and not saw_completed:
                         emitted_in_progress_pending = True
-                        yield WorkflowStatusEvent(WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS)
+                        with _framework_event_origin():
+                            pending_status = WorkflowStatusEvent(WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS)
+                        yield pending_status
 
                 # Success path: emit a final status based on observed terminal signals
                 if saw_completed:
-                    yield WorkflowStatusEvent(WorkflowRunState.COMPLETED)
+                    with _framework_event_origin():
+                        terminal_status = WorkflowStatusEvent(WorkflowRunState.COMPLETED)
+                    yield terminal_status
                 elif saw_request:
-                    yield WorkflowStatusEvent(WorkflowRunState.IDLE_WITH_PENDING_REQUESTS)
+                    with _framework_event_origin():
+                        terminal_status = WorkflowStatusEvent(WorkflowRunState.IDLE_WITH_PENDING_REQUESTS)
+                    yield terminal_status
                 else:
-                    yield WorkflowStatusEvent(WorkflowRunState.IDLE)
+                    with _framework_event_origin():
+                        terminal_status = WorkflowStatusEvent(WorkflowRunState.IDLE)
+                    yield terminal_status
 
                 workflow_tracer.add_workflow_event("workflow.completed")
             except Exception as e:
                 # Surface structured failure details before propagating exception
                 details = WorkflowErrorDetails.from_exception(e)
-                yield WorkflowFailedEvent(details)
-                yield WorkflowStatusEvent(WorkflowRunState.FAILED)
+                with _framework_event_origin():
+                    failed_event = WorkflowFailedEvent(details)
+                yield failed_event
+                with _framework_event_origin():
+                    failed_status = WorkflowStatusEvent(WorkflowRunState.FAILED)
+                yield failed_status
                 workflow_tracer.add_workflow_error_event(e)
                 raise
 

python/packages/main/agent_framework/_workflow/_workflow_context.py

@@ -1,10 +1,19 @@
 # Copyright (c) Microsoft. All rights reserved.
 
-from typing import Any, Generic, TypeVar
+import logging
+from typing import Any, Generic, TypeVar, cast, get_args
 
 from opentelemetry.propagate import inject
 
-from ._events import WorkflowEvent
+from ._events import (
+    WorkflowEvent,
+    WorkflowEventSource,
+    WorkflowFailedEvent,
+    WorkflowLifecycleEvent,
+    WorkflowStartedEvent,
+    WorkflowStatusEvent,
+    WorkflowWarningEvent,
+)
 from ._runner_context import Message, RunnerContext
 from ._shared_state import SharedState
 from ._telemetry import workflow_tracer
@@ -12,6 +21,20 @@ from ._telemetry import workflow_tracer
 T_Out = TypeVar("T_Out")
 
 
+logger = logging.getLogger(__name__)
+
+
+_FRAMEWORK_LIFECYCLE_EVENT_TYPES: tuple[type[WorkflowEvent], ...] = cast(
+    tuple[type[WorkflowEvent], ...],
+    tuple(get_args(WorkflowLifecycleEvent))
+    or (
+        WorkflowStartedEvent,
+        WorkflowStatusEvent,
+        WorkflowFailedEvent,
+    ),
+)
+
+
 class WorkflowContext(Generic[T_Out]):
     """Context for executors in a workflow.
 
@@ -77,6 +100,16 @@ class WorkflowContext(Generic[T_Out]):
 
     async def add_event(self, event: WorkflowEvent) -> None:
         """Add an event to the workflow context."""
+        if event.origin == WorkflowEventSource.EXECUTOR and isinstance(event, _FRAMEWORK_LIFECYCLE_EVENT_TYPES):
+            event_name = event.__class__.__name__
+            warning_msg = (
+                f"Executor '{self._executor_id}' attempted to emit {event_name}, "
+                "which is reserved for framework lifecycle notifications. The "
+                "event was ignored."
+            )
+            logger.warning(warning_msg)
+            await self._runner_context.add_event(WorkflowWarningEvent(warning_msg))
+            return
         await self._runner_context.add_event(event)
 
     async def get_shared_state(self, key: str) -> Any:

python/packages/main/tests/workflow/test_runner.py

@@ -5,10 +5,19 @@ from dataclasses import dataclass
 
 import pytest
 
-from agent_framework import Executor, WorkflowCompletedEvent, WorkflowContext, WorkflowEvent, handler
+from agent_framework import (
+    AgentExecutorResponse,
+    AgentRunResponse,
+    Executor,
+    WorkflowCompletedEvent,
+    WorkflowContext,
+    WorkflowEvent,
+    WorkflowEventSource,
+    handler,
+)
 from agent_framework._workflow._edge import SingleEdgeGroup
 from agent_framework._workflow._runner import Runner
-from agent_framework._workflow._runner_context import InProcRunnerContext, RunnerContext
+from agent_framework._workflow._runner_context import InProcRunnerContext, Message, RunnerContext
 from agent_framework._workflow._shared_state import SharedState
 
 
@@ -79,6 +88,7 @@ async def test_runner_run_until_convergence():
         assert isinstance(event, WorkflowEvent)
         if isinstance(event, WorkflowCompletedEvent):
             result = event.data
+            assert event.origin is WorkflowEventSource.EXECUTOR
 
     assert result is not None and result == 10
 
@@ -148,3 +158,20 @@ async def test_runner_already_running():
                 pass
 
         await asyncio.gather(_run(), _run())
+
+
+async def test_runner_emits_runner_completion_for_agent_response_without_targets():
+    ctx = InProcRunnerContext()
+    runner = Runner([], {}, SharedState(), ctx)
+
+    await ctx.send_message(
+        Message(
+            data=AgentExecutorResponse("agent", AgentRunResponse()),
+            source_id="agent",
+        )
+    )
+
+    events: list[WorkflowEvent] = [event async for event in runner.run_until_convergence()]
+    completions = [e for e in events if isinstance(e, WorkflowCompletedEvent)]
+    assert completions
+    assert all(e.origin is WorkflowEventSource.FRAMEWORK for e in completions)

python/packages/main/tests/workflow/test_simple_sub_workflow.py

@@ -3,8 +3,6 @@
 import asyncio
 from dataclasses import dataclass
 
-import pytest
-
 from agent_framework import (
     Executor,
     WorkflowBuilder,
@@ -64,7 +62,6 @@ class SimpleParent(Executor):
         self.result = response
 
 
-@pytest.mark.asyncio
 async def test_simple_sub_workflow():
     """Test the simplest possible sub-workflow."""
     # Create sub-workflow with dummy executor to satisfy validation

python/packages/main/tests/workflow/test_sub_workflow.py

@@ -4,7 +4,6 @@ import asyncio
 from dataclasses import dataclass
 from typing import Any
 
-import pytest
 from pydantic import Field
 
 from agent_framework import (
@@ -120,7 +119,6 @@ class ParentOrchestrator(Executor):
         self.results.append(result)
 
 
-@pytest.mark.asyncio
 async def test_basic_sub_workflow() -> None:
     """Test basic sub-workflow execution without interception."""
     # Create sub-workflow
@@ -185,7 +183,6 @@ async def test_basic_sub_workflow() -> None:
     assert parent.result.is_valid is True
 
 
-@pytest.mark.asyncio
 async def test_sub_workflow_with_interception():
     """Test sub-workflow with parent interception of requests."""
     # Create sub-workflow
@@ -248,7 +245,6 @@ async def test_sub_workflow_with_interception():
     assert parent.results[0].reason == "Domain not approved"
 
 
-@pytest.mark.asyncio
 async def test_conditional_forwarding() -> None:
     """Test conditional forwarding with RequestResponse.forward()."""
 
@@ -326,7 +322,6 @@ async def test_conditional_forwarding() -> None:
     assert parent.result.is_valid is True
 
 
-@pytest.mark.asyncio
 async def test_workflow_scoped_interception() -> None:
     """Test interception scoped to specific sub-workflows."""
 

python/packages/main/tests/workflow/test_tracing.py

@@ -273,7 +273,6 @@ async def test_trace_context_handling(tracing_enabled: Any, span_exporter: InMem
     assert processing_span.attributes.get("message.type") == "str"
 
 
-@pytest.mark.asyncio
 async def test_trace_context_disabled_when_tracing_disabled() -> None:
     """Test that no trace context is added when tracing is disabled."""
     # Tracing should be disabled by default
@@ -299,7 +298,6 @@ async def test_trace_context_disabled_when_tracing_disabled() -> None:
     assert message.source_span_id is None
 
 
-@pytest.mark.asyncio
 async def test_end_to_end_workflow_tracing(tracing_enabled: Any, span_exporter: InMemorySpanExporter) -> None:
     """Test end-to-end tracing including workflow build, execution, and span linking with fan-in edges."""
     # Create executors for fan-in scenario
@@ -424,7 +422,6 @@ async def test_end_to_end_workflow_tracing(tracing_enabled: Any, span_exporter:
     assert len(aggregator_span.links) >= 2, f"Expected at least 2 links, got {len(aggregator_span.links)}"
 
 
-@pytest.mark.asyncio
 async def test_workflow_error_handling_in_tracing(tracing_enabled: Any, span_exporter: InMemorySpanExporter) -> None:
     """Test that workflow errors are properly recorded in traces."""
 
@@ -460,7 +457,6 @@ async def test_workflow_error_handling_in_tracing(tracing_enabled: Any, span_exp
     assert workflow_span.status.status_code.name == "ERROR"
 
 
-@pytest.mark.asyncio
 async def test_message_trace_context_serialization() -> None:
     """Test that message trace context is properly serialized/deserialized."""
     ctx = InProcRunnerContext()
@@ -495,7 +491,6 @@ async def test_message_trace_context_serialization() -> None:
     assert restored_msg.source_span_ids == ["span123"]  # Test new format
 
 
-@pytest.mark.asyncio
 async def test_workflow_build_error_tracing(tracing_enabled: Any, span_exporter: InMemorySpanExporter) -> None:
     """Test that build errors are properly recorded in build spans."""
 

python/packages/main/tests/workflow/test_workflow.py

@@ -231,7 +231,7 @@ async def test_fan_out():
 
     events = await workflow.run(NumberMessage(data=0))
 
-    # Each executor will emit two events: ExecutorInvokeEvent and ExecutorCompletedEvent
+    # Each executor will emit two events: ExecutorInvokedEvent and ExecutorCompletedEvent
     # executor_b will also emit a WorkflowCompletedEvent
     assert len(events) == 7
 
@@ -251,7 +251,7 @@ async def test_fan_out_multiple_completed_events():
 
     events = await workflow.run(NumberMessage(data=0))
 
-    # Each executor will emit two events: ExecutorInvokeEvent and ExecutorCompletedEvent
+    # Each executor will emit two events: ExecutorInvokedEvent and ExecutorCompletedEvent
     # executor_a and executor_b will also emit a WorkflowCompletedEvent
     assert len(events) == 8
 
@@ -276,7 +276,7 @@ async def test_fan_in():
 
     events = await workflow.run(NumberMessage(data=0))
 
-    # Each executor will emit two events: ExecutorInvokeEvent and ExecutorCompletedEvent
+    # Each executor will emit two events: ExecutorInvokedEvent and ExecutorCompletedEvent
     # aggregator will also emit a WorkflowCompletedEvent
     assert len(events) == 9
 
@@ -667,10 +667,10 @@ async def test_workflow_with_simple_cycle_and_exit_condition():
     )  # Should complete when executor_a reaches its limit
 
     # Verify cycling occurred (should have events from both executors)
-    # Check for ExecutorInvokeEvent and ExecutorCompletedEvent types that have executor_id
-    from agent_framework import ExecutorCompletedEvent, ExecutorInvokeEvent
+    # Check for ExecutorInvokedEvent and ExecutorCompletedEvent types that have executor_id
+    from agent_framework import ExecutorCompletedEvent, ExecutorInvokedEvent
 
-    executor_events = [e for e in events if isinstance(e, (ExecutorInvokeEvent, ExecutorCompletedEvent))]
+    executor_events = [e for e in events if isinstance(e, (ExecutorInvokedEvent, ExecutorCompletedEvent))]
     executor_ids = {e.executor_id for e in executor_events}
     assert "exec_a" in executor_ids, "Should have events from executor A"
     assert "exec_b" in executor_ids, "Should have events from executor B"

python/packages/main/tests/workflow/test_workflow_agent.py

@@ -76,7 +76,6 @@ class RequestingExecutor(Executor):
 class TestWorkflowAgent:
     """Test cases for WorkflowAgent end-to-end functionality."""
 
-    @pytest.mark.asyncio
     async def test_end_to_end_basic_workflow(self):
         """Test basic end-to-end workflow execution with 2 executors emitting AgentRunEvent."""
         # Create workflow with two executors
@@ -117,7 +116,6 @@ class TestWorkflowAgent:
         assert "Step1: Hello World" in step1_text
         assert "Step2: Step1: Hello World" in step2_text
 
-    @pytest.mark.asyncio
     async def test_end_to_end_basic_workflow_streaming(self):
         """Test end-to-end workflow with streaming executor that emits AgentRunStreamingEvent."""
         # Create a single streaming executor
@@ -146,7 +144,6 @@ class TestWorkflowAgent:
         assert isinstance(second_content, TextContent)
         assert "Streaming2: Streaming1: Test input" in second_content.text
 
-    @pytest.mark.asyncio
     async def test_end_to_end_request_info_handling(self):
         """Test end-to-end workflow with RequestInfoEvent handling."""
         # Create workflow with requesting executor -> request info executor (no cycle)

python/packages/main/tests/workflow/test_workflow_context.py

@@ -0,0 +1,64 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from collections.abc import AsyncIterator
+from contextlib import asynccontextmanager
+from typing import TYPE_CHECKING
+
+from agent_framework import (
+    WorkflowCompletedEvent,
+    WorkflowContext,
+    WorkflowEvent,
+    WorkflowRunState,
+    WorkflowStatusEvent,
+)
+
+if TYPE_CHECKING:
+    from _pytest.logging import LogCaptureFixture
+
+    from agent_framework._workflow._runner_context import InProcRunnerContext
+
+
+@asynccontextmanager
+async def make_context(
+    executor_id: str = "exec",
+) -> AsyncIterator[tuple[WorkflowContext[object], "InProcRunnerContext"]]:
+    from agent_framework._workflow._runner_context import InProcRunnerContext
+    from agent_framework._workflow._shared_state import SharedState
+
+    runner_ctx = InProcRunnerContext()
+    shared_state = SharedState()
+    workflow_ctx: WorkflowContext[object] = WorkflowContext(
+        executor_id,
+        ["source"],
+        shared_state,
+        runner_ctx,
+    )
+    try:
+        yield workflow_ctx, runner_ctx
+    finally:
+        await asyncio.sleep(0)
+
+
+async def test_executor_cannot_emit_framework_lifecycle_event(caplog: "LogCaptureFixture") -> None:
+    async with make_context() as (ctx, runner_ctx):
+        caplog.clear()
+        with caplog.at_level("WARNING"):
+            await ctx.add_event(WorkflowStatusEvent(state=WorkflowRunState.IN_PROGRESS))
+
+        events: list[WorkflowEvent] = await runner_ctx.drain_events()
+        assert len(events) == 1
+        assert type(events[0]).__name__ == "WorkflowWarningEvent"
+        data = getattr(events[0], "data", None)
+        assert isinstance(data, str)
+        assert "reserved for framework lifecycle notifications" in data
+        assert any("attempted to emit WorkflowStatusEvent" in message for message in list(caplog.messages))
+
+
+async def test_executor_emits_normal_event() -> None:
+    async with make_context() as (ctx, runner_ctx):
+        await ctx.add_event(WorkflowCompletedEvent("done"))
+
+        events: list[WorkflowEvent] = await runner_ctx.drain_events()
+        assert len(events) == 1
+        assert isinstance(events[0], WorkflowCompletedEvent)

python/packages/main/tests/workflow/test_workflow_states.py

@@ -14,9 +14,11 @@ from agent_framework import (
     WorkflowBuilder,
     WorkflowCompletedEvent,
     WorkflowContext,
+    WorkflowEventSource,
     WorkflowFailedEvent,
     WorkflowRunResult,
     WorkflowRunState,
+    WorkflowStartedEvent,
     WorkflowStatusEvent,
     handler,
 )
@@ -41,9 +43,12 @@ async def test_executor_failed_and_workflow_failed_events_streaming():
             events.append(ev)
 
     # Workflow-level failure and FAILED status should be surfaced
-    assert any(isinstance(e, WorkflowFailedEvent) for e in events)
+    failed_events = [e for e in events if isinstance(e, WorkflowFailedEvent)]
+    assert failed_events
+    assert all(e.origin is WorkflowEventSource.FRAMEWORK for e in failed_events)
     status = [e for e in events if isinstance(e, WorkflowStatusEvent)]
     assert status and status[-1].state == WorkflowRunState.FAILED
+    assert all(e.origin is WorkflowEventSource.FRAMEWORK for e in status)
 
 
 async def test_executor_failed_event_emitted_on_direct_execute():
@@ -58,7 +63,9 @@ async def test_executor_failed_event_emitted_on_direct_execute():
     with pytest.raises(RuntimeError, match="boom"):
         await failing.execute(0, wf_ctx)
     drained = await ctx.drain_events()
-    assert any(isinstance(e, ExecutorFailedEvent) for e in drained)
+    failed = [e for e in drained if isinstance(e, ExecutorFailedEvent)]
+    assert failed
+    assert all(e.origin is WorkflowEventSource.FRAMEWORK for e in failed)
 
 
 class Requester(Executor):
@@ -99,6 +106,19 @@ async def test_completed_status_streaming():
     # Last status should be COMPLETED
     status = [e for e in events if isinstance(e, WorkflowStatusEvent)]
     assert status and status[-1].state == WorkflowRunState.COMPLETED
+    assert all(e.origin is WorkflowEventSource.FRAMEWORK for e in status)
+
+
+async def test_started_and_completed_event_origins():
+    c = Completer(id="c-origin")
+    wf = WorkflowBuilder().set_start_executor(c).build()
+    events = [ev async for ev in wf.run_stream("payload")]
+
+    started = next(e for e in events if isinstance(e, WorkflowStartedEvent))
+    assert started.origin is WorkflowEventSource.FRAMEWORK
+
+    completed = next(e for e in events if isinstance(e, WorkflowCompletedEvent))
+    assert completed.origin is WorkflowEventSource.EXECUTOR
 
 
 async def test_non_streaming_final_state_helpers():

python/samples/getting_started/workflow/_start-here/step3_streaming.py

@@ -29,7 +29,8 @@ Purpose:
 Show how to wrap chat agents created by AzureChatClient inside workflow executors, wire them with WorkflowBuilder,
 and consume streaming events from the workflow. Demonstrate the @handler pattern with typed inputs and typed
 WorkflowContext[T] outputs, and finish by emitting a WorkflowCompletedEvent from the terminal node while printing
-intermediate events for observability.
+intermediate events for observability. The streaming loop also surfaces WorkflowEvent.origin so you can
+distinguish runner-generated lifecycle events from executor-generated data-plane events.
 
 Prerequisites:
 - Azure OpenAI configured for AzureChatClient with required environment variables.
@@ -123,36 +124,42 @@ async def main():
         ChatMessage(role="user", text="Create a slogan for a new electric SUV that is affordable and fun to drive.")
     ):
         if isinstance(event, WorkflowStatusEvent):
+            prefix = f"State ({event.origin.value}): "
             if event.state == WorkflowRunState.IN_PROGRESS:
-                print("State: IN_PROGRESS")
+                print(prefix + "IN_PROGRESS")
             elif event.state == WorkflowRunState.COMPLETED:
-                print("State: COMPLETED")
+                print(prefix + "COMPLETED")
             elif event.state == WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS:
-                print("State: IN_PROGRESS_PENDING_REQUESTS (requests in flight)")
+                print(prefix + "IN_PROGRESS_PENDING_REQUESTS (requests in flight)")
             elif event.state == WorkflowRunState.IDLE:
-                print("State: IDLE (no active work)")
+                print(prefix + "IDLE (no active work)")
             elif event.state == WorkflowRunState.IDLE_WITH_PENDING_REQUESTS:
-                print("State: IDLE_WITH_PENDING_REQUESTS (prompt user or UI now)")
+                print(prefix + "IDLE_WITH_PENDING_REQUESTS (prompt user or UI now)")
             else:
-                print(f"State: {event.state}")
+                print(prefix + str(event.state))
+        elif isinstance(event, WorkflowCompletedEvent):
+            print(f"Workflow completed ({event.origin.value}): {event.data}")
         elif isinstance(event, ExecutorFailedEvent):
-            print(f"Executor failed: {event.executor_id} {event.details.error_type}: {event.details.message}")
+            print(
+                f"Executor failed ({event.origin.value}): "
+                f"{event.executor_id} {event.details.error_type}: {event.details.message}"
+            )
         elif isinstance(event, WorkflowFailedEvent):
             details = event.details
-            print(f"Workflow failed: {details.error_type}: {details.message}")
+            print(f"Workflow failed ({event.origin.value}): {details.error_type}: {details.message}")
         else:
-            print(event)
+            print(f"{event.__class__.__name__} ({event.origin.value}): {event}")
 
     """
     Sample Output:
 
-    State: IN_PROGRESS
-    ExecutorInvokeEvent(executor_id=writer)
-    ExecutorCompletedEvent(executor_id=writer)
-    ExecutorInvokeEvent(executor_id=reviewer)
-    WorkflowCompletedEvent(data=Drive the Future. Affordable Adventure, Electrified.)
-    ExecutorCompletedEvent(executor_id=reviewer)
-    State: COMPLETED
+    State (RUNNER): IN_PROGRESS
+    ExecutorInvokeEvent (RUNNER): ExecutorInvokeEvent(executor_id=writer)
+    ExecutorCompletedEvent (RUNNER): ExecutorCompletedEvent(executor_id=writer)
+    ExecutorInvokeEvent (RUNNER): ExecutorInvokeEvent(executor_id=reviewer)
+    Workflow completed (EXECUTOR): Drive the Future. Affordable Adventure, Electrified.
+    ExecutorCompletedEvent (RUNNER): ExecutorCompletedEvent(executor_id=reviewer)
+    State (RUNNER): COMPLETED
     """
 
 

python/samples/getting_started/workflow/checkpoint/checkpoint_with_resume.py

@@ -275,15 +275,15 @@ async def main():
 
     Running workflow with initial message...
     UpperCaseExecutor: 'hello world' -> 'HELLO WORLD'
-    Event: ExecutorInvokeEvent(executor_id=upper_case_executor)
+    Event: ExecutorInvokedEvent(executor_id=upper_case_executor)
     Event: ExecutorCompletedEvent(executor_id=upper_case_executor)
     ReverseTextExecutor: 'HELLO WORLD' -> 'DLROW OLLEH'
-    Event: ExecutorInvokeEvent(executor_id=reverse_text_executor)
+    Event: ExecutorInvokedEvent(executor_id=reverse_text_executor)
     Event: ExecutorCompletedEvent(executor_id=reverse_text_executor)
     LowerAgent (shared_state): original_input='hello world', upper_output='HELLO WORLD'
-    Event: ExecutorInvokeEvent(executor_id=submit_lower)
-    Event: ExecutorInvokeEvent(executor_id=lower_agent)
-    Event: ExecutorInvokeEvent(executor_id=finalize)
+    Event: ExecutorInvokedEvent(executor_id=submit_lower)
+    Event: ExecutorInvokedEvent(executor_id=lower_agent)
+    Event: ExecutorInvokedEvent(executor_id=finalize)
     Event: WorkflowCompletedEvent(data=dlrow olleh)
 
     Checkpoint summary:
@@ -300,9 +300,9 @@ async def main():
 
     Resuming from checkpoint: a78c345a-e5d9-45ba-82c0-cb725452d91b
     LowerAgent (shared_state): original_input='hello world', upper_output='HELLO WORLD'
-    Resumed Event: ExecutorInvokeEvent(executor_id=submit_lower)
-    Resumed Event: ExecutorInvokeEvent(executor_id=lower_agent)
-    Resumed Event: ExecutorInvokeEvent(executor_id=finalize)
+    Resumed Event: ExecutorInvokedEvent(executor_id=submit_lower)
+    Resumed Event: ExecutorInvokedEvent(executor_id=lower_agent)
+    Resumed Event: ExecutorInvokedEvent(executor_id=finalize)
     Resumed Event: WorkflowCompletedEvent(data=dlrow olleh)
     """  # noqa: E501
 

python/samples/getting_started/workflow/control-flow/sequential_streaming.py

@@ -13,7 +13,7 @@ The second reverses the text and completes the workflow. Events are printed as t
 Purpose:
 Show how to declare executors with the @executor decorator, connect them with WorkflowBuilder,
 pass intermediate values using ctx.send_message, and signal completion with ctx.add_event by emitting a
-WorkflowCompletedEvent. Demonstrate how streaming exposes ExecutorInvokeEvent and WorkflowCompletedEvent
+WorkflowCompletedEvent. Demonstrate how streaming exposes ExecutorInvokedEvent and WorkflowCompletedEvent
 for observability.
 
 Prerequisites:
@@ -72,9 +72,9 @@ async def main():
     """
     Sample Output:
 
-    Event: ExecutorInvokeEvent(executor_id=upper_case_executor)
+    Event: ExecutorInvokedEvent(executor_id=upper_case_executor)
     Event: ExecutorCompletedEvent(executor_id=upper_case_executor)
-    Event: ExecutorInvokeEvent(executor_id=reverse_text_executor)
+    Event: ExecutorInvokedEvent(executor_id=reverse_text_executor)
     Event: WorkflowCompletedEvent(data=DLROW OLLEH)
     Event: ExecutorCompletedEvent(executor_id=reverse_text_executor)
     Workflow completed with result: DLROW OLLEH