[BREAKING] Python: Refactor workflow events to unified discriminated union pattern (#3690)

* Refactor events

* Merge main

* Fixes

* Cleanup

* Update samples and tests

* Remove unused imports

* PR feedback

* Merge main. Add properties for events to help typing

* Formatting

* Cleanup

* use builtins.type to avoid shadowing by WorkflowEvent.type attribute

* Final improvements

python/samples/getting_started/workflows/tool-approval/concurrent_builder_tool_approval.py

@@ -6,14 +6,12 @@ from typing import Annotated
 
 from agent_framework import (
     ChatMessage,
-    ConcurrentBuilder,
     Content,
-    RequestInfoEvent,
     WorkflowEvent,
-    WorkflowOutputEvent,
     tool,
 )
 from agent_framework.openai import OpenAIChatClient
+from agent_framework.orchestrations import ConcurrentBuilder
 
 """
 Sample: Concurrent Workflow with Tool Approval Requests
@@ -36,7 +34,7 @@ agents may independently trigger approval requests.
 
 Demonstrate:
 - Handling multiple approval requests from different agents in concurrent workflows.
-- Handling RequestInfoEvent during concurrent agent execution.
+- Handling  during concurrent agent execution.
 - Understanding that approval pauses only the agent that triggered it, not all agents.
 
 Prerequisites:
@@ -89,12 +87,12 @@ def get_portfolio_balance() -> str:
     return "Portfolio: $50,000 invested, $10,000 cash available. Holdings: AAPL, GOOGL, MSFT."
 
 
-def _print_output(event: WorkflowOutputEvent) -> None:
+def _print_output(event: WorkflowEvent) -> None:
     if not event.data:
-        raise ValueError("WorkflowOutputEvent has no data")
+        raise ValueError("WorkflowEvent has no data")
 
     if not isinstance(event.data, list) and not all(isinstance(msg, ChatMessage) for msg in event.data):
-        raise ValueError("WorkflowOutputEvent data is not a list of ChatMessage")
+        raise ValueError("WorkflowEvent data is not a list of ChatMessage")
 
     messages: list[ChatMessage] = event.data  # type: ignore
 
@@ -109,10 +107,10 @@ async def process_event_stream(stream: AsyncIterable[WorkflowEvent]) -> dict[str
     """Process events from the workflow stream to capture human feedback requests."""
     requests: dict[str, Content] = {}
     async for event in stream:
-        if isinstance(event, RequestInfoEvent) and isinstance(event.data, Content):
+        if event.type == "request_info" and isinstance(event.data, Content):
             # We are only expecting tool approval requests in this sample
             requests[event.request_id] = event.data
-        elif isinstance(event, WorkflowOutputEvent):
+        elif event.type == "output":
             _print_output(event)
 
     responses: dict[str, Content] = {}

python/samples/getting_started/workflows/tool-approval/group_chat_builder_tool_approval.py

@@ -7,14 +7,11 @@ from typing import Annotated, cast
 from agent_framework import (
     ChatMessage,
     Content,
-    GroupChatBuilder,
-    GroupChatState,
-    RequestInfoEvent,
     WorkflowEvent,
-    WorkflowOutputEvent,
     tool,
 )
 from agent_framework.openai import OpenAIChatClient
+from agent_framework.orchestrations import GroupChatBuilder, GroupChatState
 
 """
 Sample: Group Chat Workflow with Tool Approval Requests
@@ -36,7 +33,7 @@ different agents have different levels of tool access.
 
 Demonstrate:
 - Using set_select_speakers_func with agents that have approval-required tools.
-- Handling RequestInfoEvent in group chat scenarios.
+- Handling request_info events (type='request_info') in group chat scenarios.
 - Multi-round group chat with tool approval interruption and resumption.
 
 Prerequisites:
@@ -99,16 +96,16 @@ async def process_event_stream(stream: AsyncIterable[WorkflowEvent]) -> dict[str
     """Process events from the workflow stream to capture human feedback requests."""
     requests: dict[str, Content] = {}
     async for event in stream:
-        if isinstance(event, RequestInfoEvent) and isinstance(event.data, Content):
+        if event.type == "request_info" and isinstance(event.data, Content):
             # We are only expecting tool approval requests in this sample
             requests[event.request_id] = event.data
-        elif isinstance(event, WorkflowOutputEvent):
+        elif event.type == "output":
             # The output of the workflow comes from the orchestrator and it's a list of messages
             print("\n" + "=" * 60)
             print("Workflow summary:")
             outputs = cast(list[ChatMessage], event.data)
             for msg in outputs:
-                speaker = msg.author_name or msg.role.value
+                speaker = msg.author_name or msg.role
                 print(f"[{speaker}]: {msg.text}")
 
     responses: dict[str, Content] = {}

python/samples/getting_started/workflows/tool-approval/sequential_builder_tool_approval.py

@@ -7,13 +7,11 @@ from typing import Annotated, cast
 from agent_framework import (
     ChatMessage,
     Content,
-    RequestInfoEvent,
-    SequentialBuilder,
     WorkflowEvent,
-    WorkflowOutputEvent,
     tool,
 )
 from agent_framework.openai import OpenAIChatClient
+from agent_framework.orchestrations import SequentialBuilder
 
 """
 Sample: Sequential Workflow with Tool Approval Requests
@@ -26,7 +24,7 @@ This sample works as follows:
 1. A SequentialBuilder workflow is created with a single agent that has tools requiring approval.
 2. The agent receives a user task and determines it needs to call a sensitive tool.
 3. The tool call triggers a function_approval_request Content, pausing the workflow.
-4. The sample simulates human approval by responding to the RequestInfoEvent.
+4. The sample simulates human approval by responding to the .
 5. Once approved, the tool executes and the agent completes its response.
 6. The workflow outputs the final conversation with all messages.
 
@@ -36,7 +34,7 @@ requiring any additional builder configuration.
 
 Demonstrate:
 - Using @tool(approval_mode="always_require") for sensitive operations.
-- Handling RequestInfoEvent with function_approval_request Content in sequential workflows.
+- Handling  with function_approval_request Content in sequential workflows.
 - Resuming workflow execution after approval via send_responses_streaming.
 
 Prerequisites:
@@ -55,7 +53,9 @@ def execute_database_query(
     return f"Query executed successfully. Results: 3 rows affected by '{query}'"
 
 
-# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py.
+# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production;
+# see samples/getting_started/tools/function_tool_with_approval.py and
+# samples/getting_started/tools/function_tool_with_approval_and_threads.py.
 @tool(approval_mode="never_require")
 def get_database_schema() -> str:
     """Get the current database schema. Does not require approval."""
@@ -71,10 +71,10 @@ async def process_event_stream(stream: AsyncIterable[WorkflowEvent]) -> dict[str
     """Process events from the workflow stream to capture human feedback requests."""
     requests: dict[str, Content] = {}
     async for event in stream:
-        if isinstance(event, RequestInfoEvent) and isinstance(event.data, Content):
+        if event.type == "request_info" and isinstance(event.data, Content):
             # We are only expecting tool approval requests in this sample
             requests[event.request_id] = event.data
-        elif isinstance(event, WorkflowOutputEvent):
+        elif event.type == "output":
             # The output of the workflow comes from the orchestrator and it's a list of messages
             print("\n" + "=" * 60)
             print("Workflow summary:")