Python: Add executor I/O data to ExecutorInvokedEvent and ExecutorCompletedEvent (#2591)

* Add executor I/O data to ExecutorInvokedEvent and ExecutorCompletedEvent

* Sample cleanup
This commit is contained in:
Evan Mattson
2025-12-04 10:41:40 +09:00
committed by GitHub
Unverified
parent b86c130411
commit f7a9005235
6 changed files with 315 additions and 8 deletions
@@ -264,7 +264,7 @@ class Executor(RequestInfoMixin, DictConvertible):
# Invoke the handler with the message and context
with _framework_event_origin():
invoke_event = ExecutorInvokedEvent(self.id)
invoke_event = ExecutorInvokedEvent(self.id, message)
await context.add_event(invoke_event)
try:
await handler(message, context)
@@ -275,7 +275,9 @@ class Executor(RequestInfoMixin, DictConvertible):
await context.add_event(failure_event)
raise
with _framework_event_origin():
completed_event = ExecutorCompletedEvent(self.id)
# Include sent messages as the completion data
sent_messages = context.get_sent_messages()
completed_event = ExecutorCompletedEvent(self.id, sent_messages if sent_messages else None)
await context.add_event(completed_event)
def _create_context_for_handler(
@@ -287,6 +287,9 @@ class WorkflowContext(Generic[T_Out, T_W_Out]):
self._runner_context = runner_context
self._shared_state = shared_state
# Track messages sent via send_message() for ExecutorCompletedEvent
self._sent_messages: list[Any] = []
# Store trace contexts and source span IDs for linking (supporting multiple sources)
self._trace_contexts = trace_contexts or []
self._source_span_ids = source_span_ids or []
@@ -313,6 +316,9 @@ class WorkflowContext(Generic[T_Out, T_W_Out]):
# Create Message wrapper
msg = Message(data=message, source_id=self._executor_id, target_id=target_id)
# Track sent message for ExecutorCompletedEvent
self._sent_messages.append(message)
# Inject current trace context if tracing enabled
if OBSERVABILITY_SETTINGS.ENABLED and span and span.is_recording(): # type: ignore[name-defined]
trace_context: dict[str, str] = {}
@@ -410,6 +416,14 @@ class WorkflowContext(Generic[T_Out, T_W_Out]):
"""Get the shared state."""
return self._shared_state
def get_sent_messages(self) -> list[Any]:
"""Get all messages sent via send_message() during this handler execution.
Returns:
A list of messages that were sent to downstream executors.
"""
return self._sent_messages.copy()
@deprecated(
"Override `on_checkpoint_save()` methods instead. "
"For cross-executor state sharing, use set_shared_state() instead. "
@@ -448,7 +462,7 @@ class WorkflowContext(Generic[T_Out, T_W_Out]):
if not isinstance(existing_states, dict):
raise ValueError("Existing executor states in shared state is not a dictionary.")
return existing_states.get(self._executor_id)
return existing_states.get(self._executor_id) # type: ignore
def is_streaming(self) -> bool:
"""Check if the workflow is running in streaming mode.
@@ -2,7 +2,15 @@
import pytest
from agent_framework import Executor, Message, WorkflowContext, handler
from agent_framework import (
Executor,
ExecutorCompletedEvent,
ExecutorInvokedEvent,
Message,
WorkflowBuilder,
WorkflowContext,
handler,
)
def test_executor_without_id():
@@ -101,3 +109,155 @@ def test_executor_handlers_with_output_types():
assert int_handler._handler_spec["name"] == "handle_integer" # type: ignore
assert int_handler._handler_spec["message_type"] is int # type: ignore
assert int_handler._handler_spec["output_types"] == [int] # type: ignore
async def test_executor_invoked_event_contains_input_data():
"""Test that ExecutorInvokedEvent contains the input message data."""
class UpperCaseExecutor(Executor):
@handler
async def handle(self, text: str, ctx: WorkflowContext[str]) -> None:
await ctx.send_message(text.upper())
class CollectorExecutor(Executor):
@handler
async def handle(self, text: str, ctx: WorkflowContext) -> None:
pass
upper = UpperCaseExecutor(id="upper")
collector = CollectorExecutor(id="collector")
workflow = WorkflowBuilder().add_edge(upper, collector).set_start_executor(upper).build()
events = await workflow.run("hello world")
invoked_events = [e for e in events if isinstance(e, ExecutorInvokedEvent)]
assert len(invoked_events) == 2
# First invoked event should be for 'upper' executor with input "hello world"
upper_invoked = next(e for e in invoked_events if e.executor_id == "upper")
assert upper_invoked.data == "hello world"
# Second invoked event should be for 'collector' executor with input "HELLO WORLD"
collector_invoked = next(e for e in invoked_events if e.executor_id == "collector")
assert collector_invoked.data == "HELLO WORLD"
async def test_executor_completed_event_contains_sent_messages():
"""Test that ExecutorCompletedEvent contains the messages sent via ctx.send_message()."""
class MultiSenderExecutor(Executor):
@handler
async def handle(self, text: str, ctx: WorkflowContext[str]) -> None:
await ctx.send_message(f"{text}-first")
await ctx.send_message(f"{text}-second")
class CollectorExecutor(Executor):
def __init__(self, id: str) -> None:
super().__init__(id=id)
self.received: list[str] = []
@handler
async def handle(self, text: str, ctx: WorkflowContext) -> None:
self.received.append(text)
sender = MultiSenderExecutor(id="sender")
collector = CollectorExecutor(id="collector")
workflow = WorkflowBuilder().add_edge(sender, collector).set_start_executor(sender).build()
events = await workflow.run("hello")
completed_events = [e for e in events if isinstance(e, ExecutorCompletedEvent)]
# Sender should have completed with the sent messages
sender_completed = next(e for e in completed_events if e.executor_id == "sender")
assert sender_completed.data is not None
assert sender_completed.data == ["hello-first", "hello-second"]
# Collector should have completed with no sent messages (None)
collector_completed_events = [e for e in completed_events if e.executor_id == "collector"]
# Collector is called twice (once per message from sender)
assert len(collector_completed_events) == 2
for collector_completed in collector_completed_events:
assert collector_completed.data is None
async def test_executor_completed_event_none_when_no_messages_sent():
"""Test that ExecutorCompletedEvent.data is None when no messages are sent."""
from typing_extensions import Never
from agent_framework import WorkflowOutputEvent
class YieldOnlyExecutor(Executor):
@handler
async def handle(self, text: str, ctx: WorkflowContext[Never, str]) -> None:
await ctx.yield_output(text.upper())
executor = YieldOnlyExecutor(id="yielder")
workflow = WorkflowBuilder().set_start_executor(executor).build()
events = await workflow.run("test")
completed_events = [e for e in events if isinstance(e, ExecutorCompletedEvent)]
assert len(completed_events) == 1
assert completed_events[0].executor_id == "yielder"
assert completed_events[0].data is None
# Verify the output was still yielded correctly
output_events = [e for e in events if isinstance(e, WorkflowOutputEvent)]
assert len(output_events) == 1
assert output_events[0].data == "TEST"
async def test_executor_events_with_complex_message_types():
"""Test that executor events correctly capture complex message types."""
from dataclasses import dataclass
@dataclass
class Request:
query: str
limit: int
@dataclass
class Response:
results: list[str]
class ProcessorExecutor(Executor):
@handler
async def handle(self, request: Request, ctx: WorkflowContext[Response]) -> None:
response = Response(results=[request.query.upper()] * request.limit)
await ctx.send_message(response)
class CollectorExecutor(Executor):
@handler
async def handle(self, response: Response, ctx: WorkflowContext) -> None:
pass
processor = ProcessorExecutor(id="processor")
collector = CollectorExecutor(id="collector")
workflow = WorkflowBuilder().add_edge(processor, collector).set_start_executor(processor).build()
input_request = Request(query="hello", limit=3)
events = await workflow.run(input_request)
invoked_events = [e for e in events if isinstance(e, ExecutorInvokedEvent)]
completed_events = [e for e in events if isinstance(e, ExecutorCompletedEvent)]
# Check processor invoked event has the Request object
processor_invoked = next(e for e in invoked_events if e.executor_id == "processor")
assert isinstance(processor_invoked.data, Request)
assert processor_invoked.data.query == "hello"
assert processor_invoked.data.limit == 3
# Check processor completed event has the Response object
processor_completed = next(e for e in completed_events if e.executor_id == "processor")
assert processor_completed.data is not None
assert len(processor_completed.data) == 1
assert isinstance(processor_completed.data[0], Response)
assert processor_completed.data[0].results == ["HELLO", "HELLO", "HELLO"]
# Check collector invoked event has the Response object
collector_invoked = next(e for e in invoked_events if e.executor_id == "collector")
assert isinstance(collector_invoked.data, Response)
assert collector_invoked.data.results == ["HELLO", "HELLO", "HELLO"]
@@ -23,6 +23,7 @@ from agent_framework import (
WorkflowOutputEvent,
)
from agent_framework._mcp import MCPTool
from agent_framework._workflows import AgentRunEvent
from agent_framework._workflows import _handoff as handoff_module # type: ignore
from agent_framework._workflows._handoff import _clone_chat_agent # type: ignore[reportPrivateUsage]
from agent_framework._workflows._workflow_builder import WorkflowBuilder
@@ -224,12 +225,12 @@ async def test_handoff_preserves_complex_additional_properties(complex_metadata:
# Initial run should preserve complex metadata in the triage response
events = await _drain(workflow.run_stream("Need help with a return"))
agent_events = [ev for ev in events if hasattr(ev, "data") and hasattr(ev.data, "messages")]
agent_events = [ev for ev in events if isinstance(ev, AgentRunEvent)]
if agent_events:
first_agent_event = agent_events[0]
first_agent_event_data = first_agent_event.data
if first_agent_event_data and hasattr(first_agent_event_data, "messages"):
first_agent_message = first_agent_event_data.messages[0] # type: ignore[attr-defined]
if first_agent_event_data and first_agent_event_data.messages:
first_agent_message = first_agent_event_data.messages[0]
assert "complex" in first_agent_message.additional_properties, "Agent event lost complex metadata"
requests = [ev for ev in events if isinstance(ev, RequestInfoEvent)]
assert requests, "Workflow should request additional user input"
@@ -84,7 +84,11 @@ Once comfortable with these, explore the rest of the samples below.
### observability
For observability samples in Agent Framework, see the [observability getting started samples](../observability/README.md). The [sample](../observability/workflow_observability.py) demonstrates integrating observability into workflows.
| Sample | File | Concepts |
|---|---|---|
| Executor I/O Observation | [observability/executor_io_observation.py](./observability/executor_io_observation.py) | Observe executor input/output data via ExecutorInvokedEvent and ExecutorCompletedEvent without modifying executor code |
For additional observability samples in Agent Framework, see the [observability getting started samples](../observability/README.md). The [sample](../observability/workflow_observability.py) demonstrates integrating observability into workflows.
### orchestration
@@ -0,0 +1,126 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
from typing import Any, cast
from agent_framework import (
Executor,
ExecutorCompletedEvent,
ExecutorInvokedEvent,
WorkflowBuilder,
WorkflowContext,
WorkflowOutputEvent,
handler,
)
from typing_extensions import Never
"""
Executor I/O Observation
This sample demonstrates how to observe executor input and output data without modifying
executor code. This is useful for debugging, logging, or building monitoring tools.
What this example shows:
- ExecutorInvokedEvent.data contains the input message received by the executor
- ExecutorCompletedEvent.data contains the messages sent via ctx.send_message()
- How to generically observe all executor I/O through workflow streaming events
This approach allows you to instrument any workflow for observability without
changing the executor implementations.
Prerequisites:
- No external services required.
"""
class UpperCaseExecutor(Executor):
"""Convert input text to uppercase and forward to next executor."""
def __init__(self, id: str = "upper_case"):
super().__init__(id=id)
@handler
async def handle(self, text: str, ctx: WorkflowContext[str]) -> None:
result = text.upper()
await ctx.send_message(result)
class ReverseTextExecutor(Executor):
"""Reverse the input text and yield as workflow output."""
def __init__(self, id: str = "reverse_text"):
super().__init__(id=id)
@handler
async def handle(self, text: str, ctx: WorkflowContext[Never, str]) -> None:
result = text[::-1]
await ctx.yield_output(result)
def format_io_data(data: Any) -> str:
"""Format executor I/O data for display.
This helper formats common data types for readable output.
Customize based on the types used in your workflow.
"""
type_name = type(data).__name__
if data is None:
return "None"
if isinstance(data, str):
preview = data[:80] + "..." if len(data) > 80 else data
return f"{type_name}: '{preview}'"
if isinstance(data, list):
data_list = cast(list[Any], data)
if len(data_list) == 0:
return f"{type_name}: []"
# For sent_messages, show each item with its type
if len(data_list) <= 3:
items = [format_io_data(item) for item in data_list]
return f"{type_name}: [{', '.join(items)}]"
return f"{type_name}: [{len(data_list)} items]"
return f"{type_name}: {repr(data)}"
async def main() -> None:
"""Build a workflow and observe executor I/O through streaming events."""
upper_case = UpperCaseExecutor()
reverse_text = ReverseTextExecutor()
workflow = WorkflowBuilder().add_edge(upper_case, reverse_text).set_start_executor(upper_case).build()
print("Running workflow with executor I/O observation...\n")
async for event in workflow.run_stream("hello world"):
if isinstance(event, ExecutorInvokedEvent):
# The input message received by the executor is in event.data
print(f"[INVOKED] {event.executor_id}")
print(f" Input: {format_io_data(event.data)}")
elif isinstance(event, ExecutorCompletedEvent):
# Messages sent via ctx.send_message() are in event.data
print(f"[COMPLETED] {event.executor_id}")
if event.data:
print(f" Output: {format_io_data(event.data)}")
elif isinstance(event, WorkflowOutputEvent):
print(f"[WORKFLOW OUTPUT] {format_io_data(event.data)}")
"""
Sample Output:
Running workflow with executor I/O observation...
[INVOKED] upper_case
Input: str: 'hello world'
[COMPLETED] upper_case
Output: list: [str: 'HELLO WORLD']
[INVOKED] reverse_text
Input: str: 'HELLO WORLD'
[WORKFLOW OUTPUT] str: 'DLROW OLLEH'
[COMPLETED] reverse_text
"""
if __name__ == "__main__":
asyncio.run(main())