Files
agent-framework/python/packages/orchestrations/tests/test_concurrent.py
T
Evan Mattson 866a325b48 Python: [BREAKING] Standardize orchestration terminal outputs as AgentResponse (#5301)
* Fix orchestration outputs so as_agent() returns the final answer only. Align other orchestration outputs

* Fix orchestration output issues from review comments

1. Sample cleanup: Remove commented-out FoundryChatClient block and update
   prerequisites to reference OPENAI_CHAT_MODEL_ID instead of FOUNDRY_* vars.

2. Sequential approval output: Change _EndWithConversation.end_with_agent_executor_response
   from a no-op sink to yield response.agent_response. When the last participant is
   AgentApprovalExecutor (via with_request_info), _EndWithConversation is the output
   executor so the yield produces the terminal answer. When the last participant is a
   regular AgentExecutor, _EndWithConversation is not in output_executors so the yield
   is silently filtered out.

3. Forward data events through WorkflowExecutor: _process_workflow_result now also
   forwards 'data' events from sub-workflows so that emit_intermediate_data=True on
   AgentExecutor works correctly when wrapped in AgentApprovalExecutor.

4. Concurrent docstring: Update _AggregateAgentConversations docstring to say
   'deterministic participant order' instead of 'completion order'.

5. Add test_concurrent_intermediate_outputs_emits_data_events verifying that
   ConcurrentBuilder(intermediate_outputs=True) emits per-participant data events
   alongside the single aggregated output event.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Add tests for sequential workflow with_request_info and intermediate_outputs (#5301)

Address PR review comments 2, 3, and 5:

- Add test_sequential_request_info_last_participant_emits_output:
  Verifies that when the last participant is wrapped via with_request_info()
  (AgentApprovalExecutor), the workflow still emits a terminal output after
  approval, exercising the _EndWithConversation.end_with_agent_executor_response
  fallback path.

- Add test_sequential_request_info_with_intermediate_outputs_emits_data_events:
  Verifies that emit_intermediate_data=True works correctly through
  AgentApprovalExecutor wrapping—WorkflowExecutor._process_result already
  forwards data events from sub-workflows, so intermediate agent responses
  surface as data events in the parent workflow.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix pyright type errors from AgentResponse output refactor (#5301)

Update cast() calls in _group_chat.py and _magentic.py to use
WorkflowContext[Never, AgentResponse] instead of the old
WorkflowContext[Never, list[Message]], matching the updated method
signatures in _base_group_chat_orchestrator.py.

Fix _sequential.py _EndWithConversation.end_with_agent_executor_response
to declare WorkflowContext[Any, AgentResponse] so yield_output accepts
AgentResponse[None].

Fix _workflow_executor.py data event forwarding to handle nullable
executor_id.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix pyright reportUnknownVariableType in _agent.py (#5301)

Extract event.data into a typed local variable before the isinstance
check to avoid pyright narrowing it to AgentResponse[Unknown].

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix pyright reportMissingImports for orjson in file history samples (#5301)

Add pyright: ignore[reportMissingImports] to orjson imports that are
already guarded by try/except ImportError, matching the existing pattern
used elsewhere in the samples.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address review feedback for #5301: review comment fixes

* Address review feedback for #5301: review comment fixes

* Revert sequential_workflow_as_agent sample to FoundryChatClient

Reverts the mistaken switch from FoundryChatClient to OpenAIChatClient
in the sequential workflow as agent sample.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address ultrareview feedback: emit_data_events rename + WorkflowAgent reasoning conversion

Layered on top of the prior review-feedback work in this branch.

Renames:
- AgentExecutor.emit_intermediate_data -> emit_data_events (mechanical
  rename; orchestration semantics live at the orchestration layer, not
  the general-purpose executor). Forwarded through MagenticAgentExecutor,
  AgentApprovalExecutor, and all orchestration call sites.
- HandoffAgentExecutor._check_terminate_and_yield -> _should_terminate
  (pure predicate; no longer yields anything). HandoffBuilder docstring
  rewritten to describe the new per-agent AgentResponse output contract.

WorkflowAgent reasoning-content conversion:
- Add _rewrite_text_to_reasoning(contents) and _msg_as_reasoning(msg)
  helpers; the as_agent() path now reframes text content from data events
  as text_reasoning Content blocks before merging into the AgentResponse.
- Consumers iterate msg.contents and branch on content.type — same path
  they already use for Claude thinking and OpenAI reasoning. No new
  field on Message/AgentResponse/WorkflowEvent.
- Streaming branch constructs fresh AgentResponseUpdate instances instead
  of mutating shared payloads (regression test added).
- Helper _msg_maybe_reasoning consolidates the conditional rewrite at
  three call sites in the non-streaming conversion.

Tests:
- TestWorkflowAgentReasoningHelpers + TestWorkflowAgentDataEventReasoningConversion
  add 9 new tests covering helpers, non-streaming, streaming, mixed content,
  already-reasoning passthrough, and mutation-safety regression.
- Updated test_sequential_as_agent_with_intermediate_outputs_includes_chain
  to assert text_reasoning content for intermediate agents.

* Fix pyright: widen event.data to Any to avoid partial-unknown narrowing

The streaming conversion path narrowed event.data via isinstance against
generic AgentResponse, producing AgentResponse[Unknown] and tripping
reportUnknownVariableType/reportUnknownMemberType. Binding data: Any
before the check keeps runtime behavior identical while restoring a fully
known type for downstream access.

* Clean up design

* Scope to agent output semantics only

* yield AgentResponseUpdate streaming, AgentResponse non-streaming

* Fix mypy/pyright: widen cast types at GroupChat callsites

Eight callsites in _group_chat.py still cast to WorkflowContext[Never,
AgentResponse] but the base orchestrator methods now accept the wider
WorkflowContext[Never, AgentResponse | AgentResponseUpdate] (mode-aware
yields). W_OutT is invariant, so the narrower cast is not assignable.
Magentic was widened in the same commit; this catches the GroupChat
callsites that were missed.

* Python: skip flaky Foundry / Foundry Hosting integration tests (#5553)

These two integration tests have been failing in the merge queue across
multiple unrelated PRs (5301, 5531). Both are marked `@pytest.mark.flaky`
with 3 retries, but all attempts fail back-to-back. Skipping both with a
reason pointing to #5553 so they can be fixed properly without continuing
to block unrelated merges.

- packages/foundry_hosting/tests/test_responses_int.py::TestOptions::test_temperature_and_max_tokens
- packages/foundry/tests/foundry/test_foundry_embedding_client.py::TestFoundryEmbeddingIntegration::test_text_embedding_live

Also includes a one-line uv.lock specifier-ordering normalization
auto-applied by the poe-check pre-commit hook.

---------

Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-29 00:35:36 +00:00

377 lines
14 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
from collections.abc import AsyncIterable, Awaitable
from typing import Any, Literal, cast, overload
import pytest
from agent_framework import (
AgentExecutorRequest,
AgentExecutorResponse,
AgentResponse,
AgentResponseUpdate,
AgentRunInputs,
AgentSession,
BaseAgent,
Content,
Executor,
Message,
ResponseStream,
WorkflowContext,
WorkflowRunState,
handler,
)
from agent_framework._workflows._checkpoint import InMemoryCheckpointStorage
from agent_framework.orchestrations import ConcurrentBuilder
from typing_extensions import Never
class _FakeAgentExec(Executor):
"""Test executor that mimics an agent by emitting an AgentExecutorResponse.
It takes the incoming AgentExecutorRequest, produces a single assistant message
with the configured reply text, and sends an AgentExecutorResponse that includes
full_conversation (the original user prompt followed by the assistant message).
"""
def __init__(self, id: str, reply_text: str) -> None:
super().__init__(id)
self._reply_text = reply_text
@handler
async def run(self, request: AgentExecutorRequest, ctx: WorkflowContext[AgentExecutorResponse]) -> None:
response = AgentResponse(messages=Message(role="assistant", contents=[self._reply_text]))
full_conversation = list(request.messages) + list(response.messages)
await ctx.send_message(AgentExecutorResponse(self.id, response, full_conversation=full_conversation))
def test_concurrent_builder_rejects_empty_participants() -> None:
with pytest.raises(ValueError):
ConcurrentBuilder(participants=[])
def test_concurrent_builder_rejects_duplicate_executors() -> None:
a = _FakeAgentExec("dup", "A")
b = _FakeAgentExec("dup", "B") # same executor id
with pytest.raises(ValueError):
ConcurrentBuilder(participants=[a, b])
async def test_concurrent_default_aggregator_emits_assistants_only() -> None:
"""Default aggregator yields a single AgentResponse with one assistant message per participant.
The user prompt is intentionally not included — that belongs in the input, not the answer.
"""
e1 = _FakeAgentExec("agentA", "Alpha")
e2 = _FakeAgentExec("agentB", "Beta")
e3 = _FakeAgentExec("agentC", "Gamma")
wf = ConcurrentBuilder(participants=[e1, e2, e3]).build()
output_events = [ev for ev in await wf.run("prompt: hello world") if ev.type == "output"]
assert len(output_events) == 1
response = output_events[0].data
assert isinstance(response, AgentResponse)
# Exactly one assistant message per participant; no user prompt.
assert len(response.messages) == 3
assert all(m.role == "assistant" for m in response.messages)
assert {m.text for m in response.messages} == {"Alpha", "Beta", "Gamma"}
async def test_concurrent_custom_aggregator_callback_is_used() -> None:
# Two synthetic agent executors for brevity
e1 = _FakeAgentExec("agentA", "One")
e2 = _FakeAgentExec("agentB", "Two")
async def summarize(results: list[AgentExecutorResponse]) -> str:
texts: list[str] = []
for r in results:
msgs: list[Message] = r.agent_response.messages
texts.append(msgs[-1].text if msgs else "")
return " | ".join(sorted(texts))
wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(summarize).build()
completed = False
output: str | None = None
async for ev in wf.run("prompt: custom", stream=True):
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
completed = True
elif ev.type == "output":
output = cast(str, ev.data)
if completed and output is not None:
break
assert completed
assert output is not None
# Custom aggregator returns a string payload
assert isinstance(output, str)
assert output == "One | Two"
async def test_concurrent_custom_aggregator_sync_callback_is_used() -> None:
e1 = _FakeAgentExec("agentA", "One")
e2 = _FakeAgentExec("agentB", "Two")
# Sync callback with ctx parameter (should run via asyncio.to_thread)
def summarize_sync(results: list[AgentExecutorResponse], _ctx: WorkflowContext[Any]) -> str: # type: ignore[unused-argument]
texts: list[str] = []
for r in results:
msgs: list[Message] = r.agent_response.messages
texts.append(msgs[-1].text if msgs else "")
return " | ".join(sorted(texts))
wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(summarize_sync).build()
completed = False
output: str | None = None
async for ev in wf.run("prompt: custom sync", stream=True):
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
completed = True
elif ev.type == "output":
output = cast(str, ev.data)
if completed and output is not None:
break
assert completed
assert output is not None
assert isinstance(output, str)
assert output == "One | Two"
def test_concurrent_custom_aggregator_uses_callback_name_for_id() -> None:
e1 = _FakeAgentExec("agentA", "One")
e2 = _FakeAgentExec("agentB", "Two")
def summarize(results: list[AgentExecutorResponse]) -> str: # type: ignore[override]
return str(len(results))
wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(summarize).build()
assert "summarize" in wf.executors
aggregator = wf.executors["summarize"]
assert aggregator.id == "summarize"
async def test_concurrent_with_aggregator_executor_instance() -> None:
"""Test with_aggregator using an Executor instance (not factory)."""
class CustomAggregator(Executor):
@handler
async def aggregate(self, results: list[AgentExecutorResponse], ctx: WorkflowContext[Never, str]) -> None:
texts: list[str] = []
for r in results:
msgs: list[Message] = r.agent_response.messages
texts.append(msgs[-1].text if msgs else "")
await ctx.yield_output(" & ".join(sorted(texts)))
e1 = _FakeAgentExec("agentA", "One")
e2 = _FakeAgentExec("agentB", "Two")
aggregator_instance = CustomAggregator(id="instance_aggregator")
wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(aggregator_instance).build()
completed = False
output: str | None = None
async for ev in wf.run("prompt: instance test", stream=True):
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
completed = True
elif ev.type == "output":
output = cast(str, ev.data)
if completed and output is not None:
break
assert completed
assert output is not None
assert isinstance(output, str)
assert output == "One & Two"
def test_concurrent_builder_rejects_multiple_calls_to_with_aggregator() -> None:
"""Test that multiple calls to .with_aggregator() raises an error."""
def summarize(results: list[AgentExecutorResponse]) -> str: # type: ignore[override]
return str(len(results))
with pytest.raises(ValueError, match=r"with_aggregator\(\) has already been called"):
(
ConcurrentBuilder(participants=[_FakeAgentExec("a", "A")])
.with_aggregator(summarize)
.with_aggregator(summarize)
)
async def test_concurrent_checkpoint_resume_round_trip() -> None:
storage = InMemoryCheckpointStorage()
participants = (
_FakeAgentExec("agentA", "Alpha"),
_FakeAgentExec("agentB", "Beta"),
_FakeAgentExec("agentC", "Gamma"),
)
wf = ConcurrentBuilder(participants=list(participants), checkpoint_storage=storage).build()
baseline_output: AgentResponse | None = None
async for ev in wf.run("checkpoint concurrent", stream=True):
if ev.type == "output":
baseline_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
break
assert baseline_output is not None
checkpoints = await storage.list_checkpoints(workflow_name=wf.name)
assert checkpoints
checkpoints.sort(key=lambda cp: cp.timestamp)
resume_checkpoint = checkpoints[1]
resumed_participants = (
_FakeAgentExec("agentA", "Alpha"),
_FakeAgentExec("agentB", "Beta"),
_FakeAgentExec("agentC", "Gamma"),
)
wf_resume = ConcurrentBuilder(participants=list(resumed_participants), checkpoint_storage=storage).build()
resumed_output: AgentResponse | None = None
async for ev in wf_resume.run(checkpoint_id=resume_checkpoint.checkpoint_id, stream=True):
if ev.type == "output":
resumed_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state in (
WorkflowRunState.IDLE,
WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
):
break
assert resumed_output is not None
assert [m.role for m in resumed_output.messages] == [m.role for m in baseline_output.messages]
assert [m.text for m in resumed_output.messages] == [m.text for m in baseline_output.messages]
async def test_concurrent_checkpoint_runtime_only() -> None:
"""Test checkpointing configured ONLY at runtime, not at build time."""
storage = InMemoryCheckpointStorage()
agents = [_FakeAgentExec(id="agent1", reply_text="A1"), _FakeAgentExec(id="agent2", reply_text="A2")]
wf = ConcurrentBuilder(participants=agents).build()
baseline_output: AgentResponse | None = None
async for ev in wf.run("runtime checkpoint test", checkpoint_storage=storage, stream=True):
if ev.type == "output":
baseline_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
break
assert baseline_output is not None
checkpoints = await storage.list_checkpoints(workflow_name=wf.name)
assert len(checkpoints) >= 2, (
"Expected at least 2 checkpoints. The first one is after the start executor, "
"and the second one is after the first round of agent executions."
)
checkpoints.sort(key=lambda cp: cp.timestamp)
resume_checkpoint = checkpoints[1]
resumed_agents = [_FakeAgentExec(id="agent1", reply_text="A1"), _FakeAgentExec(id="agent2", reply_text="A2")]
wf_resume = ConcurrentBuilder(participants=resumed_agents).build()
resumed_output: AgentResponse | None = None
async for ev in wf_resume.run(
checkpoint_id=resume_checkpoint.checkpoint_id, checkpoint_storage=storage, stream=True
):
if ev.type == "output":
resumed_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state in (
WorkflowRunState.IDLE,
WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
):
break
assert resumed_output is not None
assert [m.role for m in resumed_output.messages] == [m.role for m in baseline_output.messages]
async def test_concurrent_checkpoint_runtime_overrides_buildtime() -> None:
"""Test that runtime checkpoint storage overrides build-time configuration."""
import tempfile
with tempfile.TemporaryDirectory() as temp_dir1, tempfile.TemporaryDirectory() as temp_dir2:
from agent_framework._workflows._checkpoint import FileCheckpointStorage
buildtime_storage = FileCheckpointStorage(temp_dir1)
runtime_storage = FileCheckpointStorage(temp_dir2)
agents = [_FakeAgentExec(id="agent1", reply_text="A1"), _FakeAgentExec(id="agent2", reply_text="A2")]
wf = ConcurrentBuilder(participants=agents, checkpoint_storage=buildtime_storage).build()
baseline_output: list[Message] | None = None
async for ev in wf.run("override test", checkpoint_storage=runtime_storage, stream=True):
if ev.type == "output":
baseline_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
break
assert baseline_output is not None
buildtime_checkpoints = await buildtime_storage.list_checkpoints(workflow_name=wf.name)
runtime_checkpoints = await runtime_storage.list_checkpoints(workflow_name=wf.name)
assert len(runtime_checkpoints) > 0, "Runtime storage should have checkpoints"
assert len(buildtime_checkpoints) == 0, "Build-time storage should have no checkpoints when overridden"
async def test_concurrent_builder_reusable_after_build_with_participants() -> None:
"""Test that the builder can be reused to build multiple identical workflows with participants()."""
e1 = _FakeAgentExec("agentA", "One")
e2 = _FakeAgentExec("agentB", "Two")
builder = ConcurrentBuilder(participants=[e1, e2])
builder.build()
assert builder._participants[0] is e1 # type: ignore
assert builder._participants[1] is e2 # type: ignore
class _EchoAgent(BaseAgent):
"""Simple agent that appends a single assistant message with its name."""
@overload
def run(
self,
messages: AgentRunInputs | None = ...,
*,
stream: Literal[False] = ...,
session: AgentSession | None = ...,
**kwargs: Any,
) -> Awaitable[AgentResponse[Any]]: ...
@overload
def run(
self,
messages: AgentRunInputs | None = ...,
*,
stream: Literal[True],
session: AgentSession | None = ...,
**kwargs: Any,
) -> ResponseStream[AgentResponseUpdate, AgentResponse[Any]]: ...
def run(
self,
messages: AgentRunInputs | None = None,
*,
stream: bool = False,
session: AgentSession | None = None,
**kwargs: Any,
) -> Awaitable[AgentResponse[Any]] | ResponseStream[AgentResponseUpdate, AgentResponse[Any]]:
if stream:
async def _stream() -> AsyncIterable[AgentResponseUpdate]:
yield AgentResponseUpdate(contents=[Content.from_text(text=f"{self.name} reply")])
return ResponseStream(_stream(), finalizer=AgentResponse.from_updates)
async def _run() -> AgentResponse:
return AgentResponse(messages=[Message("assistant", [f"{self.name} reply"])])
return _run()