From c5e6a7797f3ef024aee8d43823cf911d428c9385 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Fri, 5 Jun 2026 16:29:19 -0700 Subject: [PATCH 01/13] Move runner state management out of Workflow --- .../agent_framework/_workflows/_runner.py | 62 +++++++- .../agent_framework/_workflows/_workflow.py | 121 +++++++------- .../core/tests/workflow/test_runner.py | 150 +++++++++++++++--- .../core/tests/workflow/test_workflow.py | 13 +- 4 files changed, 251 insertions(+), 95 deletions(-) diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index 51a3312e2ba..3e1b1f3b509 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -5,6 +5,7 @@ import logging from collections import defaultdict from collections.abc import AsyncGenerator, Sequence +from enum import Enum from typing import Any from ..exceptions import ( @@ -27,6 +28,25 @@ logger = logging.getLogger(__name__) +class _RunnerLifecycle(Enum): + """Lifecycle of a single :class:`Runner` invocation. + + Three states keep concurrent-run protection in one place while still letting + :meth:`Workflow.run` reserve the runner synchronously (before any await): + + * ``IDLE`` - no run in progress. + * ``RESERVED`` - :meth:`Runner.reserve` was called by an external caller but + :meth:`Runner.run_until_convergence` has not yet entered its body. This is the + window during which ``Workflow.run`` has handed back a ``ResponseStream`` that + hasn't been iterated yet. ``run_until_convergence`` requires this state. + * ``RUNNING`` - the body of :meth:`Runner.run_until_convergence` is executing. + """ + + IDLE = "idle" + RESERVED = "reserved" + RUNNING = "running" + + class Runner: """A class to run a workflow in Pregel supersteps.""" @@ -63,7 +83,7 @@ def __init__( self._iteration = 0 self._max_iterations = max_iterations self._state = state - self._running = False + self._lifecycle: _RunnerLifecycle = _RunnerLifecycle.IDLE self._resumed_from_checkpoint = False # Track whether we resumed @property @@ -71,16 +91,48 @@ def context(self) -> RunnerContext: """Get the workflow context.""" return self._ctx + def reserve(self) -> None: + """Synchronously reserve the runner for an upcoming run. + + This is the **only** way to acquire the run lock. :meth:`run_until_convergence` + requires the runner to be in :attr:`_RunnerLifecycle.RESERVED` and will refuse + to start otherwise. Reserving synchronously lets callers (notably + :meth:`Workflow.run`) reject concurrent runs *before* any ``await`` or + async-generator suspension - otherwise a second caller could slip past a + flag-based guard while the first is still suspended above + :meth:`run_until_convergence`. The lock is released by + :meth:`run_until_convergence` in its ``finally`` clause once it begins, or by + :meth:`release` when the run never starts (for example, if early validation + raises before ``run_until_convergence`` is reached). + + Raises: + WorkflowRunnerException: If the runner is already reserved or running. + """ + if self._lifecycle is not _RunnerLifecycle.IDLE: + raise WorkflowRunnerException("Runner is already running.") + self._lifecycle = _RunnerLifecycle.RESERVED + + def release(self) -> None: + """Release the runner's run lock. Idempotent; safe to call when already idle.""" + self._lifecycle = _RunnerLifecycle.IDLE + def reset_iteration_count(self) -> None: """Reset the iteration count to zero.""" self._iteration = 0 async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: """Run the workflow until no more messages are sent.""" - if self._running: - raise WorkflowRunnerException("Runner is already running.") + # Mandatory reservation: callers must reserve() the runner first. This makes + # ``reserve`` the single entry point that takes the run lock, so all + # concurrent-run rejection happens there. Any non-RESERVED state here is a + # contract violation - either the caller forgot to reserve, or another run + # is already in progress. + if self._lifecycle is not _RunnerLifecycle.RESERVED: + raise WorkflowRunnerException( + "Runner must be reserved via Runner.reserve() before calling run_until_convergence()." + ) + self._lifecycle = _RunnerLifecycle.RUNNING - self._running = True previous_checkpoint_id: CheckpointID | None = None try: # Emit any events already produced prior to entering loop @@ -155,7 +207,7 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: logger.info(f"Workflow completed after {self._iteration} supersteps") self._resumed_from_checkpoint = False # Reset resume flag for next run finally: - self._running = False + self._lifecycle = _RunnerLifecycle.IDLE async def _run_iteration(self) -> None: """Run a single iteration of the workflow. diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index c4840bb0455..780669272d6 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -17,6 +17,7 @@ from .._sessions import ContextProvider from .._types import ResponseStream +from ..exceptions import WorkflowException, WorkflowRunnerException from ..observability import OtelAttr, capture_exception, create_workflow_span from ._checkpoint import CheckpointStorage from ._const import DEFAULT_MAX_ITERATIONS, GLOBAL_KWARGS_KEY, WORKFLOW_RUN_KWARGS_KEY @@ -357,9 +358,6 @@ def __init__( max_iterations=max_iterations, ) - # Flag to prevent concurrent workflow executions - self._is_running = False - # Current run-level status of this workflow instance. Updated in lockstep with # the status events emitted from `_run_workflow_with_tracing`. Defaults to IDLE # for a freshly built workflow that has not yet been run. @@ -376,16 +374,6 @@ def status(self) -> WorkflowRunState: """ return self._status - def _ensure_not_running(self) -> None: - """Ensure the workflow is not already running.""" - if self._is_running: - raise RuntimeError("Workflow is already running. Concurrent executions are not allowed.") - self._is_running = True - - def _reset_running_flag(self) -> None: - """Reset the running flag.""" - self._is_running = False - def to_dict(self) -> dict[str, Any]: """Serialize the workflow definition into a JSON-ready dictionary.""" data: dict[str, Any] = { @@ -745,9 +733,19 @@ def run( Raises: ValueError: If parameter combination is invalid. """ - # Validate parameters and set running flag eagerly (before any async work) + # Validate parameters first so misuse fails before we touch any run state. self._validate_run_params(message, responses, checkpoint_id) - self._ensure_not_running() + + # Acquire the run lock synchronously - before constructing the ResponseStream + # or yielding control to the event loop - so a second concurrent ``run`` call + # is rejected immediately rather than slipping past the guard while the first + # call is suspended inside its async generator. + try: + self._runner.reserve() + except WorkflowRunnerException as exc: + raise WorkflowException( + "Workflow is already running; concurrent runs are not allowed on the same instance." + ) from exc response_stream = ResponseStream[WorkflowEvent, WorkflowRunResult]( self._run_core( @@ -760,9 +758,6 @@ def run( client_kwargs=client_kwargs, ), finalizer=functools.partial(self._finalize_events, include_status_events=include_status_events), - cleanup_hooks=[ - functools.partial(self._run_cleanup, checkpoint_storage), - ], ) if stream: @@ -789,51 +784,55 @@ async def _run_core( if checkpoint_storage is not None: self._runner.context.set_runtime_checkpoint_storage(checkpoint_storage) - # Async validation: a fresh-message run is only allowed when the - # runner context has fully drained from any prior run. If it still - # has in-flight executor messages, the prior run didn't complete - - # the caller must either resume from a checkpoint or wait for the - # prior run to drain. (Pending request_info events are intentionally - # NOT blocked here: a follow-up run with message=... is the normal - # way to deliver a response to those pending requests, e.g. via - # WorkflowAgent._process_pending_requests.) - # NOTE: _validate_run_params already enforces that ``message`` is - # mutually exclusive with both ``checkpoint_id`` and ``responses``, - # so we don't need to re-check those here. - if message is not None and await self._runner.context.has_messages(): - raise RuntimeError( - "Cannot start a new run with 'message' while in-flight executor " - "messages remain from a prior run. Resume from a checkpoint " - "(checkpoint_id=...) or wait for the prior run to complete. " - "Workflows that need to recover from a mid-run failure must use " - "checkpointing; there is no in-process recovery path." - ) + try: + # Async validation: a fresh-message run is only allowed when the + # runner context has fully drained from any prior run. If it still + # has in-flight executor messages, the prior run didn't complete - + # the caller must either resume from a checkpoint or wait for the + # prior run to drain. (Pending request_info events are intentionally + # NOT blocked here: a follow-up run with message=... is the normal + # way to deliver a response to those pending requests, e.g. via + # WorkflowAgent._process_pending_requests.) + # NOTE: _validate_run_params already enforces that ``message`` is + # mutually exclusive with both ``checkpoint_id`` and ``responses``, + # so we don't need to re-check those here. + if message is not None and await self._runner.context.has_messages(): + raise RuntimeError( + "Cannot start a new run with 'message' while in-flight executor " + "messages remain from a prior run. Resume from a checkpoint " + "(checkpoint_id=...) or wait for the prior run to complete. " + "Workflows that need to recover from a mid-run failure must use " + "checkpointing; there is no in-process recovery path." + ) - initial_executor_fn = self._resolve_execution_mode(message, responses, checkpoint_id, checkpoint_storage) - - async for event in self._run_workflow_with_tracing( - initial_executor_fn=initial_executor_fn, - is_continuation=(message is None), - streaming=streaming, - function_invocation_kwargs=function_invocation_kwargs, - client_kwargs=client_kwargs, - ): - if event.type == "request_info" and event.request_id in (responses or {}): - # Don't yield request_info events for which we have responses to send - - # these are considered "handled". This prevents the caller from seeing - # events for requests they are already responding to. - # This usually happens when responses are provided with a checkpoint - # (restore then send), because the request_info events are stored in the - # checkpoint and would be emitted on restoration by the runner regardless - # of if a response is provided or not. - continue - yield event + initial_executor_fn = self._resolve_execution_mode(message, responses, checkpoint_id, checkpoint_storage) - async def _run_cleanup(self, checkpoint_storage: CheckpointStorage | None) -> None: - """Cleanup hook called after stream consumption.""" - if checkpoint_storage is not None: - self._runner.context.clear_runtime_checkpoint_storage() - self._reset_running_flag() + async for event in self._run_workflow_with_tracing( + initial_executor_fn=initial_executor_fn, + is_continuation=(message is None), + streaming=streaming, + function_invocation_kwargs=function_invocation_kwargs, + client_kwargs=client_kwargs, + ): + if event.type == "request_info" and event.request_id in (responses or {}): + # Don't yield request_info events for which we have responses to send - + # these are considered "handled". This prevents the caller from seeing + # events for requests they are already responding to. + # This usually happens when responses are provided with a checkpoint + # (restore then send), because the request_info events are stored in the + # checkpoint and would be emitted on restoration by the runner regardless + # of if a response is provided or not. + continue + yield event + finally: + # Release the run lock acquired synchronously by ``run()`` via ``reserve``. + # ``run_until_convergence`` also clears it in its own ``finally`` once its + # body runs; this clause additionally covers the case where this generator + # raises (or is closed) before that body is reached - e.g. the in-flight + # messages check above. ``release`` is idempotent. + self._runner.release() + if checkpoint_storage is not None: + self._runner.context.clear_runtime_checkpoint_storage() @staticmethod def _finalize_events( diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index 4fef26bd2d2..6756bb9a9f2 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -106,6 +106,7 @@ async def test_runner_run_until_convergence(): state, # state ctx, # runner_context ) + runner.reserve() async for event in runner.run_until_convergence(): assert isinstance(event, WorkflowEvent) if event.type == "output": @@ -147,6 +148,7 @@ async def test_runner_run_until_convergence_not_completed(): WorkflowConvergenceException, match="Runner did not converge after 5 iterations.", ): + runner.reserve() async for event in runner.run_until_convergence(): assert event.type != "status" or event.state != WorkflowRunState.IDLE @@ -305,40 +307,137 @@ async def handle(self, message: MockMessage, ctx: WorkflowContext[MockMessage, i assert probe_target.call_count == 1 -async def test_runner_already_running(): - """Test that running the runner while it is already running raises an error.""" +async def test_runner_run_until_convergence_requires_reservation(): + """run_until_convergence refuses to start without a prior reserve().""" + runner = _make_runner() + with pytest.raises(WorkflowRunnerException, match="Runner must be reserved"): + async for _ in runner.run_until_convergence(): + pass + + +def _make_runner() -> Runner: + """Build a minimal runner for lifecycle tests.""" + return Runner( + [], + {}, + State(), + InProcRunnerContext(), + "test_name", + graph_signature_hash="test_hash", + ) + + +def test_runner_reserve_twice_raises(): + """Calling reserve() while already reserved rejects the second caller. + + This is what guards Workflow.run against a concurrent caller slipping in + between the first call's synchronous reserve() and its first await. + """ + runner = _make_runner() + runner.reserve() + with pytest.raises(WorkflowRunnerException, match="Runner is already running."): + runner.reserve() + + +def test_runner_reserve_after_release_is_accepted(): + """Sequential runs are permitted; only concurrent ones are blocked.""" + runner = _make_runner() + runner.reserve() + runner.release() + runner.reserve() # should not raise + + +def test_runner_release_when_idle_is_noop(): + """release() on an idle runner does not affect a subsequent reserve(). + + Workflow._run_core's finally always calls release(), even when + run_until_convergence already cleared the lock in its own finally; + that double-release must not lock out the next run. + """ + runner = _make_runner() + runner.release() # already idle - must not raise or wedge state + runner.reserve() # next run still allowed + + +async def test_runner_run_until_convergence_consumes_reservation(): + """run_until_convergence accepts a prior reservation and runs to completion.""" + runner = _make_runner() + runner.reserve() + async for _ in runner.run_until_convergence(): + pass + # A second run after the first completes must be accepted. + runner.reserve() + async for _ in runner.run_until_convergence(): + pass + + +async def test_runner_accepts_new_run_after_previous_failure(): + """A failed run must not leave the runner locked out of future runs. + + After the first run raises, a fresh ``reserve()`` and + ``run_until_convergence()`` must succeed (or fail for a different reason - + e.g. residual messages still don't converge - but never with the + lock-rejection ``"Runner is already running."``). + """ executor_a = MockExecutor(id="executor_a") executor_b = MockExecutor(id="executor_b") - - # Create a loop edges = [ SingleEdgeGroup(executor_a.id, executor_b.id), SingleEdgeGroup(executor_b.id, executor_a.id), ] - - executors: dict[str, Executor] = { - executor_a.id: executor_a, - executor_b.id: executor_b, - } + executors: dict[str, Executor] = {executor_a.id: executor_a, executor_b.id: executor_b} state = State() ctx = InProcRunnerContext() + runner = Runner(edges, executors, state, ctx, "test_name", graph_signature_hash="test_hash", max_iterations=2) - runner = Runner(edges, executors, state, ctx, "test_name", graph_signature_hash="test_hash") + await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) - await executor_a.execute( - MockMessage(data=0), - ["START"], # source_executor_ids - state, # state - ctx, # runner_context - ) + runner.reserve() + with pytest.raises(WorkflowConvergenceException): + async for _ in runner.run_until_convergence(): + pass - with pytest.raises(WorkflowRunnerException, match="Runner is already running."): + # The runner should accept a fresh reservation and run again. + runner.reserve() # must not raise + try: + async for _ in runner.run_until_convergence(): + pass + except Exception as exc: + assert "Runner is already running" not in str(exc), "Runner stayed locked after a failed run" - async def _run(): - async for _ in runner.run_until_convergence(): - pass - await asyncio.gather(_run(), _run()) +async def test_runner_rejects_concurrent_run_until_convergence(): + """While a run is in progress, a second ``reserve()`` is rejected. + + Confirms the run lock is held for the full duration of the run, not just + synchronously between ``reserve()`` and the first ``__anext__`` call. + """ + runner = _make_runner() + + started = asyncio.Event() + release = asyncio.Event() + + async def _slow_run(): + runner.reserve() + async for _ in runner.run_until_convergence(): + if not started.is_set(): + started.set() + await release.wait() + + task = asyncio.create_task(_slow_run()) + await started.wait() # first run is now executing + + try: + with pytest.raises(WorkflowRunnerException, match="Runner is already running."): + runner.reserve() + finally: + release.set() + await task + + # And after the first run finishes, a new reservation + run must be accepted. + runner.reserve() + async for _ in runner.run_until_convergence(): + pass async def test_runner_emits_runner_completion_for_agent_response_without_targets(): @@ -352,6 +451,7 @@ async def test_runner_emits_runner_completion_for_agent_response_without_targets ) ) + runner.reserve() events: list[WorkflowEvent] = [event async for event in runner.run_until_convergence()] # The runner should complete without errors when handling AgentExecutorResponse without targets # No specific events are expected since there are no executors to process the message @@ -408,6 +508,7 @@ async def run_workflow(): async for _ in runner.run_until_convergence(): pass + runner.reserve() task = asyncio.create_task(run_workflow()) # Wait for executor_a to complete (0.3s) and executor_b to start but not finish @@ -469,6 +570,7 @@ async def test_runner_iteration_exception_drains_events(): ) events: list[WorkflowEvent] = [] + runner.reserve() with pytest.raises(RuntimeError, match="Simulated executor failure"): async for event in runner.run_until_convergence(): events.append(event) @@ -579,6 +681,7 @@ async def test_runner_checkpoint_creation_failure(): # Should complete without raising, even though checkpointing fails result: int | None = None + runner.reserve() async for event in runner.run_until_convergence(): if event.type == "output": result = event.data @@ -775,6 +878,7 @@ async def test_runner_with_pre_loop_events(): await ctx.add_event(WorkflowEvent("output", executor_id="test_executor", data="pre-loop-output")) events: list[WorkflowEvent] = [] + runner.reserve() async for event in runner.run_until_convergence(): events.append(event) @@ -822,6 +926,7 @@ async def test_runner_drains_straggler_events(): ) events: list[WorkflowEvent] = [] + runner.reserve() async for event in runner.run_until_convergence(): events.append(event) @@ -875,6 +980,7 @@ async def test_runner_checkpoint_with_resumed_flag(): ) # Run until convergence + runner.reserve() async for _ in runner.run_until_convergence(): pass @@ -941,6 +1047,7 @@ async def test_runner_drains_events_on_iteration_exception(): ) events: list[WorkflowEvent] = [] + runner.reserve() with pytest.raises(RuntimeError, match="Executor failed with pending events"): async for event in runner.run_until_convergence(): events.append(event) @@ -997,6 +1104,7 @@ async def test_runner_drains_straggler_events_at_iteration_end(): ) events: list[WorkflowEvent] = [] + runner.reserve() async for event in runner.run_until_convergence(): events.append(event) diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index 27f24d26f9c..1c77ae003bc 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -26,6 +26,7 @@ WorkflowContext, WorkflowConvergenceException, WorkflowEvent, + WorkflowException, WorkflowMessage, WorkflowRunState, handler, @@ -759,8 +760,7 @@ async def run_workflow(): # Try to start a second concurrent execution - this should fail with pytest.raises( - RuntimeError, - match="Workflow is already running. Concurrent executions are not allowed.", + WorkflowException, match="Workflow is already running; concurrent runs are not allowed on the same instance." ): await workflow.run(NumberMessage(data=0)) @@ -795,8 +795,7 @@ async def consume_stream_slowly(): # Try to start a second concurrent execution - this should fail with pytest.raises( - RuntimeError, - match="Workflow is already running. Concurrent executions are not allowed.", + WorkflowException, match="Workflow is already running; concurrent runs are not allowed on the same instance." ): await workflow.run(NumberMessage(data=0)) @@ -828,14 +827,12 @@ async def consume_stream(): # Try different execution methods - all should fail with pytest.raises( - RuntimeError, - match="Workflow is already running. Concurrent executions are not allowed.", + WorkflowException, match="Workflow is already running; concurrent runs are not allowed on the same instance." ): await workflow.run(NumberMessage(data=0)) with pytest.raises( - RuntimeError, - match="Workflow is already running. Concurrent executions are not allowed.", + WorkflowException, match="Workflow is already running; concurrent runs are not allowed on the same instance." ): async for _ in workflow.run(NumberMessage(data=0), stream=True): break From 65522bdbee48b34e221697dfd58a6a91551a2aaa Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Mon, 8 Jun 2026 13:42:42 -0700 Subject: [PATCH 02/13] Add reset to workflow --- python/packages/core/agent_framework/_mcp.py | 23 +- .../packages/core/agent_framework/_skills.py | 10 +- .../_workflows/_agent_executor.py | 37 +- .../agent_framework/_workflows/_executor.py | 8 + .../agent_framework/_workflows/_runner.py | 40 +- .../agent_framework/_workflows/_workflow.py | 31 +- .../_workflows/_workflow_executor.py | 13 + .../core/tests/core/test_mcp_observability.py | 4 +- .../core/tests/core/test_mcp_skills.py | 190 +- .../tests/workflow/test_agent_executor.py | 105 +- .../core/tests/workflow/test_executor.py | 50 + .../core/tests/workflow/test_runner.py | 252 + .../core/tests/workflow/test_sub_workflow.py | 86 + .../core/tests/workflow/test_workflow.py | 142 + .../_base_group_chat_orchestrator.py | 22 + .../_group_chat.py | 20 + .../_magentic.py | 8 + .../orchestrations/tests/test_group_chat.py | 136 + python/uv.lock | 8049 ++++++++--------- 19 files changed, 5038 insertions(+), 4188 deletions(-) diff --git a/python/packages/core/agent_framework/_mcp.py b/python/packages/core/agent_framework/_mcp.py index 8c2bdaefacc..19e56a16b9d 100644 --- a/python/packages/core/agent_framework/_mcp.py +++ b/python/packages/core/agent_framework/_mcp.py @@ -1643,9 +1643,7 @@ async def call_tool_as_task(self, tool_name: str, **kwargs: Any) -> str | list[C return parser(fallback_result) if task_id is None: - raise ToolExecutionException( - f"MCP server did not return a task_id or fallback result for '{tool_name}'." - ) + raise ToolExecutionException(f"MCP server did not return a task_id or fallback result for '{tool_name}'.") # Track to completion: poll until terminal, then fetch payload. Never re-issue # tools/call past this point; reconnect-and-retry only against the same task_id. @@ -1765,9 +1763,7 @@ async def _poll_task_until_terminal(self, task_id: str) -> types.GetTaskResult: transient_codes: frozenset[int] = frozenset({int(httpx.codes.REQUEST_TIMEOUT)}) while True: - request = types.ClientRequest( - types.GetTaskRequest(params=types.GetTaskRequestParams(taskId=task_id)) - ) + request = types.ClientRequest(types.GetTaskRequest(params=types.GetTaskRequestParams(taskId=task_id))) try: # GetTaskResult.ttl is required-but-Optional in the SDK; coerce below. lenient = await self._send_with_one_reconnect( @@ -1775,9 +1771,7 @@ async def _poll_task_until_terminal(self, task_id: str) -> types.GetTaskResult: ) except McpError as ex: if ex.error.code in transient_codes: - logger.debug( - "Transient %s on tasks/get for '%s'; will retry.", ex.error.code, task_id - ) + logger.debug("Transient %s on tasks/get for '%s'; will retry.", ex.error.code, task_id) await asyncio.sleep(_MCP_TASK_MIN_POLL_INTERVAL.total_seconds()) continue # Hard server error mid-poll: task may still be running. @@ -1906,9 +1900,7 @@ async def _send_with_one_reconnect( if not self._is_connection_lost(ex): raise if attempt < _MCP_RECONNECT_ATTEMPTS - 1: - logger.info( - "MCP connection lost during %s; reconnecting (task_id=%s).", operation, task_id - ) + logger.info("MCP connection lost during %s; reconnecting (task_id=%s).", operation, task_id) try: await self.connect(reset=True) except Exception as reconn_ex: @@ -1967,9 +1959,7 @@ async def _try_cancel_task(self, task_id: str) -> None: """ from mcp import types - request = types.ClientRequest( - types.CancelTaskRequest(params=types.CancelTaskRequestParams(taskId=task_id)) - ) + request = types.ClientRequest(types.CancelTaskRequest(params=types.CancelTaskRequestParams(taskId=task_id))) try: await asyncio.wait_for( self.session.send_request(request, types.CancelTaskResult), # type: ignore[union-attr] @@ -1979,8 +1969,7 @@ async def _try_cancel_task(self, task_id: str) -> None: raise except asyncio.TimeoutError: logger.warning( - "Best-effort tasks/cancel for '%s' timed out after %.1fs; " - "remote task may still be running.", + "Best-effort tasks/cancel for '%s' timed out after %.1fs; remote task may still be running.", task_id, _MCP_TASK_CANCEL_TIMEOUT.total_seconds(), ) diff --git a/python/packages/core/agent_framework/_skills.py b/python/packages/core/agent_framework/_skills.py index 97afe66cea9..91bdb619143 100644 --- a/python/packages/core/agent_framework/_skills.py +++ b/python/packages/core/agent_framework/_skills.py @@ -3516,9 +3516,7 @@ async def get_content(self) -> str: result = await self._client.read_resource(_mcp_any_url(self._skill_md_uri)) text = _mcp_join_text(result) if not text: - raise ValueError( - f"The MCP server returned no text content for SKILL.md resource '{self._skill_md_uri}'." - ) + raise ValueError(f"The MCP server returned no text content for SKILL.md resource '{self._skill_md_uri}'.") self._content = text return text @@ -3572,11 +3570,7 @@ def _validate_resource_name(name: str) -> str | None: or ``None`` if the name is unsafe. """ normalized = name.replace("\\", "/") - if ( - normalized.startswith("/") - or "://" in normalized - or any(seg == ".." for seg in normalized.split("/")) - ): + if normalized.startswith("/") or "://" in normalized or any(seg == ".." for seg in normalized.split("/")): logger.debug("Rejecting resource name with unsafe path components: %r", name) return None return normalized diff --git a/python/packages/core/agent_framework/_workflows/_agent_executor.py b/python/packages/core/agent_framework/_workflows/_agent_executor.py index d96929ce793..fb4cb62a541 100644 --- a/python/packages/core/agent_framework/_workflows/_agent_executor.py +++ b/python/packages/core/agent_framework/_workflows/_agent_executor.py @@ -166,6 +166,10 @@ def __init__( raise ValueError("Agent must have a non-empty name or id or an explicit id must be provided.") super().__init__(exec_id) self._agent = agent + # Track whether the caller supplied a session so reset() can preserve their + # session reference (which may be wired to external/service-side storage) + # and only replace sessions we created ourselves. + self._session_supplied_by_caller = session is not None self._session = session or self._agent.create_session() self._pending_agent_requests: dict[str, Content] = {} @@ -365,10 +369,37 @@ async def on_checkpoint_restore(self, state: dict[str, Any]) -> None: pending_responses_payload = state.get("pending_responses_to_agent") self._pending_responses_to_agent = pending_responses_payload or [] - def reset(self) -> None: - """Reset the internal cache of the executor.""" - logger.debug("AgentExecutor %s: Resetting cache", self.id) + @override + async def reset(self) -> None: + """Reset the executor to its initial state for a new workflow run. + + Clears the message cache, full conversation snapshot, and any pending + user-input request/response bookkeeping. + + Session handling: + * If the session was created by this executor (no ``session`` argument + was passed to ``__init__``), it is replaced with a fresh one via + ``agent.create_session()`` so prior conversation history does not + leak into the next run. + * If the session was supplied by the caller, it is left untouched. + The caller owns the session lifecycle (it may be backed by + service-side or external storage) and is responsible for clearing + or rotating it if a clean slate is desired. + """ + logger.debug("AgentExecutor %s: Resetting state", self.id) self._cache.clear() + self._full_conversation.clear() + self._pending_agent_requests.clear() + self._pending_responses_to_agent.clear() + if not self._session_supplied_by_caller: + self._session = self._agent.create_session() + else: + logger.warning( + "AgentExecutor %s: Session was supplied by the caller and will not be reset. " + "Prior conversation history retained in the session may leak into the next run. " + "Reset or rotate the session externally if a clean slate is required.", + self.id, + ) async def _run_agent_and_emit( self, diff --git a/python/packages/core/agent_framework/_workflows/_executor.py b/python/packages/core/agent_framework/_workflows/_executor.py index f57102b2bce..d562a925b24 100644 --- a/python/packages/core/agent_framework/_workflows/_executor.py +++ b/python/packages/core/agent_framework/_workflows/_executor.py @@ -516,6 +516,14 @@ async def on_checkpoint_restore(self, state: dict[str, Any]) -> None: """ ... + async def reset(self) -> None: + """Reset the executor to its initial state. + + Override this method in subclasses to implement custom logic that should + run when the workflow is reset. + """ + ... + # endregion: Executor diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index 3e1b1f3b509..efe9bcaead4 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -88,9 +88,14 @@ def __init__( @property def context(self) -> RunnerContext: - """Get the workflow context.""" + """Get the runner context for message, event, and checkpoint handling.""" return self._ctx + @property + def state(self) -> State: + """Get the shared state for the workflow.""" + return self._state + def reserve(self) -> None: """Synchronously reserve the runner for an upcoming run. @@ -117,9 +122,38 @@ def release(self) -> None: self._lifecycle = _RunnerLifecycle.IDLE def reset_iteration_count(self) -> None: - """Reset the iteration count to zero.""" + """Reset the iteration count to zero. + + This is useful when the workflow resumes from a new set of messages. + + Note: + When a workflow is resumed from a response (for a request_info_event) + or a checkpoint, the iteration count is normally NOT reset. + """ self._iteration = 0 + async def reset_for_new_run(self) -> None: + """Reset the runner for a new run. + + This is useful when reusing the same workflow instance for a different run + that is independent from prior runs. + + Raises: + WorkflowRunnerException: If the runner is reserved or running. Reset is only + allowed when the runner is idle to avoid clobbering in-flight run state. + """ + if self._lifecycle is not _RunnerLifecycle.IDLE: + raise WorkflowRunnerException( + "Cannot reset the runner while a run is in progress. " + "Wait for the current run to complete before calling reset_for_new_run()." + ) + self.reset_iteration_count() + self._ctx.reset_for_new_run() + self._state.clear() + self._resumed_from_checkpoint = False + for executor in self._executors.values(): + await executor.reset() + async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: """Run the workflow until no more messages are sent.""" # Mandatory reservation: callers must reserve() the runner first. This makes @@ -294,7 +328,7 @@ async def restore_from_checkpoint( checkpoint_id: CheckpointID, checkpoint_storage: CheckpointStorage | None = None, ) -> None: - """Restore workflow state from a checkpoint. + """Restore the runner from a checkpoint. Args: checkpoint_id: The ID of the checkpoint to restore from diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 780669272d6..9135677cbab 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -347,11 +347,10 @@ def __init__( # Store non-serializable runtime objects as private attributes self._runner_context = runner_context self._runner_context.set_yield_output_classifier(self._output_designation.classify) - self._state = State() self._runner: Runner = Runner( self.edge_groups, self.executors, - self._state, + State(), runner_context, self.name, self.graph_signature_hash, @@ -552,14 +551,14 @@ async def _run_workflow_with_tracing( combined_kwargs["client_kwargs"] = self._resolve_invocation_kwargs( client_kwargs, "client_kwargs" ) - self._state.set(WORKFLOW_RUN_KWARGS_KEY, combined_kwargs) + self._runner.state.set(WORKFLOW_RUN_KWARGS_KEY, combined_kwargs) elif not is_continuation: - self._state.set(WORKFLOW_RUN_KWARGS_KEY, {}) - self._state.commit() # Commit immediately so kwargs are available + self._runner.state.set(WORKFLOW_RUN_KWARGS_KEY, {}) + self._runner.state.commit() # Commit immediately so kwargs are available # Set streaming mode (always set explicitly per run since # reset_for_new_run() no longer runs to clear it). - self._runner_context.set_streaming(streaming) + self._runner.context.set_streaming(streaming) # Execute initial setup if provided if initial_executor_fn: @@ -653,7 +652,7 @@ async def _execute_with_message_or_checkpoint( await executor.execute( message, [self.__class__.__name__], - self._state, + self._runner.state, self._runner.context, trace_contexts=None, source_span_ids=None, @@ -934,7 +933,7 @@ async def _restore_and_send_responses( async def _send_responses_internal(self, responses: Mapping[str, Any]) -> None: """Internal method to validate and send responses to the executors.""" - pending_requests = await self._runner_context.get_pending_request_info_events() + pending_requests = await self._runner.context.get_pending_request_info_events() if not pending_requests: raise RuntimeError("No pending requests found in workflow context.") @@ -954,7 +953,7 @@ async def _send_responses_internal(self, responses: Mapping[str, Any]) -> None: coerced_responses[request_id] = response await asyncio.gather(*[ - self._runner_context.send_request_info_response(request_id, response) + self._runner.context.send_request_info_response(request_id, response) for request_id, response in coerced_responses.items() ]) @@ -1150,3 +1149,17 @@ def as_agent( context_providers=context_providers, **kwargs, ) + + async def reset_for_new_run(self) -> None: + """Reset the workflow for a new run that is independent from prior runs. + + Note: + This will reset EVERYTHING - executor states, workflow state, and runner + context (including pending requests/messages). + + Raises: + WorkflowRunnerException: If a run is currently in progress. Reset is only + allowed when the workflow is idle to avoid clobbering in-flight run state. + + """ + await self._runner.reset_for_new_run() diff --git a/python/packages/core/agent_framework/_workflows/_workflow_executor.py b/python/packages/core/agent_framework/_workflows/_workflow_executor.py index e1315334293..7868651b474 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow_executor.py +++ b/python/packages/core/agent_framework/_workflows/_workflow_executor.py @@ -534,6 +534,19 @@ async def on_checkpoint_restore(self, state: dict[str, Any]) -> None: for event in request_info_events ]) + @override + async def reset(self) -> None: + """Reset the WorkflowExecutor to its initial state for a new workflow run. + + Clears in-flight execution contexts and the request-to-execution mapping, + then recursively resets the wrapped sub-workflow so its executors, runner + context, and shared state are also returned to a clean state. + """ + logger.debug("WorkflowExecutor %s: Resetting state", self.id) + self._execution_contexts.clear() + self._request_to_execution.clear() + await self.workflow.reset_for_new_run() + async def _process_workflow_result( self, result: WorkflowRunResult, diff --git a/python/packages/core/tests/core/test_mcp_observability.py b/python/packages/core/tests/core/test_mcp_observability.py index 226e9761205..8b17f3dc88c 100644 --- a/python/packages/core/tests/core/test_mcp_observability.py +++ b/python/packages/core/tests/core/test_mcp_observability.py @@ -281,9 +281,7 @@ async def test_mcp_prompts_get_creates_client_span(span_exporter: InMemorySpanEx async def test_mcp_prompts_get_mcp_error_sets_error_type(span_exporter: InMemorySpanExporter): """When session.get_prompt() raises McpError, the span should have error.type and ERROR status.""" tool = _make_connected_mcp_tool() - tool.session.get_prompt = AsyncMock( - side_effect=McpError(ErrorData(code=-32602, message="prompt not found")) - ) + tool.session.get_prompt = AsyncMock(side_effect=McpError(ErrorData(code=-32602, message="prompt not found"))) span_exporter.clear() with pytest.raises(ToolExecutionException): diff --git a/python/packages/core/tests/core/test_mcp_skills.py b/python/packages/core/tests/core/test_mcp_skills.py index 3e7c67662af..74993997d0e 100644 --- a/python/packages/core/tests/core/test_mcp_skills.py +++ b/python/packages/core/tests/core/test_mcp_skills.py @@ -35,26 +35,22 @@ Body content here. """ -SAMPLE_SKILL_INDEX = json.dumps( - { - "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", - "skills": [ - { - "name": "unit-converter", - "type": "skill-md", - "description": "Convert between common units.", - "url": "skill://unit-converter/SKILL.md", - } - ], - } -) +SAMPLE_SKILL_INDEX = json.dumps({ + "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", + "skills": [ + { + "name": "unit-converter", + "type": "skill-md", + "description": "Convert between common units.", + "url": "skill://unit-converter/SKILL.md", + } + ], +}) def _make_text_result(text: str, uri: str = "skill://test") -> ReadResourceResult: """Create a ReadResourceResult with a single TextResourceContents.""" - return ReadResourceResult( - contents=[TextResourceContents(uri=AnyUrl(uri), text=text, mimeType="text/markdown")] - ) + return ReadResourceResult(contents=[TextResourceContents(uri=AnyUrl(uri), text=text, mimeType="text/markdown")]) def _make_blob_result( @@ -230,12 +226,10 @@ async def test_get_content_raises_on_empty(self) -> None: @pytest.mark.asyncio async def test_get_resource_text(self) -> None: - client = _make_client( - **{ - "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), - "skill://unit-converter/references/checklist.md": _make_text_result("- check thing 1\n- check thing 2"), - } - ) + client = _make_client(**{ + "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), + "skill://unit-converter/references/checklist.md": _make_text_result("- check thing 1\n- check thing 2"), + }) from agent_framework import SkillFrontmatter fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.") @@ -249,12 +243,10 @@ async def test_get_resource_text(self) -> None: @pytest.mark.asyncio async def test_get_resource_binary(self) -> None: data = bytes([0x01, 0x02, 0x03, 0x04]) - client = _make_client( - **{ - "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), - "skill://unit-converter/assets/icon.bin": _make_blob_result(data), - } - ) + client = _make_client(**{ + "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), + "skill://unit-converter/assets/icon.bin": _make_blob_result(data), + }) from agent_framework import SkillFrontmatter fm = SkillFrontmatter(name="unit-converter", description="Convert between common units.") @@ -345,12 +337,10 @@ class TestMCPSkillsSource: @pytest.mark.asyncio async def test_index_based_discovery_returns_skill(self) -> None: - client = _make_client( - **{ - "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"), - "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), - } - ) + client = _make_client(**{ + "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"), + "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), + }) source = MCPSkillsSource(client=client) skills = await source.get_skills() @@ -373,9 +363,7 @@ async def test_no_index_returns_empty(self) -> None: async def test_does_not_read_skill_md_during_discovery(self) -> None: # Index points to a skill, but SKILL.md is not registered on the server. # Discovery should succeed because it only reads the index. - client = _make_client( - **{"skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json")} - ) + client = _make_client(**{"skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() @@ -384,19 +372,17 @@ async def test_does_not_read_skill_md_during_discovery(self) -> None: @pytest.mark.asyncio async def test_invalid_name_is_skipped(self) -> None: - index_json = json.dumps( - { - "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", - "skills": [ - { - "name": "UnitConverter", # Invalid: uppercase - "type": "skill-md", - "description": "Convert between common units.", - "url": "skill://UnitConverter/SKILL.md", - } - ], - } - ) + index_json = json.dumps({ + "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", + "skills": [ + { + "name": "UnitConverter", # Invalid: uppercase + "type": "skill-md", + "description": "Convert between common units.", + "url": "skill://UnitConverter/SKILL.md", + } + ], + }) client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() @@ -404,18 +390,16 @@ async def test_invalid_name_is_skipped(self) -> None: @pytest.mark.asyncio async def test_missing_required_fields_is_skipped(self) -> None: - index_json = json.dumps( - { - "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", - "skills": [ - { - "name": "unit-converter", - "type": "skill-md", - # Missing description and url - } - ], - } - ) + index_json = json.dumps({ + "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", + "skills": [ + { + "name": "unit-converter", + "type": "skill-md", + # Missing description and url + } + ], + }) client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() @@ -423,19 +407,17 @@ async def test_missing_required_fields_is_skipped(self) -> None: @pytest.mark.asyncio async def test_unsupported_type_is_skipped(self) -> None: - index_json = json.dumps( - { - "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", - "skills": [ - { - "name": "some-skill", - "type": "archive", - "description": "Packaged skill.", - "url": "skill://some-skill.tar.gz", - } - ], - } - ) + index_json = json.dumps({ + "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", + "skills": [ + { + "name": "some-skill", + "type": "archive", + "description": "Packaged skill.", + "url": "skill://some-skill.tar.gz", + } + ], + }) client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() @@ -443,18 +425,16 @@ async def test_unsupported_type_is_skipped(self) -> None: @pytest.mark.asyncio async def test_template_type_is_skipped(self) -> None: - index_json = json.dumps( - { - "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", - "skills": [ - { - "type": "mcp-resource-template", - "description": "Per-product documentation skill", - "url": "skill://docs/{product}/SKILL.md", - } - ], - } - ) + index_json = json.dumps({ + "$schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json", + "skills": [ + { + "type": "mcp-resource-template", + "description": "Per-product documentation skill", + "url": "skill://docs/{product}/SKILL.md", + } + ], + }) client = _make_client(**{"skill://index.json": _make_text_result(index_json, uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() @@ -462,31 +442,25 @@ async def test_template_type_is_skipped(self) -> None: @pytest.mark.asyncio async def test_empty_index_returns_empty(self) -> None: - client = _make_client( - **{"skill://index.json": _make_text_result('{"skills": []}', uri="skill://index.json")} - ) + client = _make_client(**{"skill://index.json": _make_text_result('{"skills": []}', uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() assert skills == [] @pytest.mark.asyncio async def test_malformed_index_json_returns_empty(self) -> None: - client = _make_client( - **{"skill://index.json": _make_text_result("not valid json", uri="skill://index.json")} - ) + client = _make_client(**{"skill://index.json": _make_text_result("not valid json", uri="skill://index.json")}) source = MCPSkillsSource(client=client) skills = await source.get_skills() assert skills == [] @pytest.mark.asyncio async def test_sibling_text_resource(self) -> None: - client = _make_client( - **{ - "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"), - "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), - "skill://unit-converter/references/checklist.md": _make_text_result("- check thing 1\n- check thing 2"), - } - ) + client = _make_client(**{ + "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"), + "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), + "skill://unit-converter/references/checklist.md": _make_text_result("- check thing 1\n- check thing 2"), + }) source = MCPSkillsSource(client=client) skill = (await source.get_skills())[0] resource = await skill.get_resource("references/checklist.md") @@ -497,13 +471,11 @@ async def test_sibling_text_resource(self) -> None: @pytest.mark.asyncio async def test_sibling_binary_resource(self) -> None: data = bytes([0x01, 0x02, 0x03, 0x04]) - client = _make_client( - **{ - "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"), - "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), - "skill://unit-converter/assets/icon.bin": _make_blob_result(data), - } - ) + client = _make_client(**{ + "skill://index.json": _make_text_result(SAMPLE_SKILL_INDEX, uri="skill://index.json"), + "skill://unit-converter/SKILL.md": _make_text_result(SAMPLE_SKILL_MD), + "skill://unit-converter/assets/icon.bin": _make_blob_result(data), + }) source = MCPSkillsSource(client=client) skill = (await source.get_skills())[0] resource = await skill.get_resource("assets/icon.bin") @@ -649,9 +621,7 @@ async def test_get_resource_generic_mcp_error_propagates(self) -> None: from agent_framework import SkillFrontmatter client = AsyncMock() - client.read_resource = AsyncMock( - side_effect=McpError(error=ErrorData(code=0, message="Handler error")) - ) + client.read_resource = AsyncMock(side_effect=McpError(error=ErrorData(code=0, message="Handler error"))) fm = SkillFrontmatter(name="test-skill", description="Test.") skill = MCPSkill(frontmatter=fm, skill_md_uri="skill://test/SKILL.md", client=client) with pytest.raises(McpError): diff --git a/python/packages/core/tests/workflow/test_agent_executor.py b/python/packages/core/tests/workflow/test_agent_executor.py index c9004f234b1..e324d52d0d5 100644 --- a/python/packages/core/tests/workflow/test_agent_executor.py +++ b/python/packages/core/tests/workflow/test_agent_executor.py @@ -1,5 +1,6 @@ # Copyright (c) Microsoft. All rights reserved. +import logging from collections.abc import AsyncIterable, Awaitable from typing import Any, Literal, overload @@ -19,7 +20,7 @@ WorkflowEvent, WorkflowRunState, ) -from agent_framework._workflows._agent_executor import AgentExecutorResponse +from agent_framework._workflows._agent_executor import AgentExecutorRequest, AgentExecutorResponse from agent_framework._workflows._checkpoint import InMemoryCheckpointStorage from agent_framework._workflows._const import GLOBAL_KWARGS_KEY @@ -306,6 +307,108 @@ async def test_agent_executor_save_and_restore_state_directly() -> None: assert restored_session.session_id == session.session_id +# region: Tests for AgentExecutor.reset() + + +async def test_agent_executor_reset_clears_per_run_state() -> None: + """reset() clears cache, conversation snapshot, and pending request/response buffers.""" + agent = _CountingAgent(id="reset_agent", name="ResetAgent") + executor = AgentExecutor(agent, id="reset_exec") + + # Populate every per-run buffer. + executor._cache = [Message(role="user", contents=["cached"])] # type: ignore[reportPrivateUsage] + executor._full_conversation = [ # type: ignore[reportPrivateUsage] + Message(role="user", contents=["prior turn"]), + Message(role="assistant", contents=["prior response"]), + ] + pending_request = Content.from_text(text="approve?") + executor._pending_agent_requests = {"req-1": pending_request} # type: ignore[reportPrivateUsage] + executor._pending_responses_to_agent = [Content.from_text(text="approved")] # type: ignore[reportPrivateUsage] + + await executor.reset() + + assert executor._cache == [] # type: ignore[reportPrivateUsage] + assert executor._full_conversation == [] # type: ignore[reportPrivateUsage] + assert executor._pending_agent_requests == {} # type: ignore[reportPrivateUsage] + assert executor._pending_responses_to_agent == [] # type: ignore[reportPrivateUsage] + + +async def test_agent_executor_reset_creates_fresh_session_when_auto_created() -> None: + """reset() replaces the agent session when the executor created it itself.""" + agent = _CountingAgent(id="reset_session_agent", name="ResetSessionAgent") + # No session passed in — executor creates one via agent.create_session(). + executor = AgentExecutor(agent, id="reset_session_exec") + auto_created = executor._session # type: ignore[reportPrivateUsage] + auto_created.state["history"] = {"messages": [Message(role="user", contents=["old"])]} + + await executor.reset() + + new_session = executor._session # type: ignore[reportPrivateUsage] + assert new_session is not auto_created + assert new_session.session_id != auto_created.session_id + assert "history" not in new_session.state + + +async def test_agent_executor_reset_preserves_caller_supplied_session(caplog: pytest.LogCaptureFixture) -> None: + """reset() leaves a session passed in via __init__ untouched and warns the caller.""" + agent = _CountingAgent(id="reset_session_agent", name="ResetSessionAgent") + caller_session = AgentSession() + history_payload = {"messages": [Message(role="user", contents=["old"])]} + caller_session.state["history"] = history_payload + executor = AgentExecutor(agent, id="reset_session_exec", session=caller_session) + + assert executor._session is caller_session # type: ignore[reportPrivateUsage] + + with caplog.at_level(logging.WARNING, logger="agent_framework._workflows._agent_executor"): + await executor.reset() + + # Same instance, state untouched — the caller is responsible for managing the session. + assert executor._session is caller_session # type: ignore[reportPrivateUsage] + assert caller_session.state["history"] is history_payload + assert any("Session was supplied by the caller" in record.message for record in caplog.records) + + +async def test_agent_executor_reset_allows_subsequent_run() -> None: + """After reset(), the executor can be reused for a fresh workflow run without leaking state.""" + agent = _CountingAgent(id="reset_reuse_agent", name="ResetReuseAgent") + executor = AgentExecutor(agent, id="reset_reuse_exec") + workflow = WorkflowBuilder(start_executor=executor, output_from=[executor]).build() + + first_outputs: list[WorkflowEvent] = [] + async for event in workflow.run( + AgentExecutorRequest(messages=[Message(role="user", contents=["hello"])]), + stream=True, + ): + if event.type == "output": + first_outputs.append(event) + + assert first_outputs, "first run should have produced at least one output event" + # After a normal run the cache is drained but the conversation snapshot remains. + assert executor._cache == [] # type: ignore[reportPrivateUsage] + assert executor._full_conversation != [] # type: ignore[reportPrivateUsage] + first_session_id = executor._session.session_id # type: ignore[reportPrivateUsage] + + await workflow.reset_for_new_run() + + assert executor._full_conversation == [] # type: ignore[reportPrivateUsage] + # Session was auto-created, so reset() rotates it to a fresh one. + assert executor._session.session_id != first_session_id # type: ignore[reportPrivateUsage] + + second_outputs: list[WorkflowEvent] = [] + async for event in workflow.run( + AgentExecutorRequest(messages=[Message(role="user", contents=["second"])]), + stream=True, + ): + if event.type == "output": + second_outputs.append(event) + + assert second_outputs, "second run after reset should have produced at least one output event" + assert agent.call_count == 2 + + +# endregion: Tests for AgentExecutor.reset() + + async def test_prepare_agent_run_args_extracts_invocation_kwargs() -> None: """_prepare_agent_run_args extracts function_invocation_kwargs and client_kwargs.""" agent = _CountingAgent(id="test_agent", name="TestAgent") diff --git a/python/packages/core/tests/workflow/test_executor.py b/python/packages/core/tests/workflow/test_executor.py index df742b76f6a..69089005153 100644 --- a/python/packages/core/tests/workflow/test_executor.py +++ b/python/packages/core/tests/workflow/test_executor.py @@ -1004,3 +1004,53 @@ class DualBad(Executor, Generic[_T]): @handler async def process(self, message: _T, ctx) -> None: # type: ignore[no-untyped-def] pass + + +# region: Tests for Executor.reset() + + +async def test_executor_default_reset_is_noop(): + """The base Executor.reset() is a no-op and must complete without raising. + + Subclasses that don't carry reset-relevant state should be able to rely on the + default implementation. + """ + + class StatelessExecutor(Executor): + @handler + async def handle(self, message: str, ctx: WorkflowContext[str]) -> None: + await ctx.send_message(message) + + executor_instance = StatelessExecutor(id="stateless") + + # Must complete without raising and return None. + assert await executor_instance.reset() is None + + +async def test_executor_subclass_reset_is_invoked(): + """A subclass that overrides reset() can clear its own internal state.""" + + class CounterExecutor(Executor): + def __init__(self, id: str) -> None: + super().__init__(id=id) + self.counter = 0 + self.reset_calls = 0 + + @handler + async def handle(self, message: int, ctx: WorkflowContext[int]) -> None: + self.counter += message + + async def reset(self) -> None: + self.counter = 0 + self.reset_calls += 1 + + executor_instance = CounterExecutor(id="counter") + executor_instance.counter = 42 + + await executor_instance.reset() + + assert executor_instance.counter == 0 + assert executor_instance.reset_calls == 1 + + +# endregion: Tests for Executor.reset() diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index 6756bb9a9f2..2c8ea4d22ff 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -1112,3 +1112,255 @@ async def test_runner_drains_straggler_events_at_iteration_end(): output_events = [e for e in events if e.type == "output"] # We should have output events from both executors assert len(output_events) >= 2 + + +# region: Tests for InProcRunnerContext.reset_for_new_run() + + +async def test_runner_context_reset_clears_in_flight_messages(): + """reset_for_new_run drops queued executor-to-executor messages.""" + ctx = InProcRunnerContext() + await ctx.send_message(WorkflowMessage(data=MockMessage(data=1), source_id="src")) + + assert await ctx.has_messages() is True + + ctx.reset_for_new_run() + + assert await ctx.has_messages() is False + assert await ctx.drain_messages() == {} + + +async def test_runner_context_reset_drains_pending_events(): + """reset_for_new_run discards any events buffered for streaming.""" + ctx = InProcRunnerContext() + await ctx.add_event(WorkflowEvent.superstep_started(iteration=1)) + assert await ctx.has_events() is True + + ctx.reset_for_new_run() + + assert await ctx.has_events() is False + assert await ctx.drain_events() == [] + + +async def test_runner_context_reset_resets_streaming_flag(): + """reset_for_new_run resets streaming back to its non-streaming default.""" + ctx = InProcRunnerContext() + ctx.set_streaming(True) + assert ctx.is_streaming() is True + + ctx.reset_for_new_run() + + assert ctx.is_streaming() is False + + +# endregion: Tests for InProcRunnerContext.reset_for_new_run() + + +# region: Tests for Runner.reset_for_new_run() + + +async def test_runner_reset_for_new_run_resets_iteration_count(): + """reset_for_new_run resets the iteration counter back to zero.""" + runner = _make_runner() + runner._iteration = 7 # pyright: ignore[reportPrivateUsage] + + await runner.reset_for_new_run() + + assert runner._iteration == 0 # pyright: ignore[reportPrivateUsage] + + +async def test_runner_reset_for_new_run_clears_shared_state(): + """reset_for_new_run wipes both committed and pending entries from shared state.""" + state = State() + state.set("committed_key", "committed_value") + state.commit() + state.set("pending_key", "pending_value") # uncommitted + + runner = Runner( + [], + {}, + state, + InProcRunnerContext(), + "test_name", + graph_signature_hash="test_hash", + ) + + await runner.reset_for_new_run() + + assert state.get("committed_key") is None + assert state.get("pending_key") is None + assert state.has("committed_key") is False + assert state.has("pending_key") is False + + +async def test_runner_reset_for_new_run_clears_resumed_from_checkpoint_flag(): + """reset_for_new_run clears the flag set by restore_from_checkpoint.""" + runner = _make_runner() + runner._mark_resumed(iteration=5) # pyright: ignore[reportPrivateUsage] + assert runner._resumed_from_checkpoint is True # pyright: ignore[reportPrivateUsage] + + await runner.reset_for_new_run() + + assert runner._resumed_from_checkpoint is False # pyright: ignore[reportPrivateUsage] + # And the iteration count restored from the checkpoint must be wiped, too. + assert runner._iteration == 0 # pyright: ignore[reportPrivateUsage] + + +async def test_runner_reset_for_new_run_invokes_executor_reset_for_each_executor(): + """reset_for_new_run calls reset() on every registered executor exactly once.""" + + class TrackingExecutor(MockExecutor): + def __init__(self, id: str) -> None: + super().__init__(id=id) + self.reset_calls = 0 + + async def reset(self) -> None: + self.reset_calls += 1 + + executor_a = TrackingExecutor(id="executor_a") + executor_b = TrackingExecutor(id="executor_b") + + runner = Runner( + [], + {executor_a.id: executor_a, executor_b.id: executor_b}, + State(), + InProcRunnerContext(), + "test_name", + graph_signature_hash="test_hash", + ) + + await runner.reset_for_new_run() + + assert executor_a.reset_calls == 1 + assert executor_b.reset_calls == 1 + + +async def test_runner_reset_for_new_run_resets_runner_context(): + """reset_for_new_run forwards the reset to the underlying runner context.""" + ctx = InProcRunnerContext() + await ctx.send_message(WorkflowMessage(data=MockMessage(data=0), source_id="src")) + await ctx.add_event(WorkflowEvent.superstep_started(iteration=1)) + ctx.set_streaming(True) + + runner = Runner([], {}, State(), ctx, "test_name", graph_signature_hash="test_hash") + + await runner.reset_for_new_run() + + assert await ctx.has_messages() is False + assert await ctx.has_events() is False + assert ctx.is_streaming() is False + + +async def test_runner_can_run_again_after_reset_for_new_run(): + """After reset_for_new_run the runner can be reserved and converge a fresh workload.""" + executor_a = MockExecutor(id="executor_a") + executor_b = MockExecutor(id="executor_b") + + edges = [ + SingleEdgeGroup(executor_a.id, executor_b.id), + SingleEdgeGroup(executor_b.id, executor_a.id), + ] + executors: dict[str, Executor] = { + executor_a.id: executor_a, + executor_b.id: executor_b, + } + state = State() + ctx = InProcRunnerContext() + + runner = Runner(edges, executors, state, ctx, "test_name", graph_signature_hash="test_hash") + + # First run: drives MockExecutor's loop until it yields the terminal value. + await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) + runner.reserve() + async for _ in runner.run_until_convergence(): + pass + assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage] + + await runner.reset_for_new_run() + + # Second run: must succeed cleanly using the same runner instance. + await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) + runner.reserve() + second_run_outputs: list[int] = [] + async for event in runner.run_until_convergence(): + if event.type == "output": + second_run_outputs.append(event.data) + + assert second_run_outputs == [10] + assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage] + + +async def test_runner_reset_for_new_run_rejected_when_reserved(): + """reset_for_new_run refuses to run when the runner is reserved but not yet running.""" + runner = _make_runner() + runner.reserve() + + with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"): + await runner.reset_for_new_run() + + +async def test_runner_reset_for_new_run_rejected_while_running(): + """reset_for_new_run refuses to run while a run is mid-execution.""" + runner = _make_runner() + + started = asyncio.Event() + release = asyncio.Event() + + async def _slow_run() -> None: + runner.reserve() + async for _ in runner.run_until_convergence(): + if not started.is_set(): + started.set() + await release.wait() + + task = asyncio.create_task(_slow_run()) + await started.wait() # first run is now executing inside run_until_convergence + + try: + with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"): + await runner.reset_for_new_run() + finally: + release.set() + await task + + # Once the run drained, reset must succeed again. + await runner.reset_for_new_run() + + +async def test_runner_reset_for_new_run_does_not_mutate_when_rejected(): + """When reset is rejected, the runner's iteration counter and state are untouched.""" + + class TrackingExecutor(MockExecutor): + def __init__(self, id: str) -> None: + super().__init__(id=id) + self.reset_calls = 0 + + async def reset(self) -> None: + self.reset_calls += 1 + + executor = TrackingExecutor(id="executor") + state = State() + state.set("preserved", 42) + state.commit() + + runner = Runner( + [], + {executor.id: executor}, + state, + InProcRunnerContext(), + "test_name", + graph_signature_hash="test_hash", + ) + runner._iteration = 7 # pyright: ignore[reportPrivateUsage] + runner.reserve() + + with pytest.raises(WorkflowRunnerException): + await runner.reset_for_new_run() + + # Nothing was mutated by the failed reset. + assert runner._iteration == 7 # pyright: ignore[reportPrivateUsage] + assert state.get("preserved") == 42 + assert executor.reset_calls == 0 + + +# endregion: Tests for Runner.reset_for_new_run() diff --git a/python/packages/core/tests/workflow/test_sub_workflow.py b/python/packages/core/tests/workflow/test_sub_workflow.py index 7bf38a06f32..17b7e059619 100644 --- a/python/packages/core/tests/workflow/test_sub_workflow.py +++ b/python/packages/core/tests/workflow/test_sub_workflow.py @@ -689,3 +689,89 @@ async def run(self, message: str, ctx: WorkflowContext[Never, str]) -> None: # The parent's own terminal output is unaffected. assert any(e.executor_id == "parent_sink" and e.data == "final: hello" for e in output_events) + + +# region: Tests for WorkflowExecutor.reset() + + +async def test_workflow_executor_reset_clears_execution_state() -> None: + """reset() clears the WorkflowExecutor's per-run execution contexts and request mappings.""" + validation_workflow = create_email_validation_workflow() + parent = Coordinator() + workflow_executor = WorkflowExecutor(validation_workflow, "email_validation_workflow") + + main_workflow = ( + WorkflowBuilder(start_executor=parent) + .add_edge(parent, workflow_executor) + .add_edge(workflow_executor, parent) + .build() + ) + + # First run pauses with a pending request from the sub-workflow. + result = await main_workflow.run("test@example.com") + assert len(result.get_request_info_events()) == 1 + assert len(workflow_executor._execution_contexts) == 1 # type: ignore[reportPrivateUsage] + assert len(workflow_executor._request_to_execution) == 1 # type: ignore[reportPrivateUsage] + + await main_workflow.reset_for_new_run() + + assert workflow_executor._execution_contexts == {} # type: ignore[reportPrivateUsage] + assert workflow_executor._request_to_execution == {} # type: ignore[reportPrivateUsage] + + +async def test_workflow_executor_reset_resets_wrapped_workflow() -> None: + """reset() recursively resets the wrapped workflow (runner iteration counter cleared).""" + validation_workflow = create_email_validation_workflow() + parent = Coordinator() + workflow_executor = WorkflowExecutor(validation_workflow, "email_validation_workflow") + + main_workflow = ( + WorkflowBuilder(start_executor=parent) + .add_edge(parent, workflow_executor) + .add_edge(workflow_executor, parent) + .build() + ) + + await main_workflow.run("test@example.com") + # The sub-workflow's runner advanced past iteration 0 during execution. + assert validation_workflow._runner._iteration > 0 # type: ignore[reportPrivateUsage] + + await main_workflow.reset_for_new_run() + + # The wrapped workflow's runner was reset along with the parent. + assert validation_workflow._runner._iteration == 0 # type: ignore[reportPrivateUsage] + + +async def test_workflow_executor_reset_allows_subsequent_run() -> None: + """After reset(), the parent + WorkflowExecutor can be reused for a fresh run with no leakage.""" + validation_workflow = create_email_validation_workflow() + parent = Coordinator() + workflow_executor = WorkflowExecutor(validation_workflow, "email_validation_workflow") + + main_workflow = ( + WorkflowBuilder(start_executor=parent) + .add_edge(parent, workflow_executor) + .add_edge(workflow_executor, parent) + .build() + ) + + first_result = await main_workflow.run("first@example.com") + assert len(first_result.get_request_info_events()) == 1 + + await main_workflow.reset_for_new_run() + + # State on the WorkflowExecutor and parent's pending-request bookkeeping is clean. + assert workflow_executor._execution_contexts == {} # type: ignore[reportPrivateUsage] + assert workflow_executor._request_to_execution == {} # type: ignore[reportPrivateUsage] + + second_result = await main_workflow.run("second@example.com") + second_requests = second_result.get_request_info_events() + assert len(second_requests) == 1 + assert isinstance(second_requests[0].data, DomainCheckRequest) + # Confirm the new run produced a request from the second email, not the cached first one. + assert second_requests[0].data.email == "second@example.com" + # And the WorkflowExecutor is now tracking exactly one fresh execution. + assert len(workflow_executor._execution_contexts) == 1 # type: ignore[reportPrivateUsage] + + +# endregion: Tests for WorkflowExecutor.reset() diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index 1c77ae003bc..9267a17f689 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -28,6 +28,7 @@ WorkflowEvent, WorkflowException, WorkflowMessage, + WorkflowRunnerException, WorkflowRunState, handler, response_handler, @@ -1266,3 +1267,144 @@ async def test_output_executors_filtering_with_run_responses_streaming() -> None # endregion + + +# region: Tests for Workflow.reset_for_new_run() + + +async def test_workflow_reset_for_new_run_allows_subsequent_run() -> None: + """After reset_for_new_run() the same workflow instance can be run again from scratch.""" + executor_a = IncrementExecutor(id="executor_a") + executor_b = IncrementExecutor(id="executor_b") + + workflow = ( + WorkflowBuilder(start_executor=executor_a, output_from=[executor_a, executor_b]) + .add_edge(executor_a, executor_b) + .add_edge(executor_b, executor_a) + .build() + ) + + first = await workflow.run(NumberMessage(data=0)) + assert first.get_outputs() == [10] + + await workflow.reset_for_new_run() + + second = await workflow.run(NumberMessage(data=0)) + assert second.get_outputs() == [10] + + +async def test_workflow_reset_for_new_run_clears_workflow_state() -> None: + """reset_for_new_run() clears values that executors persisted in shared workflow state.""" + + class StateWritingExecutor(Executor): + @handler + async def handle(self, message: NumberMessage, ctx: WorkflowContext[Any, int]) -> None: + previous = ctx.get_state("seen") or 0 + ctx.set_state("seen", previous + 1) + await ctx.yield_output(previous + 1) + + state_writer = StateWritingExecutor(id="state_writer") + workflow = WorkflowBuilder(start_executor=state_writer, output_from=[state_writer]).build() + + first = await workflow.run(NumberMessage(data=1)) + assert first.get_outputs() == [1] + # State was persisted by the executor. + assert workflow._runner.state.get("seen") == 1 # pyright: ignore[reportPrivateUsage] + + await workflow.reset_for_new_run() + + # The runner's shared state has been wiped. + assert workflow._runner.state.get("seen") is None # pyright: ignore[reportPrivateUsage] + + second = await workflow.run(NumberMessage(data=1)) + # Counter started fresh from 0 again; output is 1, not 2. + assert second.get_outputs() == [1] + + +async def test_workflow_reset_for_new_run_invokes_executor_reset_hook() -> None: + """reset_for_new_run() calls Executor.reset() on every executor in the workflow.""" + + class ResettableExecutor(Executor): + def __init__(self, id: str) -> None: + super().__init__(id=id) + self.reset_calls = 0 + self.handled = 0 + + @handler + async def handle(self, message: NumberMessage, ctx: WorkflowContext[Any, int]) -> None: + self.handled += 1 + await ctx.yield_output(self.handled) + + async def reset(self) -> None: + self.reset_calls += 1 + self.handled = 0 + + executor = ResettableExecutor(id="resettable") + workflow = WorkflowBuilder(start_executor=executor, output_from=[executor]).build() + + await workflow.run(NumberMessage(data=1)) + assert executor.handled == 1 + assert executor.reset_calls == 0 + + await workflow.reset_for_new_run() + + assert executor.reset_calls == 1 + # The executor's own counter was wiped by its overridden reset(). + assert executor.handled == 0 + + +async def test_workflow_reset_for_new_run_resets_runner_iteration_counter() -> None: + """reset_for_new_run() drops the iteration counter accumulated during a prior run.""" + executor_a = IncrementExecutor(id="executor_a") + executor_b = IncrementExecutor(id="executor_b") + + workflow = ( + WorkflowBuilder(start_executor=executor_a, output_from=[executor_a, executor_b]) + .add_edge(executor_a, executor_b) + .add_edge(executor_b, executor_a) + .build() + ) + + await workflow.run(NumberMessage(data=0)) + assert workflow._runner._iteration > 0 # pyright: ignore[reportPrivateUsage] + + await workflow.reset_for_new_run() + + assert workflow._runner._iteration == 0 # pyright: ignore[reportPrivateUsage] + + +async def test_workflow_reset_for_new_run_rejected_during_streaming_run() -> None: + """reset_for_new_run() raises WorkflowRunnerException while a streaming run is in progress.""" + executor_a = IncrementExecutor(id="executor_a") + executor_b = IncrementExecutor(id="executor_b") + + workflow = ( + WorkflowBuilder(start_executor=executor_a, output_from=[executor_a, executor_b]) + .add_edge(executor_a, executor_b) + .add_edge(executor_b, executor_a) + .build() + ) + + async def consume_stream_slowly() -> list[WorkflowEvent]: + events: list[WorkflowEvent] = [] + async for event in workflow.run(NumberMessage(data=0), stream=True): + events.append(event) + await asyncio.sleep(0.01) + return events + + task = asyncio.create_task(consume_stream_slowly()) + # Let the streaming run start. + await asyncio.sleep(0.02) + + try: + with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"): + await workflow.reset_for_new_run() + finally: + await task + + # After the run completes, reset succeeds again. + await workflow.reset_for_new_run() + assert workflow._runner._iteration == 0 # pyright: ignore[reportPrivateUsage] + + +# endregion diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py b/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py index a4108b23f08..8cdf71a0d01 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py @@ -598,3 +598,25 @@ def _restore_pattern_metadata(self, metadata: dict[str, Any]) -> None: metadata: Pattern-specific state dict """ pass + + @override + async def reset(self) -> None: + """Reset the orchestrator to its initial state for a new workflow run. + + Clears the shared conversation history and round counter, then delegates + to ``_reset_pattern_state()`` so subclasses can clean up any + pattern-specific per-run state (caches, sessions, ledgers, etc.). + """ + logger.debug("%s %s: Resetting state", self.__class__.__name__, self.id) + self._full_conversation.clear() + self._round_index = 0 + self._reset_pattern_state() + + def _reset_pattern_state(self) -> None: + """Reset pattern-specific state. + + Override this method in subclasses to clear pattern-specific per-run state + when ``reset()`` is invoked. Called after the base class clears the shared + conversation and round counter. + """ + pass diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py b/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py index 728f3e388cc..f6bbac54002 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py @@ -327,6 +327,7 @@ def __init__( ) self._agent = agent self._retry_attempts = retry_attempts + self._session_supplied_by_caller = session is not None self._session = session or agent.create_session() # Cache for messages since last agent invocation # This is different from the full conversation history maintained by the base orchestrator @@ -337,6 +338,25 @@ def _append_messages(self, messages: Sequence[Message]) -> None: self._cache.extend(messages) return super()._append_messages(messages) + @override + def _reset_pattern_state(self) -> None: + """Reset pattern-specific state for a new workflow run. + + Clears the per-run message cache and rotates the orchestrator agent's + session unless the caller supplied a session explicitly (in which case + the caller is responsible for the session's lifecycle). + """ + self._cache.clear() + if self._session_supplied_by_caller: + logger.warning( + "%s %s: Session was supplied by the caller and will not be reset. " + "If you want a fresh session for the next run, reset or replace it before invoking the workflow.", + self.__class__.__name__, + self.id, + ) + else: + self._session = self._agent.create_session() + @override async def _handle_messages( self, diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py b/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py index f8cbf88fd73..ab79dbbfa3d 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py @@ -1263,6 +1263,14 @@ async def _reset_participants(self, ctx: WorkflowContext[MagenticResetSignal]) - # a target will broadcast to all. await ctx.send_message(MagenticResetSignal()) + @override + def _reset_pattern_state(self) -> None: + """Reset Magentic-specific per-run state for a new workflow run.""" + self._magentic_context = None + self._task_ledger = None + self._progress_ledger = None + self._terminated = False + @override async def on_checkpoint_save(self) -> dict[str, Any]: """Capture current orchestrator state for checkpointing.""" diff --git a/python/packages/orchestrations/tests/test_group_chat.py b/python/packages/orchestrations/tests/test_group_chat.py index 50f58e781a2..56a6f4a0b4b 100644 --- a/python/packages/orchestrations/tests/test_group_chat.py +++ b/python/packages/orchestrations/tests/test_group_chat.py @@ -1097,3 +1097,139 @@ def invalid_factory() -> Any: # endregion + + +# region Reset + + +async def test_base_orchestrator_reset_clears_conversation_and_round_index() -> None: + """reset() clears the conversation history and the round counter.""" + from agent_framework.orchestrations import GroupChatOrchestrator + + from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry + + selector = make_sequence_selector() + orchestrator = GroupChatOrchestrator( + id="orch", + participant_registry=ParticipantRegistry([]), + selection_func=selector, + max_rounds=2, + ) + orchestrator._full_conversation = [Message(role="user", contents=["hi"], author_name="user")] + orchestrator._round_index = 4 + + await orchestrator.reset() + + assert orchestrator._full_conversation == [] + assert orchestrator._round_index == 0 + + +async def test_base_orchestrator_reset_invokes_pattern_state_hook() -> None: + """reset() calls _reset_pattern_state() so subclasses can clean up their own state.""" + from agent_framework.orchestrations import GroupChatOrchestrator + + from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry + + selector = make_sequence_selector() + + class TrackingOrchestrator(GroupChatOrchestrator): + reset_calls: int = 0 + + def _reset_pattern_state(self) -> None: + type(self).reset_calls += 1 + + orchestrator = TrackingOrchestrator( + id="orch", + participant_registry=ParticipantRegistry([]), + selection_func=selector, + max_rounds=2, + ) + + await orchestrator.reset() + await orchestrator.reset() + + assert TrackingOrchestrator.reset_calls == 2 + + +async def test_agent_based_orchestrator_reset_clears_cache_and_rotates_session() -> None: + """When the session was not supplied by the caller, reset() rotates the session and clears the cache.""" + from agent_framework.orchestrations import AgentBasedGroupChatOrchestrator + + from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry + + agent = cast(Agent, StubManagerAgent()) + orchestrator = AgentBasedGroupChatOrchestrator( + agent=agent, + participant_registry=ParticipantRegistry([]), + max_rounds=2, + ) + original_session = orchestrator._session + orchestrator._cache = [Message(role="assistant", contents=["x"], author_name="agent")] + orchestrator._full_conversation = [Message(role="user", contents=["x"], author_name="user")] + orchestrator._round_index = 3 + + await orchestrator.reset() + + assert orchestrator._cache == [] + assert orchestrator._full_conversation == [] + assert orchestrator._round_index == 0 + assert orchestrator._session is not original_session + + +async def test_agent_based_orchestrator_reset_warns_when_session_supplied(caplog: pytest.LogCaptureFixture) -> None: + """When the caller supplied a session, reset() preserves it and logs a warning.""" + import logging + + from agent_framework.orchestrations import AgentBasedGroupChatOrchestrator + + from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry + + agent = cast(Agent, StubManagerAgent()) + supplied_session = agent.create_session() + orchestrator = AgentBasedGroupChatOrchestrator( + agent=agent, + participant_registry=ParticipantRegistry([]), + session=supplied_session, + max_rounds=2, + ) + orchestrator._cache = [Message(role="assistant", contents=["x"], author_name="agent")] + + with caplog.at_level(logging.WARNING, logger="agent_framework_orchestrations._group_chat"): + await orchestrator.reset() + + assert orchestrator._cache == [] + # The caller-owned session must be preserved. + assert orchestrator._session is supplied_session + warnings = [ + r for r in caplog.records if r.levelno == logging.WARNING and "Session was supplied by the caller" in r.message + ] + assert warnings, f"expected a warning about caller-supplied session, got: {[r.message for r in caplog.records]}" + + +async def test_workflow_reset_resets_group_chat_orchestrator() -> None: + """End-to-end: workflow.reset_for_new_run() resets the orchestrator's conversation state.""" + selector = make_sequence_selector() + alpha = StubAgent("alpha", "ack from alpha") + beta = StubAgent("beta", "ack from beta") + + workflow = GroupChatBuilder( + participants=[alpha, beta], + max_rounds=2, + selection_func=selector, + orchestrator_name="manager", + ).build() + + async for _ in workflow.run("first task", stream=True): + pass + + orchestrator = cast(BaseGroupChatOrchestrator, workflow.executors[GroupChatBuilder.DEFAULT_ORCHESTRATOR_ID]) + assert orchestrator._full_conversation, "orchestrator should have accumulated conversation after first run" + assert orchestrator._round_index > 0 + + await workflow.reset_for_new_run() + + assert orchestrator._full_conversation == [] + assert orchestrator._round_index == 0 + + +# endregion diff --git a/python/uv.lock b/python/uv.lock index 5a420aafa27..48e56c0aea0 100644 --- a/python/uv.lock +++ b/python/uv.lock @@ -1,5 +1,4 @@ version = 1 -revision = 3 requires-python = ">=3.10" resolution-markers = [ "python_full_version >= '3.15' and sys_platform == 'darwin'", @@ -87,18 +86,18 @@ dependencies = [ { name = "protobuf", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, { name = "pydantic", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" }, ] -sdist = { url = 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Tao Chen Date: Mon, 8 Jun 2026 14:57:01 -0700 Subject: [PATCH 03/13] Add reset to hosted workflow --- .../_responses.py | 6 ++ .../foundry_hosting/tests/test_responses.py | 75 +++++++++++++++++++ 2 files changed, 81 insertions(+) diff --git a/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py b/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py index ec4a9d85336..498879861b1 100644 --- a/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py +++ b/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py @@ -649,6 +649,12 @@ async def _handle_inner_workflow( checkpoint_id=latest_checkpoint_id, checkpoint_storage=restore_storage, ) + else: + # We reset the workflow if neither conversation_id nor previous_response_id + # was supplied, because this implies there's no prior state to restore and + # we want to ensure a clean slate. Workflow may contain in-memory state that + # needs to be cleared on new conversations. + await self._agent.workflow.reset_for_new_run() # Now run the agent with the latest input response_event_stream = ResponseEventStream(response_id=context.response_id, model=request.model) diff --git a/python/packages/foundry_hosting/tests/test_responses.py b/python/packages/foundry_hosting/tests/test_responses.py index 8bc09c5d13d..df3aec0d653 100644 --- a/python/packages/foundry_hosting/tests/test_responses.py +++ b/python/packages/foundry_hosting/tests/test_responses.py @@ -3971,5 +3971,80 @@ async def test_round_trip_approval_response_rejected(self) -> None: assert len(approval_responses) == 1 assert approval_responses[0].approved is False # type: ignore[attr-defined] + async def test_workflow_is_reset_when_no_prior_conversation(self) -> None: + """Without ``previous_response_id`` or ``conversation_id`` the host must + reset the workflow so any in-memory state from a previous request is + cleared before the new turn runs.""" + workflow_agent = _build_text_workflow_agent("fresh") + server = _make_server(workflow_agent) + + with patch.object( + workflow_agent.workflow, + "reset_for_new_run", + new=AsyncMock(wraps=workflow_agent.workflow.reset_for_new_run), + ) as reset_spy: + resp = await _post(server, input_text="hi", stream=False) + + assert resp.status_code == 200 + assert reset_spy.await_count == 1 + + async def test_workflow_is_reset_across_independent_requests(self) -> None: + """Two consecutive requests without a chaining context id must each + reset the workflow.""" + workflow_agent = _build_text_workflow_agent("again") + server = _make_server(workflow_agent) + + with patch.object( + workflow_agent.workflow, + "reset_for_new_run", + new=AsyncMock(wraps=workflow_agent.workflow.reset_for_new_run), + ) as reset_spy: + first = await _post(server, input_text="hi", stream=False) + second = await _post(server, input_text="hi again", stream=False) + + assert first.status_code == 200 + assert second.status_code == 200 + assert reset_spy.await_count == 2 + + async def test_workflow_is_not_reset_when_resuming_from_checkpoint(self) -> None: + """When ``previous_response_id`` resolves to an existing workflow + checkpoint the host restores the checkpoint instead of resetting + the workflow.""" + workflow_agent, _ = _build_approval_workflow_agent( + approval_request_id="apr_no_reset", + final_text="resumed", + ) + server = _make_server(workflow_agent) + + first = await _post(server, stream=False) + assert first.status_code == 200 + first_body = first.json() + first_response_id = first_body["id"] + approval_request_id = next(it["id"] for it in first_body["output"] if it["type"] == "mcp_approval_request") + + with patch.object( + workflow_agent.workflow, + "reset_for_new_run", + new=AsyncMock(wraps=workflow_agent.workflow.reset_for_new_run), + ) as reset_spy: + second = await _post_json( + server, + { + "model": "test-model", + "input": [ + { + "type": "mcp_approval_response", + "approval_request_id": approval_request_id, + "approve": True, + } + ], + "stream": False, + "previous_response_id": first_response_id, + }, + ) + + assert second.status_code == 200 + assert reset_spy.await_count == 0 + # endregion From 598ad231ba113341610d015ca9caa138364ee5b7 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Mon, 8 Jun 2026 16:07:26 -0700 Subject: [PATCH 04/13] Add sample --- python/samples/03-workflows/README.md | 1 + .../state-management/workflow_reset.py | 212 ++++++++++++++++++ 2 files changed, 213 insertions(+) create mode 100644 python/samples/03-workflows/state-management/workflow_reset.py diff --git a/python/samples/03-workflows/README.md b/python/samples/03-workflows/README.md index c79203d7429..adcb57dadb3 100644 --- a/python/samples/03-workflows/README.md +++ b/python/samples/03-workflows/README.md @@ -169,6 +169,7 @@ callers can still inspect progress or supporting work from the response messages | Sample | File | Concepts | | -------------------------------- | ------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------- | | State with Agents | [state-management/state_with_agents.py](./state-management/state_with_agents.py) | Store in state once and later reuse across agents | +| Reset Workflow Between Runs | [state-management/workflow_reset.py](./state-management/workflow_reset.py) | Reuse one workflow instance across independent runs via `reset_for_new_run()` | | Workflow Kwargs - Global Context | [state-management/workflow_kwargs_global.py](./state-management/workflow_kwargs_global.py) | Pass custom context (data, user tokens) via kwargs to `@tool` tools in all agents | | Workflow Kwargs - Per Agent | [state-management/workflow_kwargs_per_agent.py](./state-management/workflow_kwargs_per_agent.py) | Pass custom context (data, user tokens) via kwargs to `@tool` tools in individual agents | diff --git a/python/samples/03-workflows/state-management/workflow_reset.py b/python/samples/03-workflows/state-management/workflow_reset.py new file mode 100644 index 00000000000..d751e6b066b --- /dev/null +++ b/python/samples/03-workflows/state-management/workflow_reset.py @@ -0,0 +1,212 @@ +# Copyright (c) Microsoft. All rights reserved. + +import asyncio +from dataclasses import dataclass + +from agent_framework import Executor, Workflow, WorkflowBuilder, WorkflowContext, handler +from typing_extensions import Never, override + +""" +Sample: Reusing a Workflow across independent jobs with reset_for_new_run(). + +Build a small moderation pipeline that silently accumulates stats as messages +flow through it and emits a summary only when the caller asks for one. Drive +the same workflow instance across multiple independent jobs and show that +``Workflow.reset_for_new_run()`` clears all per-executor state without +rebuilding the graph. + +Two custom executors share the work, each with its own per-job state and its +own ``reset()`` override: + +- ``FlaggedKeywordCounter`` is the start executor. It accepts message strings + to inspect (silently updating local stats, sending nothing downstream) and + ``ReportRequest`` markers that cause it to forward a ``StatsSnapshot``. +- ``StatsReporter`` formats the snapshot, increments its own emitted-reports + counter, and yields the summary as the workflow output. + +A run with a string produces no output, just a state update. A run with a +``ReportRequest`` produces exactly one summary. Job boundaries are entirely +controlled by the caller via ``reset_for_new_run()``, which calls ``reset()`` +on every executor in the graph. + +Purpose: +Show how to: +- Hold per-job aggregate state on a custom Executor subclass. +- Override ``Executor.reset()`` on every executor that owns per-run state, so + it is cleared automatically when the workflow is reset. +- Call ``Workflow.reset_for_new_run()`` between independent jobs so a single + workflow instance can serve a stream of unrelated batches without leaking + state. + +Prerequisites: +- No external services or credentials required; this sample runs entirely in-process. +- Familiarity with WorkflowBuilder and Executor subclasses. +""" + + +@dataclass +class ReportRequest: + """Marker input that asks the workflow to emit a summary of stats so far.""" + + +@dataclass +class StatsSnapshot: + """Snapshot the counter forwards to the reporter when a report is requested.""" + + messages_seen: int + flagged_messages: int + flagged_keywords: list[str] + + +class FlaggedKeywordCounter(Executor): + """Executor that silently accumulates per-job stats; emits on demand. + + Holds three instance attributes that build up across the runs that make up a + single job: + + - ``_messages_seen``: how many messages have been inspected. + - ``_flagged_messages``: how many of those messages contained any flagged keyword. + - ``_flagged_keywords``: the set of distinct keywords actually observed. + + Two handlers dispatch by input type: + + - ``inspect`` accepts a string, updates the counters, and sends nothing. + - ``emit_report`` accepts a ``ReportRequest`` and forwards a current + ``StatsSnapshot`` to the downstream reporter. + + Without overriding ``reset()`` this state would leak into the next job when the + workflow is reused via ``Workflow.reset_for_new_run()``. The override below + clears these attributes so each fresh job starts empty. + """ + + FLAGGED_KEYWORDS = frozenset({"spam", "scam", "phishing"}) + + def __init__(self, id: str) -> None: + super().__init__(id=id) + self._messages_seen: int = 0 + self._flagged_messages: int = 0 + self._flagged_keywords: set[str] = set() + + @handler + async def inspect(self, message: str, ctx: WorkflowContext[StatsSnapshot]) -> None: + """Inspect ``message`` and update local stats. Sends nothing downstream.""" + self._messages_seen += 1 + hits = {kw for kw in self.FLAGGED_KEYWORDS if kw in message.lower()} + if hits: + self._flagged_messages += 1 + self._flagged_keywords.update(hits) + + @handler + async def emit_report(self, _: ReportRequest, ctx: WorkflowContext[StatsSnapshot]) -> None: + """Forward the current stats snapshot to the reporter on request.""" + await ctx.send_message( + StatsSnapshot( + messages_seen=self._messages_seen, + flagged_messages=self._flagged_messages, + flagged_keywords=sorted(self._flagged_keywords), + ) + ) + + @override + async def reset(self) -> None: + """Clear per-job aggregate state when the workflow is reset. + + ``Workflow.reset_for_new_run()`` calls ``reset()`` on every executor in the + graph; overriding it here is what makes a reused workflow safe to drive with + a brand-new job. + """ + self._messages_seen = 0 + self._flagged_messages = 0 + self._flagged_keywords.clear() + + +class StatsReporter(Executor): + """Terminal executor that formats a snapshot and yields it as workflow output. + + Holds a single instance attribute, ``_reports_emitted``, that tracks how many + summaries this reporter has produced on this workflow instance, and clears + it on reset so a reset workflow behaves identically to a freshly built one. + """ + + def __init__(self, id: str) -> None: + super().__init__(id=id) + self._reports_emitted: int = 0 + + @handler + async def report(self, snapshot: StatsSnapshot, ctx: WorkflowContext[Never, str]) -> None: + self._reports_emitted += 1 + summary = ( + f"messages={snapshot.messages_seen}, " + f"flagged={snapshot.flagged_messages}, " + f"keywords={snapshot.flagged_keywords or 'none'}, " + f"reports_emitted={self._reports_emitted}" + ) + await ctx.yield_output(summary) + + @override + async def reset(self) -> None: + """Clear the emitted-reports counter when the workflow is reset.""" + self._reports_emitted = 0 + + +async def _process(workflow: Workflow, messages: list[str]) -> None: + """Send each message through the workflow; no output is produced.""" + for message in messages: + await workflow.run(message) + + +async def _request_report(workflow: Workflow) -> str: + """Ask the workflow for a summary of the stats accumulated so far.""" + events = await workflow.run(ReportRequest()) + outputs = events.get_outputs() + return outputs[0] if outputs else "" + + +async def main() -> None: + """Build the moderation workflow once, then run it across three independent jobs.""" + + # 1. Build the moderation pipeline once. The same workflow instance will be + # reused for every job; that's the whole point of this sample. + counter = FlaggedKeywordCounter(id="counter") + reporter = StatsReporter(id="reporter") + workflow = WorkflowBuilder(start_executor=counter, output_from=[reporter]).add_edge(counter, reporter).build() + + # 2. First job -- inspect three messages, then request a report. Note this + # batch happens to be three messages, but any size works. + await _process(workflow, ["hello there", "free phishing kit", "lunch plans?"]) + print(f"Batch A summary: {await _request_report(workflow)}") + + # 3. Second job WITHOUT reset. State from batch A leaks in: the counter's + # tallies and the reporter's emitted-reports counter both keep + # accumulating even though batch B is conceptually a separate job. + await _process(workflow, ["weekly status update", "team offsite agenda", "quarterly review"]) + print(f"Batch B summary (no reset): {await _request_report(workflow)}") + + # 4. Now reset between jobs and process the same batch B again. The summary + # reflects only batch B and every per-run counter starts fresh, because + # reset_for_new_run() calls reset() on every executor in the graph: + # - FlaggedKeywordCounter clears its message / flag / keyword tallies. + # - StatsReporter clears its emitted-reports counter. + await workflow.reset_for_new_run() + await _process(workflow, ["weekly status update", "team offsite agenda", "quarterly review"]) + print(f"Batch B summary (after reset): {await _request_report(workflow)}") + + # 5. Reset again before a final unrelated job. A reset workflow is + # indistinguishable from a freshly built one for state purposes, but + # cheaper because the graph and executor objects are reused. + await workflow.reset_for_new_run() + await _process(workflow, ["spam offer #1", "scam alert", "phishing attempt"]) + print(f"Batch C summary (after reset): {await _request_report(workflow)}") + + """ + Sample Output: + + Batch A summary: messages=3, flagged=1, keywords=['phishing'], reports_emitted=1 + Batch B summary (no reset): messages=6, flagged=1, keywords=['phishing'], reports_emitted=2 + Batch B summary (after reset): messages=3, flagged=0, keywords=none, reports_emitted=1 + Batch C summary (after reset): messages=3, flagged=3, keywords=['phishing', 'scam', 'spam'], reports_emitted=1 + """ + + +if __name__ == "__main__": + asyncio.run(main()) From 568afdd293536ee49c521f2fb744ac86fcc6e287 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Mon, 8 Jun 2026 16:30:59 -0700 Subject: [PATCH 05/13] Fix tests and address comments --- .../agent_framework/_workflows/_runner.py | 2 +- .../agent_framework/_workflows/_workflow.py | 3 +-- .../core/tests/workflow/test_runner.py | 4 ++-- .../tests/test_http_request_executor.py | 22 +++++++++---------- .../test_http_request_yaml_integration.py | 2 +- .../tests/test_invoke_mcp_tool_executor.py | 20 ++++++++--------- .../tests/test_workflow_factory.py | 8 +++---- 7 files changed, 30 insertions(+), 31 deletions(-) diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index efe9bcaead4..bd02a22bc1f 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -114,7 +114,7 @@ def reserve(self) -> None: WorkflowRunnerException: If the runner is already reserved or running. """ if self._lifecycle is not _RunnerLifecycle.IDLE: - raise WorkflowRunnerException("Runner is already running.") + raise WorkflowRunnerException("Runner is already reserved or running.") self._lifecycle = _RunnerLifecycle.RESERVED def release(self) -> None: diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 9135677cbab..4a36e395746 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -556,8 +556,7 @@ async def _run_workflow_with_tracing( self._runner.state.set(WORKFLOW_RUN_KWARGS_KEY, {}) self._runner.state.commit() # Commit immediately so kwargs are available - # Set streaming mode (always set explicitly per run since - # reset_for_new_run() no longer runs to clear it). + # Explicitly set streaming mode per run self._runner.context.set_streaming(streaming) # Execute initial setup if provided diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index 2c8ea4d22ff..0019ed1e92a 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -335,7 +335,7 @@ def test_runner_reserve_twice_raises(): """ runner = _make_runner() runner.reserve() - with pytest.raises(WorkflowRunnerException, match="Runner is already running."): + with pytest.raises(WorkflowRunnerException, match="Runner is already reserved or running."): runner.reserve() @@ -428,7 +428,7 @@ async def _slow_run(): await started.wait() # first run is now executing try: - with pytest.raises(WorkflowRunnerException, match="Runner is already running."): + with pytest.raises(WorkflowRunnerException, match="Runner is already reserved or running."): runner.reserve() finally: release.set() diff --git a/python/packages/declarative/tests/test_http_request_executor.py b/python/packages/declarative/tests/test_http_request_executor.py index 4030cf42946..f07f19d27a3 100644 --- a/python/packages/declarative/tests/test_http_request_executor.py +++ b/python/packages/declarative/tests/test_http_request_executor.py @@ -90,7 +90,7 @@ async def _run(yaml_def: dict[str, Any], handler: HttpRequestHandler) -> Any: def _state(workflow: Any, events: Any) -> dict[str, Any]: """Read declarative state out of the workflow after run completes.""" - return workflow._state.get(DECLARATIVE_STATE_KEY) or {} + return workflow._runner.state.get(DECLARATIVE_STATE_KEY) or {} # Helper used by parametrised path tests @@ -151,7 +151,7 @@ async def test_get_parses_json_object(self) -> None: workflow = factory.create_workflow_from_definition(_yaml(_action(method="GET", response="Local.Result"))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == {"key": "value", "number": 42} assert handler.last_info is not None assert handler.last_info.method == "GET" @@ -164,7 +164,7 @@ async def test_get_parses_plain_string(self) -> None: workflow = factory.create_workflow_from_definition(_yaml(_action(response="Local.Result"))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == "not-json content" @pytest.mark.asyncio @@ -174,7 +174,7 @@ async def test_get_empty_body_yields_none(self) -> None: workflow = factory.create_workflow_from_definition(_yaml(_action(response="Local.Result"))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] is None @pytest.mark.asyncio @@ -184,7 +184,7 @@ async def test_response_object_form_path(self) -> None: workflow = factory.create_workflow_from_definition(_yaml(_action(response={"path": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == {"x": 1} @pytest.mark.asyncio @@ -517,7 +517,7 @@ async def test_response_headers_folded_with_commas(self) -> None: factory = WorkflowFactory(http_request_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(response_headers="Local.H"))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) h = decl["Local"]["H"] assert h["Content-Type"] == "application/json" assert h["Set-Cookie"] == "a=1,b=2" @@ -528,7 +528,7 @@ async def test_response_headers_empty_assigned_none(self) -> None: factory = WorkflowFactory(http_request_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(response_headers="Local.H"))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["H"] is None @pytest.mark.asyncio @@ -538,7 +538,7 @@ async def test_non_2xx_still_publishes_headers(self) -> None: workflow = factory.create_workflow_from_definition(_yaml(_action(response_headers="Local.H"))) with pytest.raises(DeclarativeActionError): await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["H"] == {"X-Trace": "abc"} @@ -559,7 +559,7 @@ async def test_conversation_id_appends_message(self) -> None: ) ) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) conv = decl["System"]["conversations"].get("conv-test-1") assert conv is not None assert len(conv["messages"]) == 1 @@ -570,7 +570,7 @@ async def test_empty_conversation_id_does_not_append(self) -> None: factory = WorkflowFactory(http_request_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(response="Local.Result", conversation_id=""))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) # Auto-init creates an entry for the System.ConversationId conversation, # but it should NOT have HTTP-appended messages from us. for _cid, conv in decl["System"]["conversations"].items(): @@ -582,7 +582,7 @@ async def test_empty_body_skips_conversation_append(self) -> None: factory = WorkflowFactory(http_request_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(conversation_id="conv-test-1"))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) # No conversation entry should have been created either. assert "conv-test-1" not in decl["System"]["conversations"] diff --git a/python/packages/declarative/tests/test_http_request_yaml_integration.py b/python/packages/declarative/tests/test_http_request_yaml_integration.py index 49cd0d15e83..64454e2b841 100644 --- a/python/packages/declarative/tests/test_http_request_yaml_integration.py +++ b/python/packages/declarative/tests/test_http_request_yaml_integration.py @@ -73,7 +73,7 @@ async def test_http_request_yaml_roundtrip() -> None: workflow = factory.create_workflow_from_yaml_path(FIXTURE_PATH) await workflow.run({}) - decl: dict[str, Any] = workflow._state.get(DECLARATIVE_STATE_KEY) or {} + decl: dict[str, Any] = workflow._runner.state.get(DECLARATIVE_STATE_KEY) or {} local = decl.get("Local") or {} assert local.get("RepoOwner") == "dotnet" diff --git a/python/packages/declarative/tests/test_invoke_mcp_tool_executor.py b/python/packages/declarative/tests/test_invoke_mcp_tool_executor.py index fdee1f7df1d..cfff22b84ea 100644 --- a/python/packages/declarative/tests/test_invoke_mcp_tool_executor.py +++ b/python/packages/declarative/tests/test_invoke_mcp_tool_executor.py @@ -244,7 +244,7 @@ async def test_output_result_parses_json_text(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == [{"k": "v", "n": 1}] @pytest.mark.asyncio @@ -253,7 +253,7 @@ async def test_output_result_falls_back_to_raw_text(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == ["plain text not json"] @pytest.mark.asyncio @@ -262,7 +262,7 @@ async def test_output_messages_writes_single_tool_role_message(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"messages": "Local.Messages"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) msg = decl["Local"]["Messages"] # Single Tool-role message containing both contents (parity with .NET). assert isinstance(msg, Message) @@ -276,7 +276,7 @@ async def test_uri_content_serialised_as_uri_string(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == ["https://example.com/file.txt"] @pytest.mark.asyncio @@ -285,7 +285,7 @@ async def test_output_path_object_form(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": {"path": "Local.Result"}}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == ["ok"] @@ -306,7 +306,7 @@ async def test_conversation_id_appends_assistant_message(self) -> None: ) ) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) conv = decl["System"]["conversations"]["conv-42"] msgs = conv["messages"] if isinstance(conv, dict) else conv.messages assert len(msgs) == 1 @@ -328,7 +328,7 @@ async def test_empty_conversation_id_does_not_append(self) -> None: ) ) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) # Empty conversation id must not produce a `""` entry under System.conversations. conversations = decl.get("System", {}).get("conversations", {}) assert "" not in conversations @@ -562,7 +562,7 @@ async def test_handler_returns_error_result_assigns_error_string(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == "Error: server down" @pytest.mark.asyncio @@ -571,7 +571,7 @@ async def test_tool_execution_exception_becomes_error_result(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert decl["Local"]["Result"] == "Error: invalid arguments" @pytest.mark.asyncio @@ -580,7 +580,7 @@ async def test_httpx_error_becomes_error_result(self) -> None: factory = WorkflowFactory(mcp_tool_handler=handler) workflow = factory.create_workflow_from_definition(_yaml(_action(output={"result": "Local.Result"}))) await workflow.run({}) - decl = workflow._state.get(DECLARATIVE_STATE_KEY) + decl = workflow._runner.state.get(DECLARATIVE_STATE_KEY) result = decl["Local"]["Result"] assert isinstance(result, str) assert result.startswith("Error:") diff --git a/python/packages/declarative/tests/test_workflow_factory.py b/python/packages/declarative/tests/test_workflow_factory.py index f163cd18f0b..b6d0aaa6dad 100644 --- a/python/packages/declarative/tests/test_workflow_factory.py +++ b/python/packages/declarative/tests/test_workflow_factory.py @@ -289,11 +289,11 @@ async def test_as_agent_continuation_preserves_prior_state(self): # Stamp a marker into the declarative state between turns. The # continuation branch must preserve it; a state-clearing run would # wipe ``DECLARATIVE_STATE_KEY`` and force re-initialization. - state_data = workflow._state.get(DECLARATIVE_STATE_KEY) + state_data = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert isinstance(state_data, dict), "Expected declarative state to be initialized after turn 1" state_data["Local"] = {"persisted_marker": "kept-from-turn-1"} - workflow._state.set(DECLARATIVE_STATE_KEY, state_data) - workflow._state.commit() + workflow._runner.state.set(DECLARATIVE_STATE_KEY, state_data) + workflow._runner.state.commit() second = await agent.run("turn-2-msg") assert second.text == "turn-2-msg", ( @@ -303,7 +303,7 @@ async def test_as_agent_continuation_preserves_prior_state(self): # The continuation branch in ``_ensure_state_initialized`` must: # 1. preserve the cross-turn marker we stamped above # 2. refresh Inputs.input and System.LastMessage* to the new turn - post_state = workflow._state.get(DECLARATIVE_STATE_KEY) + post_state = workflow._runner.state.get(DECLARATIVE_STATE_KEY) assert isinstance(post_state, dict), "declarative state vanished between turns" local = post_state.get("Local", {}) assert local.get("persisted_marker") == "kept-from-turn-1", ( From 6eb85477fc6a8fa74121c1cbae13c24fe4be1851 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Tue, 9 Jun 2026 09:27:21 -0700 Subject: [PATCH 06/13] Remove lifecycle flag --- .../agent_framework/_workflows/_runner.py | 191 ++++++----------- .../agent_framework/_workflows/_workflow.py | 51 +++-- .../core/tests/workflow/test_runner.py | 196 ++---------------- .../core/tests/workflow/test_workflow.py | 89 +++++++- 4 files changed, 205 insertions(+), 322 deletions(-) diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index bd02a22bc1f..3c441863ecd 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -5,13 +5,11 @@ import logging from collections import defaultdict from collections.abc import AsyncGenerator, Sequence -from enum import Enum from typing import Any from ..exceptions import ( WorkflowCheckpointException, WorkflowConvergenceException, - WorkflowRunnerException, ) from ._checkpoint import CheckpointID, CheckpointStorage, WorkflowCheckpoint from ._const import EXECUTOR_STATE_KEY @@ -28,25 +26,6 @@ logger = logging.getLogger(__name__) -class _RunnerLifecycle(Enum): - """Lifecycle of a single :class:`Runner` invocation. - - Three states keep concurrent-run protection in one place while still letting - :meth:`Workflow.run` reserve the runner synchronously (before any await): - - * ``IDLE`` - no run in progress. - * ``RESERVED`` - :meth:`Runner.reserve` was called by an external caller but - :meth:`Runner.run_until_convergence` has not yet entered its body. This is the - window during which ``Workflow.run`` has handed back a ``ResponseStream`` that - hasn't been iterated yet. ``run_until_convergence`` requires this state. - * ``RUNNING`` - the body of :meth:`Runner.run_until_convergence` is executing. - """ - - IDLE = "idle" - RESERVED = "reserved" - RUNNING = "running" - - class Runner: """A class to run a workflow in Pregel supersteps.""" @@ -83,7 +62,6 @@ def __init__( self._iteration = 0 self._max_iterations = max_iterations self._state = state - self._lifecycle: _RunnerLifecycle = _RunnerLifecycle.IDLE self._resumed_from_checkpoint = False # Track whether we resumed @property @@ -96,31 +74,6 @@ def state(self) -> State: """Get the shared state for the workflow.""" return self._state - def reserve(self) -> None: - """Synchronously reserve the runner for an upcoming run. - - This is the **only** way to acquire the run lock. :meth:`run_until_convergence` - requires the runner to be in :attr:`_RunnerLifecycle.RESERVED` and will refuse - to start otherwise. Reserving synchronously lets callers (notably - :meth:`Workflow.run`) reject concurrent runs *before* any ``await`` or - async-generator suspension - otherwise a second caller could slip past a - flag-based guard while the first is still suspended above - :meth:`run_until_convergence`. The lock is released by - :meth:`run_until_convergence` in its ``finally`` clause once it begins, or by - :meth:`release` when the run never starts (for example, if early validation - raises before ``run_until_convergence`` is reached). - - Raises: - WorkflowRunnerException: If the runner is already reserved or running. - """ - if self._lifecycle is not _RunnerLifecycle.IDLE: - raise WorkflowRunnerException("Runner is already reserved or running.") - self._lifecycle = _RunnerLifecycle.RESERVED - - def release(self) -> None: - """Release the runner's run lock. Idempotent; safe to call when already idle.""" - self._lifecycle = _RunnerLifecycle.IDLE - def reset_iteration_count(self) -> None: """Reset the iteration count to zero. @@ -138,15 +91,10 @@ async def reset_for_new_run(self) -> None: This is useful when reusing the same workflow instance for a different run that is independent from prior runs. - Raises: - WorkflowRunnerException: If the runner is reserved or running. Reset is only - allowed when the runner is idle to avoid clobbering in-flight run state. + Concurrent-run rejection lives at the :class:`Workflow` level via the + active-run weak reference, so this method does not re-validate that + no run is in progress; callers are expected to have already done so. """ - if self._lifecycle is not _RunnerLifecycle.IDLE: - raise WorkflowRunnerException( - "Cannot reset the runner while a run is in progress. " - "Wait for the current run to complete before calling reset_for_new_run()." - ) self.reset_iteration_count() self._ctx.reset_for_new_run() self._state.clear() @@ -156,92 +104,79 @@ async def reset_for_new_run(self) -> None: async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: """Run the workflow until no more messages are sent.""" - # Mandatory reservation: callers must reserve() the runner first. This makes - # ``reserve`` the single entry point that takes the run lock, so all - # concurrent-run rejection happens there. Any non-RESERVED state here is a - # contract violation - either the caller forgot to reserve, or another run - # is already in progress. - if self._lifecycle is not _RunnerLifecycle.RESERVED: - raise WorkflowRunnerException( - "Runner must be reserved via Runner.reserve() before calling run_until_convergence()." - ) - self._lifecycle = _RunnerLifecycle.RUNNING - previous_checkpoint_id: CheckpointID | None = None - try: - # Emit any events already produced prior to entering loop - if await self._ctx.has_events(): - logger.info("Yielding pre-loop events") - for event in await self._ctx.drain_events(): - yield event - # Create the first checkpoint. Checkpoints are usually considered to be created at the end of an iteration, - # we can think of the first checkpoint as being created at the end of a "superstep 0" which captures the - # states after which the start executor has run. Note that we execute the start executor outside of the - # main iteration loop. - if await self._ctx.has_messages() and not self._resumed_from_checkpoint: - previous_checkpoint_id = await self._create_checkpoint_if_enabled(previous_checkpoint_id) - - while self._iteration < self._max_iterations: - logger.info(f"Starting superstep {self._iteration + 1}") - yield WorkflowEvent.superstep_started(iteration=self._iteration + 1) - - # Run iteration concurrently with live event streaming: we poll - # for new events while the iteration coroutine progresses. - iteration_task = asyncio.create_task(self._run_iteration()) - try: - while not iteration_task.done(): - try: - # Wait briefly for any new event; timeout allows progress checks - event = await asyncio.wait_for(self._ctx.next_event(), timeout=0.05) - yield event - except asyncio.TimeoutError: - # Periodically continue to let iteration advance - continue - except asyncio.CancelledError: - # Propagate cancellation to the iteration task to avoid orphaned work - iteration_task.cancel() - with contextlib.suppress(asyncio.CancelledError): - await iteration_task - raise - - # Propagate errors from iteration, but first surface any pending events - try: + # Emit any events already produced prior to entering loop + if await self._ctx.has_events(): + logger.info("Yielding pre-loop events") + for event in await self._ctx.drain_events(): + yield event + + # Create the first checkpoint. Checkpoints are usually considered to be created at the end of an iteration, + # we can think of the first checkpoint as being created at the end of a "superstep 0" which captures the + # states after which the start executor has run. Note that we execute the start executor outside of the + # main iteration loop. + if await self._ctx.has_messages() and not self._resumed_from_checkpoint: + previous_checkpoint_id = await self._create_checkpoint_if_enabled(previous_checkpoint_id) + + while self._iteration < self._max_iterations: + logger.info(f"Starting superstep {self._iteration + 1}") + yield WorkflowEvent.superstep_started(iteration=self._iteration + 1) + + # Run iteration concurrently with live event streaming: we poll + # for new events while the iteration coroutine progresses. + iteration_task = asyncio.create_task(self._run_iteration()) + try: + while not iteration_task.done(): + try: + # Wait briefly for any new event; timeout allows progress checks + event = await asyncio.wait_for(self._ctx.next_event(), timeout=0.05) + yield event + except asyncio.TimeoutError: + # Periodically continue to let iteration advance + continue + except asyncio.CancelledError: + # Propagate cancellation to the iteration task to avoid orphaned work + iteration_task.cancel() + with contextlib.suppress(asyncio.CancelledError): await iteration_task - except Exception: - # Make sure failure-related events (like ExecutorFailedEvent) are surfaced - if await self._ctx.has_events(): - for event in await self._ctx.drain_events(): - yield event - raise - self._iteration += 1 - - # Drain any straggler events emitted at tail end + raise + + # Propagate errors from iteration, but first surface any pending events + try: + await iteration_task + except Exception: + # Make sure failure-related events (like ExecutorFailedEvent) are surfaced if await self._ctx.has_events(): for event in await self._ctx.drain_events(): yield event + raise + self._iteration += 1 - logger.info(f"Completed superstep {self._iteration}") + # Drain any straggler events emitted at tail end + if await self._ctx.has_events(): + for event in await self._ctx.drain_events(): + yield event + + logger.info(f"Completed superstep {self._iteration}") - # Commit pending state changes at superstep boundary - self._state.commit() + # Commit pending state changes at superstep boundary + self._state.commit() - # Create checkpoint after each superstep iteration - previous_checkpoint_id = await self._create_checkpoint_if_enabled(previous_checkpoint_id) + # Create checkpoint after each superstep iteration + previous_checkpoint_id = await self._create_checkpoint_if_enabled(previous_checkpoint_id) - yield WorkflowEvent.superstep_completed(iteration=self._iteration) + yield WorkflowEvent.superstep_completed(iteration=self._iteration) - # Check for convergence: no more messages to process - if not await self._ctx.has_messages(): - break + # Check for convergence: no more messages to process + if not await self._ctx.has_messages(): + break - if self._iteration >= self._max_iterations and await self._ctx.has_messages(): - raise WorkflowConvergenceException(f"Runner did not converge after {self._max_iterations} iterations.") + if self._iteration >= self._max_iterations and await self._ctx.has_messages(): + raise WorkflowConvergenceException(f"Runner did not converge after {self._max_iterations} iterations.") - logger.info(f"Workflow completed after {self._iteration} supersteps") - self._resumed_from_checkpoint = False # Reset resume flag for next run - finally: - self._lifecycle = _RunnerLifecycle.IDLE + logger.info(f"Workflow completed after {self._iteration} supersteps") + self._resumed_from_checkpoint = False # Reset resume flag for next run async def _run_iteration(self) -> None: """Run a single iteration of the workflow. diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 4a36e395746..6e240a10968 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -11,6 +11,7 @@ import types import uuid import warnings +import weakref from collections.abc import AsyncIterable, Awaitable, Callable, Mapping, Sequence from dataclasses import dataclass, field from typing import TYPE_CHECKING, Any, Literal, overload @@ -362,6 +363,14 @@ def __init__( # for a freshly built workflow that has not yet been run. self._status: WorkflowRunState = WorkflowRunState.IDLE + # Weak reference to the in-flight run's ``ResponseStream``. Used as the single + # concurrency lock: if the previous stream is still alive, ``run()`` rejects a + # new run synchronously (before any await). When the stream is fully consumed + # ``_run_core``'s finally clears this; if the caller drops the stream without + # ever iterating, the weakref dereferences to ``None`` once Python collects it, + # so a subsequent ``run()`` is allowed. + self._active_run: weakref.ref[ResponseStream[WorkflowEvent, WorkflowRunResult]] | None = None + @property def status(self) -> WorkflowRunState: """Return the current run-level status of this workflow instance. @@ -734,16 +743,20 @@ def run( # Validate parameters first so misuse fails before we touch any run state. self._validate_run_params(message, responses, checkpoint_id) - # Acquire the run lock synchronously - before constructing the ResponseStream - # or yielding control to the event loop - so a second concurrent ``run`` call - # is rejected immediately rather than slipping past the guard while the first - # call is suspended inside its async generator. - try: - self._runner.reserve() - except WorkflowRunnerException as exc: + # Concurrency check: reject a second run synchronously - before constructing + # the ResponseStream or yielding control to the event loop - so a concurrent + # ``run`` call can't slip past the guard while the first call is suspended + # inside its async generator. The ``ResponseStream`` returned below is the + # lock: as long as the caller holds a reference to it, ``self._active_run()`` + # resolves to a live object and a new ``run`` is rejected. When the stream is + # fully consumed, ``_run_core``'s finally clears the attribute. When the + # caller drops the stream without iterating, garbage collection invalidates + # the weakref, so a subsequent ``run`` is permitted. + existing_stream = self._active_run() if self._active_run is not None else None + if existing_stream is not None: raise WorkflowException( "Workflow is already running; concurrent runs are not allowed on the same instance." - ) from exc + ) response_stream = ResponseStream[WorkflowEvent, WorkflowRunResult]( self._run_core( @@ -757,6 +770,7 @@ def run( ), finalizer=functools.partial(self._finalize_events, include_status_events=include_status_events), ) + self._active_run = weakref.ref(response_stream) if stream: return response_stream @@ -823,12 +837,14 @@ async def _run_core( continue yield event finally: - # Release the run lock acquired synchronously by ``run()`` via ``reserve``. - # ``run_until_convergence`` also clears it in its own ``finally`` once its - # body runs; this clause additionally covers the case where this generator - # raises (or is closed) before that body is reached - e.g. the in-flight - # messages check above. ``release`` is idempotent. - self._runner.release() + # Clear the active-run weakref so a subsequent ``run()`` is allowed. + # ``run()`` set this synchronously after constructing the ResponseStream; + # we clear it here once the run has finished (success, error, early + # close, or partial iteration). This is in-band, so by the time the + # caller's stream is later garbage collected, ``_active_run`` is already + # ``None`` (or has been replaced by a newer run's weakref) - no GC-time + # finalizer is needed. + self._active_run = None if checkpoint_storage is not None: self._runner.context.clear_runtime_checkpoint_storage() @@ -1161,4 +1177,11 @@ async def reset_for_new_run(self) -> None: allowed when the workflow is idle to avoid clobbering in-flight run state. """ + existing_stream = self._active_run() if self._active_run is not None else None + if existing_stream is not None: + raise WorkflowRunnerException( + "Cannot reset the workflow while a run is in progress. " + "Wait for the current run to complete before calling reset_for_new_run()." + ) + self._active_run = None await self._runner.reset_for_new_run() diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index 0019ed1e92a..b41e43beeed 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -17,7 +17,6 @@ WorkflowContext, WorkflowConvergenceException, WorkflowEvent, - WorkflowRunnerException, WorkflowRunState, handler, ) @@ -106,7 +105,6 @@ async def test_runner_run_until_convergence(): state, # state ctx, # runner_context ) - runner.reserve() async for event in runner.run_until_convergence(): assert isinstance(event, WorkflowEvent) if event.type == "output": @@ -148,7 +146,6 @@ async def test_runner_run_until_convergence_not_completed(): WorkflowConvergenceException, match="Runner did not converge after 5 iterations.", ): - runner.reserve() async for event in runner.run_until_convergence(): assert event.type != "status" or event.state != WorkflowRunState.IDLE @@ -307,16 +304,22 @@ async def handle(self, message: MockMessage, ctx: WorkflowContext[MockMessage, i assert probe_target.call_count == 1 -async def test_runner_run_until_convergence_requires_reservation(): - """run_until_convergence refuses to start without a prior reserve().""" +async def test_runner_run_until_convergence_runs_sequentially(): + """run_until_convergence can be invoked back-to-back on the same Runner. + + The Runner itself does not enforce concurrency; that responsibility lives on + :class:`Workflow`. This test simply confirms the Runner is reusable across + sequential runs. + """ runner = _make_runner() - with pytest.raises(WorkflowRunnerException, match="Runner must be reserved"): - async for _ in runner.run_until_convergence(): - pass + async for _ in runner.run_until_convergence(): + pass + async for _ in runner.run_until_convergence(): + pass def _make_runner() -> Runner: - """Build a minimal runner for lifecycle tests.""" + """Build a minimal runner for runner-level tests.""" return Runner( [], {}, @@ -327,57 +330,11 @@ def _make_runner() -> Runner: ) -def test_runner_reserve_twice_raises(): - """Calling reserve() while already reserved rejects the second caller. - - This is what guards Workflow.run against a concurrent caller slipping in - between the first call's synchronous reserve() and its first await. - """ - runner = _make_runner() - runner.reserve() - with pytest.raises(WorkflowRunnerException, match="Runner is already reserved or running."): - runner.reserve() - - -def test_runner_reserve_after_release_is_accepted(): - """Sequential runs are permitted; only concurrent ones are blocked.""" - runner = _make_runner() - runner.reserve() - runner.release() - runner.reserve() # should not raise - - -def test_runner_release_when_idle_is_noop(): - """release() on an idle runner does not affect a subsequent reserve(). - - Workflow._run_core's finally always calls release(), even when - run_until_convergence already cleared the lock in its own finally; - that double-release must not lock out the next run. - """ - runner = _make_runner() - runner.release() # already idle - must not raise or wedge state - runner.reserve() # next run still allowed - - -async def test_runner_run_until_convergence_consumes_reservation(): - """run_until_convergence accepts a prior reservation and runs to completion.""" - runner = _make_runner() - runner.reserve() - async for _ in runner.run_until_convergence(): - pass - # A second run after the first completes must be accepted. - runner.reserve() - async for _ in runner.run_until_convergence(): - pass - - async def test_runner_accepts_new_run_after_previous_failure(): - """A failed run must not leave the runner locked out of future runs. + """A failed run must not leave the Runner unable to start a new run. - After the first run raises, a fresh ``reserve()`` and - ``run_until_convergence()`` must succeed (or fail for a different reason - - e.g. residual messages still don't converge - but never with the - lock-rejection ``"Runner is already running."``). + After the first run raises, ``run_until_convergence()`` must be callable + again and not surface any lifecycle-related rejection. """ executor_a = MockExecutor(id="executor_a") executor_b = MockExecutor(id="executor_b") @@ -392,13 +349,12 @@ async def test_runner_accepts_new_run_after_previous_failure(): await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) - runner.reserve() with pytest.raises(WorkflowConvergenceException): async for _ in runner.run_until_convergence(): pass - # The runner should accept a fresh reservation and run again. - runner.reserve() # must not raise + # A second run on the same Runner must not be blocked by stale lifecycle + # state from the failed run. try: async for _ in runner.run_until_convergence(): pass @@ -406,40 +362,6 @@ async def test_runner_accepts_new_run_after_previous_failure(): assert "Runner is already running" not in str(exc), "Runner stayed locked after a failed run" -async def test_runner_rejects_concurrent_run_until_convergence(): - """While a run is in progress, a second ``reserve()`` is rejected. - - Confirms the run lock is held for the full duration of the run, not just - synchronously between ``reserve()`` and the first ``__anext__`` call. - """ - runner = _make_runner() - - started = asyncio.Event() - release = asyncio.Event() - - async def _slow_run(): - runner.reserve() - async for _ in runner.run_until_convergence(): - if not started.is_set(): - started.set() - await release.wait() - - task = asyncio.create_task(_slow_run()) - await started.wait() # first run is now executing - - try: - with pytest.raises(WorkflowRunnerException, match="Runner is already reserved or running."): - runner.reserve() - finally: - release.set() - await task - - # And after the first run finishes, a new reservation + run must be accepted. - runner.reserve() - async for _ in runner.run_until_convergence(): - pass - - async def test_runner_emits_runner_completion_for_agent_response_without_targets(): ctx = InProcRunnerContext() runner = Runner([], {}, State(), ctx, "test_name", graph_signature_hash="test_hash") @@ -451,7 +373,6 @@ async def test_runner_emits_runner_completion_for_agent_response_without_targets ) ) - runner.reserve() events: list[WorkflowEvent] = [event async for event in runner.run_until_convergence()] # The runner should complete without errors when handling AgentExecutorResponse without targets # No specific events are expected since there are no executors to process the message @@ -508,7 +429,6 @@ async def run_workflow(): async for _ in runner.run_until_convergence(): pass - runner.reserve() task = asyncio.create_task(run_workflow()) # Wait for executor_a to complete (0.3s) and executor_b to start but not finish @@ -570,7 +490,6 @@ async def test_runner_iteration_exception_drains_events(): ) events: list[WorkflowEvent] = [] - runner.reserve() with pytest.raises(RuntimeError, match="Simulated executor failure"): async for event in runner.run_until_convergence(): events.append(event) @@ -681,7 +600,6 @@ async def test_runner_checkpoint_creation_failure(): # Should complete without raising, even though checkpointing fails result: int | None = None - runner.reserve() async for event in runner.run_until_convergence(): if event.type == "output": result = event.data @@ -878,7 +796,6 @@ async def test_runner_with_pre_loop_events(): await ctx.add_event(WorkflowEvent("output", executor_id="test_executor", data="pre-loop-output")) events: list[WorkflowEvent] = [] - runner.reserve() async for event in runner.run_until_convergence(): events.append(event) @@ -926,7 +843,6 @@ async def test_runner_drains_straggler_events(): ) events: list[WorkflowEvent] = [] - runner.reserve() async for event in runner.run_until_convergence(): events.append(event) @@ -980,7 +896,6 @@ async def test_runner_checkpoint_with_resumed_flag(): ) # Run until convergence - runner.reserve() async for _ in runner.run_until_convergence(): pass @@ -1047,7 +962,6 @@ async def test_runner_drains_events_on_iteration_exception(): ) events: list[WorkflowEvent] = [] - runner.reserve() with pytest.raises(RuntimeError, match="Executor failed with pending events"): async for event in runner.run_until_convergence(): events.append(event) @@ -1104,7 +1018,6 @@ async def test_runner_drains_straggler_events_at_iteration_end(): ) events: list[WorkflowEvent] = [] - runner.reserve() async for event in runner.run_until_convergence(): events.append(event) @@ -1271,7 +1184,6 @@ async def test_runner_can_run_again_after_reset_for_new_run(): # First run: drives MockExecutor's loop until it yields the terminal value. await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) - runner.reserve() async for _ in runner.run_until_convergence(): pass assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage] @@ -1280,7 +1192,6 @@ async def test_runner_can_run_again_after_reset_for_new_run(): # Second run: must succeed cleanly using the same runner instance. await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) - runner.reserve() second_run_outputs: list[int] = [] async for event in runner.run_until_convergence(): if event.type == "output": @@ -1290,77 +1201,4 @@ async def test_runner_can_run_again_after_reset_for_new_run(): assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage] -async def test_runner_reset_for_new_run_rejected_when_reserved(): - """reset_for_new_run refuses to run when the runner is reserved but not yet running.""" - runner = _make_runner() - runner.reserve() - - with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"): - await runner.reset_for_new_run() - - -async def test_runner_reset_for_new_run_rejected_while_running(): - """reset_for_new_run refuses to run while a run is mid-execution.""" - runner = _make_runner() - - started = asyncio.Event() - release = asyncio.Event() - - async def _slow_run() -> None: - runner.reserve() - async for _ in runner.run_until_convergence(): - if not started.is_set(): - started.set() - await release.wait() - - task = asyncio.create_task(_slow_run()) - await started.wait() # first run is now executing inside run_until_convergence - - try: - with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"): - await runner.reset_for_new_run() - finally: - release.set() - await task - - # Once the run drained, reset must succeed again. - await runner.reset_for_new_run() - - -async def test_runner_reset_for_new_run_does_not_mutate_when_rejected(): - """When reset is rejected, the runner's iteration counter and state are untouched.""" - - class TrackingExecutor(MockExecutor): - def __init__(self, id: str) -> None: - super().__init__(id=id) - self.reset_calls = 0 - - async def reset(self) -> None: - self.reset_calls += 1 - - executor = TrackingExecutor(id="executor") - state = State() - state.set("preserved", 42) - state.commit() - - runner = Runner( - [], - {executor.id: executor}, - state, - InProcRunnerContext(), - "test_name", - graph_signature_hash="test_hash", - ) - runner._iteration = 7 # pyright: ignore[reportPrivateUsage] - runner.reserve() - - with pytest.raises(WorkflowRunnerException): - await runner.reset_for_new_run() - - # Nothing was mutated by the failed reset. - assert runner._iteration == 7 # pyright: ignore[reportPrivateUsage] - assert state.get("preserved") == 42 - assert executor.reset_calls == 0 - - # endregion: Tests for Runner.reset_for_new_run() diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index 9267a17f689..4e607ca8f9c 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -1,6 +1,7 @@ # Copyright (c) Microsoft. All rights reserved. import asyncio +import gc import tempfile from collections.abc import AsyncIterable, Awaitable, Sequence from dataclasses import dataclass, field @@ -846,6 +847,92 @@ async def consume_stream(): assert result.get_final_state() == WorkflowRunState.IDLE +async def test_workflow_sequential_runs_after_completion() -> None: + """A completed run must release the runner so the next ``run`` succeeds. + + This is the happy-path counterpart to the concurrent-run guard tests: + those tests verify that a *concurrent* run is rejected, but they do not + verify that the lock is actually released afterwards. This test + exercises that release path explicitly across the three call shapes + (non-streaming, streaming-iterated, streaming-via-get_final_response) + and across multiple consecutive turns to catch lock leaks. + """ + executor = IncrementExecutor(id="seq_executor", limit=3, increment=1) + workflow = WorkflowBuilder(start_executor=executor).build() + + # Non-streaming -> non-streaming + r1 = await workflow.run(NumberMessage(data=0)) + assert r1.get_final_state() == WorkflowRunState.IDLE + + r2 = await workflow.run(NumberMessage(data=0)) + assert r2.get_final_state() == WorkflowRunState.IDLE + + # Non-streaming -> streaming-iterated + stream_events: list[WorkflowEvent] = [] + async for event in workflow.run(NumberMessage(data=0), stream=True): + stream_events.append(event) + assert any(e.type == "status" and e.state == WorkflowRunState.IDLE for e in stream_events) + + # Streaming -> streaming via get_final_response (no manual iteration) + r3 = await workflow.run(NumberMessage(data=0), stream=True).get_final_response() + assert r3.get_final_state() == WorkflowRunState.IDLE + + # Streaming -> non-streaming (back to the start) + r4 = await workflow.run(NumberMessage(data=0)) + assert r4.get_final_state() == WorkflowRunState.IDLE + + +async def test_workflow_unconsumed_stream_releases_run_lock() -> None: + """An unconsumed stream must not leak the run lock. + + ``Workflow.run`` reserves the runner *synchronously* so that concurrent + callers are rejected immediately. The reservation is normally released + by ``_run_core``'s ``finally`` once the stream is iterated. If the + caller never iterates the stream, a GC-time finalizer must release the + reservation instead - otherwise every subsequent ``Workflow.run`` call + on this instance would fail with the concurrent-run error. + """ + executor = IncrementExecutor(id="unconsumed_stream_exec", limit=3, increment=1) + workflow = WorkflowBuilder(start_executor=executor).build() + + # Build a stream and immediately drop it without iterating. + stream = workflow.run(NumberMessage(data=0), stream=True) + assert stream is not None # silence unused-variable warnings; stream is GC'd below + del stream + gc.collect() + # Yield to the event loop so any scheduled finalizer work can run. + await asyncio.sleep(0) + + # The runner should be back to IDLE; a fresh run must succeed. + result = await workflow.run(NumberMessage(data=0)) + assert result.get_final_state() == WorkflowRunState.IDLE + + +async def test_workflow_unawaited_run_coroutine_releases_run_lock() -> None: + """An un-awaited non-streaming ``run()`` coroutine must also not leak the lock. + + ``Workflow.run`` (non-streaming) returns a coroutine produced by + ``ResponseStream.get_final_response``. The underlying ResponseStream is + held alive by that coroutine, so dropping the coroutine without + awaiting it must still release the reservation via the same GC-time + fallback used for unconsumed streams. + """ + executor = IncrementExecutor(id="unawaited_run_exec", limit=3, increment=1) + workflow = WorkflowBuilder(start_executor=executor).build() + + coro = workflow.run(NumberMessage(data=0)) + # Closing suppresses the "coroutine was never awaited" warning. We cast to + # ``Any`` because the typed return is ``Awaitable[...]``; in practice it is + # a coroutine that exposes ``close``. + cast(Any, coro).close() + del coro + gc.collect() + await asyncio.sleep(0) + + result = await workflow.run(NumberMessage(data=0)) + assert result.get_final_state() == WorkflowRunState.IDLE + + class _StreamingTestAgent(BaseAgent): """Test agent that supports both streaming and non-streaming modes.""" @@ -1397,7 +1484,7 @@ async def consume_stream_slowly() -> list[WorkflowEvent]: await asyncio.sleep(0.02) try: - with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"): + with pytest.raises(WorkflowRunnerException, match="Cannot reset the workflow while a run is in progress"): await workflow.reset_for_new_run() finally: await task From 47012f1dcfa68cb0254e360221058556b1774851 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Tue, 9 Jun 2026 11:02:17 -0700 Subject: [PATCH 07/13] Address comments --- .../_workflows/_runner_context.py | 1 + .../core/tests/workflow/test_runner.py | 18 +++ .../_magentic.py | 15 ++ .../orchestrations/tests/test_magentic.py | 132 ++++++++++++++++++ 4 files changed, 166 insertions(+) diff --git a/python/packages/core/agent_framework/_workflows/_runner_context.py b/python/packages/core/agent_framework/_workflows/_runner_context.py index 2e4901f4118..23a748f0beb 100644 --- a/python/packages/core/agent_framework/_workflows/_runner_context.py +++ b/python/packages/core/agent_framework/_workflows/_runner_context.py @@ -409,6 +409,7 @@ def reset_for_new_run(self) -> None: self._messages.clear() # Clear any pending events (best-effort) by recreating the queue self._event_queue = asyncio.Queue() + self._pending_request_info_events.clear() self._streaming = False # Reset streaming flag async def apply_checkpoint(self, checkpoint: WorkflowCheckpoint) -> None: diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index b41e43beeed..37c17fd1caf 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -1066,6 +1066,24 @@ async def test_runner_context_reset_resets_streaming_flag(): assert ctx.is_streaming() is False +async def test_runner_context_reset_clears_pending_request_info_events(): + """reset_for_new_run clears any pending request_info events tracked for correlation.""" + ctx = InProcRunnerContext() + request_info_event = WorkflowEvent.request_info( + request_id="request-123", + source_executor_id="source", + request_data=MockMessage(data=0), + response_type=bool, + ) + await ctx.add_request_info_event(request_info_event) + + assert "request-123" in await ctx.get_pending_request_info_events() + + ctx.reset_for_new_run() + + assert await ctx.get_pending_request_info_events() == {} + + # endregion: Tests for InProcRunnerContext.reset_for_new_run() diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py b/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py index ab79dbbfa3d..7288b67d2f8 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py @@ -509,6 +509,14 @@ def on_checkpoint_restore(self, state: dict[str, Any]) -> None: """Restore runtime state from checkpoint data.""" return + def on_reset(self) -> None: + """Reset per-run runtime state for a new workflow run. + + Subclasses should clear any state accumulated during a run (e.g. cached + ledgers, agent sessions) so the manager is ready to start fresh. + """ + return + class StandardMagenticManager(MagenticManagerBase): """Standard Magentic manager that performs real LLM calls via a Agent. @@ -761,6 +769,12 @@ def on_checkpoint_restore(self, state: dict[str, Any]) -> None: except Exception: # pragma: no cover - defensive logger.warning("Failed to restore manager agent session from checkpoint state") + @override + def on_reset(self) -> None: + """Clear cached ledger and start a fresh agent session for a new run.""" + self.task_ledger = None + self._session = self._agent.create_session() + # endregion Magentic Manager @@ -1270,6 +1284,7 @@ def _reset_pattern_state(self) -> None: self._task_ledger = None self._progress_ledger = None self._terminated = False + self._manager.on_reset() @override async def on_checkpoint_save(self) -> dict[str, Any]: diff --git a/python/packages/orchestrations/tests/test_magentic.py b/python/packages/orchestrations/tests/test_magentic.py index 615ba998bcc..343d4eff7a6 100644 --- a/python/packages/orchestrations/tests/test_magentic.py +++ b/python/packages/orchestrations/tests/test_magentic.py @@ -1243,3 +1243,135 @@ def test_standard_manager_checkpoint_restore_empty_state(): # endregion + + +# region Manager Reset Tests + + +def test_magentic_manager_base_on_reset_is_noop_by_default(): + """MagenticManagerBase.on_reset() is a no-op so subclasses can opt in.""" + mgr = FakeManager() + # Seed some state on the fake to confirm the base hook does not touch it. + mgr.task_ledger = _SimpleLedger( + facts=Message("assistant", ["facts"]), + plan=Message("assistant", ["plan"]), + ) + + mgr.on_reset() # base implementation is a no-op + + assert mgr.task_ledger is not None + + +def test_standard_manager_on_reset_clears_ledger_and_rotates_session(): + """StandardMagenticManager.on_reset() clears the cached ledger and creates a fresh session.""" + from agent_framework_orchestrations._magentic import _MagenticTaskLedger # type: ignore[reportPrivateUsage] + + agent = StubManagerAgent() + mgr = StandardMagenticManager(agent=agent) + mgr.task_ledger = _MagenticTaskLedger( + facts=Message("assistant", ["facts"]), + plan=Message("assistant", ["plan"]), + ) + original_session = mgr._session + + mgr.on_reset() + + assert mgr.task_ledger is None + assert mgr._session is not original_session + assert mgr._session.session_id != original_session.session_id + + +async def test_magentic_orchestrator_reset_invokes_manager_on_reset() -> None: + """_reset_pattern_state() clears orchestrator state and delegates to manager.on_reset().""" + from agent_framework_orchestrations._base_group_chat_orchestrator import ( + ParticipantRegistry, # type: ignore[reportPrivateUsage] + ) + + class TrackingManager(FakeManager): + reset_calls: int = 0 + + @override + def on_reset(self) -> None: + type(self).reset_calls += 1 + + manager = TrackingManager() + orchestrator = MagenticOrchestrator( + manager=manager, + participant_registry=ParticipantRegistry([]), + ) + # Seed magentic-specific state to confirm it is cleared. + orchestrator._magentic_context = MagenticContext( # type: ignore[reportPrivateUsage] + task="task", + participant_descriptions={"agentA": "desc"}, + ) + orchestrator._task_ledger = Message("assistant", ["ledger"]) # type: ignore[reportPrivateUsage] + orchestrator._progress_ledger = MagenticProgressLedger( # type: ignore[reportPrivateUsage] + is_request_satisfied=MagenticProgressLedgerItem(reason="r", answer=False), + is_in_loop=MagenticProgressLedgerItem(reason="r", answer=False), + is_progress_being_made=MagenticProgressLedgerItem(reason="r", answer=True), + next_speaker=MagenticProgressLedgerItem(reason="r", answer="agentA"), + instruction_or_question=MagenticProgressLedgerItem(reason="r", answer="do"), + ) + orchestrator._terminated = True # type: ignore[reportPrivateUsage] + + await orchestrator.reset() + + assert orchestrator._magentic_context is None # type: ignore[reportPrivateUsage] + assert orchestrator._task_ledger is None # type: ignore[reportPrivateUsage] + assert orchestrator._progress_ledger is None # type: ignore[reportPrivateUsage] + assert orchestrator._terminated is False # type: ignore[reportPrivateUsage] + assert TrackingManager.reset_calls == 1 + + +async def test_magentic_orchestrator_reset_propagates_manager_on_reset_failure() -> None: + """Failures in manager.on_reset() must propagate so callers can react.""" + from agent_framework_orchestrations._base_group_chat_orchestrator import ( + ParticipantRegistry, # type: ignore[reportPrivateUsage] + ) + + class FailingManager(FakeManager): + @override + def on_reset(self) -> None: + raise RuntimeError("boom") + + manager = FailingManager() + orchestrator = MagenticOrchestrator( + manager=manager, + participant_registry=ParticipantRegistry([]), + ) + + with pytest.raises(RuntimeError, match="boom"): + await orchestrator.reset() + + +async def test_workflow_reset_resets_magentic_orchestrator_and_manager() -> None: + """End-to-end: workflow.reset_for_new_run() resets Magentic orchestrator and manager state.""" + manager = FakeManager() + manager.task_ledger = _SimpleLedger( + facts=Message("assistant", ["seeded facts"]), + plan=Message("assistant", ["seeded plan"]), + ) + workflow = MagenticBuilder( + participants=[StubAgent(manager.next_speaker_name, "first draft")], + manager=manager, + ).build() + + async for _ in workflow.run("first task", stream=True): + pass + + orchestrator = next(e for e in workflow.executors.values() if isinstance(e, MagenticOrchestrator)) + assert orchestrator._terminated is True # type: ignore[reportPrivateUsage] + assert orchestrator._task_ledger is not None # type: ignore[reportPrivateUsage] + assert manager.task_ledger is not None + + await workflow.reset_for_new_run() + + assert orchestrator._magentic_context is None # type: ignore[reportPrivateUsage] + assert orchestrator._task_ledger is None # type: ignore[reportPrivateUsage] + assert orchestrator._progress_ledger is None # type: ignore[reportPrivateUsage] + assert orchestrator._terminated is False # type: ignore[reportPrivateUsage] + # FakeManager.on_reset is the base no-op, but the orchestrator still tolerates that case. + # For the standard manager we exercise full clearing in the dedicated unit test above. + + +# endregion From 0e3831192a62c48fbd34a4c655335fbd3c4d1b2b Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Wed, 10 Jun 2026 16:36:15 -0700 Subject: [PATCH 08/13] Fix checkpoint ancestry bug --- .../agent_framework/_workflows/_runner.py | 43 ++++++--- .../core/tests/workflow/test_checkpoint.py | 91 ++++++++++++++++++ .../core/tests/workflow/test_runner.py | 96 ++++++++++++++++++- 3 files changed, 213 insertions(+), 17 deletions(-) diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index 3c441863ecd..124cc2fb572 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -62,7 +62,10 @@ def __init__( self._iteration = 0 self._max_iterations = max_iterations self._state = state - self._resumed_from_checkpoint = False # Track whether we resumed + + # Checkpointing related attributes + self._resumed_from_checkpoint = False + self._previous_checkpoint_id: CheckpointID | None = None @property def context(self) -> RunnerContext: @@ -104,8 +107,6 @@ async def reset_for_new_run(self) -> None: async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: """Run the workflow until no more messages are sent.""" - previous_checkpoint_id: CheckpointID | None = None - # Emit any events already produced prior to entering loop if await self._ctx.has_events(): logger.info("Yielding pre-loop events") @@ -117,7 +118,7 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: # states after which the start executor has run. Note that we execute the start executor outside of the # main iteration loop. if await self._ctx.has_messages() and not self._resumed_from_checkpoint: - previous_checkpoint_id = await self._create_checkpoint_if_enabled(previous_checkpoint_id) + await self._create_checkpoint_if_enabled() while self._iteration < self._max_iterations: logger.info(f"Starting superstep {self._iteration + 1}") @@ -164,7 +165,7 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: self._state.commit() # Create checkpoint after each superstep iteration - previous_checkpoint_id = await self._create_checkpoint_if_enabled(previous_checkpoint_id) + await self._create_checkpoint_if_enabled() yield WorkflowEvent.superstep_completed(iteration=self._iteration) @@ -230,10 +231,10 @@ async def _deliver_messages_for_edge_runner(edge_runner: EdgeRunner) -> None: ] await asyncio.gather(*tasks) - async def _create_checkpoint_if_enabled(self, previous_checkpoint_id: CheckpointID | None) -> CheckpointID | None: + async def _create_checkpoint_if_enabled(self) -> None: """Create a checkpoint if checkpointing is enabled and attach a label and metadata.""" if not self._ctx.has_checkpointing(): - return None + return try: # Save executor states into the shared state before creating the checkpoint, @@ -248,15 +249,26 @@ async def _create_checkpoint_if_enabled(self, previous_checkpoint_id: Checkpoint self._workflow_name, self._graph_signature_hash, self._state, - previous_checkpoint_id, + self._previous_checkpoint_id, self._iteration, ) - logger.info(f"Created checkpoint: {checkpoint_id}") - return checkpoint_id + logger.info( + "Created checkpoint: %s with parent checkpoint at iteration %d: %s", + checkpoint_id, + self._iteration, + self._previous_checkpoint_id, + ) + self._previous_checkpoint_id = checkpoint_id except Exception as e: - logger.warning(f"Failed to create checkpoint: {e}") - return None + logger.warning( + "Failed to create checkpoint at iteration %d: %s. " + "Note that this does not fail the workflow run. " + "The next successfully-created checkpoint will be parented to the last successful checkpoint: %s", + self._iteration, + e, + self._previous_checkpoint_id, + ) async def restore_from_checkpoint( self, @@ -311,7 +323,7 @@ async def restore_from_checkpoint( # Apply the checkpoint to the context await self._ctx.apply_checkpoint(checkpoint) # Mark the runner as resumed - self._mark_resumed(checkpoint.iteration_count) + self._mark_resumed(checkpoint) logger.info(f"Successfully restored workflow from checkpoint: {checkpoint_id}") except WorkflowCheckpointException: @@ -377,13 +389,14 @@ def _parse_edge_runners(self, edge_runners: list[EdgeRunner]) -> dict[str, list[ return parsed - def _mark_resumed(self, iteration: int) -> None: + def _mark_resumed(self, checkpoint: WorkflowCheckpoint) -> None: """Mark the runner as having resumed from a checkpoint. Optionally set the current iteration and max iterations. """ self._resumed_from_checkpoint = True - self._iteration = iteration + self._iteration = checkpoint.iteration_count + self._previous_checkpoint_id = checkpoint.checkpoint_id async def _set_executor_state(self, executor_id: str, state: dict[str, Any]) -> None: """Store executor state in state under a reserved key. diff --git a/python/packages/core/tests/workflow/test_checkpoint.py b/python/packages/core/tests/workflow/test_checkpoint.py index e395655afaf..fe1df65822d 100644 --- a/python/packages/core/tests/workflow/test_checkpoint.py +++ b/python/packages/core/tests/workflow/test_checkpoint.py @@ -336,6 +336,97 @@ async def finish(self, message: str, ctx: WorkflowContext[Never, str]) -> None: ) +async def test_workflow_checkpoint_ancestry_preserved_after_resume(): + """Resuming from a checkpoint must preserve ancestry: future checkpoints chain back to the resumed one.""" + from typing_extensions import Never + + from agent_framework import WorkflowBuilder, WorkflowContext, handler + from agent_framework._workflows._executor import Executor + + class StartExecutor(Executor): + @handler + async def run(self, message: str, ctx: WorkflowContext[str]) -> None: + await ctx.send_message(message, target_id="middle") + + class MiddleExecutor(Executor): + @handler + async def process(self, message: str, ctx: WorkflowContext[str]) -> None: + await ctx.send_message(message + "-processed", target_id="finish") + + class FinishExecutor(Executor): + @handler + async def finish(self, message: str, ctx: WorkflowContext[Never, str]) -> None: + await ctx.yield_output(message + "-done") + + storage = InMemoryCheckpointStorage() + + def _build_workflow() -> Any: + start = StartExecutor(id="start") + middle = MiddleExecutor(id="middle") + finish = FinishExecutor(id="finish") + return ( + WorkflowBuilder( + name="resume-ancestry-test", + max_iterations=10, + start_executor=start, + checkpoint_storage=storage, + ) + .add_edge(start, middle) + .add_edge(middle, finish) + .build() + ) + + # First run: produce an initial chain of checkpoints + workflow = _build_workflow() + workflow_name = workflow.name + _ = [event async for event in workflow.run("hello", stream=True)] + + initial_checkpoints = sorted(await storage.list_checkpoints(workflow_name=workflow_name), key=lambda c: c.timestamp) + assert len(initial_checkpoints) >= 3, ( + f"Need at least 3 initial checkpoints to pick a middle one, got {len(initial_checkpoints)}" + ) + initial_ids = {cp.checkpoint_id for cp in initial_checkpoints} + + # Pick an intermediate checkpoint to resume from (not the first, not the last) + resume_from = initial_checkpoints[len(initial_checkpoints) // 2] + + # Resume on a fresh workflow instance (same graph signature) and run to completion + resumed_workflow = _build_workflow() + assert resumed_workflow.name == workflow_name + _ = [event async for event in resumed_workflow.run(checkpoint_id=resume_from.checkpoint_id, stream=True)] + + # Inspect new checkpoints created after resuming + all_checkpoints = sorted(await storage.list_checkpoints(workflow_name=workflow_name), key=lambda c: c.timestamp) + new_checkpoints = [cp for cp in all_checkpoints if cp.checkpoint_id not in initial_ids] + assert new_checkpoints, "Resuming from an intermediate checkpoint should produce new checkpoints" + + # The very first checkpoint created after resuming must chain back to the resumed checkpoint + assert new_checkpoints[0].previous_checkpoint_id == resume_from.checkpoint_id, ( + "First post-resume checkpoint must chain to the checkpoint that was resumed from; " + f"got previous_checkpoint_id={new_checkpoints[0].previous_checkpoint_id!r}, " + f"expected {resume_from.checkpoint_id!r}" + ) + + # Subsequent post-resume checkpoints must continue chaining + for i in range(1, len(new_checkpoints)): + assert new_checkpoints[i].previous_checkpoint_id == new_checkpoints[i - 1].checkpoint_id, ( + f"Post-resume checkpoint {i} should chain to checkpoint {i - 1}" + ) + + # Walking the chain backwards from the most recent checkpoint must reach the original root + # without breaks (i.e. the full ancestry across the resume boundary is intact). + checkpoints_by_id = {cp.checkpoint_id: cp for cp in all_checkpoints} + chain: list[str] = [] + cursor: str | None = new_checkpoints[-1].checkpoint_id + while cursor is not None: + chain.append(cursor) + cursor = checkpoints_by_id[cursor].previous_checkpoint_id + # Chain must include the resumed-from checkpoint and terminate at the original root + assert resume_from.checkpoint_id in chain + assert chain[-1] == initial_checkpoints[0].checkpoint_id + assert checkpoints_by_id[chain[-1]].previous_checkpoint_id is None + + async def test_memory_checkpoint_storage_roundtrip_json_native_types(): """Test that JSON-native types (str, int, float, bool, None) roundtrip correctly.""" storage = InMemoryCheckpointStorage() diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index 37c17fd1caf..6199bcd8ecc 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -883,7 +883,13 @@ async def test_runner_checkpoint_with_resumed_flag(): state = State() runner = Runner(edges, executors, state, ctx, "test_name", graph_signature_hash="test_hash") - runner._mark_resumed(5) # pyright: ignore[reportPrivateUsage] + resumed_checkpoint = WorkflowCheckpoint( + checkpoint_id="resumed-cp", + workflow_name="test_name", + graph_signature_hash="test_hash", + iteration_count=5, + ) + runner._mark_resumed(resumed_checkpoint) # pyright: ignore[reportPrivateUsage] # Add a message to trigger the checkpoint creation path await ctx.send_message(WorkflowMessage(data=MockMessage(data=8), source_id="START")) @@ -903,6 +909,86 @@ async def test_runner_checkpoint_with_resumed_flag(): assert runner._resumed_from_checkpoint is False # pyright: ignore[reportPrivateUsage] +async def test_runner_mark_resumed_sets_previous_checkpoint_id(): + """_mark_resumed must populate _previous_checkpoint_id so future checkpoints chain back to the resume point.""" + runner = Runner( + [], + {}, + State(), + InProcRunnerContext(), + "test_name", + graph_signature_hash="test_hash", + ) + + # Pre-condition: nothing to chain back to + assert runner._previous_checkpoint_id is None # pyright: ignore[reportPrivateUsage] + + resumed_checkpoint = WorkflowCheckpoint( + checkpoint_id="resumed-cp-id", + workflow_name="test_name", + graph_signature_hash="test_hash", + iteration_count=3, + ) + runner._mark_resumed(resumed_checkpoint) # pyright: ignore[reportPrivateUsage] + + assert runner._resumed_from_checkpoint is True # pyright: ignore[reportPrivateUsage] + assert runner._iteration == 3 # pyright: ignore[reportPrivateUsage] + assert runner._previous_checkpoint_id == "resumed-cp-id" # pyright: ignore[reportPrivateUsage] + + +async def test_runner_post_resume_checkpoint_chains_to_resumed_checkpoint(): + """After resuming, the next checkpoint created must reference the resumed checkpoint as its parent.""" + storage = InMemoryCheckpointStorage() + ctx = CheckpointingContext(storage) + executor_a = MockExecutor(id="executor_a") + executor_b = MockExecutor(id="executor_b") + + edges = [ + SingleEdgeGroup(executor_a.id, executor_b.id), + SingleEdgeGroup(executor_b.id, executor_a.id), + ] + + executors: dict[str, Executor] = { + executor_a.id: executor_a, + executor_b.id: executor_b, + } + state = State() + + runner = Runner(edges, executors, state, ctx, "test_name", graph_signature_hash="test_hash") + + # Simulate having resumed from a prior checkpoint + resumed_checkpoint = WorkflowCheckpoint( + checkpoint_id="parent-checkpoint-id", + workflow_name="test_name", + graph_signature_hash="test_hash", + iteration_count=1, + ) + runner._mark_resumed(resumed_checkpoint) # pyright: ignore[reportPrivateUsage] + + # Seed a message so the runner has work to do (and creates checkpoints at superstep boundaries) + await ctx.send_message(WorkflowMessage(data=MockMessage(data=8), source_id=executor_a.id)) + + async for _ in runner.run_until_convergence(): + pass + + # Find the first checkpoint created after the resume point (across all workflows tracked by storage) + new_checkpoints = sorted( + await storage.list_checkpoints(workflow_name="test_name"), + key=lambda c: c.timestamp, + ) + assert new_checkpoints, "Resuming and running should produce at least one new checkpoint" + + # The first new checkpoint must chain to the resumed-from checkpoint, not to None + assert new_checkpoints[0].previous_checkpoint_id == "parent-checkpoint-id", ( + "First post-resume checkpoint must chain to the resumed checkpoint id; " + f"got {new_checkpoints[0].previous_checkpoint_id!r}" + ) + + # Subsequent post-resume checkpoints continue the chain + for i in range(1, len(new_checkpoints)): + assert new_checkpoints[i].previous_checkpoint_id == new_checkpoints[i - 1].checkpoint_id + + class ExecutorThatFailsWithEvents(Executor): """An executor that emits events and then raises an exception after receiving messages.""" @@ -1127,7 +1213,13 @@ async def test_runner_reset_for_new_run_clears_shared_state(): async def test_runner_reset_for_new_run_clears_resumed_from_checkpoint_flag(): """reset_for_new_run clears the flag set by restore_from_checkpoint.""" runner = _make_runner() - runner._mark_resumed(iteration=5) # pyright: ignore[reportPrivateUsage] + resumed_checkpoint = WorkflowCheckpoint( + checkpoint_id="resumed-cp", + workflow_name="test_name", + graph_signature_hash="test_hash", + iteration_count=5, + ) + runner._mark_resumed(resumed_checkpoint) # pyright: ignore[reportPrivateUsage] assert runner._resumed_from_checkpoint is True # pyright: ignore[reportPrivateUsage] await runner.reset_for_new_run() From 6534a739d04d0868b47d8c5e3f746ddc000e450a Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Wed, 10 Jun 2026 22:20:10 -0700 Subject: [PATCH 09/13] Add create checkpoint to workflow interface --- .../packages/core/agent_framework/__init__.py | 4 +- .../agent_framework/_workflows/_runner.py | 26 +++--- .../agent_framework/_workflows/_workflow.py | 50 +++++++++++- .../core/tests/workflow/test_runner.py | 4 +- .../_responses.py | 81 +++++++++---------- 5 files changed, 103 insertions(+), 62 deletions(-) diff --git a/python/packages/core/agent_framework/__init__.py b/python/packages/core/agent_framework/__init__.py index 33d16cd9bbb..1c1a78a9f07 100644 --- a/python/packages/core/agent_framework/__init__.py +++ b/python/packages/core/agent_framework/__init__.py @@ -242,6 +242,7 @@ ) from ._workflows._agent_utils import resolve_agent_id from ._workflows._checkpoint import ( + CheckpointID, CheckpointStorage, FileCheckpointStorage, InMemoryCheckpointStorage, @@ -285,7 +286,6 @@ workflow, ) from ._workflows._request_info_mixin import response_handler -from ._workflows._runner import Runner from ._workflows._runner_context import ( InProcRunnerContext, RunnerContext, @@ -379,6 +379,7 @@ "ChatResponse", "ChatResponseUpdate", "CheckResult", + "CheckpointID", "CheckpointStorage", "ClassSkill", "CompactionProvider", @@ -470,7 +471,6 @@ "RoleLiteral", "RubricScore", "RunContext", - "Runner", "RunnerContext", "SecretString", "SelectiveToolCallCompactionStrategy", diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index 124cc2fb572..28f1bec7d53 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -65,7 +65,7 @@ def __init__( # Checkpointing related attributes self._resumed_from_checkpoint = False - self._previous_checkpoint_id: CheckpointID | None = None + self.previous_checkpoint_id: CheckpointID | None = None @property def context(self) -> RunnerContext: @@ -113,12 +113,12 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: for event in await self._ctx.drain_events(): yield event - # Create the first checkpoint. Checkpoints are usually considered to be created at the end of an iteration, - # we can think of the first checkpoint as being created at the end of a "superstep 0" which captures the - # states after which the start executor has run. Note that we execute the start executor outside of the - # main iteration loop. + # Create a checkpoint before a run starts. Checkpoints are usually considered to be created at the + # end of an iteration, we can think of this checkpoint as being created at the end of a "superstep 0" + # which captures the states after which the start executor has run. Note that we execute the start + # executor outside of the main iteration loop. if await self._ctx.has_messages() and not self._resumed_from_checkpoint: - await self._create_checkpoint_if_enabled() + await self.create_checkpoint_if_enabled() while self._iteration < self._max_iterations: logger.info(f"Starting superstep {self._iteration + 1}") @@ -165,7 +165,7 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: self._state.commit() # Create checkpoint after each superstep iteration - await self._create_checkpoint_if_enabled() + await self.create_checkpoint_if_enabled() yield WorkflowEvent.superstep_completed(iteration=self._iteration) @@ -231,7 +231,7 @@ async def _deliver_messages_for_edge_runner(edge_runner: EdgeRunner) -> None: ] await asyncio.gather(*tasks) - async def _create_checkpoint_if_enabled(self) -> None: + async def create_checkpoint_if_enabled(self) -> None: """Create a checkpoint if checkpointing is enabled and attach a label and metadata.""" if not self._ctx.has_checkpointing(): return @@ -249,7 +249,7 @@ async def _create_checkpoint_if_enabled(self) -> None: self._workflow_name, self._graph_signature_hash, self._state, - self._previous_checkpoint_id, + self.previous_checkpoint_id, self._iteration, ) @@ -257,9 +257,9 @@ async def _create_checkpoint_if_enabled(self) -> None: "Created checkpoint: %s with parent checkpoint at iteration %d: %s", checkpoint_id, self._iteration, - self._previous_checkpoint_id, + self.previous_checkpoint_id, ) - self._previous_checkpoint_id = checkpoint_id + self.previous_checkpoint_id = checkpoint_id except Exception as e: logger.warning( "Failed to create checkpoint at iteration %d: %s. " @@ -267,7 +267,7 @@ async def _create_checkpoint_if_enabled(self) -> None: "The next successfully-created checkpoint will be parented to the last successful checkpoint: %s", self._iteration, e, - self._previous_checkpoint_id, + self.previous_checkpoint_id, ) async def restore_from_checkpoint( @@ -396,7 +396,7 @@ def _mark_resumed(self, checkpoint: WorkflowCheckpoint) -> None: """ self._resumed_from_checkpoint = True self._iteration = checkpoint.iteration_count - self._previous_checkpoint_id = checkpoint.checkpoint_id + self.previous_checkpoint_id = checkpoint.checkpoint_id async def _set_executor_state(self, executor_id: str, state: dict[str, Any]) -> None: """Store executor state in state under a reserved key. diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 6e240a10968..5c9a78dd75b 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -18,9 +18,9 @@ from .._sessions import ContextProvider from .._types import ResponseStream -from ..exceptions import WorkflowException, WorkflowRunnerException +from ..exceptions import WorkflowCheckpointException, WorkflowException, WorkflowRunnerException from ..observability import OtelAttr, capture_exception, create_workflow_span -from ._checkpoint import CheckpointStorage +from ._checkpoint import CheckpointID, CheckpointStorage from ._const import DEFAULT_MAX_ITERATIONS, GLOBAL_KWARGS_KEY, WORKFLOW_RUN_KWARGS_KEY from ._edge import ( EdgeGroup, @@ -474,6 +474,43 @@ def get_executors_list(self) -> list[Executor]: """Get the list of executors in the workflow.""" return list(self.executors.values()) + async def create_checkpoint(self, checkpoint_storage: CheckpointStorage | None) -> CheckpointID: + """Create a checkpoint of the current workflow state in the provided storage. + + Args: + checkpoint_storage: The CheckpointStorage instance where the checkpoint will be stored. + If None, will use the workflow's default checkpoint storage if configured, or raise + if checkpointing is not enabled. + + Notes: + - Checkpoints can only be created when the workflow is idle (not actively running). + - Checkpoints are automatically created at the end of each superstep if a checkpoint storage is configured. + Use this method only when necessary, for example to capture the initial state of the workflow prior to the + first run. + - Creating a checkpoint manually will alter the checkpoint lineage. The new checkpoint will become the + parent of the next checkpoint created automatically (if checkpointing is enabled by providing a storage). + """ + if self._is_run_active(): + raise WorkflowException( + "Cannot create checkpoint while a workflow run is active. " + "Checkpointing is only allowed between runs when the workflow is idle." + ) + + if checkpoint_storage is None and not self._runner.context.has_checkpointing(): + raise WorkflowCheckpointException( + "Checkpoint storage must be provided to create a checkpoint when checkpointing is not enabled." + ) + if checkpoint_storage is not None: + self._runner.context.set_runtime_checkpoint_storage(checkpoint_storage) + + try: + await self._runner.create_checkpoint_if_enabled() + if self._runner.previous_checkpoint_id is None: + raise WorkflowCheckpointException("Failed to create checkpoint.") + return self._runner.previous_checkpoint_id + finally: + self._runner.context.clear_runtime_checkpoint_storage() + async def _run_workflow_with_tracing( self, initial_executor_fn: Callable[[], Awaitable[None]] | None = None, @@ -1165,6 +1202,15 @@ def as_agent( **kwargs, ) + def _is_run_active(self) -> bool: + """Check if a workflow run is currently active. + + Returns: + True if a run is active, False otherwise. + """ + existing_stream = self._active_run() if self._active_run is not None else None + return existing_stream is not None + async def reset_for_new_run(self) -> None: """Reset the workflow for a new run that is independent from prior runs. diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index 6199bcd8ecc..f6b36ebe32d 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -921,7 +921,7 @@ async def test_runner_mark_resumed_sets_previous_checkpoint_id(): ) # Pre-condition: nothing to chain back to - assert runner._previous_checkpoint_id is None # pyright: ignore[reportPrivateUsage] + assert runner.previous_checkpoint_id is None resumed_checkpoint = WorkflowCheckpoint( checkpoint_id="resumed-cp-id", @@ -933,7 +933,7 @@ async def test_runner_mark_resumed_sets_previous_checkpoint_id(): assert runner._resumed_from_checkpoint is True # pyright: ignore[reportPrivateUsage] assert runner._iteration == 3 # pyright: ignore[reportPrivateUsage] - assert runner._previous_checkpoint_id == "resumed-cp-id" # pyright: ignore[reportPrivateUsage] + assert runner.previous_checkpoint_id == "resumed-cp-id" async def test_runner_post_resume_checkpoint_chains_to_resumed_checkpoint(): diff --git a/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py b/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py index 498879861b1..1a5b0e32d00 100644 --- a/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py +++ b/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py @@ -17,6 +17,7 @@ from agent_framework import ( ChatOptions, + CheckpointID, Content, ContextProvider, FileCheckpointStorage, @@ -343,6 +344,7 @@ class ResponsesHostServer(ResponsesAgentServerHost): # TODO(@taochen): Allow a different checkpoint storage that stores checkpoints externally CHECKPOINT_STORAGE_PATH = "/.checkpoints" + INITIAL_CHECKPOINT_STORAGE_NAME = "initial" FUNCTION_APPROVAL_STORAGE_PATH = "/.function_approvals/approval_requests.json" def __init__( @@ -386,7 +388,6 @@ def __init__( ) self._is_workflow_agent = False - self._checkpoint_storage_path = None if isinstance(agent, WorkflowAgent): if agent.workflow._runner_context.has_checkpointing(): # pyright: ignore[reportPrivateUsage] raise RuntimeError( @@ -399,6 +400,12 @@ def __init__( else os.path.join(os.getcwd(), self.CHECKPOINT_STORAGE_PATH.lstrip("/")) ) self._is_workflow_agent = True + # The initial checkpoint storage that stores the workflow's initial state. We will use this checkpoint + # to restore the workflow when no conversation_id or previous_response_id is supplied in a request. + self._initial_checkpoint_storage = _checkpoint_storage_for_context( + self._checkpoint_storage_path, self.INITIAL_CHECKPOINT_STORAGE_NAME + ) + self._initial_checkpoint_id: CheckpointID | None = None self._agent = agent self._approval_storage = ( @@ -580,8 +587,6 @@ async def _handle_inner_workflow( # The following should never happen due to the checks above. # This is for type safety and defensive programming. - if self._checkpoint_storage_path is None: - raise RuntimeError("Checkpoint storage path is not configured for workflow agent.") if not isinstance(self._agent, WorkflowAgent): raise RuntimeError("Agent is not a workflow agent.") @@ -590,6 +595,12 @@ async def _handle_inner_workflow( # any future async resources owned by the workflow are entered here. await self._ensure_agent_ready() + # Create a checkpoint to store the initial state of the workflow, if it doesn't already exist. + # This allows us to restore to a clean slate when no conversation_id or previous_response_id + # is supplied in a request. + if self._initial_checkpoint_id is None: + self._initial_checkpoint_id = await self._agent.workflow.create_checkpoint(self._initial_checkpoint_storage) + # Determine the latest checkpoint (if any) so we can resume the # workflow's prior state for this turn. The directory is keyed by # the inbound context id (conversation_id when set, otherwise @@ -599,15 +610,36 @@ async def _handle_inner_workflow( # the only place that state lives is the workflow checkpoint, so # on every turn we restore the latest checkpoint and feed the new # input back into the start executor as a continuation rather than - # a fresh run. - latest_checkpoint_id: str | None = None - restore_storage: FileCheckpointStorage | None = None + # a fresh run. If no conversation_id or previous_response_id is + # supplied, the workflow will be restored to the initial checkpoint + # to avoid context bleed between requests. + latest_checkpoint_id: str = self._initial_checkpoint_id + restore_storage: FileCheckpointStorage = self._initial_checkpoint_storage if context_id is not None: restore_storage = _checkpoint_storage_for_context(self._checkpoint_storage_path, context_id) latest_checkpoint = await restore_storage.get_latest(workflow_name=self._agent.workflow.name) if latest_checkpoint is not None: latest_checkpoint_id = latest_checkpoint.checkpoint_id + # Restore the workflow to the latest checkpoint and run it with the + # new input. Events (including request info events) will not be emitted + # during restoration (in streaming) or after restoration (in non-streaming) + # since we assume the client had already seen those events and we don't want + # to emit duplicates. + if is_streaming_request: + async for _ in self._agent.run( + stream=True, + checkpoint_id=latest_checkpoint_id, + checkpoint_storage=restore_storage, + ): + pass + else: + await self._agent.run( + stream=False, + checkpoint_id=latest_checkpoint_id, + checkpoint_storage=restore_storage, + ) + # Storage that will receive checkpoints written during this turn. # When the caller chains with previous_response_id, the next turn # will reference the current response_id as its previous_response_id, @@ -619,43 +651,6 @@ async def _handle_inner_workflow( write_context_id = context.conversation_id or context.response_id write_storage = _checkpoint_storage_for_context(self._checkpoint_storage_path, write_context_id) - # Multi-turn pattern: when we have a prior checkpoint, restore it - # first (drive the workflow back to idle with prior state intact), - # then make a separate call that delivers the new user input. This - # depends on Workflow.run preserving shared state across calls. The - # restore-only call may yield events from any pending in-flight - # work in the checkpoint; we consume those internally here so they - # don't surface to the response stream as duplicates. - # - # If the restored checkpoint had pending request_info events, the - # restore-only call replays them through - # ``WorkflowAgent._convert_workflow_event_to_agent_response_updates`` - # and populates ``self._agent.pending_requests``. That is the correct - # state: those requests are genuinely outstanding, and the next - # ``run(input_messages, ...)`` call may contain ``function_call_output`` - # items (carried as FunctionResult/FunctionApprovalResponse content) - # that fulfill them via :meth:`WorkflowAgent._process_pending_requests`. - if latest_checkpoint_id is not None: - if is_streaming_request: - async for _ in self._agent.run( - stream=True, - checkpoint_id=latest_checkpoint_id, - checkpoint_storage=restore_storage, - ): - pass - else: - await self._agent.run( - stream=False, - checkpoint_id=latest_checkpoint_id, - checkpoint_storage=restore_storage, - ) - else: - # We reset the workflow if neither conversation_id nor previous_response_id - # was supplied, because this implies there's no prior state to restore and - # we want to ensure a clean slate. Workflow may contain in-memory state that - # needs to be cleared on new conversations. - await self._agent.workflow.reset_for_new_run() - # Now run the agent with the latest input response_event_stream = ResponseEventStream(response_id=context.response_id, model=request.model) From 9da83347c865f6feb6182866d8808fa45a8817d3 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Thu, 11 Jun 2026 11:14:36 -0700 Subject: [PATCH 10/13] Remove reset --- .../_workflows/_agent_executor.py | 37 +-- .../agent_framework/_workflows/_executor.py | 8 - .../agent_framework/_workflows/_runner.py | 17 -- .../agent_framework/_workflows/_workflow.py | 36 +-- .../_workflows/_workflow_executor.py | 13 -- .../tests/workflow/test_agent_executor.py | 105 +-------- .../core/tests/workflow/test_executor.py | 50 ----- .../core/tests/workflow/test_runner.py | 201 ----------------- .../core/tests/workflow/test_sub_workflow.py | 86 ------- .../core/tests/workflow/test_workflow.py | 142 ------------ .../foundry_hosting/tests/test_responses.py | 78 +------ .../mem0/tests/test_mem0_context_provider.py | 7 +- .../_base_group_chat_orchestrator.py | 22 -- .../_group_chat.py | 20 -- .../_magentic.py | 23 -- .../orchestrations/tests/test_group_chat.py | 136 ----------- .../orchestrations/tests/test_magentic.py | 132 ----------- python/samples/03-workflows/README.md | 1 - .../state-management/workflow_reset.py | 212 ------------------ 19 files changed, 15 insertions(+), 1311 deletions(-) delete mode 100644 python/samples/03-workflows/state-management/workflow_reset.py diff --git a/python/packages/core/agent_framework/_workflows/_agent_executor.py b/python/packages/core/agent_framework/_workflows/_agent_executor.py index fb4cb62a541..d96929ce793 100644 --- a/python/packages/core/agent_framework/_workflows/_agent_executor.py +++ b/python/packages/core/agent_framework/_workflows/_agent_executor.py @@ -166,10 +166,6 @@ def __init__( raise ValueError("Agent must have a non-empty name or id or an explicit id must be provided.") super().__init__(exec_id) self._agent = agent - # Track whether the caller supplied a session so reset() can preserve their - # session reference (which may be wired to external/service-side storage) - # and only replace sessions we created ourselves. - self._session_supplied_by_caller = session is not None self._session = session or self._agent.create_session() self._pending_agent_requests: dict[str, Content] = {} @@ -369,37 +365,10 @@ async def on_checkpoint_restore(self, state: dict[str, Any]) -> None: pending_responses_payload = state.get("pending_responses_to_agent") self._pending_responses_to_agent = pending_responses_payload or [] - @override - async def reset(self) -> None: - """Reset the executor to its initial state for a new workflow run. - - Clears the message cache, full conversation snapshot, and any pending - user-input request/response bookkeeping. - - Session handling: - * If the session was created by this executor (no ``session`` argument - was passed to ``__init__``), it is replaced with a fresh one via - ``agent.create_session()`` so prior conversation history does not - leak into the next run. - * If the session was supplied by the caller, it is left untouched. - The caller owns the session lifecycle (it may be backed by - service-side or external storage) and is responsible for clearing - or rotating it if a clean slate is desired. - """ - logger.debug("AgentExecutor %s: Resetting state", self.id) + def reset(self) -> None: + """Reset the internal cache of the executor.""" + logger.debug("AgentExecutor %s: Resetting cache", self.id) self._cache.clear() - self._full_conversation.clear() - self._pending_agent_requests.clear() - self._pending_responses_to_agent.clear() - if not self._session_supplied_by_caller: - self._session = self._agent.create_session() - else: - logger.warning( - "AgentExecutor %s: Session was supplied by the caller and will not be reset. " - "Prior conversation history retained in the session may leak into the next run. " - "Reset or rotate the session externally if a clean slate is required.", - self.id, - ) async def _run_agent_and_emit( self, diff --git a/python/packages/core/agent_framework/_workflows/_executor.py b/python/packages/core/agent_framework/_workflows/_executor.py index d562a925b24..f57102b2bce 100644 --- a/python/packages/core/agent_framework/_workflows/_executor.py +++ b/python/packages/core/agent_framework/_workflows/_executor.py @@ -516,14 +516,6 @@ async def on_checkpoint_restore(self, state: dict[str, Any]) -> None: """ ... - async def reset(self) -> None: - """Reset the executor to its initial state. - - Override this method in subclasses to implement custom logic that should - run when the workflow is reset. - """ - ... - # endregion: Executor diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index 28f1bec7d53..d36c53186eb 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -88,23 +88,6 @@ def reset_iteration_count(self) -> None: """ self._iteration = 0 - async def reset_for_new_run(self) -> None: - """Reset the runner for a new run. - - This is useful when reusing the same workflow instance for a different run - that is independent from prior runs. - - Concurrent-run rejection lives at the :class:`Workflow` level via the - active-run weak reference, so this method does not re-validate that - no run is in progress; callers are expected to have already done so. - """ - self.reset_iteration_count() - self._ctx.reset_for_new_run() - self._state.clear() - self._resumed_from_checkpoint = False - for executor in self._executors.values(): - await executor.reset() - async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: """Run the workflow until no more messages are sent.""" # Emit any events already produced prior to entering loop diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 5c9a78dd75b..0e0d9fe6cd4 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -18,7 +18,7 @@ from .._sessions import ContextProvider from .._types import ResponseStream -from ..exceptions import WorkflowCheckpointException, WorkflowException, WorkflowRunnerException +from ..exceptions import WorkflowCheckpointException, WorkflowException from ..observability import OtelAttr, capture_exception, create_workflow_span from ._checkpoint import CheckpointID, CheckpointStorage from ._const import DEFAULT_MAX_ITERATIONS, GLOBAL_KWARGS_KEY, WORKFLOW_RUN_KWARGS_KEY @@ -568,13 +568,12 @@ async def _run_workflow_with_tracing( yield in_progress # noqa: RUF070 # Per-run reset for fresh-message runs only. We deliberately - # do NOT clear shared workflow state (`_state.clear()`) or the - # runner context's in-flight messages (`reset_for_new_run()`) - # here - state and pending work persist across `run()` calls - # so that a `WorkflowAgent` can deliver multi-turn input on - # the same instance and have prior turns' context survive. - # Iteration counting and per-run kwargs ARE per-run though, - # so they're reset here. + # do NOT clear shared workflow state or the runner context's + # in-flight messages here - state and pending work persist + # across `run()` calls so that a `WorkflowAgent` can deliver + # multi-turn input on the same instance and have prior turns' + # context survive. Iteration counting and per-run kwargs ARE + # per-run though, so they're reset here. if not is_continuation: self._runner.reset_iteration_count() @@ -1210,24 +1209,3 @@ def _is_run_active(self) -> bool: """ existing_stream = self._active_run() if self._active_run is not None else None return existing_stream is not None - - async def reset_for_new_run(self) -> None: - """Reset the workflow for a new run that is independent from prior runs. - - Note: - This will reset EVERYTHING - executor states, workflow state, and runner - context (including pending requests/messages). - - Raises: - WorkflowRunnerException: If a run is currently in progress. Reset is only - allowed when the workflow is idle to avoid clobbering in-flight run state. - - """ - existing_stream = self._active_run() if self._active_run is not None else None - if existing_stream is not None: - raise WorkflowRunnerException( - "Cannot reset the workflow while a run is in progress. " - "Wait for the current run to complete before calling reset_for_new_run()." - ) - self._active_run = None - await self._runner.reset_for_new_run() diff --git a/python/packages/core/agent_framework/_workflows/_workflow_executor.py b/python/packages/core/agent_framework/_workflows/_workflow_executor.py index 7868651b474..e1315334293 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow_executor.py +++ b/python/packages/core/agent_framework/_workflows/_workflow_executor.py @@ -534,19 +534,6 @@ async def on_checkpoint_restore(self, state: dict[str, Any]) -> None: for event in request_info_events ]) - @override - async def reset(self) -> None: - """Reset the WorkflowExecutor to its initial state for a new workflow run. - - Clears in-flight execution contexts and the request-to-execution mapping, - then recursively resets the wrapped sub-workflow so its executors, runner - context, and shared state are also returned to a clean state. - """ - logger.debug("WorkflowExecutor %s: Resetting state", self.id) - self._execution_contexts.clear() - self._request_to_execution.clear() - await self.workflow.reset_for_new_run() - async def _process_workflow_result( self, result: WorkflowRunResult, diff --git a/python/packages/core/tests/workflow/test_agent_executor.py b/python/packages/core/tests/workflow/test_agent_executor.py index e324d52d0d5..c9004f234b1 100644 --- a/python/packages/core/tests/workflow/test_agent_executor.py +++ b/python/packages/core/tests/workflow/test_agent_executor.py @@ -1,6 +1,5 @@ # Copyright (c) Microsoft. All rights reserved. -import logging from collections.abc import AsyncIterable, Awaitable from typing import Any, Literal, overload @@ -20,7 +19,7 @@ WorkflowEvent, WorkflowRunState, ) -from agent_framework._workflows._agent_executor import AgentExecutorRequest, AgentExecutorResponse +from agent_framework._workflows._agent_executor import AgentExecutorResponse from agent_framework._workflows._checkpoint import InMemoryCheckpointStorage from agent_framework._workflows._const import GLOBAL_KWARGS_KEY @@ -307,108 +306,6 @@ async def test_agent_executor_save_and_restore_state_directly() -> None: assert restored_session.session_id == session.session_id -# region: Tests for AgentExecutor.reset() - - -async def test_agent_executor_reset_clears_per_run_state() -> None: - """reset() clears cache, conversation snapshot, and pending request/response buffers.""" - agent = _CountingAgent(id="reset_agent", name="ResetAgent") - executor = AgentExecutor(agent, id="reset_exec") - - # Populate every per-run buffer. - executor._cache = [Message(role="user", contents=["cached"])] # type: ignore[reportPrivateUsage] - executor._full_conversation = [ # type: ignore[reportPrivateUsage] - Message(role="user", contents=["prior turn"]), - Message(role="assistant", contents=["prior response"]), - ] - pending_request = Content.from_text(text="approve?") - executor._pending_agent_requests = {"req-1": pending_request} # type: ignore[reportPrivateUsage] - executor._pending_responses_to_agent = [Content.from_text(text="approved")] # type: ignore[reportPrivateUsage] - - await executor.reset() - - assert executor._cache == [] # type: ignore[reportPrivateUsage] - assert executor._full_conversation == [] # type: ignore[reportPrivateUsage] - assert executor._pending_agent_requests == {} # type: ignore[reportPrivateUsage] - assert executor._pending_responses_to_agent == [] # type: ignore[reportPrivateUsage] - - -async def test_agent_executor_reset_creates_fresh_session_when_auto_created() -> None: - """reset() replaces the agent session when the executor created it itself.""" - agent = _CountingAgent(id="reset_session_agent", name="ResetSessionAgent") - # No session passed in — executor creates one via agent.create_session(). - executor = AgentExecutor(agent, id="reset_session_exec") - auto_created = executor._session # type: ignore[reportPrivateUsage] - auto_created.state["history"] = {"messages": [Message(role="user", contents=["old"])]} - - await executor.reset() - - new_session = executor._session # type: ignore[reportPrivateUsage] - assert new_session is not auto_created - assert new_session.session_id != auto_created.session_id - assert "history" not in new_session.state - - -async def test_agent_executor_reset_preserves_caller_supplied_session(caplog: pytest.LogCaptureFixture) -> None: - """reset() leaves a session passed in via __init__ untouched and warns the caller.""" - agent = _CountingAgent(id="reset_session_agent", name="ResetSessionAgent") - caller_session = AgentSession() - history_payload = {"messages": [Message(role="user", contents=["old"])]} - caller_session.state["history"] = history_payload - executor = AgentExecutor(agent, id="reset_session_exec", session=caller_session) - - assert executor._session is caller_session # type: ignore[reportPrivateUsage] - - with caplog.at_level(logging.WARNING, logger="agent_framework._workflows._agent_executor"): - await executor.reset() - - # Same instance, state untouched — the caller is responsible for managing the session. - assert executor._session is caller_session # type: ignore[reportPrivateUsage] - assert caller_session.state["history"] is history_payload - assert any("Session was supplied by the caller" in record.message for record in caplog.records) - - -async def test_agent_executor_reset_allows_subsequent_run() -> None: - """After reset(), the executor can be reused for a fresh workflow run without leaking state.""" - agent = _CountingAgent(id="reset_reuse_agent", name="ResetReuseAgent") - executor = AgentExecutor(agent, id="reset_reuse_exec") - workflow = WorkflowBuilder(start_executor=executor, output_from=[executor]).build() - - first_outputs: list[WorkflowEvent] = [] - async for event in workflow.run( - AgentExecutorRequest(messages=[Message(role="user", contents=["hello"])]), - stream=True, - ): - if event.type == "output": - first_outputs.append(event) - - assert first_outputs, "first run should have produced at least one output event" - # After a normal run the cache is drained but the conversation snapshot remains. - assert executor._cache == [] # type: ignore[reportPrivateUsage] - assert executor._full_conversation != [] # type: ignore[reportPrivateUsage] - first_session_id = executor._session.session_id # type: ignore[reportPrivateUsage] - - await workflow.reset_for_new_run() - - assert executor._full_conversation == [] # type: ignore[reportPrivateUsage] - # Session was auto-created, so reset() rotates it to a fresh one. - assert executor._session.session_id != first_session_id # type: ignore[reportPrivateUsage] - - second_outputs: list[WorkflowEvent] = [] - async for event in workflow.run( - AgentExecutorRequest(messages=[Message(role="user", contents=["second"])]), - stream=True, - ): - if event.type == "output": - second_outputs.append(event) - - assert second_outputs, "second run after reset should have produced at least one output event" - assert agent.call_count == 2 - - -# endregion: Tests for AgentExecutor.reset() - - async def test_prepare_agent_run_args_extracts_invocation_kwargs() -> None: """_prepare_agent_run_args extracts function_invocation_kwargs and client_kwargs.""" agent = _CountingAgent(id="test_agent", name="TestAgent") diff --git a/python/packages/core/tests/workflow/test_executor.py b/python/packages/core/tests/workflow/test_executor.py index 69089005153..df742b76f6a 100644 --- a/python/packages/core/tests/workflow/test_executor.py +++ b/python/packages/core/tests/workflow/test_executor.py @@ -1004,53 +1004,3 @@ class DualBad(Executor, Generic[_T]): @handler async def process(self, message: _T, ctx) -> None: # type: ignore[no-untyped-def] pass - - -# region: Tests for Executor.reset() - - -async def test_executor_default_reset_is_noop(): - """The base Executor.reset() is a no-op and must complete without raising. - - Subclasses that don't carry reset-relevant state should be able to rely on the - default implementation. - """ - - class StatelessExecutor(Executor): - @handler - async def handle(self, message: str, ctx: WorkflowContext[str]) -> None: - await ctx.send_message(message) - - executor_instance = StatelessExecutor(id="stateless") - - # Must complete without raising and return None. - assert await executor_instance.reset() is None - - -async def test_executor_subclass_reset_is_invoked(): - """A subclass that overrides reset() can clear its own internal state.""" - - class CounterExecutor(Executor): - def __init__(self, id: str) -> None: - super().__init__(id=id) - self.counter = 0 - self.reset_calls = 0 - - @handler - async def handle(self, message: int, ctx: WorkflowContext[int]) -> None: - self.counter += message - - async def reset(self) -> None: - self.counter = 0 - self.reset_calls += 1 - - executor_instance = CounterExecutor(id="counter") - executor_instance.counter = 42 - - await executor_instance.reset() - - assert executor_instance.counter == 0 - assert executor_instance.reset_calls == 1 - - -# endregion: Tests for Executor.reset() diff --git a/python/packages/core/tests/workflow/test_runner.py b/python/packages/core/tests/workflow/test_runner.py index f6b36ebe32d..5c458be7c45 100644 --- a/python/packages/core/tests/workflow/test_runner.py +++ b/python/packages/core/tests/workflow/test_runner.py @@ -1111,204 +1111,3 @@ async def test_runner_drains_straggler_events_at_iteration_end(): output_events = [e for e in events if e.type == "output"] # We should have output events from both executors assert len(output_events) >= 2 - - -# region: Tests for InProcRunnerContext.reset_for_new_run() - - -async def test_runner_context_reset_clears_in_flight_messages(): - """reset_for_new_run drops queued executor-to-executor messages.""" - ctx = InProcRunnerContext() - await ctx.send_message(WorkflowMessage(data=MockMessage(data=1), source_id="src")) - - assert await ctx.has_messages() is True - - ctx.reset_for_new_run() - - assert await ctx.has_messages() is False - assert await ctx.drain_messages() == {} - - -async def test_runner_context_reset_drains_pending_events(): - """reset_for_new_run discards any events buffered for streaming.""" - ctx = InProcRunnerContext() - await ctx.add_event(WorkflowEvent.superstep_started(iteration=1)) - assert await ctx.has_events() is True - - ctx.reset_for_new_run() - - assert await ctx.has_events() is False - assert await ctx.drain_events() == [] - - -async def test_runner_context_reset_resets_streaming_flag(): - """reset_for_new_run resets streaming back to its non-streaming default.""" - ctx = InProcRunnerContext() - ctx.set_streaming(True) - assert ctx.is_streaming() is True - - ctx.reset_for_new_run() - - assert ctx.is_streaming() is False - - -async def test_runner_context_reset_clears_pending_request_info_events(): - """reset_for_new_run clears any pending request_info events tracked for correlation.""" - ctx = InProcRunnerContext() - request_info_event = WorkflowEvent.request_info( - request_id="request-123", - source_executor_id="source", - request_data=MockMessage(data=0), - response_type=bool, - ) - await ctx.add_request_info_event(request_info_event) - - assert "request-123" in await ctx.get_pending_request_info_events() - - ctx.reset_for_new_run() - - assert await ctx.get_pending_request_info_events() == {} - - -# endregion: Tests for InProcRunnerContext.reset_for_new_run() - - -# region: Tests for Runner.reset_for_new_run() - - -async def test_runner_reset_for_new_run_resets_iteration_count(): - """reset_for_new_run resets the iteration counter back to zero.""" - runner = _make_runner() - runner._iteration = 7 # pyright: ignore[reportPrivateUsage] - - await runner.reset_for_new_run() - - assert runner._iteration == 0 # pyright: ignore[reportPrivateUsage] - - -async def test_runner_reset_for_new_run_clears_shared_state(): - """reset_for_new_run wipes both committed and pending entries from shared state.""" - state = State() - state.set("committed_key", "committed_value") - state.commit() - state.set("pending_key", "pending_value") # uncommitted - - runner = Runner( - [], - {}, - state, - InProcRunnerContext(), - "test_name", - graph_signature_hash="test_hash", - ) - - await runner.reset_for_new_run() - - assert state.get("committed_key") is None - assert state.get("pending_key") is None - assert state.has("committed_key") is False - assert state.has("pending_key") is False - - -async def test_runner_reset_for_new_run_clears_resumed_from_checkpoint_flag(): - """reset_for_new_run clears the flag set by restore_from_checkpoint.""" - runner = _make_runner() - resumed_checkpoint = WorkflowCheckpoint( - checkpoint_id="resumed-cp", - workflow_name="test_name", - graph_signature_hash="test_hash", - iteration_count=5, - ) - runner._mark_resumed(resumed_checkpoint) # pyright: ignore[reportPrivateUsage] - assert runner._resumed_from_checkpoint is True # pyright: ignore[reportPrivateUsage] - - await runner.reset_for_new_run() - - assert runner._resumed_from_checkpoint is False # pyright: ignore[reportPrivateUsage] - # And the iteration count restored from the checkpoint must be wiped, too. - assert runner._iteration == 0 # pyright: ignore[reportPrivateUsage] - - -async def test_runner_reset_for_new_run_invokes_executor_reset_for_each_executor(): - """reset_for_new_run calls reset() on every registered executor exactly once.""" - - class TrackingExecutor(MockExecutor): - def __init__(self, id: str) -> None: - super().__init__(id=id) - self.reset_calls = 0 - - async def reset(self) -> None: - self.reset_calls += 1 - - executor_a = TrackingExecutor(id="executor_a") - executor_b = TrackingExecutor(id="executor_b") - - runner = Runner( - [], - {executor_a.id: executor_a, executor_b.id: executor_b}, - State(), - InProcRunnerContext(), - "test_name", - graph_signature_hash="test_hash", - ) - - await runner.reset_for_new_run() - - assert executor_a.reset_calls == 1 - assert executor_b.reset_calls == 1 - - -async def test_runner_reset_for_new_run_resets_runner_context(): - """reset_for_new_run forwards the reset to the underlying runner context.""" - ctx = InProcRunnerContext() - await ctx.send_message(WorkflowMessage(data=MockMessage(data=0), source_id="src")) - await ctx.add_event(WorkflowEvent.superstep_started(iteration=1)) - ctx.set_streaming(True) - - runner = Runner([], {}, State(), ctx, "test_name", graph_signature_hash="test_hash") - - await runner.reset_for_new_run() - - assert await ctx.has_messages() is False - assert await ctx.has_events() is False - assert ctx.is_streaming() is False - - -async def test_runner_can_run_again_after_reset_for_new_run(): - """After reset_for_new_run the runner can be reserved and converge a fresh workload.""" - executor_a = MockExecutor(id="executor_a") - executor_b = MockExecutor(id="executor_b") - - edges = [ - SingleEdgeGroup(executor_a.id, executor_b.id), - SingleEdgeGroup(executor_b.id, executor_a.id), - ] - executors: dict[str, Executor] = { - executor_a.id: executor_a, - executor_b.id: executor_b, - } - state = State() - ctx = InProcRunnerContext() - - runner = Runner(edges, executors, state, ctx, "test_name", graph_signature_hash="test_hash") - - # First run: drives MockExecutor's loop until it yields the terminal value. - await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) - async for _ in runner.run_until_convergence(): - pass - assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage] - - await runner.reset_for_new_run() - - # Second run: must succeed cleanly using the same runner instance. - await executor_a.execute(MockMessage(data=0), ["START"], state, ctx) - second_run_outputs: list[int] = [] - async for event in runner.run_until_convergence(): - if event.type == "output": - second_run_outputs.append(event.data) - - assert second_run_outputs == [10] - assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage] - - -# endregion: Tests for Runner.reset_for_new_run() diff --git a/python/packages/core/tests/workflow/test_sub_workflow.py b/python/packages/core/tests/workflow/test_sub_workflow.py index 17b7e059619..7bf38a06f32 100644 --- a/python/packages/core/tests/workflow/test_sub_workflow.py +++ b/python/packages/core/tests/workflow/test_sub_workflow.py @@ -689,89 +689,3 @@ async def run(self, message: str, ctx: WorkflowContext[Never, str]) -> None: # The parent's own terminal output is unaffected. assert any(e.executor_id == "parent_sink" and e.data == "final: hello" for e in output_events) - - -# region: Tests for WorkflowExecutor.reset() - - -async def test_workflow_executor_reset_clears_execution_state() -> None: - """reset() clears the WorkflowExecutor's per-run execution contexts and request mappings.""" - validation_workflow = create_email_validation_workflow() - parent = Coordinator() - workflow_executor = WorkflowExecutor(validation_workflow, "email_validation_workflow") - - main_workflow = ( - WorkflowBuilder(start_executor=parent) - .add_edge(parent, workflow_executor) - .add_edge(workflow_executor, parent) - .build() - ) - - # First run pauses with a pending request from the sub-workflow. - result = await main_workflow.run("test@example.com") - assert len(result.get_request_info_events()) == 1 - assert len(workflow_executor._execution_contexts) == 1 # type: ignore[reportPrivateUsage] - assert len(workflow_executor._request_to_execution) == 1 # type: ignore[reportPrivateUsage] - - await main_workflow.reset_for_new_run() - - assert workflow_executor._execution_contexts == {} # type: ignore[reportPrivateUsage] - assert workflow_executor._request_to_execution == {} # type: ignore[reportPrivateUsage] - - -async def test_workflow_executor_reset_resets_wrapped_workflow() -> None: - """reset() recursively resets the wrapped workflow (runner iteration counter cleared).""" - validation_workflow = create_email_validation_workflow() - parent = Coordinator() - workflow_executor = WorkflowExecutor(validation_workflow, "email_validation_workflow") - - main_workflow = ( - WorkflowBuilder(start_executor=parent) - .add_edge(parent, workflow_executor) - .add_edge(workflow_executor, parent) - .build() - ) - - await main_workflow.run("test@example.com") - # The sub-workflow's runner advanced past iteration 0 during execution. - assert validation_workflow._runner._iteration > 0 # type: ignore[reportPrivateUsage] - - await main_workflow.reset_for_new_run() - - # The wrapped workflow's runner was reset along with the parent. - assert validation_workflow._runner._iteration == 0 # type: ignore[reportPrivateUsage] - - -async def test_workflow_executor_reset_allows_subsequent_run() -> None: - """After reset(), the parent + WorkflowExecutor can be reused for a fresh run with no leakage.""" - validation_workflow = create_email_validation_workflow() - parent = Coordinator() - workflow_executor = WorkflowExecutor(validation_workflow, "email_validation_workflow") - - main_workflow = ( - WorkflowBuilder(start_executor=parent) - .add_edge(parent, workflow_executor) - .add_edge(workflow_executor, parent) - .build() - ) - - first_result = await main_workflow.run("first@example.com") - assert len(first_result.get_request_info_events()) == 1 - - await main_workflow.reset_for_new_run() - - # State on the WorkflowExecutor and parent's pending-request bookkeeping is clean. - assert workflow_executor._execution_contexts == {} # type: ignore[reportPrivateUsage] - assert workflow_executor._request_to_execution == {} # type: ignore[reportPrivateUsage] - - second_result = await main_workflow.run("second@example.com") - second_requests = second_result.get_request_info_events() - assert len(second_requests) == 1 - assert isinstance(second_requests[0].data, DomainCheckRequest) - # Confirm the new run produced a request from the second email, not the cached first one. - assert second_requests[0].data.email == "second@example.com" - # And the WorkflowExecutor is now tracking exactly one fresh execution. - assert len(workflow_executor._execution_contexts) == 1 # type: ignore[reportPrivateUsage] - - -# endregion: Tests for WorkflowExecutor.reset() diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index 4e607ca8f9c..fb46e6d426a 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -29,7 +29,6 @@ WorkflowEvent, WorkflowException, WorkflowMessage, - WorkflowRunnerException, WorkflowRunState, handler, response_handler, @@ -1354,144 +1353,3 @@ async def test_output_executors_filtering_with_run_responses_streaming() -> None # endregion - - -# region: Tests for Workflow.reset_for_new_run() - - -async def test_workflow_reset_for_new_run_allows_subsequent_run() -> None: - """After reset_for_new_run() the same workflow instance can be run again from scratch.""" - executor_a = IncrementExecutor(id="executor_a") - executor_b = IncrementExecutor(id="executor_b") - - workflow = ( - WorkflowBuilder(start_executor=executor_a, output_from=[executor_a, executor_b]) - .add_edge(executor_a, executor_b) - .add_edge(executor_b, executor_a) - .build() - ) - - first = await workflow.run(NumberMessage(data=0)) - assert first.get_outputs() == [10] - - await workflow.reset_for_new_run() - - second = await workflow.run(NumberMessage(data=0)) - assert second.get_outputs() == [10] - - -async def test_workflow_reset_for_new_run_clears_workflow_state() -> None: - """reset_for_new_run() clears values that executors persisted in shared workflow state.""" - - class StateWritingExecutor(Executor): - @handler - async def handle(self, message: NumberMessage, ctx: WorkflowContext[Any, int]) -> None: - previous = ctx.get_state("seen") or 0 - ctx.set_state("seen", previous + 1) - await ctx.yield_output(previous + 1) - - state_writer = StateWritingExecutor(id="state_writer") - workflow = WorkflowBuilder(start_executor=state_writer, output_from=[state_writer]).build() - - first = await workflow.run(NumberMessage(data=1)) - assert first.get_outputs() == [1] - # State was persisted by the executor. - assert workflow._runner.state.get("seen") == 1 # pyright: ignore[reportPrivateUsage] - - await workflow.reset_for_new_run() - - # The runner's shared state has been wiped. - assert workflow._runner.state.get("seen") is None # pyright: ignore[reportPrivateUsage] - - second = await workflow.run(NumberMessage(data=1)) - # Counter started fresh from 0 again; output is 1, not 2. - assert second.get_outputs() == [1] - - -async def test_workflow_reset_for_new_run_invokes_executor_reset_hook() -> None: - """reset_for_new_run() calls Executor.reset() on every executor in the workflow.""" - - class ResettableExecutor(Executor): - def __init__(self, id: str) -> None: - super().__init__(id=id) - self.reset_calls = 0 - self.handled = 0 - - @handler - async def handle(self, message: NumberMessage, ctx: WorkflowContext[Any, int]) -> None: - self.handled += 1 - await ctx.yield_output(self.handled) - - async def reset(self) -> None: - self.reset_calls += 1 - self.handled = 0 - - executor = ResettableExecutor(id="resettable") - workflow = WorkflowBuilder(start_executor=executor, output_from=[executor]).build() - - await workflow.run(NumberMessage(data=1)) - assert executor.handled == 1 - assert executor.reset_calls == 0 - - await workflow.reset_for_new_run() - - assert executor.reset_calls == 1 - # The executor's own counter was wiped by its overridden reset(). - assert executor.handled == 0 - - -async def test_workflow_reset_for_new_run_resets_runner_iteration_counter() -> None: - """reset_for_new_run() drops the iteration counter accumulated during a prior run.""" - executor_a = IncrementExecutor(id="executor_a") - executor_b = IncrementExecutor(id="executor_b") - - workflow = ( - WorkflowBuilder(start_executor=executor_a, output_from=[executor_a, executor_b]) - .add_edge(executor_a, executor_b) - .add_edge(executor_b, executor_a) - .build() - ) - - await workflow.run(NumberMessage(data=0)) - assert workflow._runner._iteration > 0 # pyright: ignore[reportPrivateUsage] - - await workflow.reset_for_new_run() - - assert workflow._runner._iteration == 0 # pyright: ignore[reportPrivateUsage] - - -async def test_workflow_reset_for_new_run_rejected_during_streaming_run() -> None: - """reset_for_new_run() raises WorkflowRunnerException while a streaming run is in progress.""" - executor_a = IncrementExecutor(id="executor_a") - executor_b = IncrementExecutor(id="executor_b") - - workflow = ( - WorkflowBuilder(start_executor=executor_a, output_from=[executor_a, executor_b]) - .add_edge(executor_a, executor_b) - .add_edge(executor_b, executor_a) - .build() - ) - - async def consume_stream_slowly() -> list[WorkflowEvent]: - events: list[WorkflowEvent] = [] - async for event in workflow.run(NumberMessage(data=0), stream=True): - events.append(event) - await asyncio.sleep(0.01) - return events - - task = asyncio.create_task(consume_stream_slowly()) - # Let the streaming run start. - await asyncio.sleep(0.02) - - try: - with pytest.raises(WorkflowRunnerException, match="Cannot reset the workflow while a run is in progress"): - await workflow.reset_for_new_run() - finally: - await task - - # After the run completes, reset succeeds again. - await workflow.reset_for_new_run() - assert workflow._runner._iteration == 0 # pyright: ignore[reportPrivateUsage] - - -# endregion diff --git a/python/packages/foundry_hosting/tests/test_responses.py b/python/packages/foundry_hosting/tests/test_responses.py index df3aec0d653..f3061885e44 100644 --- a/python/packages/foundry_hosting/tests/test_responses.py +++ b/python/packages/foundry_hosting/tests/test_responses.py @@ -3032,6 +3032,7 @@ async def test_handle_inner_workflow_restores_message_role_checkpoint_from_previ agent.workflow = MagicMock() agent.workflow.name = "wf" agent.workflow._runner_context.has_checkpointing = MagicMock(return_value=False) + agent.workflow.create_checkpoint = AsyncMock(return_value="cp_initial") agent.run = AsyncMock( side_effect=[ AgentResponse(messages=[]), @@ -3155,6 +3156,8 @@ async def test_handle_inner_workflow_rejects_malicious_context_id( agent.workflow = MagicMock() agent.workflow.name = "wf" agent.workflow._runner_context.has_checkpointing = MagicMock(return_value=False) + agent.workflow.create_checkpoint = AsyncMock(return_value="cp_initial") + agent.run = AsyncMock(return_value=AgentResponse(messages=[])) # Constructor inspects WorkflowAgent.workflow internals; bypass setup # by feeding a configured mock through a normal init. @@ -3971,80 +3974,5 @@ async def test_round_trip_approval_response_rejected(self) -> None: assert len(approval_responses) == 1 assert approval_responses[0].approved is False # type: ignore[attr-defined] - async def test_workflow_is_reset_when_no_prior_conversation(self) -> None: - """Without ``previous_response_id`` or ``conversation_id`` the host must - reset the workflow so any in-memory state from a previous request is - cleared before the new turn runs.""" - workflow_agent = _build_text_workflow_agent("fresh") - server = _make_server(workflow_agent) - - with patch.object( - workflow_agent.workflow, - "reset_for_new_run", - new=AsyncMock(wraps=workflow_agent.workflow.reset_for_new_run), - ) as reset_spy: - resp = await _post(server, input_text="hi", stream=False) - - assert resp.status_code == 200 - assert reset_spy.await_count == 1 - - async def test_workflow_is_reset_across_independent_requests(self) -> None: - """Two consecutive requests without a chaining context id must each - reset the workflow.""" - workflow_agent = _build_text_workflow_agent("again") - server = _make_server(workflow_agent) - - with patch.object( - workflow_agent.workflow, - "reset_for_new_run", - new=AsyncMock(wraps=workflow_agent.workflow.reset_for_new_run), - ) as reset_spy: - first = await _post(server, input_text="hi", stream=False) - second = await _post(server, input_text="hi again", stream=False) - - assert first.status_code == 200 - assert second.status_code == 200 - assert reset_spy.await_count == 2 - - async def test_workflow_is_not_reset_when_resuming_from_checkpoint(self) -> None: - """When ``previous_response_id`` resolves to an existing workflow - checkpoint the host restores the checkpoint instead of resetting - the workflow.""" - workflow_agent, _ = _build_approval_workflow_agent( - approval_request_id="apr_no_reset", - final_text="resumed", - ) - server = _make_server(workflow_agent) - - first = await _post(server, stream=False) - assert first.status_code == 200 - first_body = first.json() - first_response_id = first_body["id"] - approval_request_id = next(it["id"] for it in first_body["output"] if it["type"] == "mcp_approval_request") - - with patch.object( - workflow_agent.workflow, - "reset_for_new_run", - new=AsyncMock(wraps=workflow_agent.workflow.reset_for_new_run), - ) as reset_spy: - second = await _post_json( - server, - { - "model": "test-model", - "input": [ - { - "type": "mcp_approval_response", - "approval_request_id": approval_request_id, - "approve": True, - } - ], - "stream": False, - "previous_response_id": first_response_id, - }, - ) - - assert second.status_code == 200 - assert reset_spy.await_count == 0 - # endregion diff --git a/python/packages/mem0/tests/test_mem0_context_provider.py b/python/packages/mem0/tests/test_mem0_context_provider.py index a047af1638f..d5c9e2fe677 100644 --- a/python/packages/mem0/tests/test_mem0_context_provider.py +++ b/python/packages/mem0/tests/test_mem0_context_provider.py @@ -198,12 +198,7 @@ async def test_oss_client_all_scoping_params_except_app_id(self, mock_oss_mem0_c """OSS client with all scoping parameters passes them as isolated concurrent kwargs.""" mock_oss_mem0_client.search.return_value = [] - provider = Mem0ContextProvider( - source_id="mem0", - mem0_client=mock_oss_mem0_client, - user_id="u1", - agent_id="a1" - ) + provider = Mem0ContextProvider(source_id="mem0", mem0_client=mock_oss_mem0_client, user_id="u1", agent_id="a1") mock_context = MagicMock(spec=SessionContext) mock_msg = MagicMock() diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py b/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py index 8cdf71a0d01..a4108b23f08 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_base_group_chat_orchestrator.py @@ -598,25 +598,3 @@ def _restore_pattern_metadata(self, metadata: dict[str, Any]) -> None: metadata: Pattern-specific state dict """ pass - - @override - async def reset(self) -> None: - """Reset the orchestrator to its initial state for a new workflow run. - - Clears the shared conversation history and round counter, then delegates - to ``_reset_pattern_state()`` so subclasses can clean up any - pattern-specific per-run state (caches, sessions, ledgers, etc.). - """ - logger.debug("%s %s: Resetting state", self.__class__.__name__, self.id) - self._full_conversation.clear() - self._round_index = 0 - self._reset_pattern_state() - - def _reset_pattern_state(self) -> None: - """Reset pattern-specific state. - - Override this method in subclasses to clear pattern-specific per-run state - when ``reset()`` is invoked. Called after the base class clears the shared - conversation and round counter. - """ - pass diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py b/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py index f6bbac54002..728f3e388cc 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py @@ -327,7 +327,6 @@ def __init__( ) self._agent = agent self._retry_attempts = retry_attempts - self._session_supplied_by_caller = session is not None self._session = session or agent.create_session() # Cache for messages since last agent invocation # This is different from the full conversation history maintained by the base orchestrator @@ -338,25 +337,6 @@ def _append_messages(self, messages: Sequence[Message]) -> None: self._cache.extend(messages) return super()._append_messages(messages) - @override - def _reset_pattern_state(self) -> None: - """Reset pattern-specific state for a new workflow run. - - Clears the per-run message cache and rotates the orchestrator agent's - session unless the caller supplied a session explicitly (in which case - the caller is responsible for the session's lifecycle). - """ - self._cache.clear() - if self._session_supplied_by_caller: - logger.warning( - "%s %s: Session was supplied by the caller and will not be reset. " - "If you want a fresh session for the next run, reset or replace it before invoking the workflow.", - self.__class__.__name__, - self.id, - ) - else: - self._session = self._agent.create_session() - @override async def _handle_messages( self, diff --git a/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py b/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py index 7288b67d2f8..f8cbf88fd73 100644 --- a/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py +++ b/python/packages/orchestrations/agent_framework_orchestrations/_magentic.py @@ -509,14 +509,6 @@ def on_checkpoint_restore(self, state: dict[str, Any]) -> None: """Restore runtime state from checkpoint data.""" return - def on_reset(self) -> None: - """Reset per-run runtime state for a new workflow run. - - Subclasses should clear any state accumulated during a run (e.g. cached - ledgers, agent sessions) so the manager is ready to start fresh. - """ - return - class StandardMagenticManager(MagenticManagerBase): """Standard Magentic manager that performs real LLM calls via a Agent. @@ -769,12 +761,6 @@ def on_checkpoint_restore(self, state: dict[str, Any]) -> None: except Exception: # pragma: no cover - defensive logger.warning("Failed to restore manager agent session from checkpoint state") - @override - def on_reset(self) -> None: - """Clear cached ledger and start a fresh agent session for a new run.""" - self.task_ledger = None - self._session = self._agent.create_session() - # endregion Magentic Manager @@ -1277,15 +1263,6 @@ async def _reset_participants(self, ctx: WorkflowContext[MagenticResetSignal]) - # a target will broadcast to all. await ctx.send_message(MagenticResetSignal()) - @override - def _reset_pattern_state(self) -> None: - """Reset Magentic-specific per-run state for a new workflow run.""" - self._magentic_context = None - self._task_ledger = None - self._progress_ledger = None - self._terminated = False - self._manager.on_reset() - @override async def on_checkpoint_save(self) -> dict[str, Any]: """Capture current orchestrator state for checkpointing.""" diff --git a/python/packages/orchestrations/tests/test_group_chat.py b/python/packages/orchestrations/tests/test_group_chat.py index 56a6f4a0b4b..50f58e781a2 100644 --- a/python/packages/orchestrations/tests/test_group_chat.py +++ b/python/packages/orchestrations/tests/test_group_chat.py @@ -1097,139 +1097,3 @@ def invalid_factory() -> Any: # endregion - - -# region Reset - - -async def test_base_orchestrator_reset_clears_conversation_and_round_index() -> None: - """reset() clears the conversation history and the round counter.""" - from agent_framework.orchestrations import GroupChatOrchestrator - - from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry - - selector = make_sequence_selector() - orchestrator = GroupChatOrchestrator( - id="orch", - participant_registry=ParticipantRegistry([]), - selection_func=selector, - max_rounds=2, - ) - orchestrator._full_conversation = [Message(role="user", contents=["hi"], author_name="user")] - orchestrator._round_index = 4 - - await orchestrator.reset() - - assert orchestrator._full_conversation == [] - assert orchestrator._round_index == 0 - - -async def test_base_orchestrator_reset_invokes_pattern_state_hook() -> None: - """reset() calls _reset_pattern_state() so subclasses can clean up their own state.""" - from agent_framework.orchestrations import GroupChatOrchestrator - - from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry - - selector = make_sequence_selector() - - class TrackingOrchestrator(GroupChatOrchestrator): - reset_calls: int = 0 - - def _reset_pattern_state(self) -> None: - type(self).reset_calls += 1 - - orchestrator = TrackingOrchestrator( - id="orch", - participant_registry=ParticipantRegistry([]), - selection_func=selector, - max_rounds=2, - ) - - await orchestrator.reset() - await orchestrator.reset() - - assert TrackingOrchestrator.reset_calls == 2 - - -async def test_agent_based_orchestrator_reset_clears_cache_and_rotates_session() -> None: - """When the session was not supplied by the caller, reset() rotates the session and clears the cache.""" - from agent_framework.orchestrations import AgentBasedGroupChatOrchestrator - - from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry - - agent = cast(Agent, StubManagerAgent()) - orchestrator = AgentBasedGroupChatOrchestrator( - agent=agent, - participant_registry=ParticipantRegistry([]), - max_rounds=2, - ) - original_session = orchestrator._session - orchestrator._cache = [Message(role="assistant", contents=["x"], author_name="agent")] - orchestrator._full_conversation = [Message(role="user", contents=["x"], author_name="user")] - orchestrator._round_index = 3 - - await orchestrator.reset() - - assert orchestrator._cache == [] - assert orchestrator._full_conversation == [] - assert orchestrator._round_index == 0 - assert orchestrator._session is not original_session - - -async def test_agent_based_orchestrator_reset_warns_when_session_supplied(caplog: pytest.LogCaptureFixture) -> None: - """When the caller supplied a session, reset() preserves it and logs a warning.""" - import logging - - from agent_framework.orchestrations import AgentBasedGroupChatOrchestrator - - from agent_framework_orchestrations._base_group_chat_orchestrator import ParticipantRegistry - - agent = cast(Agent, StubManagerAgent()) - supplied_session = agent.create_session() - orchestrator = AgentBasedGroupChatOrchestrator( - agent=agent, - participant_registry=ParticipantRegistry([]), - session=supplied_session, - max_rounds=2, - ) - orchestrator._cache = [Message(role="assistant", contents=["x"], author_name="agent")] - - with caplog.at_level(logging.WARNING, logger="agent_framework_orchestrations._group_chat"): - await orchestrator.reset() - - assert orchestrator._cache == [] - # The caller-owned session must be preserved. - assert orchestrator._session is supplied_session - warnings = [ - r for r in caplog.records if r.levelno == logging.WARNING and "Session was supplied by the caller" in r.message - ] - assert warnings, f"expected a warning about caller-supplied session, got: {[r.message for r in caplog.records]}" - - -async def test_workflow_reset_resets_group_chat_orchestrator() -> None: - """End-to-end: workflow.reset_for_new_run() resets the orchestrator's conversation state.""" - selector = make_sequence_selector() - alpha = StubAgent("alpha", "ack from alpha") - beta = StubAgent("beta", "ack from beta") - - workflow = GroupChatBuilder( - participants=[alpha, beta], - max_rounds=2, - selection_func=selector, - orchestrator_name="manager", - ).build() - - async for _ in workflow.run("first task", stream=True): - pass - - orchestrator = cast(BaseGroupChatOrchestrator, workflow.executors[GroupChatBuilder.DEFAULT_ORCHESTRATOR_ID]) - assert orchestrator._full_conversation, "orchestrator should have accumulated conversation after first run" - assert orchestrator._round_index > 0 - - await workflow.reset_for_new_run() - - assert orchestrator._full_conversation == [] - assert orchestrator._round_index == 0 - - -# endregion diff --git a/python/packages/orchestrations/tests/test_magentic.py b/python/packages/orchestrations/tests/test_magentic.py index 343d4eff7a6..615ba998bcc 100644 --- a/python/packages/orchestrations/tests/test_magentic.py +++ b/python/packages/orchestrations/tests/test_magentic.py @@ -1243,135 +1243,3 @@ def test_standard_manager_checkpoint_restore_empty_state(): # endregion - - -# region Manager Reset Tests - - -def test_magentic_manager_base_on_reset_is_noop_by_default(): - """MagenticManagerBase.on_reset() is a no-op so subclasses can opt in.""" - mgr = FakeManager() - # Seed some state on the fake to confirm the base hook does not touch it. - mgr.task_ledger = _SimpleLedger( - facts=Message("assistant", ["facts"]), - plan=Message("assistant", ["plan"]), - ) - - mgr.on_reset() # base implementation is a no-op - - assert mgr.task_ledger is not None - - -def test_standard_manager_on_reset_clears_ledger_and_rotates_session(): - """StandardMagenticManager.on_reset() clears the cached ledger and creates a fresh session.""" - from agent_framework_orchestrations._magentic import _MagenticTaskLedger # type: ignore[reportPrivateUsage] - - agent = StubManagerAgent() - mgr = StandardMagenticManager(agent=agent) - mgr.task_ledger = _MagenticTaskLedger( - facts=Message("assistant", ["facts"]), - plan=Message("assistant", ["plan"]), - ) - original_session = mgr._session - - mgr.on_reset() - - assert mgr.task_ledger is None - assert mgr._session is not original_session - assert mgr._session.session_id != original_session.session_id - - -async def test_magentic_orchestrator_reset_invokes_manager_on_reset() -> None: - """_reset_pattern_state() clears orchestrator state and delegates to manager.on_reset().""" - from agent_framework_orchestrations._base_group_chat_orchestrator import ( - ParticipantRegistry, # type: ignore[reportPrivateUsage] - ) - - class TrackingManager(FakeManager): - reset_calls: int = 0 - - @override - def on_reset(self) -> None: - type(self).reset_calls += 1 - - manager = TrackingManager() - orchestrator = MagenticOrchestrator( - manager=manager, - participant_registry=ParticipantRegistry([]), - ) - # Seed magentic-specific state to confirm it is cleared. - orchestrator._magentic_context = MagenticContext( # type: ignore[reportPrivateUsage] - task="task", - participant_descriptions={"agentA": "desc"}, - ) - orchestrator._task_ledger = Message("assistant", ["ledger"]) # type: ignore[reportPrivateUsage] - orchestrator._progress_ledger = MagenticProgressLedger( # type: ignore[reportPrivateUsage] - is_request_satisfied=MagenticProgressLedgerItem(reason="r", answer=False), - is_in_loop=MagenticProgressLedgerItem(reason="r", answer=False), - is_progress_being_made=MagenticProgressLedgerItem(reason="r", answer=True), - next_speaker=MagenticProgressLedgerItem(reason="r", answer="agentA"), - instruction_or_question=MagenticProgressLedgerItem(reason="r", answer="do"), - ) - orchestrator._terminated = True # type: ignore[reportPrivateUsage] - - await orchestrator.reset() - - assert orchestrator._magentic_context is None # type: ignore[reportPrivateUsage] - assert orchestrator._task_ledger is None # type: ignore[reportPrivateUsage] - assert orchestrator._progress_ledger is None # type: ignore[reportPrivateUsage] - assert orchestrator._terminated is False # type: ignore[reportPrivateUsage] - assert TrackingManager.reset_calls == 1 - - -async def test_magentic_orchestrator_reset_propagates_manager_on_reset_failure() -> None: - """Failures in manager.on_reset() must propagate so callers can react.""" - from agent_framework_orchestrations._base_group_chat_orchestrator import ( - ParticipantRegistry, # type: ignore[reportPrivateUsage] - ) - - class FailingManager(FakeManager): - @override - def on_reset(self) -> None: - raise RuntimeError("boom") - - manager = FailingManager() - orchestrator = MagenticOrchestrator( - manager=manager, - participant_registry=ParticipantRegistry([]), - ) - - with pytest.raises(RuntimeError, match="boom"): - await orchestrator.reset() - - -async def test_workflow_reset_resets_magentic_orchestrator_and_manager() -> None: - """End-to-end: workflow.reset_for_new_run() resets Magentic orchestrator and manager state.""" - manager = FakeManager() - manager.task_ledger = _SimpleLedger( - facts=Message("assistant", ["seeded facts"]), - plan=Message("assistant", ["seeded plan"]), - ) - workflow = MagenticBuilder( - participants=[StubAgent(manager.next_speaker_name, "first draft")], - manager=manager, - ).build() - - async for _ in workflow.run("first task", stream=True): - pass - - orchestrator = next(e for e in workflow.executors.values() if isinstance(e, MagenticOrchestrator)) - assert orchestrator._terminated is True # type: ignore[reportPrivateUsage] - assert orchestrator._task_ledger is not None # type: ignore[reportPrivateUsage] - assert manager.task_ledger is not None - - await workflow.reset_for_new_run() - - assert orchestrator._magentic_context is None # type: ignore[reportPrivateUsage] - assert orchestrator._task_ledger is None # type: ignore[reportPrivateUsage] - assert orchestrator._progress_ledger is None # type: ignore[reportPrivateUsage] - assert orchestrator._terminated is False # type: ignore[reportPrivateUsage] - # FakeManager.on_reset is the base no-op, but the orchestrator still tolerates that case. - # For the standard manager we exercise full clearing in the dedicated unit test above. - - -# endregion diff --git a/python/samples/03-workflows/README.md b/python/samples/03-workflows/README.md index adcb57dadb3..c79203d7429 100644 --- a/python/samples/03-workflows/README.md +++ b/python/samples/03-workflows/README.md @@ -169,7 +169,6 @@ callers can still inspect progress or supporting work from the response messages | Sample | File | Concepts | | -------------------------------- | ------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------- | | State with Agents | [state-management/state_with_agents.py](./state-management/state_with_agents.py) | Store in state once and later reuse across agents | -| Reset Workflow Between Runs | [state-management/workflow_reset.py](./state-management/workflow_reset.py) | Reuse one workflow instance across independent runs via `reset_for_new_run()` | | Workflow Kwargs - Global Context | [state-management/workflow_kwargs_global.py](./state-management/workflow_kwargs_global.py) | Pass custom context (data, user tokens) via kwargs to `@tool` tools in all agents | | Workflow Kwargs - Per Agent | [state-management/workflow_kwargs_per_agent.py](./state-management/workflow_kwargs_per_agent.py) | Pass custom context (data, user tokens) via kwargs to `@tool` tools in individual agents | diff --git a/python/samples/03-workflows/state-management/workflow_reset.py b/python/samples/03-workflows/state-management/workflow_reset.py deleted file mode 100644 index d751e6b066b..00000000000 --- a/python/samples/03-workflows/state-management/workflow_reset.py +++ /dev/null @@ -1,212 +0,0 @@ -# Copyright (c) Microsoft. All rights reserved. - -import asyncio -from dataclasses import dataclass - -from agent_framework import Executor, Workflow, WorkflowBuilder, WorkflowContext, handler -from typing_extensions import Never, override - -""" -Sample: Reusing a Workflow across independent jobs with reset_for_new_run(). - -Build a small moderation pipeline that silently accumulates stats as messages -flow through it and emits a summary only when the caller asks for one. Drive -the same workflow instance across multiple independent jobs and show that -``Workflow.reset_for_new_run()`` clears all per-executor state without -rebuilding the graph. - -Two custom executors share the work, each with its own per-job state and its -own ``reset()`` override: - -- ``FlaggedKeywordCounter`` is the start executor. It accepts message strings - to inspect (silently updating local stats, sending nothing downstream) and - ``ReportRequest`` markers that cause it to forward a ``StatsSnapshot``. -- ``StatsReporter`` formats the snapshot, increments its own emitted-reports - counter, and yields the summary as the workflow output. - -A run with a string produces no output, just a state update. A run with a -``ReportRequest`` produces exactly one summary. Job boundaries are entirely -controlled by the caller via ``reset_for_new_run()``, which calls ``reset()`` -on every executor in the graph. - -Purpose: -Show how to: -- Hold per-job aggregate state on a custom Executor subclass. -- Override ``Executor.reset()`` on every executor that owns per-run state, so - it is cleared automatically when the workflow is reset. -- Call ``Workflow.reset_for_new_run()`` between independent jobs so a single - workflow instance can serve a stream of unrelated batches without leaking - state. - -Prerequisites: -- No external services or credentials required; this sample runs entirely in-process. -- Familiarity with WorkflowBuilder and Executor subclasses. -""" - - -@dataclass -class ReportRequest: - """Marker input that asks the workflow to emit a summary of stats so far.""" - - -@dataclass -class StatsSnapshot: - """Snapshot the counter forwards to the reporter when a report is requested.""" - - messages_seen: int - flagged_messages: int - flagged_keywords: list[str] - - -class FlaggedKeywordCounter(Executor): - """Executor that silently accumulates per-job stats; emits on demand. - - Holds three instance attributes that build up across the runs that make up a - single job: - - - ``_messages_seen``: how many messages have been inspected. - - ``_flagged_messages``: how many of those messages contained any flagged keyword. - - ``_flagged_keywords``: the set of distinct keywords actually observed. - - Two handlers dispatch by input type: - - - ``inspect`` accepts a string, updates the counters, and sends nothing. - - ``emit_report`` accepts a ``ReportRequest`` and forwards a current - ``StatsSnapshot`` to the downstream reporter. - - Without overriding ``reset()`` this state would leak into the next job when the - workflow is reused via ``Workflow.reset_for_new_run()``. The override below - clears these attributes so each fresh job starts empty. - """ - - FLAGGED_KEYWORDS = frozenset({"spam", "scam", "phishing"}) - - def __init__(self, id: str) -> None: - super().__init__(id=id) - self._messages_seen: int = 0 - self._flagged_messages: int = 0 - self._flagged_keywords: set[str] = set() - - @handler - async def inspect(self, message: str, ctx: WorkflowContext[StatsSnapshot]) -> None: - """Inspect ``message`` and update local stats. Sends nothing downstream.""" - self._messages_seen += 1 - hits = {kw for kw in self.FLAGGED_KEYWORDS if kw in message.lower()} - if hits: - self._flagged_messages += 1 - self._flagged_keywords.update(hits) - - @handler - async def emit_report(self, _: ReportRequest, ctx: WorkflowContext[StatsSnapshot]) -> None: - """Forward the current stats snapshot to the reporter on request.""" - await ctx.send_message( - StatsSnapshot( - messages_seen=self._messages_seen, - flagged_messages=self._flagged_messages, - flagged_keywords=sorted(self._flagged_keywords), - ) - ) - - @override - async def reset(self) -> None: - """Clear per-job aggregate state when the workflow is reset. - - ``Workflow.reset_for_new_run()`` calls ``reset()`` on every executor in the - graph; overriding it here is what makes a reused workflow safe to drive with - a brand-new job. - """ - self._messages_seen = 0 - self._flagged_messages = 0 - self._flagged_keywords.clear() - - -class StatsReporter(Executor): - """Terminal executor that formats a snapshot and yields it as workflow output. - - Holds a single instance attribute, ``_reports_emitted``, that tracks how many - summaries this reporter has produced on this workflow instance, and clears - it on reset so a reset workflow behaves identically to a freshly built one. - """ - - def __init__(self, id: str) -> None: - super().__init__(id=id) - self._reports_emitted: int = 0 - - @handler - async def report(self, snapshot: StatsSnapshot, ctx: WorkflowContext[Never, str]) -> None: - self._reports_emitted += 1 - summary = ( - f"messages={snapshot.messages_seen}, " - f"flagged={snapshot.flagged_messages}, " - f"keywords={snapshot.flagged_keywords or 'none'}, " - f"reports_emitted={self._reports_emitted}" - ) - await ctx.yield_output(summary) - - @override - async def reset(self) -> None: - """Clear the emitted-reports counter when the workflow is reset.""" - self._reports_emitted = 0 - - -async def _process(workflow: Workflow, messages: list[str]) -> None: - """Send each message through the workflow; no output is produced.""" - for message in messages: - await workflow.run(message) - - -async def _request_report(workflow: Workflow) -> str: - """Ask the workflow for a summary of the stats accumulated so far.""" - events = await workflow.run(ReportRequest()) - outputs = events.get_outputs() - return outputs[0] if outputs else "" - - -async def main() -> None: - """Build the moderation workflow once, then run it across three independent jobs.""" - - # 1. Build the moderation pipeline once. The same workflow instance will be - # reused for every job; that's the whole point of this sample. - counter = FlaggedKeywordCounter(id="counter") - reporter = StatsReporter(id="reporter") - workflow = WorkflowBuilder(start_executor=counter, output_from=[reporter]).add_edge(counter, reporter).build() - - # 2. First job -- inspect three messages, then request a report. Note this - # batch happens to be three messages, but any size works. - await _process(workflow, ["hello there", "free phishing kit", "lunch plans?"]) - print(f"Batch A summary: {await _request_report(workflow)}") - - # 3. Second job WITHOUT reset. State from batch A leaks in: the counter's - # tallies and the reporter's emitted-reports counter both keep - # accumulating even though batch B is conceptually a separate job. - await _process(workflow, ["weekly status update", "team offsite agenda", "quarterly review"]) - print(f"Batch B summary (no reset): {await _request_report(workflow)}") - - # 4. Now reset between jobs and process the same batch B again. The summary - # reflects only batch B and every per-run counter starts fresh, because - # reset_for_new_run() calls reset() on every executor in the graph: - # - FlaggedKeywordCounter clears its message / flag / keyword tallies. - # - StatsReporter clears its emitted-reports counter. - await workflow.reset_for_new_run() - await _process(workflow, ["weekly status update", "team offsite agenda", "quarterly review"]) - print(f"Batch B summary (after reset): {await _request_report(workflow)}") - - # 5. Reset again before a final unrelated job. A reset workflow is - # indistinguishable from a freshly built one for state purposes, but - # cheaper because the graph and executor objects are reused. - await workflow.reset_for_new_run() - await _process(workflow, ["spam offer #1", "scam alert", "phishing attempt"]) - print(f"Batch C summary (after reset): {await _request_report(workflow)}") - - """ - Sample Output: - - Batch A summary: messages=3, flagged=1, keywords=['phishing'], reports_emitted=1 - Batch B summary (no reset): messages=6, flagged=1, keywords=['phishing'], reports_emitted=2 - Batch B summary (after reset): messages=3, flagged=0, keywords=none, reports_emitted=1 - Batch C summary (after reset): messages=3, flagged=3, keywords=['phishing', 'scam', 'spam'], reports_emitted=1 - """ - - -if __name__ == "__main__": - asyncio.run(main()) From ed272415435193b549488979bd167c401c6f9ef1 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Thu, 11 Jun 2026 11:43:41 -0700 Subject: [PATCH 11/13] Add tests --- .../agent_framework/_workflows/_runner.py | 2 +- .../agent_framework/_workflows/_workflow.py | 3 +- .../tests/workflow/test_runner_context.py | 72 +++++++++++ .../core/tests/workflow/test_workflow.py | 110 +++++++++++++++++ .../foundry_hosting/tests/test_responses.py | 115 ++++++++++++++++++ 5 files changed, 299 insertions(+), 3 deletions(-) create mode 100644 python/packages/core/tests/workflow/test_runner_context.py diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index d36c53186eb..820864c9e51 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -97,7 +97,7 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: yield event # Create a checkpoint before a run starts. Checkpoints are usually considered to be created at the - # end of an iteration, we can think of this checkpoint as being created at the end of a "superstep 0" + # end of an iteration, we can think of this checkpoint as being created at the end of "superstep 0" # which captures the states after which the start executor has run. Note that we execute the start # executor outside of the main iteration loop. if await self._ctx.has_messages() and not self._resumed_from_checkpoint: diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 0e0d9fe6cd4..8127e6dc01b 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -788,8 +788,7 @@ def run( # fully consumed, ``_run_core``'s finally clears the attribute. When the # caller drops the stream without iterating, garbage collection invalidates # the weakref, so a subsequent ``run`` is permitted. - existing_stream = self._active_run() if self._active_run is not None else None - if existing_stream is not None: + if self._is_run_active(): raise WorkflowException( "Workflow is already running; concurrent runs are not allowed on the same instance." ) diff --git a/python/packages/core/tests/workflow/test_runner_context.py b/python/packages/core/tests/workflow/test_runner_context.py new file mode 100644 index 00000000000..2a4662db574 --- /dev/null +++ b/python/packages/core/tests/workflow/test_runner_context.py @@ -0,0 +1,72 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Tests for `InProcRunnerContext`.""" + +import pytest + +from agent_framework import ( + InProcRunnerContext, + WorkflowEvent, + WorkflowMessage, +) + + +def _make_request_info_event(request_id: str, source_executor_id: str = "executor") -> WorkflowEvent[str]: + return WorkflowEvent.request_info( + request_id=request_id, + source_executor_id=source_executor_id, + request_data="please respond", + response_type=str, + ) + + +class TestInProcRunnerContextResetForNewRun: + """Verify `reset_for_new_run` clears per-run state, including pending request_info events.""" + + async def test_reset_clears_pending_request_info_events(self) -> None: + ctx = InProcRunnerContext() + + await ctx.add_request_info_event(_make_request_info_event("req-1")) + await ctx.add_request_info_event(_make_request_info_event("req-2")) + + assert set((await ctx.get_pending_request_info_events()).keys()) == {"req-1", "req-2"} + + ctx.reset_for_new_run() + + assert await ctx.get_pending_request_info_events() == {} + + async def test_reset_clears_pending_request_info_events_when_already_empty(self) -> None: + ctx = InProcRunnerContext() + + assert await ctx.get_pending_request_info_events() == {} + + ctx.reset_for_new_run() + + assert await ctx.get_pending_request_info_events() == {} + + async def test_reset_after_pending_event_blocks_response_correlation(self) -> None: + """After `reset_for_new_run`, prior request ids must no longer correlate to a response.""" + ctx = InProcRunnerContext() + await ctx.add_request_info_event(_make_request_info_event("req-1")) + + ctx.reset_for_new_run() + + with pytest.raises(ValueError, match="No pending request found for request_id: req-1"): + await ctx.send_request_info_response("req-1", "answer") + + async def test_reset_clears_messages_events_and_streaming_flag(self) -> None: + """Sanity-check the other state `reset_for_new_run` is documented to clear.""" + ctx = InProcRunnerContext() + await ctx.send_message(WorkflowMessage(data="hello", source_id="executor")) + await ctx.add_event(WorkflowEvent("status", data="running")) + ctx.set_streaming(True) + + assert await ctx.has_messages() is True + assert await ctx.has_events() is True + assert ctx.is_streaming() is True + + ctx.reset_for_new_run() + + assert await ctx.has_messages() is False + assert await ctx.has_events() is False + assert ctx.is_streaming() is False diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index fb46e6d426a..ce23cfda3dc 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -20,6 +20,7 @@ Content, Executor, FileCheckpointStorage, + InMemoryCheckpointStorage, Message, ResponseStream, WorkflowBuilder, @@ -1353,3 +1354,112 @@ async def test_output_executors_filtering_with_run_responses_streaming() -> None # endregion + + +# region Workflow.create_checkpoint + + +class TestWorkflowCreateCheckpoint: + """Tests for :meth:`Workflow.create_checkpoint`.""" + + async def test_returns_checkpoint_id_with_runtime_storage(self, simple_executor: Executor) -> None: + """Calling `create_checkpoint` with a runtime storage persists a checkpoint and returns its id.""" + storage = InMemoryCheckpointStorage() + workflow = WorkflowBuilder(start_executor=simple_executor).add_edge(simple_executor, simple_executor).build() + + checkpoint_id = await workflow.create_checkpoint(storage) + + assert checkpoint_id + loaded = await storage.load(checkpoint_id) + assert loaded is not None + assert loaded.checkpoint_id == checkpoint_id + assert loaded.workflow_name == workflow.name + assert loaded.graph_signature_hash == workflow.graph_signature_hash + + async def test_uses_buildtime_storage_when_none_provided(self, simple_executor: Executor) -> None: + """When called with `None`, the build-time storage is used.""" + storage = InMemoryCheckpointStorage() + workflow = ( + WorkflowBuilder(start_executor=simple_executor, checkpoint_storage=storage) + .add_edge(simple_executor, simple_executor) + .build() + ) + + checkpoint_id = await workflow.create_checkpoint(None) + + loaded = await storage.load(checkpoint_id) + assert loaded is not None + assert loaded.checkpoint_id == checkpoint_id + + async def test_raises_when_no_storage_available(self, simple_executor: Executor) -> None: + """Without build-time or runtime storage, `create_checkpoint(None)` raises.""" + workflow = WorkflowBuilder(start_executor=simple_executor).add_edge(simple_executor, simple_executor).build() + + with pytest.raises(WorkflowCheckpointException, match="Checkpoint storage must be provided"): + await workflow.create_checkpoint(None) + + async def test_raises_while_run_active(self, simple_executor: Executor) -> None: + """`create_checkpoint` must reject while a workflow run is still active.""" + storage = InMemoryCheckpointStorage() + workflow = WorkflowBuilder(start_executor=simple_executor).add_edge(simple_executor, simple_executor).build() + + # Hold a live reference to a streaming run without iterating it so that + # ``_is_run_active`` remains True (the active-run weakref still resolves). + active_stream = workflow.run(WorkflowMessage(data="hi", source_id="test"), stream=True) + try: + with pytest.raises(WorkflowException, match="Cannot create checkpoint while a workflow run is active"): + await workflow.create_checkpoint(storage) + finally: + # Drain the stream so the run completes cleanly and the active-run + # weakref is cleared; otherwise pytest's asyncio teardown can leak + # the unconsumed generator. + async for _ in active_stream: + pass + + async def test_clears_runtime_storage_after_call(self, simple_executor: Executor) -> None: + """The runtime storage override must not leak past the call.""" + storage = InMemoryCheckpointStorage() + workflow = WorkflowBuilder(start_executor=simple_executor).add_edge(simple_executor, simple_executor).build() + + await workflow.create_checkpoint(storage) + + assert workflow._runner.context.has_checkpointing() is False + assert workflow._runner.context._runtime_checkpoint_storage is None # type: ignore[attr-defined] + + async def test_clears_runtime_storage_after_failure(self, simple_executor: Executor) -> None: + """The runtime storage override must be cleared even if checkpoint creation fails.""" + from unittest.mock import AsyncMock + + storage = InMemoryCheckpointStorage() + workflow = WorkflowBuilder(start_executor=simple_executor).add_edge(simple_executor, simple_executor).build() + + # The runner logs-and-swallows storage save errors, so a failed save + # surfaces as the "Failed to create checkpoint." path when + # ``previous_checkpoint_id`` remains ``None``. Either way, the + # ``finally`` cleanup must still clear the runtime override. + storage.save = AsyncMock(side_effect=RuntimeError("boom")) # type: ignore[method-assign] + + with pytest.raises(WorkflowCheckpointException, match="Failed to create checkpoint"): + await workflow.create_checkpoint(storage) + + assert workflow._runner.context._runtime_checkpoint_storage is None # type: ignore[attr-defined] + + async def test_alters_lineage_for_next_checkpoint(self, simple_executor: Executor) -> None: + """A manually created checkpoint becomes the parent of the next checkpoint.""" + storage = InMemoryCheckpointStorage() + workflow = ( + WorkflowBuilder(start_executor=simple_executor, checkpoint_storage=storage) + .add_edge(simple_executor, simple_executor) + .build() + ) + + first_id = await workflow.create_checkpoint(None) + second_id = await workflow.create_checkpoint(None) + + assert first_id != second_id + second = await storage.load(second_id) + assert second is not None + assert second.previous_checkpoint_id == first_id + + +# endregion diff --git a/python/packages/foundry_hosting/tests/test_responses.py b/python/packages/foundry_hosting/tests/test_responses.py index f3061885e44..d9c0512c4c9 100644 --- a/python/packages/foundry_hosting/tests/test_responses.py +++ b/python/packages/foundry_hosting/tests/test_responses.py @@ -3063,6 +3063,121 @@ async def test_handle_inner_workflow_restores_message_role_checkpoint_from_previ assert new_turn_messages[0].text == "next turn" assert new_turn_call.kwargs["checkpoint_storage"].storage_path == (root / response_id).resolve() + async def test_handle_inner_workflow_restores_initial_checkpoint_when_no_context_id(self, tmp_path: Any) -> None: + """When neither previous_response_id nor conversation_id is supplied, the workflow + must be restored from the initial checkpoint to avoid context bleed between requests. + """ + from agent_framework import WorkflowAgent + from azure.ai.agentserver.responses import ResponseContext + from azure.ai.agentserver.responses.models import CreateResponse, ItemMessage + + response_id = "resp_current" + root = tmp_path / "root" + root.mkdir() + + agent = MagicMock(spec=WorkflowAgent) + agent.id = "wf-agent" + agent.name = "wf" + agent.description = "" + agent.context_providers = [] + agent.workflow = MagicMock() + agent.workflow.name = "wf" + agent.workflow._runner_context.has_checkpointing = MagicMock(return_value=False) + agent.workflow.create_checkpoint = AsyncMock(return_value="cp_initial") + agent.run = AsyncMock( + side_effect=[ + AgentResponse(messages=[]), + AgentResponse(messages=[Message(role="assistant", contents=[Content.from_text("ok")])]), + ] + ) + server = ResponsesHostServer(agent, store=InMemoryResponseProvider()) + server._checkpoint_storage_path = str(root) # pyright: ignore[reportPrivateUsage] + + # No previous_response_id and no conversation_id. + request = CreateResponse(model="m", input="hi") + context = ResponseContext(response_id=response_id, mode_flags=MagicMock()) + input_item = ItemMessage({"type": "message", "role": "user", "content": "fresh turn"}) + + with patch.object(ResponseContext, "get_input_items", new=AsyncMock(return_value=[input_item])): + async for _ in server._handle_inner_workflow(request, context): # pyright: ignore[reportPrivateUsage] + pass + + # The initial checkpoint must have been created exactly once, against the + # initial checkpoint storage owned by the server. + assert agent.workflow.create_checkpoint.await_count == 1 + (initial_storage_arg,) = agent.workflow.create_checkpoint.await_args.args + assert initial_storage_arg is server._initial_checkpoint_storage # pyright: ignore[reportPrivateUsage] + + # First run() call is the restoration: no positional input, restored from + # the initial checkpoint id, using the initial checkpoint storage (NOT a + # per-context directory). + assert agent.run.call_count == 2 + restore_call = agent.run.call_args_list[0] + assert restore_call.args == () + assert restore_call.kwargs["checkpoint_id"] == "cp_initial" + assert restore_call.kwargs["checkpoint_storage"] is server._initial_checkpoint_storage # pyright: ignore[reportPrivateUsage] + + # Second run() call delivers the new input; checkpoints land under response_id + # (the write-sink directory keyed by the current response id). + new_turn_call = agent.run.call_args_list[1] + new_turn_messages = new_turn_call.args[0] + assert len(new_turn_messages) == 1 + assert new_turn_messages[0].text == "fresh turn" + assert new_turn_call.kwargs["checkpoint_storage"].storage_path == (root / response_id).resolve() + + async def test_handle_inner_workflow_creates_initial_checkpoint_once_across_requests(self, tmp_path: Any) -> None: + """The initial checkpoint must be created exactly once and reused across + subsequent requests, regardless of whether the requests carry a context id. + """ + from agent_framework import WorkflowAgent + from azure.ai.agentserver.responses import ResponseContext + from azure.ai.agentserver.responses.models import CreateResponse, ItemMessage + + root = tmp_path / "root" + root.mkdir() + + agent = MagicMock(spec=WorkflowAgent) + agent.id = "wf-agent" + agent.name = "wf" + agent.description = "" + agent.context_providers = [] + agent.workflow = MagicMock() + agent.workflow.name = "wf" + agent.workflow._runner_context.has_checkpointing = MagicMock(return_value=False) + agent.workflow.create_checkpoint = AsyncMock(return_value="cp_initial") + # Four run() calls total: restore + new turn for each of the two requests. + agent.run = AsyncMock(return_value=AgentResponse(messages=[])) + + server = ResponsesHostServer(agent, store=InMemoryResponseProvider()) + server._checkpoint_storage_path = str(root) # pyright: ignore[reportPrivateUsage] + + request1 = CreateResponse(model="m", input="hi") + context1 = ResponseContext(response_id="resp_first", mode_flags=MagicMock()) + request2 = CreateResponse(model="m", input="hi again") + context2 = ResponseContext(response_id="resp_second", mode_flags=MagicMock()) + input_item = ItemMessage({"type": "message", "role": "user", "content": "turn"}) + + with patch.object(ResponseContext, "get_input_items", new=AsyncMock(return_value=[input_item])): + async for _ in server._handle_inner_workflow(request1, context1): # pyright: ignore[reportPrivateUsage] + pass + async for _ in server._handle_inner_workflow(request2, context2): # pyright: ignore[reportPrivateUsage] + pass + + # Initial checkpoint creation must not be repeated on the second request. + assert agent.workflow.create_checkpoint.await_count == 1 + + # Both requests' restoration calls must use the same initial checkpoint id + # and the same initial checkpoint storage instance. + restore_call_1 = agent.run.call_args_list[0] + restore_call_2 = agent.run.call_args_list[2] + assert restore_call_1.kwargs["checkpoint_id"] == "cp_initial" + assert restore_call_2.kwargs["checkpoint_id"] == "cp_initial" + assert ( + restore_call_1.kwargs["checkpoint_storage"] + is restore_call_2.kwargs["checkpoint_storage"] + is server._initial_checkpoint_storage # pyright: ignore[reportPrivateUsage] + ) + @pytest.mark.parametrize( "bad_id", [ From b0d0224ed40b83b2f2fb5b381f81d67e8a280a92 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Thu, 11 Jun 2026 15:27:36 -0700 Subject: [PATCH 12/13] Address comments --- .../_workflows/_runner_context.py | 5 +- .../agent_framework/_workflows/_workflow.py | 11 +++- .../core/tests/workflow/test_workflow.py | 31 ++++++++++ .../_responses.py | 9 ++- .../foundry_hosting/tests/test_responses.py | 60 +++++++++++++++++++ 5 files changed, 110 insertions(+), 6 deletions(-) diff --git a/python/packages/core/agent_framework/_workflows/_runner_context.py b/python/packages/core/agent_framework/_workflows/_runner_context.py index 23a748f0beb..30f82955244 100644 --- a/python/packages/core/agent_framework/_workflows/_runner_context.py +++ b/python/packages/core/agent_framework/_workflows/_runner_context.py @@ -403,8 +403,9 @@ async def load_checkpoint(self, checkpoint_id: CheckpointID) -> WorkflowCheckpoi def reset_for_new_run(self) -> None: """Reset the context for a new workflow run. - This clears messages, events, and resets streaming flag. - Runtime checkpoint storage is NOT cleared here as it's managed at the workflow level. + Clears messages, the pending event queue, the pending request_info + correlation map, and the streaming flag. Runtime checkpoint storage is + NOT cleared here as it's managed at the workflow level. """ self._messages.clear() # Clear any pending events (best-effort) by recreating the queue diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index 8127e6dc01b..09ff6c28c18 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -503,11 +503,18 @@ async def create_checkpoint(self, checkpoint_storage: CheckpointStorage | None) if checkpoint_storage is not None: self._runner.context.set_runtime_checkpoint_storage(checkpoint_storage) + # Capture the runner's checkpoint id before attempting to save. The runner + # log-and-swallows storage save errors and only updates + # ``previous_checkpoint_id`` on success, so a failed save would otherwise + # leave the prior id in place and we'd return it as if a fresh checkpoint + # had been created. + previous_id_before = self._runner.previous_checkpoint_id try: await self._runner.create_checkpoint_if_enabled() - if self._runner.previous_checkpoint_id is None: + new_id = self._runner.previous_checkpoint_id + if new_id is None or new_id == previous_id_before: raise WorkflowCheckpointException("Failed to create checkpoint.") - return self._runner.previous_checkpoint_id + return new_id finally: self._runner.context.clear_runtime_checkpoint_storage() diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index ce23cfda3dc..9884088cdf9 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -1461,5 +1461,36 @@ async def test_alters_lineage_for_next_checkpoint(self, simple_executor: Executo assert second is not None assert second.previous_checkpoint_id == first_id + async def test_raises_when_save_fails_after_prior_success(self, simple_executor: Executor) -> None: + """A failed save after an earlier successful checkpoint must not return the stale id. + + The runner log-and-swallows storage save errors and only updates + ``previous_checkpoint_id`` on success. Without an explicit transition check, + ``create_checkpoint`` would silently return the previously stored id as if a + new checkpoint had been created. + """ + from unittest.mock import AsyncMock + + storage = InMemoryCheckpointStorage() + workflow = WorkflowBuilder(start_executor=simple_executor).add_edge(simple_executor, simple_executor).build() + + # First call succeeds and seeds ``previous_checkpoint_id``. + first_id = await workflow.create_checkpoint(storage) + assert first_id + + # Second call fails to save, so the runner leaves ``previous_checkpoint_id`` + # pointing at ``first_id``. The method must detect that the id did not + # transition and raise instead of returning the stale value. + original_save = storage.save + storage.save = AsyncMock(side_effect=RuntimeError("boom")) # type: ignore[method-assign] + try: + with pytest.raises(WorkflowCheckpointException, match="Failed to create checkpoint"): + await workflow.create_checkpoint(storage) + finally: + storage.save = original_save # type: ignore[method-assign] + + # The runner's bookkeeping is unchanged after the failed call. + assert workflow._runner.previous_checkpoint_id == first_id # type: ignore[attr-defined] + # endregion diff --git a/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py b/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py index 1a5b0e32d00..1f64d24eff4 100644 --- a/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py +++ b/python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py @@ -616,10 +616,15 @@ async def _handle_inner_workflow( latest_checkpoint_id: str = self._initial_checkpoint_id restore_storage: FileCheckpointStorage = self._initial_checkpoint_storage if context_id is not None: - restore_storage = _checkpoint_storage_for_context(self._checkpoint_storage_path, context_id) - latest_checkpoint = await restore_storage.get_latest(workflow_name=self._agent.workflow.name) + context_storage = _checkpoint_storage_for_context(self._checkpoint_storage_path, context_id) + latest_checkpoint = await context_storage.get_latest(workflow_name=self._agent.workflow.name) if latest_checkpoint is not None: + # Only switch the restore storage when a checkpoint was actually + # found under the per-context directory. Otherwise the initial + # checkpoint id would not resolve in `context_storage` and the + # restore call below would fail. latest_checkpoint_id = latest_checkpoint.checkpoint_id + restore_storage = context_storage # Restore the workflow to the latest checkpoint and run it with the # new input. Events (including request info events) will not be emitted diff --git a/python/packages/foundry_hosting/tests/test_responses.py b/python/packages/foundry_hosting/tests/test_responses.py index d9c0512c4c9..13923cc9d2d 100644 --- a/python/packages/foundry_hosting/tests/test_responses.py +++ b/python/packages/foundry_hosting/tests/test_responses.py @@ -3178,6 +3178,66 @@ async def test_handle_inner_workflow_creates_initial_checkpoint_once_across_requ is server._initial_checkpoint_storage # pyright: ignore[reportPrivateUsage] ) + async def test_handle_inner_workflow_falls_back_to_initial_storage_when_context_dir_is_empty( + self, tmp_path: Any + ) -> None: + """When ``previous_response_id`` is supplied but its checkpoint directory has no + checkpoints, the restoration must fall back to BOTH the initial checkpoint id + and the initial checkpoint storage. Otherwise the initial id would be looked up + inside the per-context storage where it does not exist, and the restore would + fail. + """ + from agent_framework import WorkflowAgent + from azure.ai.agentserver.responses import ResponseContext + from azure.ai.agentserver.responses.models import CreateResponse, ItemMessage + + previous_response_id = "resp_previous" + response_id = "resp_current" + root = tmp_path / "root" + root.mkdir() + # The per-context storage exists but contains no checkpoints. + (root / previous_response_id).mkdir() + + agent = MagicMock(spec=WorkflowAgent) + agent.id = "wf-agent" + agent.name = "wf" + agent.description = "" + agent.context_providers = [] + agent.workflow = MagicMock() + agent.workflow.name = "wf" + agent.workflow._runner_context.has_checkpointing = MagicMock(return_value=False) + agent.workflow.create_checkpoint = AsyncMock(return_value="cp_initial") + agent.run = AsyncMock( + side_effect=[ + AgentResponse(messages=[]), + AgentResponse(messages=[Message(role="assistant", contents=[Content.from_text("ok")])]), + ] + ) + server = ResponsesHostServer(agent, store=InMemoryResponseProvider()) + server._checkpoint_storage_path = str(root) # pyright: ignore[reportPrivateUsage] + + request = CreateResponse(model="m", input="hi", previous_response_id=previous_response_id) + context = ResponseContext( + response_id=response_id, previous_response_id=previous_response_id, mode_flags=MagicMock() + ) + input_item = ItemMessage({"type": "message", "role": "user", "content": "next turn"}) + + with patch.object(ResponseContext, "get_input_items", new=AsyncMock(return_value=[input_item])): + async for _ in server._handle_inner_workflow(request, context): # pyright: ignore[reportPrivateUsage] + pass + + # The restoration call must use the initial id AND the initial storage, + # not the empty per-context storage. Mismatching the two would attempt + # to load ``cp_initial`` from a directory that doesn't contain it. + assert agent.run.call_count == 2 + restore_call = agent.run.call_args_list[0] + assert restore_call.kwargs["checkpoint_id"] == "cp_initial" + assert restore_call.kwargs["checkpoint_storage"] is server._initial_checkpoint_storage # pyright: ignore[reportPrivateUsage] + + # The new turn still writes checkpoints under the current response id. + new_turn_call = agent.run.call_args_list[1] + assert new_turn_call.kwargs["checkpoint_storage"].storage_path == (root / response_id).resolve() + @pytest.mark.parametrize( "bad_id", [ From 422f7e73823e22bf5ee9a0cffaef43f85f95bf18 Mon Sep 17 00:00:00 2001 From: Tao Chen Date: Thu, 11 Jun 2026 16:54:42 -0700 Subject: [PATCH 13/13] Address comments --- python/packages/core/agent_framework/__init__.py | 2 +- python/packages/core/agent_framework/_tools.py | 4 +--- python/packages/core/agent_framework/_workflows/_runner.py | 6 +++--- 3 files changed, 5 insertions(+), 7 deletions(-) diff --git a/python/packages/core/agent_framework/__init__.py b/python/packages/core/agent_framework/__init__.py index 3a001cdb027..445f138c885 100644 --- a/python/packages/core/agent_framework/__init__.py +++ b/python/packages/core/agent_framework/__init__.py @@ -125,7 +125,6 @@ TodoSessionStore, TodoStore, ) -from ._mcp import MCPStdioTool, MCPStreamableHTTPTool, MCPTaskOptions, MCPWebsocketTool, SamplingApprovalCallback from ._harness._tool_approval import ( DEFAULT_TOOL_APPROVAL_SOURCE_ID, ToolApprovalMiddleware, @@ -135,6 +134,7 @@ create_always_approve_tool_response, create_always_approve_tool_with_arguments_response, ) +from ._mcp import MCPStdioTool, MCPStreamableHTTPTool, MCPTaskOptions, MCPWebsocketTool, SamplingApprovalCallback from ._middleware import ( AgentContext, AgentMiddleware, diff --git a/python/packages/core/agent_framework/_tools.py b/python/packages/core/agent_framework/_tools.py index ad232ffeb44..065324289f3 100644 --- a/python/packages/core/agent_framework/_tools.py +++ b/python/packages/core/agent_framework/_tools.py @@ -1989,9 +1989,7 @@ def _store_already_approved_approval_requests( return existing_groups = state.get(_ALREADY_APPROVED_APPROVAL_REQUEST_GROUPS_KEY) - pending_groups: list[Any] = ( - list(cast(Iterable[Any], existing_groups)) if isinstance(existing_groups, list) else [] - ) + pending_groups: list[Any] = list(cast(Iterable[Any], existing_groups)) if isinstance(existing_groups, list) else [] pending_groups.append({ "approval_request_ids": visible_ids, "approval_requests": [request.to_dict() for request in already_approved_requests], diff --git a/python/packages/core/agent_framework/_workflows/_runner.py b/python/packages/core/agent_framework/_workflows/_runner.py index 820864c9e51..db6b61af1f7 100644 --- a/python/packages/core/agent_framework/_workflows/_runner.py +++ b/python/packages/core/agent_framework/_workflows/_runner.py @@ -156,12 +156,12 @@ async def run_until_convergence(self) -> AsyncGenerator[WorkflowEvent, None]: if not await self._ctx.has_messages(): break - if self._iteration >= self._max_iterations and await self._ctx.has_messages(): - raise WorkflowConvergenceException(f"Runner did not converge after {self._max_iterations} iterations.") - logger.info(f"Workflow completed after {self._iteration} supersteps") self._resumed_from_checkpoint = False # Reset resume flag for next run + if self._iteration >= self._max_iterations and await self._ctx.has_messages(): + raise WorkflowConvergenceException(f"Runner did not converge after {self._max_iterations} iterations.") + async def _run_iteration(self) -> None: """Run a single iteration of the workflow.