mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Remove lifecycle flag
This commit is contained in:
@@ -17,7 +17,6 @@ from agent_framework import (
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WorkflowContext,
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WorkflowConvergenceException,
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WorkflowEvent,
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WorkflowRunnerException,
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WorkflowRunState,
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handler,
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)
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@@ -106,7 +105,6 @@ async def test_runner_run_until_convergence():
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state, # state
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ctx, # runner_context
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)
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runner.reserve()
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async for event in runner.run_until_convergence():
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assert isinstance(event, WorkflowEvent)
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if event.type == "output":
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@@ -148,7 +146,6 @@ async def test_runner_run_until_convergence_not_completed():
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WorkflowConvergenceException,
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match="Runner did not converge after 5 iterations.",
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):
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runner.reserve()
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async for event in runner.run_until_convergence():
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assert event.type != "status" or event.state != WorkflowRunState.IDLE
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@@ -307,16 +304,22 @@ async def test_fanout_edge_runner_delivers_to_multiple_targets_concurrently() ->
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assert probe_target.call_count == 1
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async def test_runner_run_until_convergence_requires_reservation():
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"""run_until_convergence refuses to start without a prior reserve()."""
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async def test_runner_run_until_convergence_runs_sequentially():
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"""run_until_convergence can be invoked back-to-back on the same Runner.
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The Runner itself does not enforce concurrency; that responsibility lives on
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:class:`Workflow`. This test simply confirms the Runner is reusable across
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sequential runs.
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"""
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runner = _make_runner()
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with pytest.raises(WorkflowRunnerException, match="Runner must be reserved"):
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async for _ in runner.run_until_convergence():
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pass
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async for _ in runner.run_until_convergence():
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pass
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async for _ in runner.run_until_convergence():
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pass
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def _make_runner() -> Runner:
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"""Build a minimal runner for lifecycle tests."""
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"""Build a minimal runner for runner-level tests."""
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return Runner(
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[],
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{},
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@@ -327,57 +330,11 @@ def _make_runner() -> Runner:
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)
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def test_runner_reserve_twice_raises():
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"""Calling reserve() while already reserved rejects the second caller.
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This is what guards Workflow.run against a concurrent caller slipping in
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between the first call's synchronous reserve() and its first await.
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"""
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runner = _make_runner()
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runner.reserve()
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with pytest.raises(WorkflowRunnerException, match="Runner is already reserved or running."):
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runner.reserve()
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def test_runner_reserve_after_release_is_accepted():
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"""Sequential runs are permitted; only concurrent ones are blocked."""
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runner = _make_runner()
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runner.reserve()
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runner.release()
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runner.reserve() # should not raise
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def test_runner_release_when_idle_is_noop():
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"""release() on an idle runner does not affect a subsequent reserve().
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Workflow._run_core's finally always calls release(), even when
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run_until_convergence already cleared the lock in its own finally;
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that double-release must not lock out the next run.
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"""
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runner = _make_runner()
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runner.release() # already idle - must not raise or wedge state
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runner.reserve() # next run still allowed
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async def test_runner_run_until_convergence_consumes_reservation():
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"""run_until_convergence accepts a prior reservation and runs to completion."""
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runner = _make_runner()
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runner.reserve()
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async for _ in runner.run_until_convergence():
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pass
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# A second run after the first completes must be accepted.
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runner.reserve()
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async for _ in runner.run_until_convergence():
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pass
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async def test_runner_accepts_new_run_after_previous_failure():
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"""A failed run must not leave the runner locked out of future runs.
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"""A failed run must not leave the Runner unable to start a new run.
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After the first run raises, a fresh ``reserve()`` and
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``run_until_convergence()`` must succeed (or fail for a different reason -
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e.g. residual messages still don't converge - but never with the
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lock-rejection ``"Runner is already running."``).
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After the first run raises, ``run_until_convergence()`` must be callable
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again and not surface any lifecycle-related rejection.
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"""
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executor_a = MockExecutor(id="executor_a")
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executor_b = MockExecutor(id="executor_b")
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@@ -392,13 +349,12 @@ async def test_runner_accepts_new_run_after_previous_failure():
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await executor_a.execute(MockMessage(data=0), ["START"], state, ctx)
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runner.reserve()
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with pytest.raises(WorkflowConvergenceException):
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async for _ in runner.run_until_convergence():
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pass
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# The runner should accept a fresh reservation and run again.
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runner.reserve() # must not raise
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# A second run on the same Runner must not be blocked by stale lifecycle
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# state from the failed run.
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try:
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async for _ in runner.run_until_convergence():
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pass
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@@ -406,40 +362,6 @@ async def test_runner_accepts_new_run_after_previous_failure():
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assert "Runner is already running" not in str(exc), "Runner stayed locked after a failed run"
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async def test_runner_rejects_concurrent_run_until_convergence():
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"""While a run is in progress, a second ``reserve()`` is rejected.
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Confirms the run lock is held for the full duration of the run, not just
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synchronously between ``reserve()`` and the first ``__anext__`` call.
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"""
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runner = _make_runner()
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started = asyncio.Event()
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release = asyncio.Event()
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async def _slow_run():
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runner.reserve()
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async for _ in runner.run_until_convergence():
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if not started.is_set():
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started.set()
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await release.wait()
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task = asyncio.create_task(_slow_run())
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await started.wait() # first run is now executing
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try:
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with pytest.raises(WorkflowRunnerException, match="Runner is already reserved or running."):
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runner.reserve()
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finally:
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release.set()
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await task
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# And after the first run finishes, a new reservation + run must be accepted.
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runner.reserve()
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async for _ in runner.run_until_convergence():
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pass
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async def test_runner_emits_runner_completion_for_agent_response_without_targets():
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ctx = InProcRunnerContext()
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runner = Runner([], {}, State(), ctx, "test_name", graph_signature_hash="test_hash")
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@@ -451,7 +373,6 @@ async def test_runner_emits_runner_completion_for_agent_response_without_targets
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)
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)
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runner.reserve()
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events: list[WorkflowEvent] = [event async for event in runner.run_until_convergence()]
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# The runner should complete without errors when handling AgentExecutorResponse without targets
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# No specific events are expected since there are no executors to process the message
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@@ -508,7 +429,6 @@ async def test_runner_cancellation_stops_active_executor():
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async for _ in runner.run_until_convergence():
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pass
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runner.reserve()
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task = asyncio.create_task(run_workflow())
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# Wait for executor_a to complete (0.3s) and executor_b to start but not finish
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@@ -570,7 +490,6 @@ async def test_runner_iteration_exception_drains_events():
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)
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events: list[WorkflowEvent] = []
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runner.reserve()
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with pytest.raises(RuntimeError, match="Simulated executor failure"):
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async for event in runner.run_until_convergence():
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events.append(event)
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@@ -681,7 +600,6 @@ async def test_runner_checkpoint_creation_failure():
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# Should complete without raising, even though checkpointing fails
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result: int | None = None
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runner.reserve()
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async for event in runner.run_until_convergence():
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if event.type == "output":
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result = event.data
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@@ -878,7 +796,6 @@ async def test_runner_with_pre_loop_events():
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await ctx.add_event(WorkflowEvent("output", executor_id="test_executor", data="pre-loop-output"))
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events: list[WorkflowEvent] = []
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runner.reserve()
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async for event in runner.run_until_convergence():
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events.append(event)
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@@ -926,7 +843,6 @@ async def test_runner_drains_straggler_events():
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)
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events: list[WorkflowEvent] = []
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runner.reserve()
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async for event in runner.run_until_convergence():
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events.append(event)
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@@ -980,7 +896,6 @@ async def test_runner_checkpoint_with_resumed_flag():
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)
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# Run until convergence
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runner.reserve()
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async for _ in runner.run_until_convergence():
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pass
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@@ -1047,7 +962,6 @@ async def test_runner_drains_events_on_iteration_exception():
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)
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events: list[WorkflowEvent] = []
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runner.reserve()
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with pytest.raises(RuntimeError, match="Executor failed with pending events"):
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async for event in runner.run_until_convergence():
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events.append(event)
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@@ -1104,7 +1018,6 @@ async def test_runner_drains_straggler_events_at_iteration_end():
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)
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events: list[WorkflowEvent] = []
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runner.reserve()
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async for event in runner.run_until_convergence():
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events.append(event)
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@@ -1271,7 +1184,6 @@ async def test_runner_can_run_again_after_reset_for_new_run():
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# First run: drives MockExecutor's loop until it yields the terminal value.
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await executor_a.execute(MockMessage(data=0), ["START"], state, ctx)
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runner.reserve()
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async for _ in runner.run_until_convergence():
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pass
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assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage]
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@@ -1280,7 +1192,6 @@ async def test_runner_can_run_again_after_reset_for_new_run():
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# Second run: must succeed cleanly using the same runner instance.
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await executor_a.execute(MockMessage(data=0), ["START"], state, ctx)
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runner.reserve()
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second_run_outputs: list[int] = []
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async for event in runner.run_until_convergence():
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if event.type == "output":
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@@ -1290,77 +1201,4 @@ async def test_runner_can_run_again_after_reset_for_new_run():
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assert runner._iteration == 10 # pyright: ignore[reportPrivateUsage]
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async def test_runner_reset_for_new_run_rejected_when_reserved():
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"""reset_for_new_run refuses to run when the runner is reserved but not yet running."""
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runner = _make_runner()
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runner.reserve()
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with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"):
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await runner.reset_for_new_run()
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async def test_runner_reset_for_new_run_rejected_while_running():
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"""reset_for_new_run refuses to run while a run is mid-execution."""
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runner = _make_runner()
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started = asyncio.Event()
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release = asyncio.Event()
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async def _slow_run() -> None:
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runner.reserve()
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async for _ in runner.run_until_convergence():
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if not started.is_set():
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started.set()
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await release.wait()
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task = asyncio.create_task(_slow_run())
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await started.wait() # first run is now executing inside run_until_convergence
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try:
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with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"):
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await runner.reset_for_new_run()
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finally:
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release.set()
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await task
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# Once the run drained, reset must succeed again.
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await runner.reset_for_new_run()
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async def test_runner_reset_for_new_run_does_not_mutate_when_rejected():
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"""When reset is rejected, the runner's iteration counter and state are untouched."""
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class TrackingExecutor(MockExecutor):
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def __init__(self, id: str) -> None:
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super().__init__(id=id)
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self.reset_calls = 0
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async def reset(self) -> None:
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self.reset_calls += 1
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executor = TrackingExecutor(id="executor")
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state = State()
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state.set("preserved", 42)
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state.commit()
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runner = Runner(
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[],
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{executor.id: executor},
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state,
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InProcRunnerContext(),
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"test_name",
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graph_signature_hash="test_hash",
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)
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runner._iteration = 7 # pyright: ignore[reportPrivateUsage]
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runner.reserve()
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with pytest.raises(WorkflowRunnerException):
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await runner.reset_for_new_run()
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# Nothing was mutated by the failed reset.
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assert runner._iteration == 7 # pyright: ignore[reportPrivateUsage]
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assert state.get("preserved") == 42
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assert executor.reset_calls == 0
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# endregion: Tests for Runner.reset_for_new_run()
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@@ -1,6 +1,7 @@
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import gc
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import tempfile
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from collections.abc import AsyncIterable, Awaitable, Sequence
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from dataclasses import dataclass, field
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@@ -846,6 +847,92 @@ async def test_workflow_concurrent_execution_prevention_mixed_methods():
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assert result.get_final_state() == WorkflowRunState.IDLE
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async def test_workflow_sequential_runs_after_completion() -> None:
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"""A completed run must release the runner so the next ``run`` succeeds.
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This is the happy-path counterpart to the concurrent-run guard tests:
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those tests verify that a *concurrent* run is rejected, but they do not
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verify that the lock is actually released afterwards. This test
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exercises that release path explicitly across the three call shapes
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(non-streaming, streaming-iterated, streaming-via-get_final_response)
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and across multiple consecutive turns to catch lock leaks.
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"""
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executor = IncrementExecutor(id="seq_executor", limit=3, increment=1)
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workflow = WorkflowBuilder(start_executor=executor).build()
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# Non-streaming -> non-streaming
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r1 = await workflow.run(NumberMessage(data=0))
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assert r1.get_final_state() == WorkflowRunState.IDLE
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r2 = await workflow.run(NumberMessage(data=0))
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assert r2.get_final_state() == WorkflowRunState.IDLE
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# Non-streaming -> streaming-iterated
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stream_events: list[WorkflowEvent] = []
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async for event in workflow.run(NumberMessage(data=0), stream=True):
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stream_events.append(event)
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assert any(e.type == "status" and e.state == WorkflowRunState.IDLE for e in stream_events)
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# Streaming -> streaming via get_final_response (no manual iteration)
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r3 = await workflow.run(NumberMessage(data=0), stream=True).get_final_response()
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assert r3.get_final_state() == WorkflowRunState.IDLE
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# Streaming -> non-streaming (back to the start)
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r4 = await workflow.run(NumberMessage(data=0))
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assert r4.get_final_state() == WorkflowRunState.IDLE
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async def test_workflow_unconsumed_stream_releases_run_lock() -> None:
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"""An unconsumed stream must not leak the run lock.
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``Workflow.run`` reserves the runner *synchronously* so that concurrent
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callers are rejected immediately. The reservation is normally released
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by ``_run_core``'s ``finally`` once the stream is iterated. If the
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caller never iterates the stream, a GC-time finalizer must release the
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reservation instead - otherwise every subsequent ``Workflow.run`` call
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on this instance would fail with the concurrent-run error.
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"""
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executor = IncrementExecutor(id="unconsumed_stream_exec", limit=3, increment=1)
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workflow = WorkflowBuilder(start_executor=executor).build()
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# Build a stream and immediately drop it without iterating.
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stream = workflow.run(NumberMessage(data=0), stream=True)
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assert stream is not None # silence unused-variable warnings; stream is GC'd below
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del stream
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gc.collect()
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# Yield to the event loop so any scheduled finalizer work can run.
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await asyncio.sleep(0)
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# The runner should be back to IDLE; a fresh run must succeed.
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result = await workflow.run(NumberMessage(data=0))
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assert result.get_final_state() == WorkflowRunState.IDLE
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async def test_workflow_unawaited_run_coroutine_releases_run_lock() -> None:
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"""An un-awaited non-streaming ``run()`` coroutine must also not leak the lock.
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``Workflow.run`` (non-streaming) returns a coroutine produced by
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``ResponseStream.get_final_response``. The underlying ResponseStream is
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held alive by that coroutine, so dropping the coroutine without
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awaiting it must still release the reservation via the same GC-time
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fallback used for unconsumed streams.
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"""
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executor = IncrementExecutor(id="unawaited_run_exec", limit=3, increment=1)
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workflow = WorkflowBuilder(start_executor=executor).build()
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coro = workflow.run(NumberMessage(data=0))
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# Closing suppresses the "coroutine was never awaited" warning. We cast to
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# ``Any`` because the typed return is ``Awaitable[...]``; in practice it is
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# a coroutine that exposes ``close``.
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cast(Any, coro).close()
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del coro
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gc.collect()
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await asyncio.sleep(0)
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result = await workflow.run(NumberMessage(data=0))
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assert result.get_final_state() == WorkflowRunState.IDLE
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class _StreamingTestAgent(BaseAgent):
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"""Test agent that supports both streaming and non-streaming modes."""
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@@ -1397,7 +1484,7 @@ async def test_workflow_reset_for_new_run_rejected_during_streaming_run() -> Non
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await asyncio.sleep(0.02)
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try:
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with pytest.raises(WorkflowRunnerException, match="Cannot reset the runner while a run is in progress"):
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with pytest.raises(WorkflowRunnerException, match="Cannot reset the workflow while a run is in progress"):
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await workflow.reset_for_new_run()
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finally:
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await task
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||||
Reference in New Issue
Block a user