feat: persist and inspect run step budgets
This commit is contained in:
@@ -0,0 +1,282 @@
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"""Stopped-run step budget migration tests (Task 4).
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Pins the v1-to-v2 upgrade contract: a pre-budget interrupted checkpoint is
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rewritten as v2 and persisted *before* resume dispatch (the runtime must
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observe the upgraded checkpoint when it is called), while ordinary
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inspection decodes v1 prospectively without touching the store.
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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from typing import Any
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from wf_api.models import RawWorkflowPlan
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from wf_api.operation_context import WorkflowOperationContext
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from wf_api.run_lifecycle import (
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create_pinned_environment,
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persist_stopped_run,
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restore_interrupted_run,
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)
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from wf_api.runs import WorkflowRunApi
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from wf_api.saved_subgraphs import SavedSubgraphTree
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from wf_artifacts import (
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FileRunStore,
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WorkflowArtifact,
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WorkflowDeployment,
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)
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from wf_authoring import NodeSpec
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from wf_core import InterruptRequest, RunState, RunStatus
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from wf_platform import CapabilitySource
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class DummyEvents:
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def record_event(self, event: object) -> None:
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pass
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def record_workflow_event(
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self,
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event_type: str,
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*,
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capability_id: str,
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payload: dict[str, Any],
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) -> None:
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pass
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class EmptySpecProvider:
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@property
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def capability_sources(self) -> dict[str, CapabilitySource]:
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return {}
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def get_qualified_spec(self, qualified_name: str) -> NodeSpec[Any, Any]:
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raise KeyError(f"unknown capability {qualified_name!r}")
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class UpgradeAssertingRuntime:
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"""Resume-only fake proving the v1 upgrade persists before dispatch.
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When the API calls resume, the upgraded v2 checkpoint must already be
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the latest persisted checkpoint; otherwise resume dispatched work on top
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of unmigrated state.
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"""
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def __init__(self, store: FileRunStore, run_id: str) -> None:
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self.store = store
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self.run_id = run_id
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self.resume_calls = 0
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async def run_workflow_from_plan(
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self,
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plan: RawWorkflowPlan,
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workflow_input: dict[str, Any],
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deployment: WorkflowDeployment | None = None,
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artifact: WorkflowArtifact | None = None,
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saved_subgraph_tree: SavedSubgraphTree | None = None,
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limits: Any | None = None,
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) -> RunState:
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raise AssertionError("test must not start new workflow runs")
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async def resume_workflow_from_plan(
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self,
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plan: RawWorkflowPlan,
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run: RunState,
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*,
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resume_payload: dict[str, Any],
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resume_outcome: str,
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deployment: WorkflowDeployment | None = None,
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artifact: WorkflowArtifact | None = None,
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saved_subgraph_tree: SavedSubgraphTree | None = None,
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) -> RunState:
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self.resume_calls += 1
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latest = self.store.get_latest_checkpoint(self.run_id)
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upgraded = latest.state.model_dump(mode="json")
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assert upgraded["version"] == 2
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assert upgraded["state"]["limits"] == {"max_steps": 10_000}
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assert upgraded["state"]["steps_executed"] == 0
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assert run.limits.max_steps == 10_000
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assert run.steps_executed == 0
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return RunState(
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workflow_name=plan.name,
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status=RunStatus.COMPLETED,
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workflow_input=run.workflow_input,
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state={"answer": resume_payload["answer"]},
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outcome=resume_outcome,
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output={"answer": resume_payload["answer"]},
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)
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def _artifact() -> WorkflowArtifact:
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return WorkflowArtifact(
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id="pause",
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version=1,
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title="Pause",
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input_schema={"type": "object", "properties": {}},
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output_schema={"type": "object", "properties": {}},
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outcomes=("ok", "submitted"),
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plan={
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"name": "pause",
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"input_schema": {"type": "object", "properties": {}},
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"state_schema": {"type": "object", "properties": {}},
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"output_schema": {"type": "object", "properties": {}},
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"outcomes": ["ok", "submitted"],
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"start": "end_submitted",
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"nodes": [{"id": "end_submitted", "type": "end", "outcome": "submitted"}],
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"edges": [],
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},
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)
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def _deployment(artifact: WorkflowArtifact) -> WorkflowDeployment:
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return WorkflowDeployment(
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id="pause.default",
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artifact_id=artifact.id,
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artifact_version=artifact.version,
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bindings=[],
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)
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def _seed_interrupted_run(store: FileRunStore) -> str:
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artifact = _artifact()
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interrupted = RunState(
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workflow_name="pause",
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status=RunStatus.INTERRUPTED,
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workflow_input={"question": "continue?"},
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state={},
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interrupt=InterruptRequest(
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id="interrupt:approval",
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frame_id="root",
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node_id="approval",
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kind="approval",
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payload={"question": "continue?"},
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),
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)
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record = persist_stopped_run(
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store=store,
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environment=create_pinned_environment(
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deployment=_deployment(artifact),
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artifact=artifact,
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tree=SavedSubgraphTree(artifacts_by_ref={}, diagnostics=[]),
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),
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run=interrupted,
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)
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return record.id
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def _checkpoint_path(store: FileRunStore, run_id: str, sequence: int) -> Path:
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return store.runs_dir / run_id / "checkpoints" / f"{sequence:06d}.json"
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def _read_raw_checkpoint(
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store: FileRunStore, run_id: str, sequence: int
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) -> dict[str, Any]:
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return json.loads(_checkpoint_path(store, run_id, sequence).read_text("utf-8"))
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def _downgrade_latest_checkpoint_to_v1(store: FileRunStore, run_id: str) -> None:
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"""Rewrite the latest checkpoint file as a pre-budget v1 envelope.
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Writes raw JSON directly so the file matches what a legacy (pre-budget)
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writer left on disk, bypassing current model validation.
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"""
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path = _checkpoint_path(store, run_id, 1)
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payload: dict[str, Any] = json.loads(path.read_text("utf-8"))
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inner = payload["state"]["state"]
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inner.pop("limits", None)
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inner.pop("steps_executed", None)
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for frame in inner.get("frames", {}).values():
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frame.pop("step_number", None)
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for entry in inner.get("trace", []):
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entry.pop("step_number", None)
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if inner.get("interrupt") is not None:
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inner["interrupt"].pop("step_number", None)
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payload["state"] = {"version": 1, "state": inner}
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path.write_text(json.dumps(payload, indent=2), encoding="utf-8")
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def _api(store: FileRunStore, runtime: UpgradeAssertingRuntime) -> WorkflowRunApi:
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return WorkflowRunApi(
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WorkflowOperationContext(
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artifact_store=None,
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draft_workspace_store=None,
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run_store=store,
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events=DummyEvents(),
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specs=EmptySpecProvider(),
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runtime=runtime,
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live_sources=None,
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)
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)
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def test_restore_interrupted_run_persists_v1_upgrade_before_returning(
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tmp_path: Path,
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) -> None:
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store = FileRunStore(tmp_path / "runs")
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run_id = _seed_interrupted_run(store)
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_downgrade_latest_checkpoint_to_v1(store, run_id)
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record, run = restore_interrupted_run(store, run_id)
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assert record.id == run_id
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assert run.limits.max_steps == 10_000
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assert run.steps_executed == 0
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assert run.steps_remaining == 10_000
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assert [item.sequence for item in store.list_checkpoints(run_id)] == [1, 2]
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upgraded = _read_raw_checkpoint(store, run_id, 2)
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assert upgraded["state"]["version"] == 2
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assert upgraded["reason"] == "interrupted"
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def test_restore_interrupted_run_leaves_v2_checkpoints_untouched(
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tmp_path: Path,
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) -> None:
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store = FileRunStore(tmp_path / "runs")
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run_id = _seed_interrupted_run(store)
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record, run = restore_interrupted_run(store, run_id)
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assert record.id == run_id
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assert run.steps_executed == 0
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assert [item.sequence for item in store.list_checkpoints(run_id)] == [1]
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async def test_resume_persists_v1_upgrade_before_runtime_dispatch(
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tmp_path: Path,
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) -> None:
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store = FileRunStore(tmp_path / "runs")
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run_id = _seed_interrupted_run(store)
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_downgrade_latest_checkpoint_to_v1(store, run_id)
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runtime = UpgradeAssertingRuntime(store, run_id)
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api = _api(store, runtime)
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result = await api.resume_run(run_id=run_id, resume_payload={"answer": "yes"})
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assert runtime.resume_calls == 1
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assert result["status"] == "completed"
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assert result["max_steps"] == 10_000
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assert result["steps_executed"] == 0
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assert result["steps_remaining"] == 10_000
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assert [item.sequence for item in store.list_checkpoints(run_id)] == [1, 2, 3]
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upgraded = _read_raw_checkpoint(store, run_id, 2)
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assert upgraded["state"]["version"] == 2
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assert upgraded["state"]["state"]["steps_executed"] == 0
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async def test_inspect_decodes_v1_without_mutation(tmp_path: Path) -> None:
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store = FileRunStore(tmp_path / "runs")
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run_id = _seed_interrupted_run(store)
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_downgrade_latest_checkpoint_to_v1(store, run_id)
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runtime = UpgradeAssertingRuntime(store, run_id)
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api = _api(store, runtime)
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summary = await api.inspect_run(run_id=run_id)
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assert summary["status"] == "interrupted"
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assert summary["max_steps"] == 10_000
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assert summary["steps_executed"] == 0
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assert summary["steps_remaining"] == 10_000
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assert runtime.resume_calls == 0
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assert [item.sequence for item in store.list_checkpoints(run_id)] == [1]
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untouched = _read_raw_checkpoint(store, run_id, 1)
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assert untouched["state"]["version"] == 1
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@@ -0,0 +1,222 @@
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"""Run step budget creation and inspection tests (Task 4).
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Pins the API surface for persisted step budgets: optional ``max_steps`` on
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run creation only, effective ``max_steps``/``steps_executed``/
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``steps_remaining`` on every run result, counter preservation across resume,
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and no replacement budget on resume.
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"""
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from __future__ import annotations
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import inspect
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from pathlib import Path
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from typing import Any
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import pytest
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from tests.wf_mcp.test_support import echo_tool
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from tests.wf_mcp.workflow_surface.conftest import echo_artifact
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from wf_api.runs import WorkflowRunApi
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from wf_artifacts import (
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FileRunStore,
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FileWorkflowArtifactStore,
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WorkflowArtifact,
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WorkflowDeployment,
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)
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from wf_mcp.broker import WfMcpService
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from wf_mcp.broker.service.workflow_operation_context import context_from_service
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from wf_mcp.models import ConnectionConfig
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from wf_mcp.storage import FileStore
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def _echo_service(root: Path) -> WfMcpService:
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artifact_store = FileWorkflowArtifactStore(root)
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artifact_store.save_artifact(echo_artifact())
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artifact_store.save_deployment(
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WorkflowDeployment(
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id="echo.personal",
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artifact_id="echo",
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artifact_version=1,
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bindings=[{"logical_source": "demo", "concrete_source": "demo.personal"}],
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)
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)
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service = WfMcpService(
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store=FileStore(root / "mcp"),
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artifact_store=artifact_store,
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run_store=FileRunStore(root / "mcp"),
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)
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service.register_connection(
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ConnectionConfig(id="demo.personal", server="demo", account="personal")
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)
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service.register_specs("demo.personal", echo_tool)
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return service
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def _interrupt_artifact() -> WorkflowArtifact:
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return WorkflowArtifact(
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id="approval",
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version=1,
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title="Approval",
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input_schema={
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"type": "object",
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"properties": {"message": {"type": "string"}},
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"required": ["message"],
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},
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output_schema={"type": "object", "properties": {}},
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outcomes=("submitted",),
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plan={
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"name": "approval",
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"input_schema": {
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"type": "object",
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"properties": {"message": {"type": "string"}},
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"required": ["message"],
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},
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"state_schema": {"fields": {}},
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"output_schema": {"type": "object", "properties": {}},
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"outcomes": ["submitted"],
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"start": "approval",
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"nodes": [
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{
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"id": "approval",
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"type": "interrupt",
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"kind": "approval",
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"request": [
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{
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"path": {"root": "input", "parts": ["message"]},
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"target": {"root": "local", "parts": ["message"]},
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}
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],
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"resume": [],
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"outcomes": ["submitted"],
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"resume_schema": {
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"type": "object",
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"properties": {"approved": {"type": "boolean"}},
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"required": ["approved"],
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"additionalProperties": False,
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},
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},
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{"id": "end_submitted", "type": "end", "outcome": "submitted"},
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],
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"edges": [
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{"from": "approval", "outcome": "submitted", "to": "end_submitted"}
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],
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},
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)
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def _interrupt_service(root: Path) -> WfMcpService:
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artifact_store = FileWorkflowArtifactStore(root)
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artifact_store.save_artifact(_interrupt_artifact())
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artifact_store.save_deployment(
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WorkflowDeployment(
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id="approval.default",
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artifact_id="approval",
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artifact_version=1,
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bindings=[],
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)
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)
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return WfMcpService(
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store=FileStore(root / "mcp"),
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artifact_store=artifact_store,
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run_store=FileRunStore(root / "mcp"),
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)
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async def test_run_deployment_reports_default_budget(tmp_path: Path) -> None:
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api = WorkflowRunApi(context_from_service(_echo_service(tmp_path / "default")))
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result = await api.run_deployment(
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deployment_id="echo.personal",
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workflow_input={"text": "hello"},
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)
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assert result["status"] == "completed"
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assert result["max_steps"] == 10_000
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assert result["steps_executed"] == 1
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assert result["steps_remaining"] == 10_000 - result["steps_executed"]
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async def test_run_deployment_accepts_requested_max_steps(tmp_path: Path) -> None:
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api = WorkflowRunApi(context_from_service(_echo_service(tmp_path / "requested")))
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result = await api.run_deployment(
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deployment_id="echo.personal",
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workflow_input={"text": "hello"},
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max_steps=5,
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)
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assert result["status"] == "completed"
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assert result["max_steps"] == 5
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assert result["steps_executed"] == 1
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assert result["steps_remaining"] == 4
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async def test_run_deployment_rejects_non_positive_max_steps(tmp_path: Path) -> None:
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api = WorkflowRunApi(context_from_service(_echo_service(tmp_path / "invalid")))
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with pytest.raises(ValueError, match="positive"):
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await api.run_deployment(
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deployment_id="echo.personal",
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workflow_input={"text": "hello"},
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max_steps=0,
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)
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async def test_inspect_run_reports_effective_budget(tmp_path: Path) -> None:
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api = WorkflowRunApi(context_from_service(_echo_service(tmp_path / "inspect")))
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started = await api.run_deployment(
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deployment_id="echo.personal",
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workflow_input={"text": "hello"},
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max_steps=7,
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)
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run_id = started["run_id"]
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assert isinstance(run_id, str)
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summary = await api.inspect_run(run_id=run_id)
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assert summary["max_steps"] == 7
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assert summary["steps_executed"] == started["steps_executed"]
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assert summary["steps_remaining"] == 7 - started["steps_executed"]
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async def test_interrupted_resume_preserves_budget_counter(tmp_path: Path) -> None:
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api = WorkflowRunApi(context_from_service(_interrupt_service(tmp_path / "resume")))
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started = await api.run_deployment(
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deployment_id="approval.default",
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workflow_input={"message": "approve?"},
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max_steps=9,
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)
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run_id = started["run_id"]
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assert isinstance(run_id, str)
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assert started["status"] == "interrupted"
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assert started["max_steps"] == 9
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||||
assert started["steps_executed"] == 1
|
||||
assert started["steps_remaining"] == 8
|
||||
|
||||
resumed = await api.resume_run(
|
||||
run_id=run_id,
|
||||
resume_payload={"approved": True},
|
||||
resume_outcome="submitted",
|
||||
)
|
||||
|
||||
assert resumed["status"] == "completed"
|
||||
assert resumed["max_steps"] == 9
|
||||
assert resumed["steps_executed"] == started["steps_executed"] + 1
|
||||
assert resumed["steps_remaining"] == 9 - resumed["steps_executed"]
|
||||
|
||||
|
||||
async def test_resume_run_accepts_no_replacement_limit(tmp_path: Path) -> None:
|
||||
api = WorkflowRunApi(context_from_service(_echo_service(tmp_path / "resume_sig")))
|
||||
parameters = inspect.signature(WorkflowRunApi.resume_run).parameters
|
||||
|
||||
assert "max_steps" not in parameters
|
||||
assert "limits" not in parameters
|
||||
|
||||
extra: dict[str, Any] = {"max_steps": 5}
|
||||
with pytest.raises(TypeError):
|
||||
await api.resume_run(
|
||||
run_id="missing",
|
||||
resume_payload={},
|
||||
**extra,
|
||||
)
|
||||
Reference in New Issue
Block a user