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[F097] orchestrator: back off grok re-park retry_after within a rate-limit episode
_probe_target returns (None, {}) for grok — the grok CLI's xAI endpoint is
closed and the SuperGrok OIDC access token is not a valid bearer for the metered
api.x.ai, so a real probe would either no-op or strand grok parked forever.
_do_probe treats url-is-None as success (time-expiry optimism), so once the
60s retry_after passes the probe loop optimistically clears the grok park, a
cleared park dispatches a fresh grok agent that hits the still-active xAI 429,
exits 75, and re-parks — a flat ~90s crash-retry cycle for the whole xAI
rate-limit window (each cycle costs container startup + a rejected grok call).
Fix: track _grok_repark_count + _grok_last_park_at in _park_grok_rate_limited
and back the re-park retry_after off exponentially within one episode
(60 -> 120 -> 240 -> ... capped at 2**4 = ~16min cycle) so the churn dampens. A
gap past _GROK_REPARK_EPISODE_GAP_S (25min, > the capped cycle) means no re-park
for that long => the rate limit actually lifted => a fresh episode resets the
count to the base 60s, so recovery latency isn't penalized across episodes.
The first park in a fresh episode is unchanged at 60s.
This commit is contained in:
@@ -10,6 +10,7 @@ Claude session/overload paths get the same loop-break for free.
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from __future__ import annotations
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from datetime import UTC, datetime, timedelta
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from unittest.mock import AsyncMock
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import pytest
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@@ -17,6 +18,8 @@ from roboco.models.runtime import AgentInstance
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from roboco.runtime.orchestrator import (
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_GROK_AUTH_EXIT_CODE,
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_GROK_RATE_LIMIT_EXIT_CODE,
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_GROK_RATE_LIMIT_RETRY_AFTER_S,
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_GROK_REPARK_BACKOFF_CAP,
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AgentOrchestrator,
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AgentState,
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)
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@@ -113,6 +116,9 @@ async def test_park_grok_rate_limited_activates_and_offlines(
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# needs the dict + persist stub to exercise that without AttributeError.
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orch._waiting_records = {}
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orch._rate_limit_ceo_notified = set()
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# F097 backoff state — the constructor (skipped here) initializes these.
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orch._grok_last_park_at = None
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orch._grok_repark_count = 0
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inst = _grok_instance()
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inst.error_count = 2 # pretend prior crashes — parking must NOT count one
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tracker = _FakeTracker()
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@@ -215,3 +221,103 @@ async def test_park_grok_auth_unavailable_activates_with_auth_missing_kind(
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"affected_agents": ["be-dev-1"],
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"kind": "auth_missing",
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}
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# --------------------------------------------------------------------------- #
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# F097 — grok has no real probe, so an optimistic clear respawns into a still-
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# active xAI 429 every ~90s. Back off the re-park retry_after within one rate-
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# limit episode so the churn dampens instead of spinning flat at 60s.
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# --------------------------------------------------------------------------- #
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class _RecordingTracker:
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"""Records every activate() retry_after across multiple re-parks."""
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def __init__(self) -> None:
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self.retry_afters: list[float] = []
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self.kinds: list[str] = []
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self.agents_lists: list[list[str]] = []
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async def activate(
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self, *, retry_after: float, affected_agents: list[str], kind: str
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) -> None:
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self.retry_afters.append(retry_after)
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self.kinds.append(kind)
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self.agents_lists.append(affected_agents)
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def _backoff_orchestrator() -> AgentOrchestrator:
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orch = AgentOrchestrator.__new__(AgentOrchestrator)
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orch._waiting_records = {}
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orch._rate_limit_ceo_notified = set()
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# Backoff state — the constructor (skipped here) initializes these.
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orch._grok_last_park_at = None
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orch._grok_repark_count = 0
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return orch
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@pytest.mark.asyncio
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async def test_grok_repark_backs_off_within_episode(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""Three re-parks within one episode (microseconds apart) must grow the
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retry_after — 60 -> 120 -> 240 — not stay flat at 60s (the ~90s crash-retry
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cycle the optimistic clear produces today)."""
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orch = _backoff_orchestrator()
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tracker = _RecordingTracker()
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monkeypatch.setattr(orch, "_make_tracker", lambda _p: tracker)
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monkeypatch.setattr(orch, "_finalize_spawn_session", AsyncMock())
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monkeypatch.setattr(orch, "_persist_waiting_record", AsyncMock())
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inst = _grok_instance()
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await orch._park_grok_rate_limited("be-dev-1", inst)
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await orch._park_grok_rate_limited("be-dev-1", inst)
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await orch._park_grok_rate_limited("be-dev-1", inst)
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assert tracker.retry_afters == [60.0, 120.0, 240.0]
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assert tracker.kinds == ["rate_limited", "rate_limited", "rate_limited"]
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@pytest.mark.asyncio
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async def test_grok_repark_resets_after_episode_gap(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""A re-park AFTER the episode gap is a fresh episode — the retry_after
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resets to the base 60s even if the prior episode had backed off."""
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orch = _backoff_orchestrator()
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orch._grok_repark_count = 3 # pretend a prior episode backed off hard
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orch._grok_last_park_at = datetime.now(UTC) - timedelta(hours=2)
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tracker = _RecordingTracker()
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monkeypatch.setattr(orch, "_make_tracker", lambda _p: tracker)
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monkeypatch.setattr(orch, "_finalize_spawn_session", AsyncMock())
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monkeypatch.setattr(orch, "_persist_waiting_record", AsyncMock())
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inst = _grok_instance()
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await orch._park_grok_rate_limited("be-dev-1", inst)
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# Fresh episode -> base retry_after, no carried-over backoff.
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assert tracker.retry_afters == [60.0]
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assert orch._grok_repark_count == 0
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@pytest.mark.asyncio
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async def test_grok_repark_backoff_caps(monkeypatch: pytest.MonkeyPatch) -> None:
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"""The backoff is capped so a long xAI rate-limit window doesn't push the
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retry_after toward infinity (bounded cycle, recovery still reachable)."""
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orch = _backoff_orchestrator()
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tracker = _RecordingTracker()
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monkeypatch.setattr(orch, "_make_tracker", lambda _p: tracker)
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monkeypatch.setattr(orch, "_finalize_spawn_session", AsyncMock())
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monkeypatch.setattr(orch, "_persist_waiting_record", AsyncMock())
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inst = _grok_instance()
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# Park once, then re-park well past the cap.
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for _ in range(_GROK_REPARK_BACKOFF_CAP + 3):
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await orch._park_grok_rate_limited("be-dev-1", inst)
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max_expected = _GROK_RATE_LIMIT_RETRY_AFTER_S * (2**_GROK_REPARK_BACKOFF_CAP)
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# Every retry_after from the cap onward is the same capped value.
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assert all(
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r == max_expected for r in tracker.retry_afters[_GROK_REPARK_BACKOFF_CAP:]
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)
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assert max(tracker.retry_afters) == max_expected
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