fix(ingest): address review round 2 (stale gauge + hygiene)

- metrics: update_ingest_queue_depth now pre-zeroes every managed ingest queue
  before applying live counts, so a queue that drains to empty (and drops out of
  procrastinate's list_queues_async) reads 0 instead of sticking at its last
  non-zero value (ghost backlog in Grafana/alerts). Adds a regression test.
- procrastinate: comment that _is_transient_infra_error treats all qdrant errors
  as transient deliberately (bounded same-tier retry; over-broad is acceptable).
- escalation: note next_tier is the building block; production routing uses
  ProcessorRegistry.next_available_tier.
- tests: add evaluate_escalation fast+ocr-only low-confidence -> ocr case.

Deck #323.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Chris Coutinho
2026-06-13 13:45:01 +02:00
co-authored by Claude Opus 4.8
parent 35f8204a16
commit e7c0c23486
5 changed files with 82 additions and 7 deletions
@@ -30,10 +30,11 @@ def next_tier(current: str) -> str | None:
"""The next tier above ``current`` in the ladder, or ``None`` if terminal.
Pure ordering only -- it does not consider whether the next tier is
*available* (a processor registered / OCR enabled). Callers that need
availability resolve it against the registry + settings (see
``ProcessorRegistry.next_available_tier``); a tier with no escalation target
is terminal and its result is indexed as-is.
*available* (a processor registered / OCR enabled). **Production routing uses
``ProcessorRegistry.next_available_tier``**, which layers availability on top
of this ordering; ``next_tier`` itself is the underlying building block
(referenced directly by tests). A tier with no escalation target is terminal
and its result is indexed as-is.
"""
try:
idx = TIER_LADDER.index(current)
+18 -3
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@@ -656,12 +656,27 @@ def update_ingest_queue_depth(by_queue: dict[str, dict[str, int]] | None) -> Non
"""Set the per-tier-queue depth gauge from procrastinate job counts (#323).
``by_queue`` is ``{queue_name: {status: count}}`` (see
``queue.procrastinate.get_ingest_job_counts_by_queue``). A queue missing a
status is set to 0 so a drained queue reads zero rather than going stale at
its last non-zero value. No-op on the memory backend (``by_queue`` is None).
``queue.procrastinate.get_ingest_job_counts_by_queue``). No-op on the memory
backend (``by_queue`` is None).
Every managed queue is zeroed first: ``list_queues_async`` stops returning a
queue once it has no jobs, so a queue that drained to empty drops out of
``by_queue`` entirely. Without the pre-zero its gauge series would stick at
its last non-zero value (ghost backlog in Grafana/alerts) instead of reading
0. The live counts then overwrite the zeros for queues that still have work.
"""
if not by_queue:
return
# Lazy import to keep observability decoupled from the queue layer at module
# load (and sidestep any import cycle); both names are public constants.
from nextcloud_mcp_server.vector.queue.procrastinate import ( # noqa: PLC0415
ALL_INGEST_QUEUES,
LEGACY_INGEST_QUEUE,
)
for queue in (*ALL_INGEST_QUEUES, LEGACY_INGEST_QUEUE):
for status in _INGEST_DEPTH_STATUSES:
ingest_queue_depth.labels(queue=queue, status=status).set(0)
for queue, per_status in by_queue.items():
for status in _INGEST_DEPTH_STATUSES:
ingest_queue_depth.labels(queue=queue, status=status).set(
@@ -279,6 +279,13 @@ def _is_transient_infra_error(exc: BaseException) -> bool:
return exc.status_code >= 500
except ImportError: # pragma: no cover -- openai is a hard dependency
pass
# Deliberately over-broad: this treats ALL qdrant_client exceptions as
# transient (not just timeouts/5xx). In a healthy cluster qdrant errors are
# transient, and a bounded same-tier retry is cheap; a genuinely permanent
# qdrant fault (e.g. schema mismatch) just exhausts the transient cap and
# then gives up. So unlike _drop_reason (which only *labels* the cause), this
# may add a few retries on a non-retriable qdrant error -- an acceptable
# trade for not having to enumerate qdrant's non-retriable status codes.
if type(exc).__module__.startswith("qdrant_client"):
return True
return False
@@ -0,0 +1,32 @@
"""Unit test for the per-tier ingest-queue-depth gauge (Deck #323).
Guards the round-2 fix: a queue that drains to empty (and so drops out of
procrastinate's ``list_queues_async``) must read 0, not its last non-zero value.
"""
import pytest
from nextcloud_mcp_server.observability.metrics import update_ingest_queue_depth
pytestmark = pytest.mark.unit
_METRIC = "astrolabe_ingest_queue_depth"
def test_drained_queue_zeroes_not_stale(metric_sample):
# ocr has a backlog this tick.
update_ingest_queue_depth({"ingest-ocr": {"todo": 4}})
assert metric_sample(_METRIC, {"queue": "ingest-ocr", "status": "todo"}) == 4.0
# Next tick ocr has drained → procrastinate omits it from by_queue entirely.
update_ingest_queue_depth({"ingest-fast": {"todo": 1}})
# The gauge must read 0 for the drained queue, not the stale 4.
assert metric_sample(_METRIC, {"queue": "ingest-ocr", "status": "todo"}) == 0.0
assert metric_sample(_METRIC, {"queue": "ingest-fast", "status": "todo"}) == 1.0
def test_none_is_noop(metric_sample):
update_ingest_queue_depth({"ingest-fast": {"doing": 2}})
# Memory backend passes None → must not wipe the last published values.
update_ingest_queue_depth(None)
assert metric_sample(_METRIC, {"queue": "ingest-fast", "status": "doing"}) == 2.0
+20
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@@ -400,3 +400,23 @@ def test_evaluate_escalation_zero_page_does_not_escalate(monkeypatch):
processor="fast",
)
assert r.evaluate_escalation(res, b"%PDF", "fast", _Settings(ocr=True)) is None
def test_evaluate_escalation_lowconf_to_ocr_when_no_structured(monkeypatch):
"""fast+ocr only: a low-confidence parse routes straight to ocr (skips the
unregistered structured rung), not to None."""
monkeypatch.setattr(reg_mod, "record_document_classification", MagicMock())
junk = "z" * 40 # non-empty but junk -> recommended ocr, total_chars > 0
r = _registry((_Fake("fast", "fast"), 20), (_Fake("ocr", "ocr"), 5))
res = ProcessingResult(
text=junk,
metadata={
"page_count": 1,
"page_boundaries": [
{"page": 1, "start_offset": 0, "end_offset": len(junk)}
],
},
processor="fast",
)
decision = r.evaluate_escalation(res, b"%PDF", "fast", _Settings(ocr=True))
assert decision == ("ocr", "low_confidence")