Insert a configurable in-cluster OCR rung into the escalation ladder (Deck #353): a tier2-eligible doc is OCR'd on the on-demand burst GPU before falling through to paid upstream OCR. The in-cluster backend is reached ONLY via the embedding gateway (model prefix routes to the GPU over the tailnet) and is a config value (default surya/surya-ocr-2, swappable to e.g. lightonocr) — never hard-coded. Ladder: fast -> structured -> ocr-incluster -> ocr-upstream (queues ingest-ocr-incluster / ingest-ocr-upstream). - escalation.py: 4-tier ladder; in-cluster flag folded into the dead-letter signature. - ocr.py: OcrProcessor(name, tier, model_setting, gateway_only); build_ocr_backend( ..., model=, gateway_only=) — gateway_only forces the gateway backend (never the direct Mistral fallback), disabling the tier with a warning if no gateway URL. - registry.py: per-rung enable map; scanned docs target minimum="ocr-incluster"; inline path runs the cheapest available OCR rung. - procrastinate.py: two OCR queues; legacy ingest-ocr kept as a drain target. - config.py: DOCUMENT_OCR_INCLUSTER_ENABLED (off) + DOCUMENT_OCR_INCLUSTER_MODEL. - __init__.py: register the two OCR instances; vector/processor.py: pages_ocr metered for the upstream (paid) rung only; cli.py: new --tier choices + legacy drain. - metrics.py: zero the legacy ingest-ocr queue gauge during rollout. - tests: migrated to the split ladder + new tests (gateway-only forcing, per-tier model incl. lightonocr override, no-hard-coded-surya guard). 1792 pass; ruff + ty green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
157 lines
6.4 KiB
Python
157 lines
6.4 KiB
Python
"""Unit tests for the per-tier escalation primitives (Deck #323).
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Covers the tier-ladder helpers + EscalateError (document_processors.escalation)
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and the procrastinate TieredEscalationStrategy that turns a raised exception
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into a queue-hop / same-tier retry / give-up decision.
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"""
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from datetime import datetime, timezone
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import httpx
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import pytest
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from procrastinate.jobs import Job
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import nextcloud_mcp_server.vector.queue.procrastinate as pq
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from nextcloud_mcp_server.document_processors.escalation import (
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TIER_LADDER,
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BatchPending,
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EscalateError,
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next_tier,
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)
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pytestmark = pytest.mark.unit
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def _job(queue: str = pq.INGEST_QUEUE_FAST, attempts: int = 1) -> Job:
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return Job(
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id=1,
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queue=queue,
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task_name=pq.INGEST_TASK_NAME,
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lock=None,
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queueing_lock=None,
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attempts=attempts,
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)
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class TestLadder:
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def test_next_tier_ordering(self):
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assert next_tier("fast") == "structured"
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assert next_tier("structured") == "ocr-incluster"
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assert next_tier("ocr-incluster") == "ocr-upstream"
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assert next_tier("ocr-upstream") is None # terminal
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assert next_tier("unknown") is None
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def test_ladder_is_cheapest_first(self):
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assert TIER_LADDER == ("fast", "structured", "ocr-incluster", "ocr-upstream")
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def test_tier_for_queue(self):
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assert pq.tier_for_queue(pq.INGEST_QUEUE_OCR_UPSTREAM) == "ocr-upstream"
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assert pq.tier_for_queue(pq.INGEST_QUEUE_STRUCTURED) == "structured"
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# Legacy / unknown / None all fall back to the cheapest tier.
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assert pq.tier_for_queue(pq.LEGACY_INGEST_QUEUE) == "fast"
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assert pq.tier_for_queue(None) == "fast"
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class TestTieredEscalationStrategy:
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def _strategy(self, max_transient: int = 5):
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return pq.TieredEscalationStrategy(max_transient_attempts=max_transient)
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def test_escalate_hops_to_target_queue(self):
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exc = EscalateError(
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from_tier="fast", to_tier="ocr-upstream", reason="empty_text"
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)
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decision = self._strategy().get_retry_decision(exception=exc, job=_job())
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assert decision is not None
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assert decision.queue == pq.INGEST_QUEUE_OCR_UPSTREAM
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def test_escalate_to_structured(self):
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exc = EscalateError(
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from_tier="fast", to_tier="structured", reason="low_confidence"
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)
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decision = self._strategy().get_retry_decision(exception=exc, job=_job())
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assert decision is not None
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assert decision.queue == pq.INGEST_QUEUE_STRUCTURED
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def test_escalate_unknown_tier_gives_up(self):
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exc = EscalateError(from_tier="ocr", to_tier="bogus", reason="low_confidence")
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decision = self._strategy().get_retry_decision(exception=exc, job=_job())
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assert decision is None
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def test_escalate_unwraps_exception_group(self):
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exc = EscalateError(
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from_tier="fast", to_tier="ocr-upstream", reason="empty_text"
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)
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group = ExceptionGroup("wrapped", [exc])
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decision = self._strategy().get_retry_decision(exception=group, job=_job())
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assert decision is not None
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assert decision.queue == pq.INGEST_QUEUE_OCR_UPSTREAM
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def test_transient_retries_same_queue_under_cap(self):
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decision = self._strategy(max_transient=5).get_retry_decision(
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exception=httpx.ConnectError("refused"), job=_job(attempts=1)
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)
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assert decision is not None
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# Same-tier retry: no queue override (stays on its current queue).
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assert decision.queue is None
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assert decision.retry_at is not None
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def test_transient_backoff_progression(self):
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# min(4 * 2**(attempts-1), 300): 4, 8, 16, ... capped at 300s.
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# procrastinate sets retry_at = utcnow() + wait at call time. Bracketing
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# the call with before/after makes the assertion exact and independent of
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# runner load: with before <= call_now <= after, we have
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# (retry_at - after) <= wait <= (retry_at - before).
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strat = self._strategy(max_transient=100)
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for attempts, expected in [(1, 4), (2, 8), (3, 16), (4, 32), (20, 300)]:
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before = datetime.now(timezone.utc)
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decision = strat.get_retry_decision(
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exception=httpx.ConnectError("x"), job=_job(attempts=attempts)
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)
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after = datetime.now(timezone.utc)
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assert decision is not None and decision.retry_at is not None
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lo = (decision.retry_at - after).total_seconds()
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hi = (decision.retry_at - before).total_seconds()
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assert lo <= expected <= hi, (
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f"attempts={attempts}: expected={expected}s not in [{lo:.3f}, {hi:.3f}]"
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)
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def test_transient_gives_up_over_cap(self):
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decision = self._strategy(max_transient=5).get_retry_decision(
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exception=httpx.ConnectError("refused"), job=_job(attempts=5)
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)
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assert decision is None
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def test_non_transient_error_gives_up(self):
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decision = self._strategy().get_retry_decision(
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exception=ValueError("permanent"), job=_job(attempts=1)
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)
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assert decision is None
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def test_batch_pending_defers_same_queue(self):
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# Batch OCR re-poll (Deck #332): same-queue deferral after retry_in.
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before = datetime.now(timezone.utc)
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decision = self._strategy().get_retry_decision(
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exception=BatchPending(retry_in=120),
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job=_job(queue=pq.INGEST_QUEUE_OCR_UPSTREAM),
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)
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after = datetime.now(timezone.utc)
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assert decision is not None
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assert decision.queue is None # stays on its own tier queue
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assert decision.retry_at is not None
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lo = (decision.retry_at - after).total_seconds()
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hi = (decision.retry_at - before).total_seconds()
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assert lo <= 120 <= hi
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def test_batch_pending_exempt_from_transient_cap(self):
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# A batch can take hours -> many polls; the transient cap must NOT stop it
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# (the OCR processor's own deadline terminates a stuck job instead).
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decision = self._strategy(max_transient=5).get_retry_decision(
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exception=BatchPending(retry_in=60), job=_job(attempts=999)
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)
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assert decision is not None and decision.retry_at is not None
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def test_batch_pending_unwraps_exception_group(self):
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group = ExceptionGroup("wrapped", [BatchPending(retry_in=60)])
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decision = self._strategy().get_retry_decision(exception=group, job=_job())
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assert decision is not None and decision.retry_at is not None
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