Files
mcp-nextcloud/tests/unit/test_document_parse_metrics.py
T
Chris CoutinhoandClaude Opus 4.8 5d205fcaab feat(observability): astrolabe_* metrics + traces for the document pipeline
Make per-tier bottlenecks in the document-processing pipeline
(scan -> fetch -> parse -> chunk -> embed -> Qdrant upsert) visible via
metrics, traces, and structured logs. Today the document_processors layer
emits only a logger.info line: no metric, no span, and page counts live only
inside a log string. The single processing-duration histogram is unlabeled and
whole-document, so it cannot isolate parse vs embed vs upsert.

New astrolabe_* metric family (distinct from the mcp_* protocol metrics):
- astrolabe_document_parse_{duration_seconds,total} + pages/chars/bytes counters
  recorded at the ProcessorRegistry.process() boundary (covers all current and
  future processors uniformly)
- astrolabe_document_escalation_total (dormant; tiered-pipeline readiness)
- astrolabe_embedding_{duration_seconds,requests_total,chunks_total,chars_total}
- astrolabe_document_chunks_total, astrolabe_documents_indexed_total{source,status}

Tracing: new document_processor.parse child span + enriched embed/chunk span
attributes (provider/model/batch_size/chunk_count). Structured logs gain a
consistent field vocabulary (doc_id, doc_type, processor, tier, pages, chars,
byte_size, chunks, duration_ms, status) so Loki can aggregate without regex.

Tier-readiness: processor/tier are labels from day one and a tier property is
added to DocumentProcessor, so adding docling/OCR/LLM tiers later is additive
(new label values, never new metrics). Tenant comes from the kube namespace
label; mime_type/model are span attributes only (cardinality). Existing
mcp_vector_sync_*/mcp_qdrant_* are left untouched.

Refs Deck #175 (superset of #173 Phase 2). Dashboard/recording-rules follow-up
tracked on #175 for homelab-argocd.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-02 17:46:20 +02:00

240 lines
8.7 KiB
Python

"""Unit tests for document-parse instrumentation.
Covers two layers:
1. The ``ProcessorRegistry.process()`` boundary — that it records a parse metric
(success and error) and opens a ``document_processor.parse`` span with the
expected attributes, while preserving the existing re-raise on failure.
2. The ``record_document_parse`` / ``record_document_chunks`` /
``record_vector_sync_processing`` helpers — that they increment the right
``astrolabe_*`` Prometheus series (and that an error parse does NOT bump the
throughput counters).
"""
from __future__ import annotations
from typing import Any
from unittest.mock import MagicMock, patch
import pytest
from prometheus_client import REGISTRY
from nextcloud_mcp_server.document_processors.base import (
DocumentProcessor,
ProcessingResult,
ProcessorError,
)
from nextcloud_mcp_server.document_processors.registry import ProcessorRegistry
from nextcloud_mcp_server.observability.metrics import (
record_document_chunks,
record_document_escalation,
record_document_parse,
record_vector_sync_processing,
)
pytestmark = pytest.mark.unit
def _sample(name: str, labels: dict[str, str]) -> float:
"""Return a Prometheus sample value, treating 'never observed' as 0."""
return REGISTRY.get_sample_value(name, labels) or 0.0
class _FakeProcessor(DocumentProcessor):
"""Minimal processor for exercising the registry instrumentation."""
def __init__(
self,
*,
result: ProcessingResult | None = None,
exc: Exception | None = None,
proc_name: str = "pymupdf",
proc_tier: str = "fast",
):
self._result = result
self._exc = exc
self._name = proc_name
self._tier = proc_tier
@property
def name(self) -> str:
return self._name
@property
def tier(self) -> str:
return self._tier
@property
def supported_mime_types(self) -> set[str]:
return {"application/pdf"}
async def process(
self,
content: bytes,
content_type: str,
filename: str | None = None,
options: dict[str, Any] | None = None,
progress_callback=None,
) -> ProcessingResult:
if self._exc is not None:
raise self._exc
assert self._result is not None
return self._result
async def health_check(self) -> bool:
return True
@pytest.fixture
def mock_tracer():
"""Patch trace_operation in the registry; expose the yielded span."""
with patch(
"nextcloud_mcp_server.document_processors.registry.trace_operation"
) as mock_trace:
span = MagicMock()
mock_trace.return_value.__enter__ = MagicMock(return_value=span)
mock_trace.return_value.__exit__ = MagicMock(return_value=False)
mock_trace.span = span
yield mock_trace
class TestRegistryParseInstrumentation:
async def test_success_records_metric_and_span(self, mock_tracer):
result = ProcessingResult(
text="x" * 1000,
metadata={"page_count": 50, "file_size": 99},
processor="pymupdf",
)
registry = ProcessorRegistry()
registry.register(_FakeProcessor(result=result))
with patch(
"nextcloud_mcp_server.document_processors.registry.record_document_parse"
) as mock_record:
out = await registry.process(
b"%PDF-1.7", "application/pdf", filename="x.pdf"
)
assert out is result
# Metric recorded with parsed pages/chars and success status.
mock_record.assert_called_once()
args = mock_record.call_args.args
kwargs = mock_record.call_args.kwargs
assert args[0] == "pymupdf" # processor
assert args[1] == "fast" # tier
assert kwargs["pages"] == 50
assert kwargs["chars"] == 1000
assert kwargs["status"] == "success"
# Span opened with the parse name + identifying attributes.
assert mock_tracer.call_args.args[0] == "document_processor.parse"
attrs = mock_tracer.call_args.kwargs["attributes"]
assert attrs["processor.name"] == "pymupdf"
assert attrs["processor.tier"] == "fast"
assert attrs["mime_type"] == "application/pdf"
assert attrs["escalated"] is False
# Post-parse attributes set on the span.
mock_tracer.span.set_attribute.assert_any_call("page_count", 50)
mock_tracer.span.set_attribute.assert_any_call("char_count", 1000)
async def test_error_records_error_metric_and_reraises(self, mock_tracer):
registry = ProcessorRegistry()
registry.register(_FakeProcessor(exc=ProcessorError("boom")))
with patch(
"nextcloud_mcp_server.document_processors.registry.record_document_parse"
) as mock_record:
with pytest.raises(ProcessorError):
await registry.process(b"data", "application/pdf")
mock_record.assert_called_once()
assert mock_record.call_args.kwargs["status"] == "error"
class TestParseMetricHelpers:
def test_success_increments_throughput_counters(self):
labels = {"processor": "uttest-success", "tier": "fast"}
before_pages = _sample("astrolabe_document_pages_processed_total", labels)
before_chars = _sample("astrolabe_document_chars_processed_total", labels)
before_bytes = _sample("astrolabe_document_bytes_processed_total", labels)
before_total = _sample(
"astrolabe_document_parse_total", {**labels, "status": "success"}
)
record_document_parse(
"uttest-success",
"fast",
1.23,
pages=50,
chars=1000,
byte_size=99,
status="success",
)
assert _sample("astrolabe_document_pages_processed_total", labels) == (
before_pages + 50
)
assert _sample("astrolabe_document_chars_processed_total", labels) == (
before_chars + 1000
)
assert _sample("astrolabe_document_bytes_processed_total", labels) == (
before_bytes + 99
)
assert _sample(
"astrolabe_document_parse_total", {**labels, "status": "success"}
) == (before_total + 1)
# The duration histogram observed one sample.
assert (
_sample(
"astrolabe_document_parse_duration_seconds_count",
{**labels, "status": "success"},
)
>= 1
)
def test_error_does_not_increment_throughput(self):
labels = {"processor": "uttest-error", "tier": "fast"}
record_document_parse(
"uttest-error",
"fast",
0.5,
pages=10,
chars=10,
byte_size=10,
status="error",
)
# Error parses count the attempt + duration, but NOT pages/chars/bytes.
assert _sample("astrolabe_document_pages_processed_total", labels) == 0.0
assert _sample("astrolabe_document_chars_processed_total", labels) == 0.0
assert (
_sample("astrolabe_document_parse_total", {**labels, "status": "error"})
== 1.0
)
def test_record_document_chunks(self):
labels = {"doc_type": "uttest-chunks"}
before = _sample("astrolabe_document_chunks_total", labels)
record_document_chunks("uttest-chunks", 7)
assert _sample("astrolabe_document_chunks_total", labels) == before + 7
def test_vector_sync_processing_increments_documents_indexed(self):
labels = {"source": "uttest-doctype", "status": "success"}
before = _sample("astrolabe_documents_indexed_total", labels)
record_vector_sync_processing(0.1, "success", doc_type="uttest-doctype")
assert _sample("astrolabe_documents_indexed_total", labels) == before + 1
def test_vector_sync_processing_without_doc_type_is_noop_for_indexed(self):
# Without doc_type, the per-type counter must not be touched (the legacy
# mcp_* counter still increments, but that is out of scope here).
labels = {"source": "uttest-absent", "status": "success"}
record_vector_sync_processing(0.1, "success")
assert _sample("astrolabe_documents_indexed_total", labels) == 0.0
def test_record_document_escalation(self):
# Dormant until the tiered pipeline lands; pin its correctness now so the
# first docling/OCR/LLM caller gets a working counter.
labels = {"from_tier": "fast", "to_tier": "ocr", "reason": "empty_text"}
before = _sample("astrolabe_document_escalation_total", labels)
record_document_escalation("fast", "ocr", "empty_text")
assert _sample("astrolabe_document_escalation_total", labels) == before + 1