f3e3545d06
Encapsulates every custom OCR metric in an OcrMetrics frozen dataclass and exposes a `build_metrics(registry)` factory. Production main.py binds against the default REGISTRY; tests construct a fresh CollectorRegistry per case and monkeypatch main.metrics, so counter values stay isolated between tests (decision #3 on issue #652, Option A). Refs #652 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
93 lines
3.2 KiB
Python
93 lines
3.2 KiB
Python
"""Prometheus metric definitions for the OCR service.
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`build_metrics(registry)` returns a fresh `OcrMetrics` instance bound to the
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given `CollectorRegistry`. Production code calls it once at module load with
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the default `REGISTRY`; tests pass a per-test `CollectorRegistry()` to keep
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counter values isolated between cases (decision #3 on issue #652).
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from prometheus_client import CollectorRegistry, Counter, Gauge, Histogram
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@dataclass(frozen=True)
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class OcrMetrics:
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"""Container for every custom OCR metric.
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Counters and gauges are immutable references to `prometheus_client`
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instances. Mutating them (`.inc()`, `.observe()`, `.set()`) is safe;
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rebinding the field on the dataclass is not — use `build_metrics` to get
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a new container.
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"""
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ocr_jobs_total: Counter
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ocr_pages_total: Counter
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ocr_skipped_pages_total: Counter
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ocr_words_total: Counter
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ocr_illegible_words_total: Counter
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ocr_processing_seconds: Histogram
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ocr_training_runs_total: Counter
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ocr_model_accuracy: Gauge
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ocr_models_ready: Gauge
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def build_metrics(registry: CollectorRegistry) -> OcrMetrics:
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"""Create one OcrMetrics instance bound to `registry`."""
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return OcrMetrics(
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ocr_jobs_total=Counter(
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"ocr_jobs_total",
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"Number of OCR jobs processed, labelled by engine and script type.",
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["engine", "script_type"],
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registry=registry,
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),
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ocr_pages_total=Counter(
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"ocr_pages_total",
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"Number of pages successfully OCR'd, labelled by engine.",
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["engine"],
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registry=registry,
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),
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ocr_skipped_pages_total=Counter(
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"ocr_skipped_pages_total",
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"Number of pages skipped because the OCR engine raised.",
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registry=registry,
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),
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ocr_words_total=Counter(
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"ocr_words_total",
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"Number of words recognized across all OCR blocks.",
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registry=registry,
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),
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ocr_illegible_words_total=Counter(
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"ocr_illegible_words_total",
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"Number of words below the confidence threshold "
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"(replaced with [unleserlich]).",
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registry=registry,
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),
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ocr_processing_seconds=Histogram(
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"ocr_processing_seconds",
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"OCR processing time per page (streaming) or per document (non-streaming).",
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["engine"],
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registry=registry,
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),
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ocr_training_runs_total=Counter(
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"ocr_training_runs_total",
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"Number of training runs, labelled by kind (recognition|segmentation) "
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"and outcome (success|error).",
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["kind", "outcome"],
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registry=registry,
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),
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ocr_model_accuracy=Gauge(
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"ocr_model_accuracy",
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"Latest model accuracy reported by a successful training run.",
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["kind"],
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registry=registry,
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),
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ocr_models_ready=Gauge(
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"ocr_models_ready",
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"1 once the lifespan startup has finished loading models, 0 before.",
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registry=registry,
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),
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)
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