518b8eca85
md-first memory extraction framework for AI agents. Markdown is the single source of truth; SQLite holds state and LanceDB provides the rebuildable vector + BM25 + scalar index. The codebase follows a single-direction DDD layering (entrypoints -> service -> memory -> infra, with component / core / config cross-cutting) enforced by import-linter. Engineering surface: - Coding conventions in .claude/rules/ (path-scoped) and workflows in .claude/skills/ (/commit, /new-branch, /pr). - GitHub Actions CI runs make lint + test + integration; pre-commit mirrors the gates locally (ruff, hygiene hooks, gitlint commit-msg). - Commit messages follow Conventional Commits, enforced by gitlint. - make lint also enforces datetime two-zone discipline and OpenAPI drift.
103 lines
2.3 KiB
Python
103 lines
2.3 KiB
Python
"""Histogram wrapper around ``prometheus_client.Histogram``."""
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from __future__ import annotations
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from collections.abc import Sequence
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from typing import Any
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from prometheus_client import Histogram as PromHistogram
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from .registry import get_metrics_registry
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class HistogramBuckets:
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"""Predefined bucket configurations for common workloads."""
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DEFAULT: tuple[float, ...] = (
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0.005,
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0.01,
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0.025,
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0.05,
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0.1,
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0.25,
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0.5,
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1.0,
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2.5,
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5.0,
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10.0,
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)
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FAST: tuple[float, ...] = (0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5)
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API_CALL: tuple[float, ...] = (
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0.01,
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0.05,
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0.1,
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0.25,
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0.5,
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1.0,
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2.0,
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5.0,
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10.0,
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30.0,
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)
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BATCH: tuple[float, ...] = (0.1, 0.5, 1.0, 5.0, 10.0, 30.0, 60.0)
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DATABASE: tuple[float, ...] = (
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0.001,
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0.005,
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0.01,
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0.025,
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0.05,
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0.1,
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0.25,
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0.5,
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1.0,
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2.5,
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5.0,
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)
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class Histogram:
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"""Distribution of observed values (latency, sizes)."""
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def __init__(
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self,
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name: str,
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description: str,
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labelnames: Sequence[str] = (),
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namespace: str = "",
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subsystem: str = "",
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unit: str = "",
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buckets: Sequence[float] = HistogramBuckets.DEFAULT,
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) -> None:
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self._histogram = PromHistogram(
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name=name,
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documentation=description,
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labelnames=labelnames,
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namespace=namespace,
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subsystem=subsystem,
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unit=unit,
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buckets=tuple(buckets),
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registry=get_metrics_registry(),
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)
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def labels(self, **labels: str) -> LabeledHistogram:
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return LabeledHistogram(self._histogram.labels(**labels))
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def observe(self, amount: float) -> None:
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self._histogram.observe(amount)
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def time(self) -> Any:
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return self._histogram.time()
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class LabeledHistogram:
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"""Histogram slice with labels applied."""
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def __init__(self, labeled: Any) -> None:
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self._labeled = labeled
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def observe(self, amount: float) -> None:
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self._labeled.observe(amount)
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def time(self) -> Any:
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return self._labeled.time()
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