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596c51a5fa
* feat(telemetry): add AggregatingSink, fixed-bucket histograms, Report and HttpExporter * fix(telemetry): add records to rows in place, guard concurrent flushes, cap restored rows and count bad histogram values Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(telemetry): give the shared row helper its lint reasons Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(telemetry): retry the same statuses as the proxy's should_retry (408, 409, 429, 5xx) Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(telemetry): cover populated block_types and header_keys in report JSON Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: nate <nate@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
import math
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from typing import Final
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import pytest
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from litellm.telemetry.histogram import Histogram
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_BOUNDS: Final = (10.0, 100.0)
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def _histogram_of(*values: float | None) -> Histogram:
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histogram: Final = Histogram.empty(_BOUNDS)
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for value in values:
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histogram.add(value)
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return histogram
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@pytest.mark.parametrize(
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("value", "expected_counts"),
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[
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(None, [0, 0, 0]),
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(0.0, [1, 0, 0]),
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(10.0, [1, 0, 0]),
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(10.5, [0, 1, 0]),
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(100.0, [0, 1, 0]),
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(100.5, [0, 0, 1]),
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],
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)
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def test_a_value_lands_in_the_first_bucket_whose_bound_it_does_not_exceed(
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value: float | None, expected_counts: list[int]
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) -> None:
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assert _histogram_of(value) == Histogram(bounds=_BOUNDS, counts=expected_counts, invalid=0)
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@pytest.mark.parametrize("value", [-1.0, math.nan, math.inf, -math.inf])
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def test_a_negative_or_non_finite_value_is_counted_as_invalid_instead_of_bucketed(value: float) -> None:
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assert _histogram_of(value, 5.0) == Histogram(bounds=_BOUNDS, counts=[1, 0, 0], invalid=1)
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def test_add_histogram_adds_bucket_and_invalid_counts() -> None:
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total: Final = _histogram_of(5.0, -1.0)
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total.add_histogram(_histogram_of(5.0, 500.0, math.nan))
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assert total == Histogram(bounds=_BOUNDS, counts=[2, 0, 1], invalid=2)
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