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https://github.com/BerriAI/litellm.git
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3090f4b23e
* test(integration): wait for customer spend rows and use owned OpenRouter cost * ci: isolate integration workers and clean up resources after crashes * docs: describe isolated extensions workers and shard census * fix(ci): restore integration service and fixture guarantees * fix(integration): preserve replay IDs and native route fixtures * fix(tests): scope integration harness imports to each unit case * fix(ci): preserve fixtures and wait for owned workers * fix(ci): isolate nested runs and telemetry cases * fix(ci): make worker readiness and fault tests deterministic * chore(ci): drop MCP fixture repair already covered by main * chore(ci): keep the local catalog fix from main --------- Co-authored-by: yuneng <yuneng@berri.ai>
51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
from __future__ import annotations
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from collections.abc import Iterator
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from pathlib import Path
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from typing import Final
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import pytest
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from integration._support.client import eventually
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from integration._support.otlp_sink import (
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AuditConfigWriter,
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SpanSinks,
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audit_configuration_writer,
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langfuse_callback_variables,
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owned_sinks,
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)
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from integration._support.prometheus_series import CapRig, series_cap_rig, spend_rows
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from pydantic import JsonValue
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@pytest.fixture(scope="module")
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def audit_sinks(tmp_path_factory: pytest.TempPathFactory) -> Iterator[SpanSinks]:
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directory: Final = tmp_path_factory.mktemp("otel-audit-sinks")
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with owned_sinks(directory) as sinks:
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yield sinks
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@pytest.fixture(scope="module")
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def otel_audit_config(audit_sinks: SpanSinks) -> AuditConfigWriter:
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return audit_configuration_writer(audit_sinks)
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@pytest.fixture(scope="module")
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def langfuse_vars(audit_sinks: SpanSinks) -> dict[str, JsonValue]:
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return langfuse_callback_variables(audit_sinks)
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@pytest.fixture(scope="session")
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def capped(tmp_path_factory: pytest.TempPathFactory) -> Iterator[CapRig]:
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"""A two-worker proxy capped at three series per metric, with three keys already holding a series each."""
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with series_cap_rig(
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tmp_path_factory.mktemp("series-cap"),
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{"prometheus_metrics_max_series_per_metric": 3},
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workers=2,
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warm_keys=3,
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) as rig:
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eventually(
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lambda: tuple(len(spend_rows(key.alias)) for key in rig.warm),
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lambda counts: all(count == 1 for count in counts),
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seconds=70,
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)
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yield rig
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