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260 lines
9.3 KiB
Python
260 lines
9.3 KiB
Python
"""Tests for provider-reported LLM cost capture."""
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from __future__ import annotations
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from types import SimpleNamespace
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from unittest.mock import MagicMock, patch
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import litellm
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import pytest
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from litellm.types.utils import LlmProviders
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from litellm.utils import ProviderConfigManager
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from strix.config.models import (
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_configure_litellm_compatibility,
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_install_openrouter_stream_cost_capture,
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)
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from strix.report.state import (
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ReportState,
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litellm_cost_callback,
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openrouter_stream_cost,
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set_global_report_state,
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streamed_openrouter_costs,
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)
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@pytest.fixture(autouse=True)
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def _clear_streamed_costs() -> None:
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streamed_openrouter_costs.clear()
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def test_streaming_logging_stays_enabled_for_cost_callback() -> None:
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with (
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patch.object(litellm, "disable_streaming_logging", new=True),
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patch("strix.config.models._register_litellm_cost_callback") as register,
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):
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_configure_litellm_compatibility()
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assert litellm.disable_streaming_logging is False
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register.assert_called_once_with()
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def test_cost_callback_reads_openrouter_stream_usage_cost() -> None:
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report_state = MagicMock()
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response = SimpleNamespace(
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usage=SimpleNamespace(cost=1.2345),
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_hidden_params={},
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)
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with patch("strix.report.state.get_global_report_state", return_value=report_state):
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litellm_cost_callback({"response_cost": None}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(1.2345)
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def test_cost_callback_reads_usage_cost_from_mapping_response() -> None:
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report_state = MagicMock()
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response = {"usage": {"cost": 0.125}}
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with patch("strix.report.state.get_global_report_state", return_value=report_state):
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litellm_cost_callback({}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(0.125)
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def test_cost_callback_reads_byok_upstream_inference_cost() -> None:
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report_state = MagicMock()
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response = SimpleNamespace(
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usage=SimpleNamespace(
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cost=0,
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is_byok=True,
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cost_details=SimpleNamespace(upstream_inference_cost=6.75e-06),
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),
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_hidden_params={},
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)
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with patch("strix.report.state.get_global_report_state", return_value=report_state):
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litellm_cost_callback({"response_cost": None}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(6.75e-06)
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def test_cost_callback_sums_usage_cost_and_upstream_inference_cost() -> None:
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report_state = MagicMock()
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response = {
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"usage": {
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"cost": 0.01,
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"is_byok": True,
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"cost_details": {"upstream_inference_cost": 0.2},
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}
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}
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with patch("strix.report.state.get_global_report_state", return_value=report_state):
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litellm_cost_callback({}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(pytest.approx(0.21))
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def test_cost_callback_ignores_upstream_cost_for_non_byok_responses() -> None:
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report_state = MagicMock()
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response = {
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"usage": {
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"cost": 0.05,
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"is_byok": False,
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"cost_details": {"upstream_inference_cost": 0.04},
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}
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}
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with patch("strix.report.state.get_global_report_state", return_value=report_state):
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litellm_cost_callback({}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(0.05)
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def test_cost_callback_estimates_cost_with_provider_prefixed_model() -> None:
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report_state = MagicMock()
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response = {"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}
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kwargs = {
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"response_cost": None,
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"model": "anthropic/claude-sonnet-4.5",
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"litellm_params": {"custom_llm_provider": "openrouter"},
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}
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def fake_completion_cost(**kwargs: object) -> float:
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if kwargs["model"] == "openrouter/anthropic/claude-sonnet-4.5":
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return 0.5
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raise ValueError(kwargs["model"])
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with (
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patch("strix.report.state.get_global_report_state", return_value=report_state),
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patch("litellm.completion_cost", side_effect=fake_completion_cost),
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):
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litellm_cost_callback(kwargs, response)
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report_state.record_observed_llm_cost.assert_called_once_with(0.5)
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def test_cost_callback_estimates_cost_with_bare_model_fallback() -> None:
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report_state = MagicMock()
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response = {"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}
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kwargs = {
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"response_cost": None,
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"model": "openai/gpt-4o-mini",
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"litellm_params": {"custom_llm_provider": "openrouter"},
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}
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def fake_completion_cost(**kwargs: object) -> float:
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if kwargs["model"] == "gpt-4o-mini":
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return 0.025
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raise ValueError(kwargs["model"])
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with (
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patch("strix.report.state.get_global_report_state", return_value=report_state),
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patch("litellm.completion_cost", side_effect=fake_completion_cost),
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):
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litellm_cost_callback(kwargs, response)
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report_state.record_observed_llm_cost.assert_called_once_with(0.025)
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def test_cost_callback_records_nothing_when_no_cost_available() -> None:
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report_state = MagicMock()
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response = {"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}
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with (
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patch("strix.report.state.get_global_report_state", return_value=report_state),
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patch("litellm.completion_cost", side_effect=ValueError("unknown model")),
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):
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litellm_cost_callback({"response_cost": None, "model": "x/y"}, response)
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report_state.record_observed_llm_cost.assert_not_called()
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def test_openrouter_stream_cost_extracts_plain_and_byok_totals() -> None:
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assert openrouter_stream_cost({"cost": 0.003168}) == pytest.approx(0.003168)
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assert openrouter_stream_cost(
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{"cost": 0.01, "is_byok": True, "cost_details": {"upstream_inference_cost": 0.2}}
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) == pytest.approx(0.21)
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# Upstream cost is only added for BYOK responses.
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assert openrouter_stream_cost(
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{"cost": 0.05, "is_byok": False, "cost_details": {"upstream_inference_cost": 0.04}}
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) == pytest.approx(0.05)
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assert openrouter_stream_cost({"prompt_tokens": 10}) is None
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assert openrouter_stream_cost(None) is None
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def test_cost_callback_recovers_streamed_openrouter_cost_by_response_id() -> None:
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report_state = MagicMock()
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streamed_openrouter_costs.remember("gen-abc", {"cost": 0.42})
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# LiteLLM strips cost from the rebuilt streamed usage; only the id survives.
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response = SimpleNamespace(id="gen-abc", usage=SimpleNamespace(cost=None), _hidden_params={})
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with (
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patch("strix.report.state.get_global_report_state", return_value=report_state),
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patch("litellm.completion_cost", side_effect=ValueError("unknown model")),
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):
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litellm_cost_callback({"response_cost": None, "model": "moonshotai/kimi-k3"}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(0.42)
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# The entry is consumed so a later response cannot double-count it.
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assert streamed_openrouter_costs.take(response) is None
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def test_streamed_openrouter_cost_prefers_provider_report_over_estimate() -> None:
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report_state = MagicMock()
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streamed_openrouter_costs.remember("gen-xyz", {"cost": 0.9})
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response = SimpleNamespace(
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id="gen-xyz",
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usage=SimpleNamespace(prompt_tokens=10, completion_tokens=5, total_tokens=15),
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_hidden_params={},
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)
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with (
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patch("strix.report.state.get_global_report_state", return_value=report_state),
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patch("litellm.completion_cost", return_value=0.1) as estimate,
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):
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litellm_cost_callback({"response_cost": None, "model": "moonshotai/kimi-k3"}, response)
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report_state.record_observed_llm_cost.assert_called_once_with(0.9)
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estimate.assert_not_called()
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def test_streamed_openrouter_costs_ignores_entries_without_cost() -> None:
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streamed_openrouter_costs.remember("gen-none", {"prompt_tokens": 10})
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streamed_openrouter_costs.remember("", {"cost": 0.5})
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assert streamed_openrouter_costs.take(SimpleNamespace(id="gen-none")) is None
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def test_streamed_openrouter_costs_cleared_on_new_run() -> None:
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streamed_openrouter_costs.remember("gen-stale", {"cost": 0.7})
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try:
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set_global_report_state(ReportState.__new__(ReportState))
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assert streamed_openrouter_costs.take(SimpleNamespace(id="gen-stale")) is None
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finally:
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set_global_report_state(None)
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def test_openrouter_stream_handler_records_cost() -> None:
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_install_openrouter_stream_cost_capture()
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# Resolve the config the way LiteLLM does in production so we prove the
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# override is actually reachable through provider resolution, not just as a
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# directly-constructed class.
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config = ProviderConfigManager.get_provider_chat_config(
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model="moonshotai/kimi-k3", provider=LlmProviders.OPENROUTER
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)
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assert config is not None
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assert type(config).__name__ == "_StrixOpenrouterConfig"
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handler = config.get_model_response_iterator(streaming_response=iter([]), sync_stream=True)
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chunk = {
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"id": "gen-stream",
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"created": 1,
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"model": "moonshotai/kimi-k3",
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"choices": [{"index": 0, "delta": {"content": None}}],
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"usage": {"prompt_tokens": 89, "completion_tokens": 138, "cost": 0.0035055},
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}
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handler.chunk_parser(chunk)
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assert streamed_openrouter_costs.take(SimpleNamespace(id="gen-stream")) == pytest.approx(
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0.0035055
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)
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