fix(report): restore cost tracking for OpenRouter and other LiteLLM-routed models (#801)

tests/test_cost_tracking.py

@@ -6,6 +6,7 @@ from types import SimpleNamespace
 from unittest.mock import MagicMock, patch
 
 import litellm
+import pytest
 
 from strix.config.models import _configure_litellm_compatibility
 from strix.report.state import litellm_cost_callback
@@ -42,3 +43,111 @@ def test_cost_callback_reads_usage_cost_from_mapping_response() -> None:
         litellm_cost_callback({}, response)
 
     report_state.record_observed_llm_cost.assert_called_once_with(0.125)
+
+
+def test_cost_callback_reads_byok_upstream_inference_cost() -> None:
+    report_state = MagicMock()
+    response = SimpleNamespace(
+        usage=SimpleNamespace(
+            cost=0,
+            is_byok=True,
+            cost_details=SimpleNamespace(upstream_inference_cost=6.75e-06),
+        ),
+        _hidden_params={},
+    )
+
+    with patch("strix.report.state.get_global_report_state", return_value=report_state):
+        litellm_cost_callback({"response_cost": None}, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(6.75e-06)
+
+
+def test_cost_callback_sums_usage_cost_and_upstream_inference_cost() -> None:
+    report_state = MagicMock()
+    response = {
+        "usage": {
+            "cost": 0.01,
+            "is_byok": True,
+            "cost_details": {"upstream_inference_cost": 0.2},
+        }
+    }
+
+    with patch("strix.report.state.get_global_report_state", return_value=report_state):
+        litellm_cost_callback({}, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(pytest.approx(0.21))
+
+
+def test_cost_callback_ignores_upstream_cost_for_non_byok_responses() -> None:
+    report_state = MagicMock()
+    response = {
+        "usage": {
+            "cost": 0.05,
+            "is_byok": False,
+            "cost_details": {"upstream_inference_cost": 0.04},
+        }
+    }
+
+    with patch("strix.report.state.get_global_report_state", return_value=report_state):
+        litellm_cost_callback({}, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(0.05)
+
+
+def test_cost_callback_estimates_cost_with_provider_prefixed_model() -> None:
+    report_state = MagicMock()
+    response = {"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}
+    kwargs = {
+        "response_cost": None,
+        "model": "anthropic/claude-sonnet-4.5",
+        "litellm_params": {"custom_llm_provider": "openrouter"},
+    }
+
+    def fake_completion_cost(**kwargs: object) -> float:
+        if kwargs["model"] == "openrouter/anthropic/claude-sonnet-4.5":
+            return 0.5
+        raise ValueError(kwargs["model"])
+
+    with (
+        patch("strix.report.state.get_global_report_state", return_value=report_state),
+        patch("litellm.completion_cost", side_effect=fake_completion_cost),
+    ):
+        litellm_cost_callback(kwargs, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(0.5)
+
+
+def test_cost_callback_estimates_cost_with_bare_model_fallback() -> None:
+    report_state = MagicMock()
+    response = {"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}
+    kwargs = {
+        "response_cost": None,
+        "model": "openai/gpt-4o-mini",
+        "litellm_params": {"custom_llm_provider": "openrouter"},
+    }
+
+    def fake_completion_cost(**kwargs: object) -> float:
+        if kwargs["model"] == "gpt-4o-mini":
+            return 0.025
+        raise ValueError(kwargs["model"])
+
+    with (
+        patch("strix.report.state.get_global_report_state", return_value=report_state),
+        patch("litellm.completion_cost", side_effect=fake_completion_cost),
+    ):
+        litellm_cost_callback(kwargs, response)
+
+    report_state.record_observed_llm_cost.assert_called_once_with(0.025)
+
+
+def test_cost_callback_records_nothing_when_no_cost_available() -> None:
+    report_state = MagicMock()
+    response = {"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}
+
+    with (
+        patch("strix.report.state.get_global_report_state", return_value=report_state),
+        patch("litellm.completion_cost", side_effect=ValueError("unknown model")),
+    ):
+        litellm_cost_callback({"response_cost": None, "model": "x/y"}, response)
+
+    report_state.record_observed_llm_cost.assert_not_called()