test_estimate_cost_resolves_router_model_alias

tests/litellm/proxy/management_endpoints/test_cost_estimate_endpoint.py

@@ -74,3 +74,66 @@ class TestCostEstimateEndpoint:
 
             assert exc_info.value.status_code == 404
 
+    @pytest.mark.asyncio
+    async def test_estimate_cost_resolves_router_model_alias(self):
+        """
+        Test that estimate_cost resolves router model aliases to underlying models.
+
+        When a user selects a model like 'my-gpt4-alias' from the UI (which is a
+        router model_name), the endpoint should resolve it to the actual model
+        (e.g., 'azure/gpt-4') for cost calculation.
+
+        This prevents the bug where custom model names fail cost lookup because
+        they aren't in model_prices_and_context_window.json.
+        """
+        request = CostEstimateRequest(
+            model="my-gpt4-alias",  # Router alias, not actual model name
+            input_tokens=1000,
+            output_tokens=500,
+        )
+
+        # Mock the router to return deployment info
+        mock_router = MagicMock()
+        mock_router.get_model_list.return_value = [
+            {
+                "model_name": "my-gpt4-alias",
+                "litellm_params": {
+                    "model": "azure/gpt-4",  # Actual model for pricing
+                    "custom_llm_provider": "azure",
+                },
+            }
+        ]
+
+        with patch(
+            "litellm.proxy.proxy_server.llm_router",
+            mock_router,
+        ):
+            with patch(
+                "litellm.proxy.management_endpoints.cost_tracking_settings.completion_cost"
+            ) as mock_completion_cost:
+                mock_completion_cost.return_value = 0.05
+
+                with patch("litellm.get_model_info") as mock_get_model_info:
+                    mock_get_model_info.return_value = {
+                        "input_cost_per_token": 0.00003,
+                        "output_cost_per_token": 0.00006,
+                        "litellm_provider": "azure",
+                    }
+
+                    response = await estimate_cost(
+                        request=request,
+                        user_api_key_dict=MagicMock(),
+                    )
+
+        # Verify router was queried for the alias
+        mock_router.get_model_list.assert_called_with(model_name="my-gpt4-alias")
+
+        # Verify completion_cost was called with RESOLVED model, not the alias
+        call_args = mock_completion_cost.call_args
+        assert call_args.kwargs["model"] == "azure/gpt-4"
+
+        # Verify response contains original model name (for UI display)
+        assert response.model == "my-gpt4-alias"
+        assert response.cost_per_request == 0.05
+        assert response.provider == "azure"
+