Merge pull request #4395 from BerriAI/litelm_use_spend_calc_aliases

Fix /spend/calculate use model_group_alias when set

litellm/proxy/spend_tracking/spend_management_endpoints.py

@@ -1265,6 +1265,19 @@ async def calculate_spend(request: SpendCalculateRequest):
             _model_in_llm_router = None
             cost_per_token: Optional[CostPerToken] = None
             if llm_router is not None:
+                if (
+                    llm_router.model_group_alias is not None
+                    and request.model in llm_router.model_group_alias
+                ):
+                    # lookup alias in llm_router
+                    _model_group_name = llm_router.model_group_alias[request.model]
+                    for model in llm_router.model_list:
+                        if model.get("model_name") == _model_group_name:
+                            _model_in_llm_router = model
+
+                else:
+                    # no model_group aliases set -> try finding model in llm_router
+                    # find model in llm_router
                     for model in llm_router.model_list:
                         if model.get("model_name") == request.model:
                             _model_in_llm_router = model

litellm/tests/test_spend_calculate_endpoint.py

@@ -101,3 +101,41 @@ async def test_spend_calc_using_response():
     print("calculated cost", cost_obj)
     cost = cost_obj["cost"]
     assert cost > 0.0
+
+
+@pytest.mark.asyncio
+async def test_spend_calc_model_alias_on_router_messages():
+    from litellm.proxy.proxy_server import llm_router as init_llm_router
+
+    temp_llm_router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-4o",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                },
+            }
+        ],
+        model_group_alias={
+            "gpt4o": "gpt-4o",
+        },
+    )
+
+    setattr(litellm.proxy.proxy_server, "llm_router", temp_llm_router)
+
+    cost_obj = await calculate_spend(
+        request=SpendCalculateRequest(
+            model="gpt4o",
+            messages=[
+                {"role": "user", "content": "What is the capital of France?"},
+            ],
+        )
+    )
+
+    print("calculated cost", cost_obj)
+    _cost = cost_obj["cost"]
+
+    assert _cost > 0.0
+
+    # set router to init value
+    setattr(litellm.proxy.proxy_server, "llm_router", init_llm_router)