fix(litellm_logging.py): use 1 cost calc function across response headers + logging integrations

Ensures consistent cost calculation when azure base models are used

litellm/litellm_core_utils/litellm_logging.py

@@ -12,6 +12,8 @@ import traceback
 import uuid
 from typing import Any, Callable, Dict, List, Literal, Optional
 
+from pydantic import BaseModel
+
 import litellm
 from litellm import (
     json_logs,
@@ -503,6 +505,34 @@ class Logging:
                 )
             )
 
+    def _response_cost_calculator(self, result: BaseModel):
+        """
+        Calculate response cost using result + logging object variables.
+
+        used for consistent cost calculation across response headers + logging integrations.
+        """
+        ## RESPONSE COST ##
+        custom_pricing = use_custom_pricing_for_model(
+            litellm_params=self.litellm_params
+        )
+
+        response_cost = litellm.response_cost_calculator(
+            response_object=result,
+            model=self.model,
+            cache_hit=self.model_call_details.get("cache_hit", False),
+            custom_llm_provider=self.model_call_details.get(
+                "custom_llm_provider", None
+            ),
+            base_model=_get_base_model_from_metadata(
+                model_call_details=self.model_call_details
+            ),
+            call_type=self.call_type,
+            optional_params=self.optional_params,
+            custom_pricing=custom_pricing,
+        )
+
+        return response_cost
+
     def _success_handler_helper_fn(
         self, result=None, start_time=None, end_time=None, cache_hit=None
     ):
@@ -537,20 +567,7 @@ class Logging:
                         litellm_params=self.litellm_params
                     )
                     self.model_call_details["response_cost"] = (
-                        litellm.response_cost_calculator(
-                            response_object=result,
-                            model=self.model,
-                            cache_hit=self.model_call_details.get("cache_hit", False),
-                            custom_llm_provider=self.model_call_details.get(
-                                "custom_llm_provider", None
-                            ),
-                            base_model=_get_base_model_from_metadata(
-                                model_call_details=self.model_call_details
-                            ),
-                            call_type=self.call_type,
-                            optional_params=self.optional_params,
-                            custom_pricing=custom_pricing,
-                        )
+                        self._response_cost_calculator(result=result)
                     )
 
                     ## HIDDEN PARAMS ##

litellm/proxy/_new_secret_config.yaml

@@ -1,4 +1,11 @@
 model_list:
   - model_name: "*"
     litellm_params:
-      model: "*"
+      model: "*"
+  - model_name: "azure-gpt-4o-mini"
+    litellm_params:
+      model: azure/my-gpt-4o-mini
+      api_key: os.environ/AZURE_API_KEY
+      api_base: os.environ/AZURE_API_BASE
+    model_info:
+      base_model: azure/global-standard/gpt-4o-mini

litellm/utils.py

@@ -1368,15 +1368,7 @@ def client(original_function):
                     optional_params=kwargs,
                 )
                 result._hidden_params["response_cost"] = (
-                    litellm.response_cost_calculator(
-                        response_object=result,
-                        model=getattr(logging_obj, "model", ""),
-                        custom_llm_provider=getattr(
-                            logging_obj, "custom_llm_provider", None
-                        ),
-                        call_type=getattr(logging_obj, "call_type", "completion"),
-                        optional_params=getattr(logging_obj, "optional_params", {}),
-                    )
+                    logging_obj._response_cost_calculator(result=result)
                 )
             if (
                 isinstance(result, ModelResponse)