use common _create_vertex_response_logging_payload_for_generate_content

litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py

@@ -100,7 +100,7 @@ class AnthropicPassthroughLoggingHandler:
         kwargs["response_cost"] = response_cost
         kwargs["model"] = model
 
-        # Make standard logging object for Vertex AI
+        # Make standard logging object for Anthropic
         standard_logging_object = get_standard_logging_object_payload(
             kwargs=kwargs,
             init_response_obj=litellm_model_response,

litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py

@@ -56,8 +56,14 @@ class VertexPassthroughLoggingHandler:
                     encoding=None,
                 )
             )
-            logging_obj.model = litellm_model_response.model or model
+            kwargs = VertexPassthroughLoggingHandler._create_vertex_response_logging_payload_for_generate_content(
-            logging_obj.model_call_details["model"] = logging_obj.model
+                litellm_model_response=litellm_model_response,
+                model=model,
+                kwargs=kwargs,
+                start_time=start_time,
+                end_time=end_time,
+                logging_obj=logging_obj,
+            )
 
             await logging_obj.async_success_handler(
                 result=litellm_model_response,
@@ -147,6 +153,14 @@ class VertexPassthroughLoggingHandler:
                 "Unable to build complete streaming response for Vertex passthrough endpoint, not logging..."
             )
             return
+        kwargs = VertexPassthroughLoggingHandler._create_vertex_response_logging_payload_for_generate_content(
+            litellm_model_response=complete_streaming_response,
+            model=model,
+            kwargs=kwargs,
+            start_time=start_time,
+            end_time=end_time,
+            logging_obj=litellm_logging_obj,
+        )
         await litellm_logging_obj.async_success_handler(
             result=complete_streaming_response,
             start_time=start_time,
@@ -193,3 +207,47 @@ class VertexPassthroughLoggingHandler:
         if match:
             return match.group(1)
         return "unknown"
+
+    @staticmethod
+    def _create_vertex_response_logging_payload_for_generate_content(
+        litellm_model_response: Union[
+            litellm.ModelResponse, litellm.TextCompletionResponse
+        ],
+        model: str,
+        kwargs: dict,
+        start_time: datetime,
+        end_time: datetime,
+        logging_obj: LiteLLMLoggingObj,
+    ):
+        """
+        Create the standard logging object for Vertex passthrough generateContent (streaming and non-streaming)
+
+        """
+        response_cost = litellm.completion_cost(
+            completion_response=litellm_model_response,
+            model=model,
+        )
+        kwargs["response_cost"] = response_cost
+        kwargs["model"] = model
+
+        # Make standard logging object for Vertex AI
+        standard_logging_object = get_standard_logging_object_payload(
+            kwargs=kwargs,
+            init_response_obj=litellm_model_response,
+            start_time=start_time,
+            end_time=end_time,
+            logging_obj=logging_obj,
+            status="success",
+        )
+
+        # pretty print standard logging object
+        verbose_proxy_logger.debug(
+            "standard_logging_object= %s", json.dumps(standard_logging_object, indent=4)
+        )
+        kwargs["standard_logging_object"] = standard_logging_object
+
+        # set litellm_call_id to logging response object
+        litellm_model_response.id = logging_obj.litellm_call_id
+        logging_obj.model = litellm_model_response.model or model
+        logging_obj.model_call_details["model"] = logging_obj.model
+        return kwargs