(fix) GCS bucket logger - apply truncate_standard_logging_payload_content to standard_logging_payload and ensure GCS flushes queue on fails (#7519)

* fix async_send_batch for gcs

* fix truncate GCS logger

* test_truncate_standard_logging_payload

litellm/integrations/custom_logger.py

@@ -293,3 +293,60 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         except Exception:
             print_verbose(f"Custom Logger Error - {traceback.format_exc()}")
             pass
+
+    # Useful helpers for custom logger classes
+
+    def truncate_standard_logging_payload_content(
+        self,
+        standard_logging_object: StandardLoggingPayload,
+    ):
+        """
+        Truncate error strings and message content in logging payload
+
+        Some loggers like DataDog/ GCS Bucket have a limit on the size of the payload. (1MB)
+
+        This function truncates the error string and the message content if they exceed a certain length.
+        """
+        MAX_STR_LENGTH = 10_000
+
+        # Truncate fields that might exceed max length
+        fields_to_truncate = ["error_str", "messages", "response"]
+        for field in fields_to_truncate:
+            self._truncate_field(
+                standard_logging_object=standard_logging_object,
+                field_name=field,
+                max_length=MAX_STR_LENGTH,
+            )
+
+    def _truncate_field(
+        self,
+        standard_logging_object: StandardLoggingPayload,
+        field_name: str,
+        max_length: int,
+    ) -> None:
+        """
+        Helper function to truncate a field in the logging payload
+
+        This converts the field to a string and then truncates it if it exceeds the max length.
+
+        Why convert to string ?
+        1. User was sending a poorly formatted list for `messages` field, we could not predict where they would send content
+            - Converting to string and then truncating the logged content catches this
+        2. We want to avoid modifying the original `messages`, `response`, and `error_str` in the logging payload since these are in kwargs and could be returned to the user
+        """
+        field_value = standard_logging_object.get(field_name)  # type: ignore
+        if field_value:
+            str_value = str(field_value)
+            if len(str_value) > max_length:
+                standard_logging_object[field_name] = self._truncate_text(  # type: ignore
+                    text=str_value, max_length=max_length
+                )
+
+    def _truncate_text(self, text: str, max_length: int) -> str:
+        """Truncate text if it exceeds max_length"""
+        return (
+            text[:max_length]
+            + "...truncated by litellm, this logger does not support large content"
+            if len(text) > max_length
+            else text
+        )

litellm/integrations/datadog/datadog.py

@@ -256,10 +256,6 @@ class DataDogLogger(CustomBatchLogger):
         """
         import json
 
-        from litellm.litellm_core_utils.litellm_logging import (
-            truncate_standard_logging_payload_content,
-        )
-
         standard_logging_object: Optional[StandardLoggingPayload] = kwargs.get(
             "standard_logging_object", None
         )
@@ -271,7 +267,7 @@ class DataDogLogger(CustomBatchLogger):
             status = DataDogStatus.ERROR
 
         # Build the initial payload
-        truncate_standard_logging_payload_content(standard_logging_object)
+        self.truncate_standard_logging_payload_content(standard_logging_object)
         json_payload = json.dumps(standard_logging_object, default=str)
 
         verbose_logger.debug("Datadog: Logger - Logging payload = %s", json_payload)

litellm/integrations/gcs_bucket/gcs_bucket.py

@@ -64,7 +64,7 @@ class GCSBucketLogger(GCSBucketBase):
             )
             if logging_payload is None:
                 raise ValueError("standard_logging_object not found in kwargs")
-
+            self.truncate_standard_logging_payload_content(logging_payload)
             # Add to logging queue - this will be flushed periodically
             self.log_queue.append(
                 GCSLogQueueItem(
@@ -88,7 +88,7 @@ class GCSBucketLogger(GCSBucketBase):
             )
             if logging_payload is None:
                 raise ValueError("standard_logging_object not found in kwargs")
-
+            self.truncate_standard_logging_payload_content(logging_payload)
             # Add to logging queue - this will be flushed periodically
             self.log_queue.append(
                 GCSLogQueueItem(
@@ -114,36 +114,38 @@ class GCSBucketLogger(GCSBucketBase):
         if not self.log_queue:
             return
 
-        try:
         for log_item in self.log_queue:
             logging_payload = log_item["payload"]
             kwargs = log_item["kwargs"]
             response_obj = log_item.get("response_obj", None) or {}
 
-                gcs_logging_config: GCSLoggingConfig = (
-                    await self.get_gcs_logging_config(kwargs)
+            gcs_logging_config: GCSLoggingConfig = await self.get_gcs_logging_config(
+                kwargs
             )
             headers = await self.construct_request_headers(
                 vertex_instance=gcs_logging_config["vertex_instance"],
                 service_account_json=gcs_logging_config["path_service_account"],
             )
             bucket_name = gcs_logging_config["bucket_name"]
-                object_name = self._get_object_name(
-                    kwargs, logging_payload, response_obj
-                )
+            object_name = self._get_object_name(kwargs, logging_payload, response_obj)
+
+            try:
                 await self._log_json_data_on_gcs(
                     headers=headers,
                     bucket_name=bucket_name,
                     object_name=object_name,
                     logging_payload=logging_payload,
                 )
+            except Exception as e:
+                # don't let one log item fail the entire batch
+                verbose_logger.exception(
+                    f"GCS Bucket error logging payload to GCS bucket: {str(e)}"
+                )
+                pass
 
         # Clear the queue after processing
         self.log_queue.clear()
 
-        except Exception as e:
-            verbose_logger.exception(f"GCS Bucket batch logging error: {str(e)}")
-
     def _get_object_name(
         self, kwargs: Dict, logging_payload: StandardLoggingPayload, response_obj: Any
     ) -> str:

litellm/litellm_core_utils/litellm_logging.py

@@ -3034,60 +3034,6 @@ def get_standard_logging_object_payload(
         return None
 
 
-def truncate_standard_logging_payload_content(
-    standard_logging_object: StandardLoggingPayload,
-):
-    """
-    Truncate error strings and message content in logging payload
-
-    Some loggers like DataDog have a limit on the size of the payload. (1MB)
-
-    This function truncates the error string and the message content if they exceed a certain length.
-    """
-    MAX_STR_LENGTH = 10_000
-
-    # Truncate fields that might exceed max length
-    fields_to_truncate = ["error_str", "messages", "response"]
-    for field in fields_to_truncate:
-        _truncate_field(
-            standard_logging_object=standard_logging_object,
-            field_name=field,
-            max_length=MAX_STR_LENGTH,
-        )
-
-
-def _truncate_text(text: str, max_length: int) -> str:
-    """Truncate text if it exceeds max_length"""
-    return (
-        text[:max_length]
-        + "...truncated by litellm, this logger does not support large content"
-        if len(text) > max_length
-        else text
-    )
-
-
-def _truncate_field(
-    standard_logging_object: StandardLoggingPayload, field_name: str, max_length: int
-) -> None:
-    """
-    Helper function to truncate a field in the logging payload
-
-    This converts the field to a string and then truncates it if it exceeds the max length.
-
-    Why convert to string ?
-    1. User was sending a poorly formatted list for `messages` field, we could not predict where they would send content
-        - Converting to string and then truncating the logged content catches this
-    2. We want to avoid modifying the original `messages`, `response`, and `error_str` in the logging payload since these are in kwargs and could be returned to the user
-    """
-    field_value = standard_logging_object.get(field_name)  # type: ignore
-    if field_value:
-        str_value = str(field_value)
-        if len(str_value) > max_length:
-            standard_logging_object[field_name] = _truncate_text(  # type: ignore
-                text=str_value, max_length=max_length
-            )
-
-
 def get_standard_logging_metadata(
     metadata: Optional[Dict[str, Any]]
 ) -> StandardLoggingMetadata:

tests/logging_callback_tests/test_standard_logging_payload.py

@@ -28,9 +28,10 @@ from create_mock_standard_logging_payload import (
 )
 from litellm.litellm_core_utils.litellm_logging import (
     StandardLoggingPayloadSetup,
-    truncate_standard_logging_payload_content,
 )
 
+from litellm.integrations.custom_logger import CustomLogger
+
 
 @pytest.mark.parametrize(
     "response_obj,expected_values",
@@ -332,6 +333,7 @@ def test_truncate_standard_logging_payload():
     1. original messages, response, and error_str should NOT BE MODIFIED, since these are from kwargs
     2. the `messages`, `response`, and `error_str` in new standard_logging_payload should be truncated
     """
+    _custom_logger = CustomLogger()
     standard_logging_payload: StandardLoggingPayload = (
         create_standard_logging_payload_with_long_content()
     )
@@ -342,7 +344,7 @@ def test_truncate_standard_logging_payload():
     original_error_str = standard_logging_payload["error_str"]
     len_original_error_str = len(str(original_error_str))
 
-    truncate_standard_logging_payload_content(standard_logging_payload)
+    _custom_logger.truncate_standard_logging_payload_content(standard_logging_payload)
 
     # Original messages, response, and error_str should NOT BE MODIFIED
     assert standard_logging_payload["messages"] != original_messages