(feat) GCS Bucket logging. Allow using IAM auth for logging to GCS (#6628)

* fix gcs bucket auth

* allow iam auth for gcs logging

* test_get_gcs_logging_config_without_service_account

litellm/integrations/gcs_bucket/gcs_bucket.py

@@ -26,10 +26,13 @@ else:
     VertexBase = Any
 
 
+IAM_AUTH_KEY = "IAM_AUTH"
+
+
 class GCSLoggingConfig(TypedDict):
     bucket_name: str
     vertex_instance: VertexBase
-    path_service_account: str
+    path_service_account: Optional[str]
 
 
 class GCSBucketLogger(GCSBucketBase):
@@ -173,7 +176,7 @@ class GCSBucketLogger(GCSBucketBase):
         )
 
         bucket_name: str
-        path_service_account: str
+        path_service_account: Optional[str]
         if standard_callback_dynamic_params is not None:
             verbose_logger.debug("Using dynamic GCS logging")
             verbose_logger.debug(
@@ -193,10 +196,6 @@ class GCSBucketLogger(GCSBucketBase):
                 raise ValueError(
                     "GCS_BUCKET_NAME is not set in the environment, but GCS Bucket is being used as a logging callback. Please set 'GCS_BUCKET_NAME' in the environment."
                 )
-            if _path_service_account is None:
-                raise ValueError(
-                    "GCS_PATH_SERVICE_ACCOUNT is not set in the environment, but GCS Bucket is being used as a logging callback. Please set 'GCS_PATH_SERVICE_ACCOUNT' in the environment."
-                )
             bucket_name = _bucket_name
             path_service_account = _path_service_account
             vertex_instance = await self.get_or_create_vertex_instance(
@@ -208,10 +207,6 @@ class GCSBucketLogger(GCSBucketBase):
                 raise ValueError(
                     "GCS_BUCKET_NAME is not set in the environment, but GCS Bucket is being used as a logging callback. Please set 'GCS_BUCKET_NAME' in the environment."
                 )
-            if self.path_service_account_json is None:
-                raise ValueError(
-                    "GCS_PATH_SERVICE_ACCOUNT is not set in the environment, but GCS Bucket is being used as a logging callback. Please set 'GCS_PATH_SERVICE_ACCOUNT' in the environment."
-                )
             bucket_name = self.BUCKET_NAME
             path_service_account = self.path_service_account_json
             vertex_instance = await self.get_or_create_vertex_instance(
@@ -224,7 +219,9 @@ class GCSBucketLogger(GCSBucketBase):
             path_service_account=path_service_account,
         )
 
-    async def get_or_create_vertex_instance(self, credentials: str) -> VertexBase:
+    async def get_or_create_vertex_instance(
+        self, credentials: Optional[str]
+    ) -> VertexBase:
         """
         This function is used to get the Vertex instance for the GCS Bucket Logger.
         It checks if the Vertex instance is already created and cached, if not it creates a new instance and caches it.
@@ -233,15 +230,27 @@ class GCSBucketLogger(GCSBucketBase):
             VertexBase,
         )
 
-        if credentials not in self.vertex_instances:
+        _in_memory_key = self._get_in_memory_key_for_vertex_instance(credentials)
+        if _in_memory_key not in self.vertex_instances:
             vertex_instance = VertexBase()
             await vertex_instance._ensure_access_token_async(
                 credentials=credentials,
                 project_id=None,
                 custom_llm_provider="vertex_ai",
             )
-            self.vertex_instances[credentials] = vertex_instance
-        return self.vertex_instances[credentials]
+            self.vertex_instances[_in_memory_key] = vertex_instance
+        return self.vertex_instances[_in_memory_key]
+
+    def _get_in_memory_key_for_vertex_instance(self, credentials: Optional[str]) -> str:
+        """
+        Returns key to use for caching the Vertex instance in-memory.
+
+        When using Vertex with Key based logging, we need to cache the Vertex instance in-memory.
+
+        - If a credentials string is provided, it is used as the key.
+        - If no credentials string is provided, "IAM_AUTH" is used as the key.
+        """
+        return credentials or IAM_AUTH_KEY
 
     async def download_gcs_object(self, object_name: str, **kwargs):
         """

litellm/integrations/gcs_bucket/gcs_bucket_base.py

@@ -33,7 +33,7 @@ class GCSBucketBase(CustomLogger):
 
     async def construct_request_headers(
         self,
-        service_account_json: str,
+        service_account_json: Optional[str],
         vertex_instance: Optional[VertexBase] = None,
     ) -> Dict[str, str]:
         from litellm import vertex_chat_completion

litellm/proxy/proxy_config.yaml

@@ -5,7 +5,5 @@ model_list:
       api_key: os.environ/OPENAI_API_KEY
       api_base: https://exampleopenaiendpoint-production.up.railway.app/
 
-
-general_settings: 
-    alerting: ["slack"]
-    alerting_threshold: 0.001
+litellm_settings:
+  callbacks: ["gcs_bucket"]

tests/local_testing/test_gcs_bucket.py

@@ -519,3 +519,50 @@ async def test_basic_gcs_logging_per_request_with_no_litellm_callback_set():
         object_name=gcs_log_id,
         standard_callback_dynamic_params=standard_callback_dynamic_params,
     )
+
+
+@pytest.mark.asyncio
+async def test_get_gcs_logging_config_without_service_account():
+    """
+    Test the get_gcs_logging_config works for IAM auth on GCS
+    1. Key based logging without a service account
+    2. Default Callback without a service account
+    """
+
+    # Mock the load_auth function to avoid credential loading issues
+    # Test 1: With standard_callback_dynamic_params (with service account)
+    gcs_logger = GCSBucketLogger()
+
+    dynamic_params = StandardCallbackDynamicParams(
+        gcs_bucket_name="dynamic-bucket",
+    )
+    config = await gcs_logger.get_gcs_logging_config(
+        {"standard_callback_dynamic_params": dynamic_params}
+    )
+
+    assert config["bucket_name"] == "dynamic-bucket"
+    assert config["path_service_account"] is None
+    assert config["vertex_instance"] is not None
+
+    # Test 2: With standard_callback_dynamic_params (without service account - this is IAM auth)
+    dynamic_params = StandardCallbackDynamicParams(
+        gcs_bucket_name="dynamic-bucket", gcs_path_service_account=None
+    )
+
+    config = await gcs_logger.get_gcs_logging_config(
+        {"standard_callback_dynamic_params": dynamic_params}
+    )
+
+    assert config["bucket_name"] == "dynamic-bucket"
+    assert config["path_service_account"] is None
+    assert config["vertex_instance"] is not None
+
+    # Test 5: With missing bucket name
+    with pytest.raises(ValueError, match="GCS_BUCKET_NAME is not set"):
+        _old_gcs_bucket_name = os.environ.get("GCS_BUCKET_NAME")
+        os.environ.pop("GCS_BUCKET_NAME")
+        gcs_logger = GCSBucketLogger(bucket_name=None)
+        await gcs_logger.get_gcs_logging_config({})
+
+        if _old_gcs_bucket_name is not None:
+            os.environ["GCS_BUCKET_NAME"] = _old_gcs_bucket_name