diff --git a/litellm/main.py b/litellm/main.py
index 65022edb0..5ea6957c0 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -471,10 +471,14 @@ def mock_completion(
         try:
             _, custom_llm_provider, _, _ = litellm.utils.get_llm_provider(model=model)
             model_response._hidden_params["custom_llm_provider"] = custom_llm_provider
-        except:
+        except Exception:
             # dont let setting a hidden param block a mock_respose
             pass
-
+        logging.post_call(
+            input=messages,
+            api_key="my-secret-key",
+            original_response="my-original-response",
+        )
         return model_response
 
     except Exception as e:
diff --git a/litellm/tests/test_custom_callback_input.py b/litellm/tests/test_custom_callback_input.py
index c6e8cd4e9..bda876b85 100644
--- a/litellm/tests/test_custom_callback_input.py
+++ b/litellm/tests/test_custom_callback_input.py
@@ -10,6 +10,7 @@ from typing import Optional, Literal, List, Union
 from litellm import completion, embedding, Cache
 import litellm
 from litellm.integrations.custom_logger import CustomLogger
+from litellm.types.utils import LiteLLMCommonStrings
 
 # Test Scenarios (test across completion, streaming, embedding)
 ## 1: Pre-API-Call
@@ -67,7 +68,18 @@ class CompletionCustomHandler(
             assert isinstance(kwargs["start_time"], (datetime, type(None)))
             assert isinstance(kwargs["stream"], bool)
             assert isinstance(kwargs["user"], (str, type(None)))
-        except Exception as e:
+            ### METADATA
+            metadata_value = kwargs["litellm_params"].get("metadata")
+            assert metadata_value is None or isinstance(metadata_value, dict)
+            if metadata_value is not None:
+                if litellm.turn_off_message_logging is True:
+                    assert (
+                        metadata_value["raw_request"]
+                        is LiteLLMCommonStrings.redacted_by_litellm.value
+                    )
+                else:
+                    assert isinstance(metadata_value["raw_request"], str)
+        except Exception:
             print(f"Assertion Error: {traceback.format_exc()}")
             self.errors.append(traceback.format_exc())
 
@@ -177,6 +189,8 @@ class CompletionCustomHandler(
             assert isinstance(
                 kwargs["original_response"],
                 (str, litellm.CustomStreamWrapper, BaseModel),
+            ), "Original Response={}. Allowed types=[str, litellm.CustomStreamWrapper, BaseModel]".format(
+                kwargs["original_response"]
             )
             assert isinstance(kwargs["additional_args"], (dict, type(None)))
             assert isinstance(kwargs["log_event_type"], str)
@@ -1053,3 +1067,25 @@ def test_image_generation_openai():
 ## Test Azure + Sync
 
 ## Test Azure + Async
+
+##### PII REDACTION ######
+
+
+def test_turn_off_message_logging():
+    """
+    If 'turn_off_message_logging' is true, assert no user request information is logged.
+    """
+    litellm.turn_off_message_logging = True
+
+    # sync completion
+    customHandler = CompletionCustomHandler()
+    litellm.callbacks = [customHandler]
+
+    _ = litellm.completion(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": "Hey, how's it going?"}],
+        mock_response="Going well!",
+    )
+
+    time.sleep(2)
+    assert len(customHandler.errors) == 0
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 7efc628ca..f16d9567f 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -1,5 +1,10 @@
 from typing import List, Optional, Union, Dict, Tuple, Literal
 from typing_extensions import TypedDict
+from enum import Enum
+
+
+class LiteLLMCommonStrings(Enum):
+    redacted_by_litellm = "redacted by litellm. 'litellm.turn_off_message_logging=True'"
 
 
 class CostPerToken(TypedDict):
diff --git a/litellm/utils.py b/litellm/utils.py
index f13d38c6b..e8d44e87d 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -1308,14 +1308,28 @@ class Logging:
                 )
             else:
                 verbose_logger.debug(f"\033[92m{curl_command}\033[0m\n")
-            # check if user wants the raw request logged to their logging provider (like LangFuse)
+            # log raw request to provider (like LangFuse)
             try:
                 # [Non-blocking Extra Debug Information in metadata]
                 _litellm_params = self.model_call_details.get("litellm_params", {})
                 _metadata = _litellm_params.get("metadata", {}) or {}
-                _metadata["raw_request"] = str(curl_command)
-            except:
-                pass
+                if (
+                    litellm.turn_off_message_logging is not None
+                    and litellm.turn_off_message_logging is True
+                ):
+                    _metadata["raw_request"] = (
+                        "redacted by litellm. \
+                        'litellm.turn_off_message_logging=True'"
+                    )
+                else:
+                    _metadata["raw_request"] = str(curl_command)
+            except Exception as e:
+                _metadata["raw_request"] = (
+                    "Unable to Log \
+                    raw request: {}".format(
+                        str(e)
+                    )
+                )
             if self.logger_fn and callable(self.logger_fn):
                 try:
                     self.logger_fn(
@@ -2684,7 +2698,9 @@ class Logging:
         # check if user opted out of logging message/response to callbacks
         if litellm.turn_off_message_logging == True:
             # remove messages, prompts, input, response from logging
-            self.model_call_details["messages"] = "redacted-by-litellm"
+            self.model_call_details["messages"] = [
+                {"role": "user", "content": "redacted-by-litellm"}
+            ]
             self.model_call_details["prompt"] = ""
             self.model_call_details["input"] = ""
 
@@ -4064,7 +4080,9 @@ def openai_token_counter(
                     for c in value:
                         if c["type"] == "text":
                             text += c["text"]
-                            num_tokens += len(encoding.encode(c["text"], disallowed_special=()))
+                            num_tokens += len(
+                                encoding.encode(c["text"], disallowed_special=())
+                            )
                         elif c["type"] == "image_url":
                             if isinstance(c["image_url"], dict):
                                 image_url_dict = c["image_url"]