diff --git a/litellm/__init__.py b/litellm/__init__.py
index 59c8c78eb9e..11d85dc0428 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -1052,6 +1052,7 @@ from .proxy.proxy_cli import run_server
 from .router import Router
 from .assistants.main import *
 from .batches.main import *
+from .moderations.main import *
 from .batch_completion.main import *  # type: ignore
 from .rerank_api.main import *
 from .llms.anthropic.experimental_pass_through.messages.handler import *
diff --git a/litellm/main.py b/litellm/main.py
index ec00e1a3491..d82cb339dbe 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -4432,108 +4432,6 @@ def adapter_completion(
     return translated_response
 
 
-##### Moderation #######################
-
-
-def moderation(
-    input: str, model: Optional[str] = None, api_key: Optional[str] = None, **kwargs
-) -> OpenAIModerationResponse:
-    # only supports open ai for now
-    api_key = (
-        api_key
-        or litellm.api_key
-        or litellm.openai_key
-        or get_secret_str("OPENAI_API_KEY")
-    )
-
-    openai_client = kwargs.get("client", None)
-    if openai_client is None:
-        openai_client = openai.OpenAI(
-            api_key=api_key,
-        )
-
-    if model is not None:
-        response = openai_client.moderations.create(input=input, model=model)
-    else:
-        response = openai_client.moderations.create(input=input)
-
-    response_dict: Dict = response.model_dump()
-    return litellm.utils.LiteLLMResponseObjectHandler.convert_to_moderation_response(
-        response_object=response_dict,
-    )
-
-
-@client
-async def amoderation(
-    input: str,
-    model: Optional[str] = None,
-    api_key: Optional[str] = None,
-    custom_llm_provider: Optional[str] = None,
-    **kwargs,
-) -> OpenAIModerationResponse:
-    from openai import AsyncOpenAI
-
-    # only supports open ai for now
-    api_key = (
-        api_key
-        or litellm.api_key
-        or litellm.openai_key
-        or get_secret_str("OPENAI_API_KEY")
-    )
-    openai_client = kwargs.get("client", None)
-    if openai_client is None or not isinstance(openai_client, AsyncOpenAI):
-        # call helper to get OpenAI client
-        # _get_openai_client maintains in-memory caching logic for OpenAI clients
-        _openai_client: AsyncOpenAI = openai_chat_completions._get_openai_client(  # type: ignore
-            is_async=True,
-            api_key=api_key,
-        )
-    else:
-        _openai_client = openai_client
-
-    optional_params = GenericLiteLLMParams(**kwargs)
-    litellm_logging_obj: Optional[LiteLLMLoggingObj] = kwargs.get(
-        "litellm_logging_obj", None
-    )
-    try:
-        (
-            model,
-            custom_llm_provider,
-            _dynamic_api_key,
-            _dynamic_api_base,
-        ) = litellm.get_llm_provider(
-            model=model or "",
-            custom_llm_provider=custom_llm_provider,
-            api_base=optional_params.api_base,
-            api_key=optional_params.api_key,
-        )
-    except litellm.BadRequestError:
-        # `model` is optional field for moderation - get_llm_provider will throw BadRequestError if model is not set / not recognized
-        pass
-
-    # update litellm_logging_obj with environment variables
-    custom_llm_provider = custom_llm_provider or litellm.LlmProviders.OPENAI.value
-    if litellm_logging_obj is not None:
-        litellm_logging_obj.update_environment_variables(
-            model=model,
-            user=kwargs.get("user", None),
-            optional_params={},
-            litellm_params={
-                **kwargs,
-            },
-            custom_llm_provider=custom_llm_provider,
-        )
-
-    if model is not None:
-        response = await _openai_client.moderations.create(input=input, model=model)
-    else:
-        response = await _openai_client.moderations.create(input=input)
-    response_dict: Dict = response.model_dump()
-    return litellm.utils.LiteLLMResponseObjectHandler.convert_to_moderation_response(
-        response_object=response_dict,
-    )
-
-
 ##### Image Generation #######################
 @client
 async def aimage_generation(*args, **kwargs) -> ImageResponse:
diff --git a/litellm/moderations/main.py b/litellm/moderations/main.py
new file mode 100644
index 00000000000..2eb336fffa1
--- /dev/null
+++ b/litellm/moderations/main.py
@@ -0,0 +1,147 @@
+from typing import Dict, Optional
+
+import openai
+
+import litellm
+
+############ Instantiated classes ############
+from litellm.main import openai_chat_completions as openai_api_client
+from litellm.moderations.utils import ModerationAPIUtils
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import OpenAIModerationResponse
+from litellm.types.router import GenericLiteLLMParams
+from litellm.utils import client
+
+############# Moderations API #######################
+
+
+@client
+def moderation(
+    input: str,
+    model: Optional[str] = None,
+    api_key: Optional[str] = None,
+    custom_llm_provider: Optional[str] = None,
+    **kwargs,
+) -> OpenAIModerationResponse:
+    # only supports open ai for now
+    api_key = (
+        api_key
+        or litellm.api_key
+        or litellm.openai_key
+        or get_secret_str("OPENAI_API_KEY")
+    )
+
+    optional_params = GenericLiteLLMParams(**kwargs)
+    try:
+        (
+            model,
+            custom_llm_provider,
+            _dynamic_api_key,
+            _dynamic_api_base,
+        ) = litellm.get_llm_provider(
+            model=model or "",
+            custom_llm_provider=custom_llm_provider,
+            api_base=optional_params.api_base,
+            api_key=optional_params.api_key,
+        )
+    except litellm.BadRequestError:
+        # `model` is optional field for moderation - get_llm_provider will throw BadRequestError if model is not set / not recognized
+        pass
+
+    openai_client = kwargs.get("client", None)
+    if openai_client is None:
+        openai_client = openai.OpenAI(
+            api_key=api_key,
+        )
+
+    # update litellm_logging_obj with request params (used for logging the correct values in the logging callbacks)
+    ModerationAPIUtils.init_litellm_logging_obj_for_moderations_call(
+        custom_llm_provider=custom_llm_provider,
+        model=model,
+        user=kwargs.get("user", None),
+        **kwargs,
+    )
+
+    if model is not None:
+        response = openai_client.moderations.create(input=input, model=model)
+    else:
+        response = openai_client.moderations.create(input=input)
+
+    response_dict: Dict = response.model_dump()
+    return litellm.utils.LiteLLMResponseObjectHandler.convert_to_moderation_response(
+        response_object=response_dict,
+    )
+
+
+@client
+async def amoderation(
+    input: str,
+    model: Optional[str] = None,
+    api_key: Optional[str] = None,
+    custom_llm_provider: Optional[str] = None,
+    **kwargs,
+) -> OpenAIModerationResponse:
+    from openai import AsyncOpenAI
+
+    ############################################################
+    ######### Pre-Request Setup #################################
+    ############################################################
+    # only supports open ai for now
+    api_key = (
+        api_key
+        or litellm.api_key
+        or litellm.openai_key
+        or get_secret_str("OPENAI_API_KEY")
+    )
+    openai_client = kwargs.get("client", None)
+    if openai_client is None or not isinstance(openai_client, AsyncOpenAI):
+        # call helper to get OpenAI client
+        # _get_openai_client maintains in-memory caching logic for OpenAI clients
+        _openai_client: AsyncOpenAI = openai_api_client._get_openai_client(  # type: ignore
+            is_async=True,
+            api_key=api_key,
+        )
+    else:
+        _openai_client = openai_client
+
+    optional_params = GenericLiteLLMParams(**kwargs)
+    try:
+        (
+            model,
+            custom_llm_provider,
+            _dynamic_api_key,
+            _dynamic_api_base,
+        ) = litellm.get_llm_provider(
+            model=model or "",
+            custom_llm_provider=custom_llm_provider,
+            api_base=optional_params.api_base,
+            api_key=optional_params.api_key,
+        )
+    except litellm.BadRequestError:
+        # `model` is optional field for moderation - get_llm_provider will throw BadRequestError if model is not set / not recognized
+        pass
+
+    # update litellm_logging_obj with request params (used for logging the correct values in the logging callbacks)
+    ModerationAPIUtils.init_litellm_logging_obj_for_moderations_call(
+        custom_llm_provider=custom_llm_provider,
+        model=model,
+        user=kwargs.get("user", None),
+        **kwargs,
+    )
+
+    ############################################################
+    ######### Make API Call #################################
+    ############################################################
+
+    if model is not None:
+        response = await _openai_client.moderations.create(input=input, model=model)
+    else:
+        response = await _openai_client.moderations.create(input=input)
+
+    ############################################################
+    ######### Post-Request Processing #################################
+    ############################################################
+    response_dict: Dict = response.model_dump()
+    return litellm.utils.LiteLLMResponseObjectHandler.convert_to_moderation_response(
+        response_object=response_dict,
+    )
diff --git a/litellm/moderations/utils.py b/litellm/moderations/utils.py
new file mode 100644
index 00000000000..c6b4a8f0563
--- /dev/null
+++ b/litellm/moderations/utils.py
@@ -0,0 +1,38 @@
+from typing import Optional
+
+import litellm
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+
+class ModerationAPIUtils:
+
+    @staticmethod
+    def init_litellm_logging_obj_for_moderations_call(
+        custom_llm_provider: Optional[str] = None,
+        model: Optional[str] = None,
+        user: Optional[str] = None,
+        **kwargs,
+    ):
+        """
+        Initialize the litellm_logging_obj for a moderations call
+
+        Ensures the correct `custom_llm_provider`, model, and user are set in the litellm_logging_obj
+
+        This will be used downstream when constructing the standard_logging_payload
+        """
+        litellm_logging_obj: Optional[LiteLLMLoggingObj] = kwargs.get(
+            "litellm_logging_obj", None
+        )
+        if litellm_logging_obj:
+            custom_llm_provider = (
+                custom_llm_provider or litellm.LlmProviders.OPENAI.value
+            )
+            litellm_logging_obj.update_environment_variables(
+                model=model,
+                user=kwargs.get("user", None),
+                optional_params={},
+                litellm_params={
+                    **kwargs,
+                },
+                custom_llm_provider=custom_llm_provider,
+            )