docs(call_hooks.md): add async_moderation_hooks to docs

docs/my-website/docs/proxy/call_hooks.md

@@ -1,6 +1,7 @@
 # Modify / Reject Incoming Requests
 
-Modify data just before making litellm completion calls call on proxy
+- Modify data before making llm api calls on proxy
+- Reject data before making llm api calls / before returning the response 
 
 See a complete example with our [parallel request rate limiter](https://github.com/BerriAI/litellm/blob/main/litellm/proxy/hooks/parallel_request_limiter.py)
 
@@ -76,3 +77,93 @@ curl --location 'http://0.0.0.0:8000/chat/completions' \
     }'
 ```
 
+
+## *NEW* async_moderation_hook 
+
+Run a moderation check in parallel to the actual LLM API call. 
+
+In your Custom Handler add a new `async_moderation_hook` function
+
+- This is currently only supported for `/chat/completion` calls. 
+- This function runs in parallel to the actual LLM API call. 
+- If your `async_moderation_hook` raises an Exception, we will return that to the user. 
+
+
+See a complete example with our [Llama Guard content moderation hook](https://github.com/BerriAI/litellm/blob/main/enterprise/hooks/llama_guard.py)
+
+```python
+from litellm.integrations.custom_logger import CustomLogger
+import litellm
+from fastapi import HTTPException
+
+# This file includes the custom callbacks for LiteLLM Proxy
+# Once defined, these can be passed in proxy_config.yaml
+class MyCustomHandler(CustomLogger): # https://docs.litellm.ai/docs/observability/custom_callback#callback-class
+    # Class variables or attributes
+    def __init__(self):
+        pass
+
+    #### ASYNC #### 
+    
+    async def async_log_stream_event(self, kwargs, response_obj, start_time, end_time):
+        pass
+
+    async def async_log_pre_api_call(self, model, messages, kwargs):
+        pass
+
+    async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
+        pass
+
+    async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time):
+        pass
+
+    #### CALL HOOKS - proxy only #### 
+
+    async def async_pre_call_hook(self, user_api_key_dict: UserAPIKeyAuth, cache: DualCache, data: dict, call_type: Literal["completion", "embeddings"]):
+        data["model"] = "my-new-model"
+        return data 
+    
+    async def async_moderation_hook( ### 👈 KEY CHANGE ###
+        self,
+        data: dict,
+    ):
+        messages = data["messages"]
+        print(messages)
+        if messages[0]["content"] == "hello world": 
+            raise HTTPException(
+                    status_code=400, detail={"error": "Violated content safety policy"}
+                )
+
+proxy_handler_instance = MyCustomHandler()
+```
+
+
+2. Add this file to your proxy config
+
+```yaml
+model_list:
+  - model_name: gpt-3.5-turbo
+    litellm_params:
+      model: gpt-3.5-turbo
+
+litellm_settings:
+  callbacks: custom_callbacks.proxy_handler_instance # sets litellm.callbacks = [proxy_handler_instance]
+```
+
+3. Start the server + test the request
+
+```shell
+$ litellm /path/to/config.yaml
+```
+```shell
+curl --location 'http://0.0.0.0:8000/chat/completions' \
+    --data ' {
+    "model": "gpt-3.5-turbo",
+    "messages": [
+        {
+        "role": "user",
+        "content": "Hello world"
+        }
+    ],
+    }'
+```

docs/my-website/sidebars.js

@@ -138,7 +138,7 @@ const sidebars = {
         },
         {
           "type": "category",
-          "label": "Admin Controls",
+          "label": "Content Moderation",
           "items": [
             "proxy/call_hooks",
             "proxy/rules",