docs(enterprise.md): add llm guard to docs

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

@@ -14,6 +14,7 @@ Features here are behind a commercial license in our `/enterprise` folder. [**Se
 Features: 
 - [ ] Content Moderation with LlamaGuard 
 - [ ] Content Moderation with Google Text Moderations 
+- [ ] Content Moderation with LLM Guard
 - [ ] Tracking Spend for Custom Tags
  
 ## Content Moderation with LlamaGuard 
@@ -48,6 +49,33 @@ callbacks: ["llamaguard_moderations"]
   llamaguard_unsafe_content_categories: /path/to/llamaguard_prompt.txt
 ```
 
+## Content Moderation with LLM Guard
+
+Set the LLM Guard API Base in your environment 
+
+```env
+LLM_GUARD_API_BASE = "http://0.0.0.0:8000"
+```
+
+Add `llmguard_moderations` as a callback 
+
+```yaml
+litellm_settings:
+    callbacks: ["llmguard_moderations"]
+```
+
+Now you can easily test it
+
+- Make a regular /chat/completion call 
+
+- Check your proxy logs for any statement with `LLM Guard:`
+
+Expected results: 
+
+```
+LLM Guard: Received response - {"sanitized_prompt": "hello world", "is_valid": true, "scanners": { "Regex": 0.0 }}
+```
+
 ## Content Moderation with Google Text Moderation 
 
 Requires your GOOGLE_APPLICATION_CREDENTIALS to be set in your .env (same as VertexAI).
@@ -102,6 +130,8 @@ Here are the category specific values:
 | "finance" | finance_threshold: 0.1 | 
 | "legal" | legal_threshold: 0.1 |
 
+
+
 ## Tracking Spend for Custom Tags
 
 Requirements: 

enterprise/enterprise_hooks/llm_guard.py

@@ -66,7 +66,9 @@ class _ENTERPRISE_LLMGuard(CustomLogger):
                         analyze_url, json=analyze_payload
                     ) as response:
                         redacted_text = await response.json()
-
+                verbose_proxy_logger.info(
+                    f"LLM Guard: Received response - {redacted_text}"
+                )
                 if redacted_text is not None:
                     if (
                         redacted_text.get("is_valid", None) is not None