diff --git a/docs/extras/integrations/llms/promptguard.ipynb b/docs/extras/integrations/llms/promptguard.ipynb
index 7cc447bbf46..f93244ecad0 100644
--- a/docs/extras/integrations/llms/promptguard.ipynb
+++ b/docs/extras/integrations/llms/promptguard.ipynb
@@ -39,7 +39,7 @@
     "\n",
     "# Set API keys\n",
     "\n",
-    "os.environ['PROMPT_GUARD_API_KEY'] = \"<PROMPT_GUARD_API_KEY>\"\n",
+    "os.environ['PROMPTGUARD_API_KEY'] = \"<PROMPTGUARD_API_KEY>\"\n",
     "os.environ['OPENAI_API_KEY'] = \"<OPENAI_API_KEY>\""
    ]
   },
@@ -47,9 +47,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Use PromptGuardLLMWrapper\n",
+    "# Use PromptGuard LLM Wrapper\n",
     "\n",
-    "Applying promptguard to your application could be as simple as wrapping your LLM using the PromptGuardLLMWrapper class by replace `llm=OpenAI()` with `llm=PromptGuardLLMWrapper(OpenAI())`."
+    "Applying promptguard to your application could be as simple as wrapping your LLM using the PromptGuard class by replace `llm=OpenAI()` with `llm=PromptGuard(base_llm=OpenAI())`."
    ]
   },
   {
@@ -64,7 +64,7 @@
     "from langchain.llms import OpenAI\n",
     "from langchain.memory import ConversationBufferWindowMemory\n",
     "\n",
-    "from langchain.llms import PromptGuardLLMWrapper\n",
+    "from langchain.llms import PromptGuard\n",
     "\n",
     "langchain.verbose = True\n",
     "langchain.debug = True\n",
@@ -106,7 +106,7 @@
     "\n",
     "chain = LLMChain(\n",
     "    prompt=PromptTemplate.from_template(prompt_template),\n",
-    "    llm=PromptGuardLLMWrapper(llm=OpenAI()),\n",
+    "    llm=PromptGuard(base_llm=OpenAI()),\n",
     "    memory=ConversationBufferWindowMemory(k=2),\n",
     "    verbose=True,\n",
     ")\n",
diff --git a/libs/langchain/langchain/llms/promptguard.py b/libs/langchain/langchain/llms/promptguard.py
index a6e85974657..9f99ff40193 100644
--- a/libs/langchain/langchain/llms/promptguard.py
+++ b/libs/langchain/langchain/llms/promptguard.py
@@ -23,10 +23,10 @@ class PromptGuard(LLM):
     Example:
         .. code-block:: python
 
-            from langchain.llms import PromptGuardLLM
+            from langchain.llms import PromptGuard
             from langchain.chat_models import ChatOpenAI
 
-            prompt_guard_llm = PromptGuardLLM(base_llm=ChatOpenAI())
+            prompt_guard_llm = PromptGuard(base_llm=ChatOpenAI())
     """
 
     base_llm: BaseLanguageModel