diff --git a/libs/community/langchain_community/chat_models/huggingface.py b/libs/community/langchain_community/chat_models/huggingface.py
index 143aff07172..f459f58e1dd 100644
--- a/libs/community/langchain_community/chat_models/huggingface.py
+++ b/libs/community/langchain_community/chat_models/huggingface.py
@@ -1,6 +1,6 @@
 """Hugging Face Chat Wrapper."""
 
-from typing import Any, List, Optional, Union
+from typing import Any, List, Optional
 
 from langchain_core.callbacks.manager import (
     AsyncCallbackManagerForLLMRun,
@@ -13,11 +13,8 @@ from langchain_core.messages import (
     HumanMessage,
     SystemMessage,
 )
-from langchain_core.outputs import (
-    ChatGeneration,
-    ChatResult,
-    LLMResult,
-)
+from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult
+from langchain_core.pydantic_v1 import root_validator
 
 from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
 from langchain_community.llms.huggingface_hub import HuggingFaceHub
@@ -42,7 +39,9 @@ class ChatHuggingFace(BaseChatModel):
     Adapted from: https://python.langchain.com/docs/integrations/chat/llama2_chat
     """
 
-    llm: Union[HuggingFaceTextGenInference, HuggingFaceEndpoint, HuggingFaceHub]
+    llm: Any
+    """LLM, must be of type HuggingFaceTextGenInference, HuggingFaceEndpoint, or 
+        HuggingFaceHub."""
     system_message: SystemMessage = SystemMessage(content=DEFAULT_SYSTEM_PROMPT)
     tokenizer: Any = None
     model_id: Optional[str] = None
@@ -60,6 +59,18 @@ class ChatHuggingFace(BaseChatModel):
             else self.tokenizer
         )
 
+    @root_validator()
+    def validate_llm(cls, values: dict) -> dict:
+        if not isinstance(
+            values["llm"],
+            (HuggingFaceTextGenInference, HuggingFaceEndpoint, HuggingFaceHub),
+        ):
+            raise TypeError(
+                "Expected llm to be one of HuggingFaceTextGenInference, "
+                f"HuggingFaceEndpoint, HuggingFaceHub, received {type(values['llm'])}"
+            )
+        return values
+
     def _generate(
         self,
         messages: List[BaseMessage],