diff --git a/backend/danswer/llm/openai.py b/backend/danswer/llm/openai.py
index 90fce9035..48673aa22 100644
--- a/backend/danswer/llm/openai.py
+++ b/backend/danswer/llm/openai.py
@@ -1,14 +1,26 @@
 from typing import Any
 from typing import cast
 
-from langchain.chat_models.openai import ChatOpenAI
+from langchain.chat_models import ChatLiteLLM
+import litellm  # type:ignore
 
 from danswer.configs.model_configs import GEN_AI_TEMPERATURE
 from danswer.llm.llm import LangChainChatLLM
 from danswer.llm.utils import should_be_verbose
 
 
+# If a user configures a different model and it doesn't support all the same
+# parameters like frequency and presence, just ignore them
+litellm.drop_params=True
+
+
 class OpenAIGPT(LangChainChatLLM):
+
+    DEFAULT_MODEL_PARAMS = {
+        "frequency_penalty": 0,
+        "presence_penalty": 0,
+    }
+
     def __init__(
         self,
         api_key: str,
@@ -19,22 +31,20 @@ class OpenAIGPT(LangChainChatLLM):
         *args: list[Any],
         **kwargs: dict[str, Any]
     ):
-        self._llm = ChatOpenAI(
+        litellm.api_key = api_key
+
+        self._llm = ChatLiteLLM(  # type: ignore
             model=model_version,
-            openai_api_key=api_key,
             # Prefer using None which is the default value, endpoint could be empty string
-            openai_api_base=cast(str, kwargs.get("endpoint")) or None,
+            api_base=cast(str, kwargs.get("endpoint")) or None,
             max_tokens=max_output_tokens,
             temperature=temperature,
             request_timeout=timeout,
-            model_kwargs={
-                "frequency_penalty": 0,
-                "presence_penalty": 0,
-            },
+            model_kwargs=OpenAIGPT.DEFAULT_MODEL_PARAMS,
             verbose=should_be_verbose(),
             max_retries=0,  # retries are handled outside of langchain
         )
 
     @property
-    def llm(self) -> ChatOpenAI:
+    def llm(self) -> ChatLiteLLM:
         return self._llm