diff --git a/libs/langchain/langchain/adapters/openai.py b/libs/langchain/langchain/adapters/openai.py
index 5d8ffb7f2dba32b..0af759ebf5b0871 100644
--- a/libs/langchain/langchain/adapters/openai.py
+++ b/libs/langchain/langchain/adapters/openai.py
@@ -11,11 +11,8 @@
     Sequence,
     Union,
     overload,
-    Optional,
 )
 
-from typing_extensions import Literal
-from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.chat_sessions import ChatSession
 from langchain_core.messages import (
     AIMessage,
@@ -28,6 +25,8 @@
     SystemMessage,
     ToolMessage,
 )
+from langchain_core.pydantic_v1 import BaseModel
+from typing_extensions import Literal
 
 
 async def aenumerate(
@@ -40,6 +39,29 @@ async def aenumerate(
         i += 1
 
 
+class IndexableBaseModel(BaseModel):
+    """Allows a BaseModel to return its fields by string variable indexing"""
+
+    def __getitem__(self, item: str) -> Any:
+        return getattr(self, item)
+
+
+class Choice(IndexableBaseModel):
+    message: dict
+
+
+class ChatCompletions(IndexableBaseModel):
+    choices: List[Choice]
+
+
+class ChoiceChunk(IndexableBaseModel):
+    delta: dict
+
+
+class ChatCompletionChunk(IndexableBaseModel):
+    choices: List[ChoiceChunk]
+
+
 def convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
     """Convert a dictionary to a LangChain message.
 
@@ -131,7 +153,7 @@ def convert_openai_messages(messages: Sequence[Dict[str, Any]]) -> List[BaseMess
     return [convert_dict_to_message(m) for m in messages]
 
 
-def _convert_message_chunk_to_delta(chunk: BaseMessageChunk, i: int) -> Dict[str, Any]:
+def _convert_message_chunk(chunk: BaseMessageChunk, i: int) -> dict:
     _dict: Dict[str, Any] = {}
     if isinstance(chunk, AIMessageChunk):
         if i == 0:
@@ -150,6 +172,11 @@ def _convert_message_chunk_to_delta(chunk: BaseMessageChunk, i: int) -> Dict[str
     # This only happens at the end of streams, and OpenAI returns as empty dict
     if _dict == {"content": ""}:
         _dict = {}
+    return _dict
+
+
+def _convert_message_chunk_to_delta(chunk: BaseMessageChunk, i: int) -> Dict[str, Any]:
+    _dict = _convert_message_chunk(chunk, i)
     return {"choices": [{"delta": _dict}]}
 
 
@@ -266,15 +293,6 @@ def convert_messages_for_finetuning(
     ]
 
 
-
-class Choice(BaseModel):
-    message: dict
-
-
-class ChatCompletions(BaseModel):
-    choices: List[Choice]
-
-
 class Completions:
     """Completion."""
 
@@ -314,10 +332,14 @@ def create(
         converted_messages = convert_openai_messages(messages)
         if not stream:
             result = model_config.invoke(converted_messages)
-            return ChatCompletions(choices=[Choice(message=convert_message_to_dict(result))])
+            return ChatCompletions(
+                choices=[Choice(message=convert_message_to_dict(result))]
+            )
         else:
             return (
-                _convert_message_chunk_to_delta(c, i)
+                ChatCompletionChunk(
+                    choices=[ChoiceChunk(delta=_convert_message_chunk(c, i))]
+                )
                 for i, c in enumerate(model_config.stream(converted_messages))
             )
 
@@ -357,16 +379,21 @@ async def acreate(
         converted_messages = convert_openai_messages(messages)
         if not stream:
             result = await model_config.ainvoke(converted_messages)
-            return ChatCompletions(choices=[Choice(message=convert_message_to_dict(result))])
+            return ChatCompletions(
+                choices=[Choice(message=convert_message_to_dict(result))]
+            )
         else:
             return (
-                _convert_message_chunk_to_delta(c, i)
+                ChatCompletionChunk(
+                    choices=[ChoiceChunk(delta=_convert_message_chunk(c, i))]
+                )
                 async for i, c in aenumerate(model_config.astream(converted_messages))
             )
 
+
 class Chat:
     def __init__(self) -> None:
         self.completions = Completions()
 
 
-chat = Chat()
\ No newline at end of file
+chat = Chat()