diff --git a/libs/langchain/langchain/chains/openai_functions/base.py b/libs/langchain/langchain/chains/openai_functions/base.py
index 9eb773eae9..db32204143 100644
--- a/libs/langchain/langchain/chains/openai_functions/base.py
+++ b/libs/langchain/langchain/chains/openai_functions/base.py
@@ -192,6 +192,7 @@ def create_openai_fn_chain(
     llm: BaseLanguageModel,
     prompt: BasePromptTemplate,
     *,
+    output_key: str = "function",
     output_parser: Optional[BaseLLMOutputParser] = None,
     **kwargs: Any,
 ) -> LLMChain:
@@ -210,6 +211,7 @@ def create_openai_fn_chain(
             pydantic.BaseModels for arguments.
         llm: Language model to use, assumed to support the OpenAI function-calling API.
         prompt: BasePromptTemplate to pass to the model.
+        output_key: The key to use when returning the output in LLMChain.__call__.
         output_parser: BaseLLMOutputParser to use for parsing model outputs. By default
             will be inferred from the function types. If pydantic.BaseModels are passed
             in, then the OutputParser will try to parse outputs using those. Otherwise
@@ -274,7 +276,7 @@ def create_openai_fn_chain(
         prompt=prompt,
         output_parser=output_parser,
         llm_kwargs=llm_kwargs,
-        output_key="function",
+        output_key=output_key,
         **kwargs,
     )
     return llm_chain
@@ -285,6 +287,7 @@ def create_structured_output_chain(
     llm: BaseLanguageModel,
     prompt: BasePromptTemplate,
     *,
+    output_key: str = "function",
     output_parser: Optional[BaseLLMOutputParser] = None,
     **kwargs: Any,
 ) -> LLMChain:
@@ -297,6 +300,7 @@ def create_structured_output_chain(
             the schema represents and descriptions for the parameters.
         llm: Language model to use, assumed to support the OpenAI function-calling API.
         prompt: BasePromptTemplate to pass to the model.
+        output_key: The key to use when returning the output in LLMChain.__call__.
         output_parser: BaseLLMOutputParser to use for parsing model outputs. By default
             will be inferred from the function types. If pydantic.BaseModels are passed
             in, then the OutputParser will try to parse outputs using those. Otherwise
@@ -354,5 +358,10 @@ def create_structured_output_chain(
             pydantic_schema=_OutputFormatter, attr_name="output"
         )
     return create_openai_fn_chain(
-        [function], llm, prompt, output_parser=output_parser, **kwargs
+        [function],
+        llm,
+        prompt,
+        output_key=output_key,
+        output_parser=output_parser,
+        **kwargs,
     )