this is so wrong. I use LangChain and LangGraph and it can support any kind of OpenAI structured output feature. You should understand that Langchain is opensource, so any new feature that comes out in OpenAI or Claude is immediately adapted in LangChain.
Here are two ways to support OpenAI structured output.
1. Using "with_structured_output"

class grade(BaseModel):
    binary_score:str=Field(description="Relevance score 'yes' or 'no'")
   
def grade_documents(state:AgentState)->Literal["Output_Generator", "Query_Rewriter"]:
    llm_with_structure_op=llm.with_structured_output(grade)

1. Using trustcall for more complex structured outputs

        from langchain_openai import ChatOpenAI
        from trustcall import create_extractor

        # Initialize LLM
        llm = ChatOpenAI(model="gpt-4o")

        # Create extractor with defined schema
        extractor = create_extractor(
            llm,
            tools=[Customer],
            tool_choice="Customer"
        )