Reasoning model with structured output

Checked other resources

• This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
• I added a clear and detailed title that summarizes the issue.
• I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
• I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.

Example Code

def get_ChatOpenAI(
        model=settings.MODEL_NAME,
        base_url=settings.BASE_URL,
        api_key=settings.API_KEY
):
    llm = BaseChatOpenAI(
        model=model,
        base_url=base_url,
        api_key=api_key,
    )
    return llm
class Section(BaseModel):
    name: dict = Field(
        description="Name of the analyzed corporate strategic focus e.g.: {'战略点名称': '智能流程自动化'}"
    )
    information: dict = Field(
        description="description of the analyzed corporate strategic focus e.g.: {'战略点说明': '在金融或医疗领域，通过大数据风控模'}"
    )


class AnalysisResult(BaseModel):

    result: List[Section] = Field(
        description="All of Name and description and all plan of the analyzed corporate strategic focus"
    )
analysis_chain = system_prompt | get_ChatOpenAI().with_structured_output(AnalysisResult)
result = analysis_chain.invoke()

Error Message and Stack Trace (if applicable)

File "E:\大模型\PyCharm 2023.1.2\plugins\python\helpers\pydev\pydevd.py", line 1496, in _exec
    pydev_imports.execfile(file, globals, locals)  # execute the script
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\大模型\PyCharm 2023.1.2\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "E:\strategy_analysis\analysis_graph\analysis_node.py", line 267, in <module>
    result = asyncio.run(graph.ainvoke(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\asyncio\runners.py", line 195, in run
    return runner.run(main)
           ^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\asyncio\runners.py", line 118, in run
    return self._loop.run_until_complete(task)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\asyncio\base_events.py", line 691, in run_until_complete
    return future.result()
           ^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\pregel\__init__.py", line 2920, in ainvoke
    async for chunk in self.astream(
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\pregel\__init__.py", line 2768, in astream
    async for _ in runner.atick(
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\pregel\runner.py", line 401, in atick
    _panic_or_proceed(
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\pregel\runner.py", line 511, in _panic_or_proceed
    raise exc
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\pregel\retry.py", line 137, in arun_with_retry
    return await task.proc.ainvoke(task.input, config)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\utils\runnable.py", line 672, in ainvoke
    input = await asyncio.create_task(
            ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langgraph\utils\runnable.py", line 440, in ainvoke
    ret = await self.afunc(*args, **kwargs)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\strategy_analysis\analysis_graph\analysis_node.py", line 159, in OverAllAnalysis
    result = await analysis_chain.ainvoke(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\runnables\base.py", line 3088, in ainvoke
    input_ = await coro_with_context(part(), context, create_task=True)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\output_parsers\base.py", line 219, in ainvoke
    return await self._acall_with_config(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\runnables\base.py", line 1990, in _acall_with_config
    output: Output = await coro_with_context(coro, context)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\output_parsers\base.py", line 280, in aparse_result
    return await run_in_executor(None, self.parse_result, result, partial=partial)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\runnables\config.py", line 616, in run_in_executor
    return await asyncio.get_running_loop().run_in_executor(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\concurrent\futures\thread.py", line 59, in run
    result = self.fn(*self.args, **self.kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\runnables\config.py", line 607, in wrapper
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\output_parsers\openai_tools.py", line 289, in parse_result
    json_results = super().parse_result(result, partial=partial)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\output_parsers\openai_tools.py", line 191, in parse_result
    tool_calls = parse_tool_calls(
                 ^^^^^^^^^^^^^^^^^
  File "C:\ProgramData\anaconda3\envs\hr_analysis\Lib\site-packages\langchain_core\output_parsers\openai_tools.py", line 132, in parse_tool_calls
    raise OutputParserException("\n\n".join(exceptions))
langchain_core.exceptions.OutputParserException: Function AnalysisResult arguments:
<think>
</think>
<tool_call>
{"result": [{"name": {"战略点名称": "促销优化"}, "information": {"战略点说明": "在成熟市场中利用促销手段增加现有产品的吸引力，从而从竞争对手手中争取更多用户。"}}, {"name": {"战略点名称": "渠道优化"}, "information": {"战略点说明": "通过优先考虑高转化率销售渠道或者增强线上/线下分布，提高现有产品的可及性以提升市场份额。"}}, {"name": {"战略点名称": "定价策略调整"}, "information": {"战略点说明": "通过优化和微转型定价策略寻找正确的价格点，既吸引用户又保持利润，压制竞争对手。"}}, {"name": {"战略点名称": "客户保留计划"}, "information": {"战略点说明": "制定奖励和忠诚度计划以提高现有客户的留存率，降低竞争对手夺回份额的机会。"}}, {"name": {"战略点名称": "小众细分定位"}, "information": {"战略点说明": "通过对市场细分挖掘，专注于未被满足的特定用户群体，提高这些群体的市场份额占比。"}}, {"name": {"战略点名称": "快速再定位策略"}, "information": {"战略点说明": "迅速调整产品定位以适应市场变化，反弹回弹能力增强，从而扮演市场领导者角色。"}}, {"name": {"战略点名称": "捆绑销售策略"}, "information": {"战略点说明": "通过将现有产品与畅销产品捆绑，提升销售转化率并吸引未使用本产品的消费者。"}}, {"name": {"战略点名称": "品牌强化活动"}, "information": {"战略点说明": "打造更强的品牌辨识度和用户信任，推动消费者选择自身产品而非竞争对手。"}}, {"name": {"战略点名称": "本地化市场策略"}, "information": {"战略点说明": "根据不同本地市场的需求和偏好，定制化产品推广策略以更好地渗透成熟市场。"}}, {"name": {"战略点名称": "竞争差异化定位"}, "information": {"战略点说明": "挖掘自身产品相比竞争对手的独特优点，利用差异化吸引消费者购买。"}}]
}
are not valid JSON. Received JSONDecodeError Expecting value: line 1 column 1 (char 0)
For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE 
For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE 
During task with name 'OverAllAnalysis' and id 'a5207214-d084-e8a3-a07a-2c31bf4dddac'
python-BaseException

Description

How to solve the error of using reasoning model with inferred output? deepseek-r1 have

System Info

python