langchain - 💡(How to fix) Fix langchain-deepseek: Missing reasoning_content passback in _get_request_payload causes 400 error on multi-turn agent calls [2 comments, 2 participants]

openai.BadRequestError: Error code: 400
{'error': {'message': 'The `reasoning_content` in the thinking mode must be passed back to the API.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_request_error'}}

---

Traceback (most recent call last):
  File "test_agent.py", line 17, in <module>
    res = agent.invoke({"messages": [{"role": "user", "content": "..."}]})
  File ".../langgraph/pregel/main.py", line 3365, in invoke
    for chunk in self.stream(...)
  ...
  File ".../langchain_deepseek/chat_models.py", line 356, in _generate
    return super()._generate(...)
  File ".../langchain_openai/chat_models/base.py", line 1653, in _generate
    _handle_openai_bad_request(e)
openai.BadRequestError: Error code: 400 - {'error': {'message': 'The `reasoning_content` in the thinking mode must be passed back to the API.'}}

---

from langchain.agents import create_agent
from langchain_core.tools import tool
from langchain.chat_models import init_chat_model

@tool(description="query weather")
def get_weather() -> str:
    return "sunny"

model = init_chat_model(model="deepseek-v4-flash")

agent = create_agent(
    model=model,
    tools=[get_weather],
    system_prompt="You are a helpful assistant.",
)

res = agent.invoke({
    "messages": [
        {"role": "user", "content": "What is the weather tomorrow?"},
    ]
})

for msg in res["messages"]:
    print(type(msg).__name__, msg.content)

---

def _get_request_payload(
    self,
    input_: LanguageModelInput,
    *,
    stop: list[str] | None = None,
    **kwargs: Any,
) -> dict:
    payload = super()._get_request_payload(input_, stop=stop, **kwargs)

    # Get original messages to preserve reasoning_content from assistant messages.
    # DeepSeek requires reasoning_content from previous responses to be passed
    # back in subsequent requests, but _convert_message_to_dict drops it.
    messages = self._convert_input(input_).to_messages()

    for i, message in enumerate(payload["messages"]):
        if message["role"] == "assistant":
            if isinstance(message.get("content"), list):
                text_parts = [
                    block.get("text", "")
                    for block in message["content"]
                    if isinstance(block, dict) and block.get("type") == "text"
                ]
                message["content"] = "".join(text_parts) if text_parts else ""

            # Pass through reasoning_content from original AIMessage
            if i < len(messages) and isinstance(messages[i], AIMessage):
                reasoning = messages[i].additional_kwargs.get(
                    "reasoning_content"
                )
                if reasoning is not None:
                    message["reasoning_content"] = reasoning

        elif message["role"] == "tool" and isinstance(message["content"], list):
            message["content"] = json.dumps(message["content"])
    return payload