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[langchain-deepseek]: reasoning_content is not streamed when response_format=json_object (aggregated into a single chunk)

langchain-ai/langchain#39601·146784·Python·35 天未动·4 条评论·上游最近活跃 ·池内状态:可认领
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上游 issue 正文

### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x] This is not related to the langchain-community package. - [x] I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS. ### Package (Required) - [ ] langchain - [x] langchain-openai - [ ] langchain-anthropic - [ ] langchain-classic - [ ] langchain-core - [ ] langchain-model-profiles - [ ] langchain-tests - [ ] langchain-text-splitters - [ ] langchain-chroma - [x] langchain-deepseek - [ ] langchain-exa - [ ] langchain-fireworks - [ ] langchain-groq - [ ] langchain-huggingface - [ ] langchain-mistralai - [ ] langchain-nomic - [ ] langchain-ollama - [ ] langchain-openrouter - [ ] langchain-perplexity - [ ] langchain-qdrant - [ ] langchain-xai - [ ] Other / not sure / general ### Related Issues / PRs #34328 (tracking: reasoning_content compatibility across providers) #35516 (closed as duplicate of #34328) ### Reproduction Steps / Example Code (Python) ```python from langchain_core.messages import HumanMessage, SystemMessage from langchain_deepseek import ChatDeepSeek llm = ChatDeepSeek( model="deepseek-v4-flash", temperature=0, max_tokens=50000, extra_body={"thinking": {"type": "enabled"}}, reasoning_effort="high", ) llm = llm.bind(response_format={"type": "json_object"}) reasoning_chunks = 0 async for chunk in llm.astream( [SystemMessage(content="..."), HumanMessage(content="...")] ): rk = chunk.additional_kwargs.get("reasoning_content", "") if rk: reasoning_chunks += 1 print(reasoning_chunks) # → 1 (aggregated) ``` ### Error Message and Stack Trace (if applicable) ```shell ``` …
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