Commit Graph

5 Commits

Author SHA1 Message Date
nikk0o046
b1c7de98f5
fix(deepseek): convert tool output arrays to strings (#31913)
## Description
When ChatDeepSeek invokes a tool that returns a list, it results in an
openai.UnprocessableEntityError due to a failure in deserializing the
JSON body.

The root of the problem is that ChatDeepSeek uses BaseChatOpenAI
internally, but the APIs are not identical: OpenAI v1/chat/completions
accepts arrays as tool results, but Deepseek API does not.

As a solution added `_get_request_payload` method to ChatDeepSeek, which
inherits the behavior from BaseChatOpenAI but adds a step to stringify
tool message content in case the content is an array. I also add a unit
test for this.

From the linked issue you can find the full reproducible example the
reporter of the issue provided. After the changes it works as expected.

Source: [Deepseek
docs](https://api-docs.deepseek.com/api/create-chat-completion/)


![image](https://github.com/user-attachments/assets/a59ed3e7-6444-46d1-9dcf-97e40e4e8952)

Source: [OpenAI
docs](https://platform.openai.com/docs/api-reference/chat/create)


![image](https://github.com/user-attachments/assets/728f4fc6-e1a3-4897-b39f-6f1ade07d3dc)


## Issue
Fixes #31394

## Dependencies:
No new dependencies.

## Twitter handle:
Don't have one.

---------

Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-07-16 12:19:44 -04:00
Mason Daugherty
231e8d0f43
deepseek[patch]: ruff fixes and rules (#31901)
* bump ruff deps
* add more thorough ruff rules
* fix said rules
2025-07-07 21:54:44 -04:00
Sydney Runkle
8c6734325b
partners[lint]: run pyupgrade to get code in line with 3.9 standards (#30781)
Using `pyupgrade` to get all `partners` code up to 3.9 standards
(mostly, fixing old `typing` imports).
2025-04-11 07:18:44 -04:00
Andras L Ferenczi
b5f49df86a
partner: ChatDeepSeek on openrouter not returning reasoning (#30240)
Deepseek model does not return reasoning when hosted on openrouter
(Issue [30067](https://github.com/langchain-ai/langchain/issues/30067))

the following code did not return reasoning:

```python
llm = ChatDeepSeek( model = 'deepseek/deepseek-r1:nitro', api_base="https://openrouter.ai/api/v1", api_key=os.getenv("OPENROUTER_API_KEY")) 
messages = [
    {"role": "system", "content": "You are an assistant."},
    {"role": "user", "content": "9.11 and 9.8, which is greater? Explain the reasoning behind this decision."}
]
response = llm.invoke(messages, extra_body={"include_reasoning": True})
print(response.content)
print(f"REASONING: {response.additional_kwargs.get('reasoning_content', '')}")
print(response)
```

The fix is to extract reasoning from
response.choices[0].message["model_extra"] and from
choices[0].delta["reasoning"]. and place in response additional_kwargs.
Change is really just the addition of a couple one-sentence if
statements.

---------

Co-authored-by: andrasfe <andrasf94@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
2025-03-21 16:35:37 +00:00
Erick Friis
dced0ed3fd
deepseek, docs: chatdeepseek integration added (#29445) 2025-01-28 06:32:58 +00:00