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feat: parse reasoning_content from OAI proxies (eg. vLLM / OpenRouter) (#5372)

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* reasonig_content support

* fix

* comment

* fix

* rm comment

---------

Co-authored-by: Charles Packer <packercharles@gmail.com>
This commit is contained in:
Kevin Lin
2025-10-13 15:14:40 -07:00
committed by Caren Thomas
parent fea13051e6
commit 08da1a64bb
2 changed files with 57 additions and 3 deletions
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18
letta/llm_api/openai_client.py
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@@ -649,6 +649,24 @@ class OpenAIClient(LLMClientBase):
# We just need to instantiate the Pydantic model for validation and type safety.
chat_completion_response = ChatCompletionResponse(**response_data)
chat_completion_response = self._fix_truncated_json_response(chat_completion_response)
# Parse reasoning_content from vLLM/OpenRouter/OpenAI proxies that return this field
# This handles cases where the proxy returns .reasoning_content in the response
if (
chat_completion_response.choices
and len(chat_completion_response.choices) > 0
and chat_completion_response.choices[0].message
and not chat_completion_response.choices[0].message.reasoning_content
):
if "choices" in response_data and len(response_data["choices"]) > 0:
choice_data = response_data["choices"][0]
if "message" in choice_data and "reasoning_content" in choice_data["message"]:
reasoning_content = choice_data["message"]["reasoning_content"]
if reasoning_content:
chat_completion_response.choices[0].message.reasoning_content = reasoning_content
chat_completion_response.choices[0].message.reasoning_content_signature = None
# Unpack inner thoughts if they were embedded in function arguments
if llm_config.put_inner_thoughts_in_kwargs:
chat_completion_response = unpack_all_inner_thoughts_from_kwargs(