mirror of
https://github.com/hwchase17/langchain.git
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openai[patch]: default to invoke on o1 stream() (#27983)
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@@ -632,24 +632,6 @@ class BaseChatOpenAI(BaseChatModel):
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default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
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base_generation_info = {}
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if "response_format" in payload and is_basemodel_subclass(
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payload["response_format"]
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):
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# TODO: Add support for streaming with Pydantic response_format.
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warnings.warn("Streaming with Pydantic response_format not yet supported.")
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chat_result = self._generate(
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messages, stop, run_manager=run_manager, **kwargs
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)
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msg = chat_result.generations[0].message
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yield ChatGenerationChunk(
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message=AIMessageChunk(
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**msg.dict(exclude={"type", "additional_kwargs"}),
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# preserve the "parsed" Pydantic object without converting to dict
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additional_kwargs=msg.additional_kwargs,
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),
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generation_info=chat_result.generations[0].generation_info,
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)
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return
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if self.include_response_headers:
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raw_response = self.client.with_raw_response.create(**payload)
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response = raw_response.parse()
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@@ -783,24 +765,6 @@ class BaseChatOpenAI(BaseChatModel):
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payload = self._get_request_payload(messages, stop=stop, **kwargs)
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default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
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base_generation_info = {}
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if "response_format" in payload and is_basemodel_subclass(
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payload["response_format"]
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):
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# TODO: Add support for streaming with Pydantic response_format.
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warnings.warn("Streaming with Pydantic response_format not yet supported.")
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chat_result = await self._agenerate(
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messages, stop, run_manager=run_manager, **kwargs
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)
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msg = chat_result.generations[0].message
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yield ChatGenerationChunk(
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message=AIMessageChunk(
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**msg.dict(exclude={"type", "additional_kwargs"}),
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# preserve the "parsed" Pydantic object without converting to dict
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additional_kwargs=msg.additional_kwargs,
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),
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generation_info=chat_result.generations[0].generation_info,
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)
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return
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if self.include_response_headers:
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raw_response = await self.async_client.with_raw_response.create(**payload)
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response = raw_response.parse()
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@@ -999,6 +963,28 @@ class BaseChatOpenAI(BaseChatModel):
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num_tokens += 3
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return num_tokens
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def _should_stream(
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self,
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*,
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async_api: bool,
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run_manager: Optional[
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Union[CallbackManagerForLLMRun, AsyncCallbackManagerForLLMRun]
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] = None,
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response_format: Optional[Union[dict, type]] = None,
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**kwargs: Any,
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) -> bool:
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if isinstance(response_format, type) and is_basemodel_subclass(response_format):
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# TODO: Add support for streaming with Pydantic response_format.
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warnings.warn("Streaming with Pydantic response_format not yet supported.")
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return False
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if self.model_name.startswith("o1"):
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# TODO: Add support for streaming with o1 once supported.
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return False
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return super()._should_stream(
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async_api=async_api, run_manager=run_manager, **kwargs
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)
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@deprecated(
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since="0.2.1",
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alternative="langchain_openai.chat_models.base.ChatOpenAI.bind_tools",
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