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openai[patch]: default to invoke on o1 stream() (#27983)

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Bagatur 2024-11-08 19:12:59 -08:00 committed by GitHub
parent 503f2487a5
commit 33dbfba08b
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2 changed files with 46 additions and 36 deletions
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58
libs/partners/openai/langchain_openai/chat_models/base.py
View File

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

24
libs/partners/openai/tests/integration_tests/chat_models/test_base.py
View File

@ -1061,3 +1061,27 @@ def test_prediction_tokens() -> None:
]
assert output_token_details["accepted_prediction_tokens"] > 0
assert output_token_details["rejected_prediction_tokens"] > 0
def test_stream_o1() -> None:
list(ChatOpenAI(model="o1-mini").stream("how are you"))
async def test_astream_o1() -> None:
async for _ in ChatOpenAI(model="o1-mini").astream("how are you"):
pass
class Foo(BaseModel):
response: str
def test_stream_response_format() -> None:
list(ChatOpenAI(model="gpt-4o-mini").stream("how are ya", response_format=Foo))
async def test_astream_response_format() -> None:
async for _ in ChatOpenAI(model="gpt-4o-mini").astream(
"how are ya", response_format=Foo
):
pass