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Partially Revert "openai[patch]: Update openai chat model to new base class interface" #19871

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merged 3 commits into from
Apr 1, 2024
Merged

Partially Revert "openai[patch]: Update openai chat model to new base class interface" #19871

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e276170
Revert "openai[patch]: Update openai chat model to new base class int…
nfcampos Apr 1, 2024
606f95e
Fix
nfcampos Apr 1, 2024
3a94946
Merge branch 'master' into revert-19729-nc/28mar/openai-chat-update
efriis Apr 1, 2024
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31 changes: 28 additions & 3 deletions libs/partners/openai/langchain_openai/chat_models/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,11 @@
CallbackManagerForLLMRun,
)
from langchain_core.language_models import LanguageModelInput
from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.language_models.chat_models import (
BaseChatModel,
agenerate_from_stream,
generate_from_stream,
)
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
Expand Down Expand Up @@ -474,19 +478,28 @@ def _stream(
chunk = ChatGenerationChunk(
message=chunk, generation_info=generation_info or None
)
if run_manager:
run_manager.on_llm_new_token(chunk.text, chunk=chunk, logprobs=logprobs)
yield chunk

def _generate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
stream: Optional[bool] = None,
**kwargs: Any,
) -> ChatResult:
should_stream = stream if stream is not None else self.streaming
if should_stream:
stream_iter = self._stream(
messages, stop=stop, run_manager=run_manager, **kwargs
)
return generate_from_stream(stream_iter)
message_dicts, params = self._create_message_dicts(messages, stop)
params = {
**params,
**({"stream": self.streaming} if self.streaming else {}),
**({"stream": stream} if stream is not None else {}),
**kwargs,
}
response = self.client.create(messages=message_dicts, **params)
Expand Down Expand Up @@ -569,19 +582,31 @@ async def _astream(
chunk = ChatGenerationChunk(
message=chunk, generation_info=generation_info or None
)
if run_manager:
await run_manager.on_llm_new_token(
token=chunk.text, chunk=chunk, logprobs=logprobs
)
yield chunk

async def _agenerate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
stream: Optional[bool] = None,
**kwargs: Any,
) -> ChatResult:
should_stream = stream if stream is not None else self.streaming
if should_stream:
stream_iter = self._astream(
messages, stop=stop, run_manager=run_manager, **kwargs
)
return await agenerate_from_stream(stream_iter)

message_dicts, params = self._create_message_dicts(messages, stop)
params = {
**params,
**({"stream": self.streaming} if self.streaming else {}),
**({"stream": stream} if stream is not None else {}),
**kwargs,
}
response = await self.async_client.create(messages=message_dicts, **params)
Expand Down