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Harrison/track token usage (#1382)

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Co-authored-by: Zak King <zaking17@gmail.com>
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Harrison Chase 2023-03-01 21:15:13 -08:00 committed by GitHub
parent 1cd8996074
commit e178008b75
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1 changed files with 20 additions and 5 deletions
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25
langchain/llms/openai.py
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@ -23,7 +23,7 @@ from tenacity import (
wait_exponential, wait_exponential,
) )
from langchain.llms.base import LLM, BaseLLM from langchain.llms.base import BaseLLM
from langchain.schema import Generation, LLMResult from langchain.schema import Generation, LLMResult
from langchain.utils import get_from_dict_or_env from langchain.utils import get_from_dict_or_env
@ -515,7 +515,7 @@ class AzureOpenAI(BaseOpenAI):
return {**{"engine": self.deployment_name}, **super()._invocation_params} return {**{"engine": self.deployment_name}, **super()._invocation_params}
class OpenAIChat(LLM, BaseModel): class OpenAIChat(BaseLLM, BaseModel):
"""Wrapper around OpenAI Chat large language models. """Wrapper around OpenAI Chat large language models.
To use, you should have the ``openai`` python package installed, and the To use, you should have the ``openai`` python package installed, and the
@ -621,15 +621,30 @@ class OpenAIChat(LLM, BaseModel):
return _completion_with_retry(**kwargs) return _completion_with_retry(**kwargs)
def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str: def _generate(
messages = self.prefix_messages + [{"role": "user", "content": prompt}] self, prompts: List[str], stop: Optional[List[str]] = None
) -> LLMResult:
if len(prompts) > 1:
raise ValueError(f"OpenAIChat only supports single prompts, got {prompts}")
messages = self.prefix_messages + [{"role": "user", "content": prompts[0]}]
params: Dict[str, Any] = {**{"model": self.model_name}, **self._default_params} params: Dict[str, Any] = {**{"model": self.model_name}, **self._default_params}
if stop is not None: if stop is not None:
if "stop" in params: if "stop" in params:
raise ValueError("`stop` found in both the input and default params.") raise ValueError("`stop` found in both the input and default params.")
params["stop"] = stop params["stop"] = stop
response = self.completion_with_retry(messages=messages, **params) response = self.completion_with_retry(messages=messages, **params)
return response["choices"][0]["message"]["content"] return LLMResult(
generations=[
[Generation(text=response["choices"][0]["message"]["content"])]
],
llm_output={"token_usage": response["usage"]},
)
async def _agenerate(
self, prompts: List[str], stop: Optional[List[str]] = None
) -> LLMResult:
"""Run the LLM on the given prompt and input."""
raise NotImplementedError("Async generation not implemented for this LLM.")
@property @property
def _identifying_params(self) -> Mapping[str, Any]: def _identifying_params(self) -> Mapping[str, Any]: