eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]#
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool#
Return whether or not the class is serializable.
pydantic model langchain.llms.OpenLM[source]#
Validators
build_extra » all fields
raise_deprecation » all fields
set_verbose » verbose
validate_environment » all fields
field allowed_special: Union[Literal['all'], AbstractSet[str]] = {}#
Set of special tokens that are allowed。
field batch_size: int = 20#
Batch size to use when passing multiple documents to generate.
field best_of: int = 1#
Generates best_of completions server-side and returns the “best”.
field disallowed_special: Union[Literal['all'], Collection[str]] = 'all'#
Set of special tokens that are not allowed。
field frequency_penalty: float = 0#
Penalizes repeated tokens according to frequency.
field logit_bias: Optional[Dict[str, float]] [Optional]#
Adjust the probability of specific tokens being generated.
field max_retries: int = 6#
Maximum number of retries to make when generating.
field max_tokens: int = 256#
The maximum number of tokens to generate in the completion.
-1 returns as many tokens as possible given the prompt and
the models maximal context size.
field model_kwargs: Dict[str, Any] [Optional]#
Holds any model parameters valid for create call not explicitly specified.
field model_name: str = 'text-davinci-003' (alias 'model')#
Model name to use.
field n: int = 1#
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html