langchain_community.llms.anyscale.Anyscale¶
class langchain_community.llms.anyscale.Anyscale[source]¶
Bases: BaseOpenAI
Anyscale large language models.
To use, you should have the environment variable ANYSCALE_API_BASE and
``ANYSCALE_API_KEY``set with your Anyscale Endpoint, or pass it as a named
parameter to the constructor.
Example
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param allowed_special: Union[Literal['all'], AbstractSet[str]] = {}¶
Set of special tokens that are allowed。
param anyscale_api_base: Optional[str] = None¶
param anyscale_api_key: Optional[pydantic.types.SecretStr] = None¶
Constraints
type = string
writeOnly = True
format = password
param batch_size: int = 20¶
Batch size to use when passing multiple documents to generate.
param best_of: int = 1¶
Generates best_of completions server-side and returns the “best”.
param cache: Optional[bool] = None¶
param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param default_headers: Union[Mapping[str, str], None] = None¶
param default_query: Union[Mapping[str, object], None] = None¶
param disallowed_special: Union[Literal['all'], Collection[str]] = 'all'¶
Set of special tokens that are not allowed。
param frequency_penalty: float = 0¶
Penalizes repeated tokens according to frequency.
param http_client: Union[Any, None] = None¶
Optional httpx.Client.
param logit_bias: Optional[Dict[str, float]] [Optional]¶
Adjust the probability of specific tokens being generated.