langchain.llms.minimax.Minimax¶
class langchain.llms.minimax.Minimax[source]¶
Bases: MinimaxCommon, LLM
Wrapper around Minimax large language models.
To use, you should have the environment variable
MINIMAX_API_KEY and MINIMAX_GROUP_ID set with your API key,
or pass them as a named parameter to the constructor.
.. rubric:: Example
. code-block:: pythonfrom langchain.llms.minimax import Minimax
minimax = Minimax(model=”<model_name>”, minimax_api_key=”my-api-key”,
minimax_group_id=”my-group-id”)
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 cache: Optional[bool] = None¶
param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param max_tokens: int = 256¶
Denotes the number of tokens to predict per generation.
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param minimax_api_host: Optional[str] = None¶
param minimax_api_key: Optional[str] = None¶
param minimax_group_id: Optional[str] = None¶
param model: str = 'abab5.5-chat'¶
Model name to use.
param model_kwargs: Dict[str, Any] [Optional]¶
Holds any model parameters valid for create call not explicitly specified.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: float = 0.7¶
A non-negative float that tunes the degree of randomness in generation.
param top_p: float = 0.95¶