langchain.llms.baseten.Baseten¶
class langchain.llms.baseten.Baseten[source]¶
Bases: LLM
Baseten models.
To use, you should have the baseten python package installed,
and run baseten.login() with your Baseten API key.
The required model param can be either a model id or model
version id. Using a model version ID will result in
slightly faster invocation.
Any other model parameters can also
be passed in with the format input={model_param: value, …}
The Baseten model must accept a dictionary of input with the key
“prompt” and return a dictionary with a key “data” which maps
to a list of response strings.
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 cache: Optional[bool] = None¶
param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param input: Dict[str, Any] [Optional]¶
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model: str [Required]¶
param model_kwargs: Dict[str, Any] [Optional]¶
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param verbose: bool [Optional]¶
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶