langchain_community.agent_toolkits.powerbi.toolkit.PowerBIToolkit¶
- class langchain_community.agent_toolkits.powerbi.toolkit.PowerBIToolkit[source]¶
Bases:
BaseToolkitToolkit for interacting with Power BI dataset.
Security Note: This toolkit interacts with an external service.
Control access to who can use this toolkit.
Make sure that the capabilities given by this toolkit to the calling code are appropriately scoped to the application.
See https://python.langchain.com/docs/security for more information.
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 callback_manager: Optional[langchain_core.callbacks.base.BaseCallbackManager] = None¶
- param examples: Optional[str] = None¶
- param llm: Union[langchain_core.language_models.base.BaseLanguageModel, langchain_core.language_models.chat_models.BaseChatModel] [Required]¶
- param max_iterations: int = 5¶
- param output_token_limit: Optional[int] = None¶
- param powerbi: langchain_community.utilities.powerbi.PowerBIDataset [Required]¶
- param tiktoken_model_name: Optional[str] = None¶
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- classmethod from_orm(obj: Any) Model¶
- json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model¶
- classmethod parse_obj(obj: Any) Model¶
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model¶
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny¶
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode¶
- classmethod update_forward_refs(**localns: Any) None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- classmethod validate(value: Any) Model¶