langchain_community.document_loaders.apify_dataset
.ApifyDatasetLoader¶
- class langchain_community.document_loaders.apify_dataset.ApifyDatasetLoader[source]¶
Bases:
BaseLoader
,BaseModel
Load datasets from Apify web scraping, crawling, and data extraction platform.
For details, see https://docs.apify.com/platform/integrations/langchain
Example
from langchain_community.document_loaders import ApifyDatasetLoader from langchain_core.documents import Document loader = ApifyDatasetLoader( dataset_id="YOUR-DATASET-ID", dataset_mapping_function=lambda dataset_item: Document( page_content=dataset_item["text"], metadata={"source": dataset_item["url"]} ), ) documents = loader.load()
Initialize the loader with an Apify dataset ID and a mapping function.
- Parameters
dataset_id (str) – The ID of the dataset on the Apify platform.
dataset_mapping_function (Callable) – A function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class.
- param apify_client: Any = None¶
An instance of the ApifyClient class from the apify-client Python package.
- param dataset_id: str [Required]¶
The ID of the dataset on the Apify platform.
- param dataset_mapping_function: Callable[[Dict], langchain_core.documents.base.Document] [Required]¶
A custom function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class.
- 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().
- load_and_split(text_splitter: Optional[TextSplitter] = None) List[Document] ¶
Load Documents and split into chunks. Chunks are returned as Documents.
- Parameters
text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.
- Returns
List of Documents.
- 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 ¶