Source code for langchain.document_loaders.hugging_face_dataset
from typing import Iterator, List, Mapping, Optional, Sequence, Union
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class HuggingFaceDatasetLoader(BaseLoader):
    """Load from `Hugging Face Hub` datasets."""
[docs]    def __init__(
        self,
        path: str,
        page_content_column: str = "text",
        name: Optional[str] = None,
        data_dir: Optional[str] = None,
        data_files: Optional[
            Union[str, Sequence[str], Mapping[str, Union[str, Sequence[str]]]]
        ] = None,
        cache_dir: Optional[str] = None,
        keep_in_memory: Optional[bool] = None,
        save_infos: bool = False,
        use_auth_token: Optional[Union[bool, str]] = None,
        num_proc: Optional[int] = None,
    ):
        """Initialize the HuggingFaceDatasetLoader.
        Args:
            path: Path or name of the dataset.
            page_content_column: Page content column name. Default is "text".
                Note: Currently the function assumes the content is a string.
                If it is not download the dataset using huggingface library and convert
                using the json or pandas loaders.
                https://github.com/langchain-ai/langchain/issues/10674
            name: Name of the dataset configuration.
            data_dir: Data directory of the dataset configuration.
            data_files: Path(s) to source data file(s).
            cache_dir: Directory to read/write data.
            keep_in_memory: Whether to copy the dataset in-memory.
            save_infos: Save the dataset information (checksums/size/splits/...).