Extract text from Diffbot on all the URLs and return Document instances
class langchain.document_loaders.DirectoryLoader(path: str, glob: str = '**/[!.]*', silent_errors: bool = False, load_hidden: bool = False, loader_cls: typing.Union[typing.Type[langchain.document_loaders.unstructured.UnstructuredFileLoader], typing.Type[langchain.document_loaders.text.TextLoader], typing.Type[langchain.document_loaders.html_bs.BSHTMLLoader]] = <class 'langchain.document_loaders.unstructured.UnstructuredFileLoader'>, loader_kwargs: typing.Optional[dict] = None, recursive: bool = False, show_progress: bool = False, use_multithreading: bool = False, max_concurrency: int = 4)[source]#
Loading logic for loading documents from a directory.
load() → List[langchain.schema.Document][source]#
Load documents.
load_file(item: pathlib.Path, path: pathlib.Path, docs: List[langchain.schema.Document], pbar: Optional[Any]) → None[source]#
class langchain.document_loaders.DiscordChatLoader(chat_log: pd.DataFrame, user_id_col: str = 'ID')[source]#
Load Discord chat logs.
load() → List[langchain.schema.Document][source]#
Load all chat messages.
pydantic model langchain.document_loaders.DocugamiLoader[source]#
Loader that loads processed docs from Docugami.
To use, you should have the lxml python package installed.
field access_token: Optional[str] = None#
field api: str = 'https://api.docugami.com/v1preview1'#
field docset_id: Optional[str] = None#
field document_ids: Optional[Sequence[str]] = None#
field file_paths: Optional[Sequence[Union[pathlib.Path, str]]] = None#
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/document_loaders.html