langchain_community.document_loaders.rst
.UnstructuredRSTLoader¶
- class langchain_community.document_loaders.rst.UnstructuredRSTLoader(file_path: str, mode: str = 'single', **unstructured_kwargs: Any)[source]¶
Load RST files using Unstructured.
You can run the loader in one of two modes: “single” and “elements”. If you use “single” mode, the document will be returned as a single langchain Document object. If you use “elements” mode, the unstructured library will split the document into elements such as Title and NarrativeText. You can pass in additional unstructured kwargs after mode to apply different unstructured settings.
Examples
from langchain_community.document_loaders import UnstructuredRSTLoader
- loader = UnstructuredRSTLoader(
“example.rst”, mode=”elements”, strategy=”fast”,
) docs = loader.load()
References
https://unstructured-io.github.io/unstructured/bricks.html#partition-rst
Initialize with a file path.
- Parameters
file_path – The path to the file to load.
mode – The mode to use for partitioning. See unstructured for details. Defaults to “single”.
**unstructured_kwargs – Additional keyword arguments to pass to unstructured.
Methods
__init__
(file_path[, mode])Initialize with a file path.
A lazy loader for Documents.
load
()Load file.
load_and_split
([text_splitter])Load Documents and split into chunks.
- __init__(file_path: str, mode: str = 'single', **unstructured_kwargs: Any)[source]¶
Initialize with a file path.
- Parameters
file_path – The path to the file to load.
mode – The mode to use for partitioning. See unstructured for details. Defaults to “single”.
**unstructured_kwargs – Additional keyword arguments to pass to unstructured.
- 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.