langchain_community.document_loaders.markdown.UnstructuredMarkdownLoader¶

class langchain_community.document_loaders.markdown.UnstructuredMarkdownLoader(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)[source]¶

Load Markdown 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 UnstructuredMarkdownLoader

loader = UnstructuredMarkdownLoader(

“example.md”, mode=”elements”, strategy=”fast”,

) docs = loader.load()

References

https://unstructured-io.github.io/unstructured/bricks.html#partition-md

Initialize with file path.

Methods

__init__(file_path[, mode])

Initialize with file path.

lazy_load()

A lazy loader for Documents.

load()

Load file.

load_and_split([text_splitter])

Load Documents and split into chunks.
__init__(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)¶

Initialize with file path.

lazy_load() → Iterator[Document]¶

A lazy loader for Documents.

load() → List[Document]¶

Load file.

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.

Examples using UnstructuredMarkdownLoader¶