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langchain/libs/community/langchain_community/document_loaders/rst.py

58 lines
1.9 KiB
Python

"""Loads RST files."""
from pathlib import Path
from typing import Any, List, Union
from langchain_community.document_loaders.unstructured import (
UnstructuredFileLoader,
validate_unstructured_version,
)
class UnstructuredRSTLoader(UnstructuredFileLoader):
"""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
"""
def __init__(
self,
file_path: Union[str, Path],
mode: str = "single",
**unstructured_kwargs: Any,
):
"""
Initialize with a file path.
Args:
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.
"""
validate_unstructured_version(min_unstructured_version="0.7.5")
super().__init__(file_path=file_path, mode=mode, **unstructured_kwargs)
def _get_elements(self) -> List:
from unstructured.partition.rst import partition_rst
return partition_rst(filename=self.file_path, **self.unstructured_kwargs)