mirror of
https://github.com/hwchase17/langchain
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60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
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"""Loads rich text files."""
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from typing import Any, List
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from langchain_community.document_loaders.unstructured import (
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UnstructuredFileLoader,
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satisfies_min_unstructured_version,
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)
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class UnstructuredRTFLoader(UnstructuredFileLoader):
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"""Load `RTF` files using `Unstructured`.
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You can run the loader in one of two modes: "single" and "elements".
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If you use "single" mode, the document will be returned as a single
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langchain Document object. If you use "elements" mode, the unstructured
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library will split the document into elements such as Title and NarrativeText.
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You can pass in additional unstructured kwargs after mode to apply
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different unstructured settings.
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Examples
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--------
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from langchain_community.document_loaders import UnstructuredRTFLoader
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loader = UnstructuredRTFLoader(
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"example.rtf", mode="elements", strategy="fast",
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)
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docs = loader.load()
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References
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----------
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https://unstructured-io.github.io/unstructured/bricks.html#partition-rtf
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"""
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def __init__(
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self, file_path: str, mode: str = "single", **unstructured_kwargs: Any
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):
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"""
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Initialize with a file path.
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Args:
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file_path: The path to the file to load.
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mode: The mode to use for partitioning. See unstructured for details.
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Defaults to "single".
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**unstructured_kwargs: Additional keyword arguments to pass
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to unstructured.
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"""
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min_unstructured_version = "0.5.12"
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if not satisfies_min_unstructured_version(min_unstructured_version):
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raise ValueError(
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"Partitioning rtf files is only supported in "
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f"unstructured>={min_unstructured_version}."
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)
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super().__init__(file_path=file_path, mode=mode, **unstructured_kwargs)
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def _get_elements(self) -> List:
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from unstructured.partition.rtf import partition_rtf
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return partition_rtf(filename=self.file_path, **self.unstructured_kwargs)
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