mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
385 lines
14 KiB
Python
385 lines
14 KiB
Python
"""Loader that uses unstructured to load files."""
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import collections
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from abc import ABC, abstractmethod
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from typing import IO, Any, Callable, Dict, Iterator, List, Optional, Sequence, Union
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseLoader
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def satisfies_min_unstructured_version(min_version: str) -> bool:
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"""Check if the installed `Unstructured` version exceeds the minimum version
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for the feature in question."""
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from unstructured.__version__ import __version__ as __unstructured_version__
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min_version_tuple = tuple([int(x) for x in min_version.split(".")])
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# NOTE(MthwRobinson) - enables the loader to work when you're using pre-release
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# versions of unstructured like 0.4.17-dev1
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_unstructured_version = __unstructured_version__.split("-")[0]
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unstructured_version_tuple = tuple(
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[int(x) for x in _unstructured_version.split(".")]
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)
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return unstructured_version_tuple >= min_version_tuple
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def validate_unstructured_version(min_unstructured_version: str) -> None:
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"""Raise an error if the `Unstructured` version does not exceed the
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specified minimum."""
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if not satisfies_min_unstructured_version(min_unstructured_version):
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raise ValueError(
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f"unstructured>={min_unstructured_version} is required in this loader."
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)
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class UnstructuredBaseLoader(BaseLoader, ABC):
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"""Base Loader that uses `Unstructured`."""
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def __init__(
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self,
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mode: str = "single",
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post_processors: Optional[List[Callable]] = None,
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**unstructured_kwargs: Any,
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):
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"""Initialize with file path."""
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try:
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import unstructured # noqa:F401
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except ImportError:
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raise ValueError(
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"unstructured package not found, please install it with "
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"`pip install unstructured`"
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)
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_valid_modes = {"single", "elements", "paged"}
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if mode not in _valid_modes:
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raise ValueError(
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f"Got {mode} for `mode`, but should be one of `{_valid_modes}`"
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)
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self.mode = mode
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if not satisfies_min_unstructured_version("0.5.4"):
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if "strategy" in unstructured_kwargs:
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unstructured_kwargs.pop("strategy")
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self.unstructured_kwargs = unstructured_kwargs
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self.post_processors = post_processors or []
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@abstractmethod
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def _get_elements(self) -> List:
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"""Get elements."""
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@abstractmethod
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def _get_metadata(self) -> dict:
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"""Get metadata."""
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def _post_process_elements(self, elements: list) -> list:
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"""Applies post processing functions to extracted unstructured elements.
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Post processing functions are str -> str callables are passed
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in using the post_processors kwarg when the loader is instantiated."""
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for element in elements:
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for post_processor in self.post_processors:
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element.apply(post_processor)
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return elements
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def lazy_load(self) -> Iterator[Document]:
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"""Load file."""
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elements = self._get_elements()
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self._post_process_elements(elements)
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if self.mode == "elements":
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for element in elements:
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metadata = self._get_metadata()
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# NOTE(MthwRobinson) - the attribute check is for backward compatibility
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# with unstructured<0.4.9. The metadata attributed was added in 0.4.9.
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if hasattr(element, "metadata"):
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metadata.update(element.metadata.to_dict())
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if hasattr(element, "category"):
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metadata["category"] = element.category
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yield Document(page_content=str(element), metadata=metadata)
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elif self.mode == "paged":
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text_dict: Dict[int, str] = {}
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meta_dict: Dict[int, Dict] = {}
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for idx, element in enumerate(elements):
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metadata = self._get_metadata()
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if hasattr(element, "metadata"):
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metadata.update(element.metadata.to_dict())
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page_number = metadata.get("page_number", 1)
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# Check if this page_number already exists in docs_dict
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if page_number not in text_dict:
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# If not, create new entry with initial text and metadata
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text_dict[page_number] = str(element) + "\n\n"
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meta_dict[page_number] = metadata
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else:
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# If exists, append to text and update the metadata
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text_dict[page_number] += str(element) + "\n\n"
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meta_dict[page_number].update(metadata)
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# Convert the dict to a list of Document objects
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for key in text_dict.keys():
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yield Document(page_content=text_dict[key], metadata=meta_dict[key])
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elif self.mode == "single":
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metadata = self._get_metadata()
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text = "\n\n".join([str(el) for el in elements])
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yield Document(page_content=text, metadata=metadata)
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else:
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raise ValueError(f"mode of {self.mode} not supported.")
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class UnstructuredFileLoader(UnstructuredBaseLoader):
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"""Load files using `Unstructured`.
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The file loader uses the
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unstructured partition function and will automatically detect the file
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type. 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 UnstructuredFileLoader
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loader = UnstructuredFileLoader(
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"example.pdf", 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
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"""
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def __init__(
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self,
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file_path: Union[str, List[str]],
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mode: str = "single",
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**unstructured_kwargs: Any,
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):
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"""Initialize with file path."""
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self.file_path = file_path
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super().__init__(mode=mode, **unstructured_kwargs)
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def _get_elements(self) -> List:
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from unstructured.partition.auto import partition
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if isinstance(self.file_path, list):
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elements = []
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for file in self.file_path:
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elements.extend(partition(filename=file, **self.unstructured_kwargs))
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return elements
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else:
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return partition(filename=self.file_path, **self.unstructured_kwargs)
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def _get_metadata(self) -> dict:
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return {"source": self.file_path}
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def get_elements_from_api(
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file_path: Union[str, List[str], None] = None,
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file: Union[IO, Sequence[IO], None] = None,
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api_url: str = "https://api.unstructured.io/general/v0/general",
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api_key: str = "",
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**unstructured_kwargs: Any,
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) -> List:
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"""Retrieve a list of elements from the `Unstructured API`."""
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if isinstance(file, collections.abc.Sequence) or isinstance(file_path, list):
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from unstructured.partition.api import partition_multiple_via_api
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_doc_elements = partition_multiple_via_api(
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filenames=file_path,
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files=file,
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api_key=api_key,
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api_url=api_url,
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**unstructured_kwargs,
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)
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elements = []
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for _elements in _doc_elements:
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elements.extend(_elements)
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return elements
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else:
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from unstructured.partition.api import partition_via_api
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return partition_via_api(
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filename=file_path,
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file=file,
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api_key=api_key,
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api_url=api_url,
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**unstructured_kwargs,
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)
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class UnstructuredAPIFileLoader(UnstructuredFileLoader):
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"""Load files using `Unstructured` API.
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By default, the loader makes a call to the hosted Unstructured API.
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If you are running the unstructured API locally, you can change the
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API rule by passing in the url parameter when you initialize the loader.
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The hosted Unstructured API requires an API key. See
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https://www.unstructured.io/api-key/ if you need to generate a key.
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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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```python
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from langchain_community.document_loaders import UnstructuredAPIFileLoader
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loader = UnstructuredFileAPILoader(
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"example.pdf", mode="elements", strategy="fast", api_key="MY_API_KEY",
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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
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https://www.unstructured.io/api-key/
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https://github.com/Unstructured-IO/unstructured-api
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"""
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def __init__(
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self,
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file_path: Union[str, List[str]] = "",
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mode: str = "single",
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url: str = "https://api.unstructured.io/general/v0/general",
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api_key: str = "",
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**unstructured_kwargs: Any,
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):
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"""Initialize with file path."""
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validate_unstructured_version(min_unstructured_version="0.10.15")
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self.url = url
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self.api_key = api_key
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super().__init__(file_path=file_path, mode=mode, **unstructured_kwargs)
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def _get_metadata(self) -> dict:
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return {"source": self.file_path}
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def _get_elements(self) -> List:
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return get_elements_from_api(
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file_path=self.file_path,
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api_key=self.api_key,
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api_url=self.url,
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**self.unstructured_kwargs,
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)
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class UnstructuredFileIOLoader(UnstructuredBaseLoader):
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"""Load files using `Unstructured`.
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The file loader
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uses the unstructured partition function and will automatically detect the file
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type. 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 UnstructuredFileIOLoader
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with open("example.pdf", "rb") as f:
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loader = UnstructuredFileIOLoader(
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f, 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
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"""
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def __init__(
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self,
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file: Union[IO, Sequence[IO]],
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mode: str = "single",
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**unstructured_kwargs: Any,
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):
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"""Initialize with file path."""
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self.file = file
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super().__init__(mode=mode, **unstructured_kwargs)
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def _get_elements(self) -> List:
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from unstructured.partition.auto import partition
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return partition(file=self.file, **self.unstructured_kwargs)
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def _get_metadata(self) -> dict:
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return {}
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class UnstructuredAPIFileIOLoader(UnstructuredFileIOLoader):
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"""Load files using `Unstructured` API.
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By default, the loader makes a call to the hosted Unstructured API.
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If you are running the unstructured API locally, you can change the
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API rule by passing in the url parameter when you initialize the loader.
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The hosted Unstructured API requires an API key. See
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https://www.unstructured.io/api-key/ if you need to generate a key.
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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 UnstructuredAPIFileLoader
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with open("example.pdf", "rb") as f:
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loader = UnstructuredFileAPILoader(
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f, mode="elements", strategy="fast", api_key="MY_API_KEY",
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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
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https://www.unstructured.io/api-key/
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https://github.com/Unstructured-IO/unstructured-api
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"""
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def __init__(
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self,
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file: Union[IO, Sequence[IO]],
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mode: str = "single",
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url: str = "https://api.unstructured.io/general/v0/general",
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api_key: str = "",
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**unstructured_kwargs: Any,
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):
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"""Initialize with file path."""
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if isinstance(file, collections.abc.Sequence):
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validate_unstructured_version(min_unstructured_version="0.6.3")
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if file:
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validate_unstructured_version(min_unstructured_version="0.6.2")
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self.url = url
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self.api_key = api_key
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super().__init__(file=file, mode=mode, **unstructured_kwargs)
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def _get_elements(self) -> List:
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return get_elements_from_api(
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file=self.file,
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api_key=self.api_key,
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api_url=self.url,
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**self.unstructured_kwargs,
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)
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