mirror of
https://github.com/hwchase17/langchain
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f7a1fd91b8
So this arose from the https://github.com/langchain-ai/langchain/pull/18397 problem of document loaders not supporting `pathlib.Path`. This pull request provides more uniform support for Path as an argument. The core ideas for this upgrade: - if there is a local file path used as an argument, it should be supported as `pathlib.Path` - if there are some external calls that may or may not support Pathlib, the argument is immidiately converted to `str` - if there `self.file_path` is used in a way that it allows for it to stay pathlib without conversion, is is only converted for the metadata. Twitter handle: https://twitter.com/mwmajewsk
65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
import logging
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from pathlib import Path
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from typing import Dict, Iterator, 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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logger = logging.getLogger(__name__)
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class BSHTMLLoader(BaseLoader):
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"""Load `HTML` files and parse them with `beautiful soup`."""
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def __init__(
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self,
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file_path: Union[str, Path],
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open_encoding: Union[str, None] = None,
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bs_kwargs: Union[dict, None] = None,
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get_text_separator: str = "",
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) -> None:
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"""initialize with path, and optionally, file encoding to use, and any kwargs
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to pass to the BeautifulSoup object.
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Args:
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file_path: The path to the file to load.
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open_encoding: The encoding to use when opening the file.
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bs_kwargs: Any kwargs to pass to the BeautifulSoup object.
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get_text_separator: The separator to use when calling get_text on the soup.
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"""
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try:
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import bs4 # noqa:F401
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except ImportError:
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raise ImportError(
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"beautifulsoup4 package not found, please install it with "
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"`pip install beautifulsoup4`"
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)
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self.file_path = file_path
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self.open_encoding = open_encoding
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if bs_kwargs is None:
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bs_kwargs = {"features": "lxml"}
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self.bs_kwargs = bs_kwargs
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self.get_text_separator = get_text_separator
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def lazy_load(self) -> Iterator[Document]:
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"""Load HTML document into document objects."""
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from bs4 import BeautifulSoup
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with open(self.file_path, "r", encoding=self.open_encoding) as f:
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soup = BeautifulSoup(f, **self.bs_kwargs)
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text = soup.get_text(self.get_text_separator)
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if soup.title:
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title = str(soup.title.string)
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else:
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title = ""
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metadata: Dict[str, Union[str, None]] = {
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"source": str(self.file_path),
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"title": title,
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}
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yield Document(page_content=text, metadata=metadata)
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