langchain/libs/community/langchain_community/document_loaders/html_bs.py
Ran c3f8733aef
fix: correct spelling mistakes of "seperate, intialise, pre-defined" (#14647)
fix spellings

**seperate -> separate**: found more occurrences, see
https://github.com/langchain-ai/langchain/pull/14602
**initialise -> intialize**: the latter is more common in the repo
**pre-defined > predefined**: adding a comma after a prefix is a
delicate matter, but this is a generally accepted word

also, another word that appears in the repo is "fs" (stands for
filesystem), e.g., in `libs/core/langchain_core/prompts/loading.py`
` """Unified method for loading a prompt from LangChainHub or local
fs."""`
Isn't "filesystem" better?
2023-12-22 11:49:35 -08:00

64 lines
2.0 KiB
Python

import logging
from typing import Dict, List, Union
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
logger = logging.getLogger(__name__)
class BSHTMLLoader(BaseLoader):
"""Load `HTML` files and parse them with `beautiful soup`."""
def __init__(
self,
file_path: str,
open_encoding: Union[str, None] = None,
bs_kwargs: Union[dict, None] = None,
get_text_separator: str = "",
) -> None:
"""initialize with path, and optionally, file encoding to use, and any kwargs
to pass to the BeautifulSoup object.
Args:
file_path: The path to the file to load.
open_encoding: The encoding to use when opening the file.
bs_kwargs: Any kwargs to pass to the BeautifulSoup object.
get_text_separator: The separator to use when calling get_text on the soup.
"""
try:
import bs4 # noqa:F401
except ImportError:
raise ImportError(
"beautifulsoup4 package not found, please install it with "
"`pip install beautifulsoup4`"
)
self.file_path = file_path
self.open_encoding = open_encoding
if bs_kwargs is None:
bs_kwargs = {"features": "lxml"}
self.bs_kwargs = bs_kwargs
self.get_text_separator = get_text_separator
def load(self) -> List[Document]:
"""Load HTML document into document objects."""
from bs4 import BeautifulSoup
with open(self.file_path, "r", encoding=self.open_encoding) as f:
soup = BeautifulSoup(f, **self.bs_kwargs)
text = soup.get_text(self.get_text_separator)
if soup.title:
title = str(soup.title.string)
else:
title = ""
metadata: Dict[str, Union[str, None]] = {
"source": self.file_path,
"title": title,
}
return [Document(page_content=text, metadata=metadata)]