id stringlengths 14 16 | text stringlengths 4 1.28k | source stringlengths 54 121 |
|---|---|---|
4db1aa5fc4dc-4 | metadata = self._get_metadata()
if hasattr(element, "metadata"):
metadata.update(element.metadata.to_dict())
page_number = metadata.get("page_number", 1)
# Check if this page_number already exists in docs_dict
if page_number not in text... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
4db1aa5fc4dc-5 | ]
elif self.mode == "single":
metadata = self._get_metadata()
text = "\n\n".join([str(el) for el in elements])
docs = [Document(page_content=text, metadata=metadata)]
else:
raise ValueError(f"mode of {self.mode} not supported.")
return docs
[docs]c... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
4db1aa5fc4dc-6 | from unstructured.partition.auto import partition
return partition(filename=self.file_path, **self.unstructured_kwargs)
def _get_metadata(self) -> dict:
return {"source": self.file_path}
def get_elements_from_api(
file_path: Union[str, List[str], None] = None,
file: Union[IO, Sequence[IO], N... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
4db1aa5fc4dc-7 | files=file,
api_key=api_key,
api_url=api_url,
**unstructured_kwargs,
)
elements = []
for _elements in _doc_elements:
elements.extend(_elements)
return elements
else:
from unstructured.partition.api import partition_via_api
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
4db1aa5fc4dc-8 | api_key: str = "",
**unstructured_kwargs: Any,
):
"""Initialize with file path."""
if isinstance(file_path, str):
validate_unstructured_version(min_unstructured_version="0.6.2")
else:
validate_unstructured_version(min_unstructured_version="0.6.3")
self... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
4db1aa5fc4dc-9 | """Loader that uses unstructured to load file IO objects."""
def __init__(
self,
file: Union[IO, Sequence[IO]],
mode: str = "single",
**unstructured_kwargs: Any,
):
"""Initialize with file path."""
self.file = file
super().__init__(mode=mode, **unstructure... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
4db1aa5fc4dc-10 | mode: str = "single",
url: str = "https://api.unstructured.io/general/v0/general",
api_key: str = "",
**unstructured_kwargs: Any,
):
"""Initialize with file path."""
if isinstance(file, collections.abc.Sequence):
validate_unstructured_version(min_unstructured_vers... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
928a54c6e8b6-0 | Source code for langchain.document_loaders.word_document
"""Loader that loads word documents."""
import os
import tempfile
from abc import ABC
from typing import List
from urllib.parse import urlparse
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
928a54c6e8b6-1 | if "~" in self.file_path:
self.file_path = os.path.expanduser(self.file_path)
# If the file is a web path, download it to a temporary file, and use that
if not os.path.isfile(self.file_path) and self._is_valid_url(self.file_path):
r = requests.get(self.file_path)
if r... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
928a54c6e8b6-2 | if hasattr(self, "temp_file"):
self.temp_file.close()
[docs] def load(self) -> List[Document]:
"""Load given path as single page."""
import docx2txt
return [
Document(
page_content=docx2txt.process(self.file_path),
metadata={"source": se... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
928a54c6e8b6-3 | from unstructured.file_utils.filetype import FileType, detect_filetype
unstructured_version = tuple(
[int(x) for x in __unstructured_version__.split(".")]
)
# NOTE(MthwRobinson) - magic will raise an import error if the libmagic
# system dependency isn't installed. If it's no... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
928a54c6e8b6-4 | "Partitioning .doc files is only supported in unstructured>=0.4.11. "
"Please upgrade the unstructured package and try again."
)
if is_doc:
from unstructured.partition.doc import partition_doc
return partition_doc(filename=self.file_path, **self.unstructured_k... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/word_document.html |
45008f3f51cc-0 | Source code for langchain.document_loaders.blockchain
import os
import re
import time
from enum import Enum
from typing import List, Optional
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
class BlockchainType(Enum):
"""Enumerator of the suppo... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
45008f3f51cc-1 | The Loader uses the Alchemy API to interact with the blockchain.
ALCHEMY_API_KEY environment variable must be set to use this loader.
The API returns 100 NFTs per request and can be paginated using the
startToken parameter.
If get_all_tokens is set to True, the loader will get all tokens
on the cont... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
45008f3f51cc-2 | """
def __init__(
self,
contract_address: str,
blockchainType: BlockchainType = BlockchainType.ETH_MAINNET,
api_key: str = "docs-demo",
startToken: str = "",
get_all_tokens: bool = False,
max_execution_time: Optional[int] = None,
):
self.contract_a... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
45008f3f51cc-3 | [docs] def load(self) -> List[Document]:
result = []
current_start_token = self.startToken
start_time = time.time()
while True:
url = (
f"https://{self.blockchainType}.g.alchemy.com/nft/v2/"
f"{self.api_key}/getNFTsForCollection?withMetadata... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
45008f3f51cc-4 | metadata = {
"source": self.contract_address,
"blockchain": self.blockchainType,
"tokenId": tokenId,
}
result.append(Document(page_content=content, metadata=metadata))
# exit after the first API call if get_all_token... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
45008f3f51cc-5 | )
return result
# add one to the tokenId, ensuring the correct tokenId format is used
def _get_next_tokenId(self, tokenId: str) -> str:
value_type = self._detect_value_type(tokenId)
if value_type == "hex_0x":
value_int = int(tokenId, 16)
elif value_type == "hex_0xbf":... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
45008f3f51cc-6 | return "0xbf" + format(result, "0" + str(len(tokenId) - 4) + "x")
else:
return str(result)
# A smart contract can use different formats for the tokenId
@staticmethod
def _detect_value_type(tokenId: str) -> str:
if isinstance(tokenId, int):
return "int"
elif to... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blockchain.html |
e075db98eb6e-0 | Source code for langchain.document_loaders.evernote
"""Load documents from Evernote.
https://gist.github.com/foxmask/7b29c43a161e001ff04afdb2f181e31c
"""
import hashlib
import logging
from base64 import b64decode
from time import strptime
from typing import Any, Dict, Iterator, List, Optional
from langchain.docstore.do... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-1 | of the Document, any non content metadata (e.g. 'author', 'created', 'updated' etc.
but not 'content-raw' or 'resource') tags on the note will be extracted and stored
as metadata on the Document.
Args:
file_path (str): The path to the notebook export with a .enex extension
load_single_docume... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-2 | self.load_single_document = load_single_document
[docs] def load(self) -> List[Document]:
"""Load documents from EverNote export file."""
documents = [
Document(
page_content=note["content"],
metadata={
**{
key: v... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-3 | )
]
@staticmethod
def _parse_content(content: str) -> str:
try:
import html2text
return html2text.html2text(content).strip()
except ImportError as e:
logging.error(
"Could not import `html2text`. Although it is not a required package "
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-4 | # Sometimes elem.text is None
rsc_dict[elem.tag] = b64decode(elem.text) if elem.text else b""
rsc_dict["hash"] = hashlib.md5(rsc_dict[elem.tag]).hexdigest()
else:
rsc_dict[elem.tag] = elem.text
return rsc_dict
@staticmethod
def _parse_note(note... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-5 | # A copy of original content
note_dict["content-raw"] = elem.text
elif elem.tag == "resource":
resources.append(EverNoteLoader._parse_resource(elem))
elif elem.tag == "created" or elem.tag == "updated":
note_dict[elem.tag] = strptime(elem.text, "%Y... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-6 | @staticmethod
def _parse_note_xml(xml_file: str) -> Iterator[Dict[str, Any]]:
"""Parse Evernote xml."""
# Without huge_tree set to True, parser may complain about huge text node
# Try to recover, because there may be " ", which will cause
# "XMLSyntaxError: Entity 'nbsp' not def... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
e075db98eb6e-7 | )
for action, elem in context:
if elem.tag == "note":
yield EverNoteLoader._parse_note(elem) | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
3f5946ba1aa8-0 | Source code for langchain.document_loaders.srt
"""Loader for .srt (subtitle) files."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class SRTLoader(BaseLoader):
"""Loader for .srt (subtitle) files."""
def __init__(self, fil... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/srt.html |
3f5946ba1aa8-1 | text = " ".join([t.text for t in parsed_info])
metadata = {"source": self.file_path}
return [Document(page_content=text, metadata=metadata)] | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/srt.html |
be5efb3be8d7-0 | Source code for langchain.document_loaders.gutenberg
"""Loader that loads .txt web files."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class GutenbergLoader(BaseLoader):
"""Loader that uses urllib to load .txt web files."""
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/gutenberg.html |
be5efb3be8d7-1 | elements = urlopen(self.file_path)
text = "\n\n".join([str(el.decode("utf-8-sig")) for el in elements])
metadata = {"source": self.file_path}
return [Document(page_content=text, metadata=metadata)] | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/gutenberg.html |
c15b07699442-0 | Source code for langchain.document_loaders.sitemap
"""Loader that fetches a sitemap and loads those URLs."""
import itertools
import re
from typing import Any, Callable, Generator, Iterable, List, Optional
from langchain.document_loaders.web_base import WebBaseLoader
from langchain.schema import Document
def _default_p... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
c15b07699442-1 | def __init__(
self,
web_path: str,
filter_urls: Optional[List[str]] = None,
parsing_function: Optional[Callable] = None,
blocksize: Optional[int] = None,
blocknum: int = 0,
meta_function: Optional[Callable] = None,
is_local: bool = False,
):
""... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
c15b07699442-2 | meta_function: Function to parse bs4.Soup output for metadata
remember when setting this method to also copy metadata["loc"]
to metadata["source"] if you are using this field
is_local: whether the sitemap is a local file
"""
if blocksize is not None and blocks... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
c15b07699442-3 | self.meta_function = meta_function or _default_meta_function
self.blocksize = blocksize
self.blocknum = blocknum
self.is_local = is_local
[docs] def parse_sitemap(self, soup: Any) -> List[dict]:
"""Parse sitemap xml and load into a list of dicts."""
els = []
for url in... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
c15b07699442-4 | if (prop := url.find(tag))
}
)
for sitemap in soup.find_all("sitemap"):
loc = sitemap.find("loc")
if not loc:
continue
soup_child = self.scrape_all([loc.text], "xml")[0]
els.extend(self.parse_sitemap(soup_child))
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
c15b07699442-5 | soup = self.scrape("xml")
els = self.parse_sitemap(soup)
if self.blocksize is not None:
elblocks = list(_batch_block(els, self.blocksize))
blockcount = len(elblocks)
if blockcount - 1 < self.blocknum:
raise ValueError(
"Selected sit... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
39fe2db54e03-0 | Source code for langchain.document_loaders.confluence
"""Load Data from a Confluence Space"""
import logging
from enum import Enum
from io import BytesIO
from typing import Any, Callable, Dict, List, Optional, Union
from tenacity import (
before_sleep_log,
retry,
stop_after_attempt,
wait_exponential,
)
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-1 | raise ValueError("unknown content format")
[docs]class ConfluenceLoader(BaseLoader):
"""
Load Confluence pages. Port of https://llamahub.ai/l/confluence
This currently supports username/api_key, Oauth2 login or personal access token
authentication.
Specify a list page_ids and/or space_key to load in... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-2 | raw XML representation for storage. The view format is the HTML representation for
viewing with macros are rendered as though it is viewed by users. You can pass
a enum `content_format` argument to `load()` to specify the content format, this is
set to `ContentFormat.STORAGE` by default.
Hint: space_key... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-3 | :param url: _description_
:type url: str
:param api_key: _description_, defaults to None
:type api_key: str, optional
:param username: _description_, defaults to None
:type username: str, optional
:param oauth2: _description_, defaults to {}
:type oauth2: dict, optional
:param token: _de... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-4 | :type max_retry_seconds: Optional[int], optional
:param confluence_kwargs: additional kwargs to initialize confluence with
:type confluence_kwargs: dict, optional
:raises ValueError: Errors while validating input
:raises ImportError: Required dependencies not installed.
"""
def __init__(
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-5 | errors = ConfluenceLoader.validate_init_args(
url, api_key, username, oauth2, token
)
if errors:
raise ValueError(f"Error(s) while validating input: {errors}")
self.base_url = url
self.number_of_retries = number_of_retries
self.min_retry_seconds = min_retr... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-6 | self.confluence = Confluence(
url=url, token=token, cloud=cloud, **confluence_kwargs
)
else:
self.confluence = Confluence(
url=url,
username=username,
password=api_key,
cloud=cloud,
**confluen... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-7 | if (api_key and not username) or (username and not api_key):
errors.append(
"If one of `api_key` or `username` is provided, "
"the other must be as well."
)
if (api_key or username) and oauth2:
errors.append(
"Cannot provide a v... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-8 | "`['access_token', 'access_token_secret', 'consumer_key', 'key_cert']`"
)
if token and (api_key or username or oauth2):
errors.append(
"Cannot provide a value for `token` and a value for `api_key`, "
"`username` or `oauth2`"
)
if errors... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-9 | limit: Optional[int] = 50,
max_pages: Optional[int] = 1000,
ocr_languages: Optional[str] = None,
) -> List[Document]:
"""
:param space_key: Space key retrieved from a confluence URL, defaults to None
:type space_key: Optional[str], optional
:param page_ids: List of sp... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-10 | defaults to False
:type include_archived_content: bool, optional
:param include_attachments: defaults to False
:type include_attachments: bool, optional
:param include_comments: defaults to False
:type include_comments: bool, optional
:param content_format: Specify conten... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-11 | :raises ValueError: _description_
:raises ImportError: _description_
:return: _description_
:rtype: List[Document]
"""
if not space_key and not page_ids and not label and not cql:
raise ValueError(
"Must specify at least one among `space_key`, `page_id... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-12 | include_attachments,
include_comments,
content_format,
ocr_languages,
)
if label:
pages = self.paginate_request(
self.confluence.get_all_pages_by_label,
label=label,
limit=limit,
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-13 | docs += self.process_pages(
pages,
include_restricted_content,
include_attachments,
include_comments,
content_format,
ocr_languages,
)
if page_ids:
for page_id in page_ids:
get... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-14 | if not include_restricted_content and not self.is_public_page(page):
continue
doc = self.process_page(
page,
include_attachments,
include_comments,
content_format,
ocr_languages,
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-15 | return response.get("results", [])
[docs] def paginate_request(self, retrieval_method: Callable, **kwargs: Any) -> List:
"""Paginate the various methods to retrieve groups of pages.
Unfortunately, due to page size, sometimes the Confluence API
doesn't match the limit value. If `limit` is >10... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-16 | just checking for the presence of a `next` key in the response like this page
would have you do:
https://developer.atlassian.com/server/confluence/pagination-in-the-rest-api/
:param retrieval_method: Function used to retrieve docs
:type retrieval_method: callable
:return: List of... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-17 | ),
before_sleep=before_sleep_log(logger, logging.WARNING),
)(retrieval_method)
batch = get_pages(**kwargs, start=len(docs))
if not batch:
break
docs.extend(batch)
return docs[:max_pages]
[docs] def is_public_page(self, page: dict... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-18 | include_comments: bool,
content_format: ContentFormat,
ocr_languages: Optional[str] = None,
) -> List[Document]:
"""Process a list of pages into a list of documents."""
docs = []
for page in pages:
if not include_restricted_content and not self.is_public_page(page... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-19 | ) -> Document:
try:
from bs4 import BeautifulSoup # type: ignore
except ImportError:
raise ImportError(
"`beautifulsoup4` package not found, please run "
"`pip install beautifulsoup4`"
)
if include_attachments:
atta... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-20 | " ", strip=True
)
for comment in comments
]
text = text + "".join(comment_texts)
return Document(
page_content=text,
metadata={
"title": page["title"],
"id": page["id"],
"source": self... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-21 | # poppler and tesseract
attachments = self.confluence.get_attachments_from_content(page_id)["results"]
texts = []
for attachment in attachments:
media_type = attachment["metadata"]["mediaType"]
absolute_url = self.base_url + attachment["_links"]["download"]
ti... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-22 | elif media_type == "application/vnd.ms-excel":
text = title + self.process_xls(absolute_url)
elif media_type == "image/svg+xml":
text = title + self.process_svg(absolute_url, ocr_languages)
else:
continue
texts.append(text)
retu... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-23 | )
response = self.confluence.request(path=link, absolute=True)
text = ""
if (
response.status_code != 200
or response.content == b""
or response.content is None
):
return text
try:
images = convert_from_bytes(response.co... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-24 | except ImportError:
raise ImportError(
"`pytesseract` or `Pillow` package not found, "
"please run `pip install pytesseract Pillow`"
)
response = self.confluence.request(path=link, absolute=True)
text = ""
if (
response.status_c... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-25 | except ImportError:
raise ImportError(
"`docx2txt` package not found, please run `pip install docx2txt`"
)
response = self.confluence.request(path=link, absolute=True)
text = ""
if (
response.status_code != 200
or response.content =... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-26 | text = ""
if (
response.status_code != 200
or response.content == b""
or response.content is None
):
return text
workbook = xlrd.open_workbook(file_contents=response.content)
for sheet in workbook.sheets():
text += f"{sheet.name... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-27 | from reportlab.graphics import renderPM # noqa: F401
from svglib.svglib import svg2rlg # noqa: F401
except ImportError:
raise ImportError(
"`pytesseract`, `Pillow`, `reportlab` or `svglib` package not found, "
"please run `pip install pytesseract Pillow ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
39fe2db54e03-28 | image = Image.open(img_data)
return pytesseract.image_to_string(image, lang=ocr_languages) | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
1d2a5ac4608a-0 | Source code for langchain.document_loaders.text
import logging
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.helpers import detect_file_encodings
logger = logging.getLogger(__name__)
[docs]class T... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html |
1d2a5ac4608a-1 | """Initialize with file path."""
self.file_path = file_path
self.encoding = encoding
self.autodetect_encoding = autodetect_encoding
[docs] def load(self) -> List[Document]:
"""Load from file path."""
text = ""
try:
with open(self.file_path, encoding=self.en... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html |
1d2a5ac4608a-2 | except Exception as e:
raise RuntimeError(f"Error loading {self.file_path}") from e
metadata = {"source": self.file_path}
return [Document(page_content=text, metadata=metadata)] | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html |
cd3f4336ba73-0 | Source code for langchain.document_loaders.azlyrics
"""Loader that loads AZLyrics."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.web_base import WebBaseLoader
[docs]class AZLyricsLoader(WebBaseLoader):
"""Loader that loads AZLyrics webpages."""
[docs] ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/azlyrics.html |
ad7486d31ad1-0 | Source code for langchain.document_loaders.weather
"""Simple reader that reads weather data from OpenWeatherMap API"""
from __future__ import annotations
from datetime import datetime
from typing import Iterator, List, Optional, Sequence
from langchain.docstore.document import Document
from langchain.document_loaders.b... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/weather.html |
ad7486d31ad1-1 | self.client = client
self.places = places
[docs] @classmethod
def from_params(
cls, places: Sequence[str], *, openweathermap_api_key: Optional[str] = None
) -> WeatherDataLoader:
client = OpenWeatherMapAPIWrapper(openweathermap_api_key=openweathermap_api_key)
return cls(client... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/weather.html |
d89ee163bbfd-0 | Source code for langchain.document_loaders.email
"""Loader that loads email files."""
import os
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
satisfies_... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/email.html |
d89ee163bbfd-1 | from unstructured.partition.msg import partition_msg
return partition_msg(filename=self.file_path, **self.unstructured_kwargs)
else:
raise ValueError(
f"Filetype {filetype} is not supported in UnstructuredEmailLoader."
)
[docs]class OutlookMessageLoader(BaseLo... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/email.html |
d89ee163bbfd-2 | "`pip install extract_msg`"
)
[docs] def load(self) -> List[Document]:
"""Load data into document objects."""
import extract_msg
msg = extract_msg.Message(self.file_path)
return [
Document(
page_content=msg.body,
metadata={
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/email.html |
e596df7fd730-0 | Source code for langchain.document_loaders.odt
"""Loader that loads Open Office ODT files."""
from typing import Any, List
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
validate_unstructured_version,
)
[docs]class UnstructuredODTLoader(UnstructuredFileLoader):
"""Loader that ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/odt.html |
1d4b6e2d55a2-0 | Source code for langchain.document_loaders.blackboard
"""Loader that loads all documents from a blackboard course."""
import contextlib
import re
from pathlib import Path
from typing import Any, List, Optional, Tuple
from urllib.parse import unquote
from langchain.docstore.document import Document
from langchain.docume... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-1 | BbRouter cookie from the browser's developer tools.
Example:
.. code-block:: python
from langchain.document_loaders import BlackboardLoader
loader = BlackboardLoader(
blackboard_course_url="https://blackboard.example.com/webapps/blackboard/execute/announcement?method=... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-2 | ):
"""Initialize with blackboard course url.
The BbRouter cookie is required for most blackboard courses.
Args:
blackboard_course_url: Blackboard course url.
bbrouter: BbRouter cookie.
load_all_recursively: If True, load all documents recursively.
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-3 | )
if basic_auth is not None:
self.session.auth = basic_auth
# Combine cookies
if cookies is None:
cookies = {}
cookies.update({"BbRouter": bbrouter})
self.session.cookies.update(cookies)
self.load_all_recursively = load_all_recursively
self... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-4 | """Load data into document objects.
Returns:
List of documents.
"""
if self.load_all_recursively:
soup_info = self.scrape()
self.folder_path = self._get_folder_path(soup_info)
relative_paths = self._get_paths(soup_info)
documents = []
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-5 | def _get_folder_path(self, soup: Any) -> str:
"""Get the folder path to save the documents in.
Args:
soup: BeautifulSoup4 soup object.
Returns:
Folder path.
"""
# Get the course name
course_name = soup.find("span", {"id": "crumb_1"})
if cou... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-6 | )
# Get the folder path
folder_path = Path(".") / course_name_clean
return str(folder_path)
def _get_documents(self, soup: Any) -> List[Document]:
"""Fetch content from page and return Documents.
Args:
soup: BeautifulSoup4 soup object.
Returns:
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-7 | if content_list is None:
raise ValueError("No content list found.")
content_list: BeautifulSoup # type: ignore
# Get all attachments
attachments = []
for attachment in content_list.find_all("ul", {"class": "attachments"}):
attachment: Tag # type: ignore
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-8 | # Download all attachments
for attachment in attachments:
self.download(attachment)
def _load_documents(self) -> List[Document]:
"""Load all documents in the folder.
Returns:
List of documents.
"""
# Create the document loader
loader = Director... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-9 | href = link.get("href")
if href is not None and href.startswith("/"):
relative_paths.append(href)
return relative_paths
[docs] def download(self, path: str) -> None:
"""Download a file from a url.
Args:
path: Path to the file.
"""
# Get ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-10 | Returns:
The filename.
"""
if (url_path := Path(url)) and url_path.suffix == ".pdf":
return url_path.name
else:
return self._parse_filename_from_url(url)
def _parse_filename_from_url(self, url: str) -> str:
"""Parse the filename from a url.
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1d4b6e2d55a2-11 | if ".pdf" not in filename:
raise ValueError(f"Incorrect file type: {filename}")
filename = filename.split(".pdf")[0] + ".pdf"
filename = unquote(filename)
filename = filename.replace("%20", " ")
return filename
if __name__ == "__main__":
loader = BlackboardLoader(
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
1811f4804ea2-0 | Source code for langchain.document_loaders.telegram
"""Loader that loads Telegram chat json dump."""
from __future__ import annotations
import asyncio
import json
from pathlib import Path
from typing import TYPE_CHECKING, Dict, List, Optional, Union
from langchain.docstore.document import Document
from langchain.docume... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-1 | def __init__(self, path: str):
"""Initialize with path."""
self.file_path = path
[docs] def load(self) -> List[Document]:
"""Load documents."""
p = Path(self.file_path)
with open(p, encoding="utf8") as f:
d = json.load(f)
text = "".join(
concate... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-2 | # Take a single string as one page
text = [text]
page_docs = [Document(page_content=page) for page in text]
# Add page numbers as metadata
for i, doc in enumerate(page_docs):
doc.metadata["page"] = i + 1
# Split pages into chunks
doc_chunks = []
for doc in page_docs:
text... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-3 | )
# Add sources a metadata
doc.metadata["source"] = f"{doc.metadata['page']}-{doc.metadata['chunk']}"
doc_chunks.append(doc)
return doc_chunks
[docs]class TelegramChatApiLoader(BaseLoader):
"""Loader that loads Telegram chat json directory dump."""
def __init__(
s... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-4 | self.file_path = file_path
[docs] async def fetch_data_from_telegram(self) -> None:
"""Fetch data from Telegram API and save it as a JSON file."""
from telethon.sync import TelegramClient
data = []
async with TelegramClient(self.username, self.api_id, self.api_hash) as client:
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-5 | }
)
with open(self.file_path, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=4)
def _get_message_threads(self, data: pd.DataFrame) -> dict:
"""Create a dictionary of message threads from the given data.
Args:
data (pd.DataFr... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-6 | """
Recursively find all replies to a given parent message ID.
Args:
parent_id (int): The parent message ID.
reply_data (pd.DataFrame): A DataFrame containing reply messages.
Returns:
list: A list of message IDs that are replies to the ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-7 | # Filter out reply messages and drop rows with NaN in 'reply_to_id'
reply_messages = data[data["is_reply"]].dropna(subset=["reply_to_id"])
# Convert 'reply_to_id' to integer
reply_messages["reply_to_id"] = reply_messages["reply_to_id"].astype(int)
# Create a dictionary of message threads... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-8 | on the list of message threads.
Args:
message_threads (dict): A dictionary where the key is the parent message \
ID and the value is a list of message IDs in ascending order.
data (pd.DataFrame): A DataFrame containing the conversation data:
- message.send... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-9 | .tolist()
)
message_texts = [str(elem) for elem in message_texts]
# Combine the message texts
combined_text += " ".join(message_texts) + ".\n"
return combined_text.strip()
[docs] def load(self) -> List[Document]:
"""Load documents."""
if self.ch... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
1811f4804ea2-10 | except ImportError:
raise ImportError(
"""`pandas` package not found.
please install with `pip install pandas`
"""
)
normalized_messages = pd.json_normalize(d)
df = pd.DataFrame(normalized_messages)
message_threads = self._... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
93d6d48400eb-0 | Source code for langchain.document_loaders.embaas
import base64
import warnings
from typing import Any, Dict, Iterator, List, Optional
import requests
from pydantic import BaseModel, root_validator, validator
from typing_extensions import NotRequired, TypedDict
from langchain.docstore.document import Document
from lang... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/embaas.html |
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