id stringlengths 14 16 | text stringlengths 4 1.28k | source stringlengths 54 121 |
|---|---|---|
371a0de63670-1 | if isinstance(path_images, str):
self.image_paths = [path_images]
else:
self.image_paths = path_images
self.blip_processor = blip_processor
self.blip_model = blip_model
[docs] def load(self) -> List[Document]:
"""
Load from a list of image files
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/image_captions.html |
371a0de63670-2 | model=model, processor=processor, path_image=path_image
)
doc = Document(page_content=caption, metadata=metadata)
results.append(doc)
return results
def _get_captions_and_metadata(
self, model: Any, processor: Any, path_image: str
) -> Tuple[str, dict]:
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/image_captions.html |
371a0de63670-3 | )
else:
image = Image.open(path_image).convert("RGB")
except Exception:
raise ValueError(f"Could not get image data for {path_image}")
inputs = processor(image, "an image of", return_tensors="pt")
output = model.generate(**inputs)
caption: str = pr... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/image_captions.html |
0104ca9f3fef-0 | Source code for langchain.document_loaders.git
import os
from typing import Callable, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class GitLoader(BaseLoader):
"""Loads files from a Git repository into a list of documents.
Repositor... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/git.html |
0104ca9f3fef-1 | file_filter: Optional[Callable[[str], bool]] = None,
):
self.repo_path = repo_path
self.clone_url = clone_url
self.branch = branch
self.file_filter = file_filter
[docs] def load(self) -> List[Document]:
try:
from git import Blob, Repo # type: ignore
ex... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/git.html |
0104ca9f3fef-2 | repo = Repo(self.repo_path)
repo.git.checkout(self.branch)
docs: List[Document] = []
for item in repo.tree().traverse():
if not isinstance(item, Blob):
continue
file_path = os.path.join(self.repo_path, item.path)
ignored_files = repo.ignore... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/git.html |
0104ca9f3fef-3 | except UnicodeDecodeError:
continue
metadata = {
"source": rel_file_path,
"file_path": rel_file_path,
"file_name": item.name,
"file_type": file_type,
}
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/git.html |
1647622f7ae7-0 | Source code for langchain.document_loaders.url_selenium
"""Loader that uses Selenium to load a page, then uses unstructured to load the html.
"""
import logging
from typing import TYPE_CHECKING, List, Literal, Optional, Union
if TYPE_CHECKING:
from selenium.webdriver import Chrome, Firefox
from langchain.docstore.d... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
1647622f7ae7-1 | binary_location (Optional[str]): The location of the browser binary.
executable_path (Optional[str]): The path to the browser executable.
headless (bool): If True, the browser will run in headless mode.
arguments [List[str]]: List of arguments to pass to the browser.
"""
def __init__(
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
1647622f7ae7-2 | except ImportError:
raise ImportError(
"selenium package not found, please install it with "
"`pip install selenium`"
)
try:
import unstructured # noqa:F401
except ImportError:
raise ImportError(
"unstructur... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
1647622f7ae7-3 | Returns:
Union[Chrome, Firefox]: A WebDriver instance for the specified browser.
"""
if self.browser.lower() == "chrome":
from selenium.webdriver import Chrome
from selenium.webdriver.chrome.options import Options as ChromeOptions
chrome_options = ChromeOp... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
1647622f7ae7-4 | firefox_options = FirefoxOptions()
for arg in self.arguments:
firefox_options.add_argument(arg)
if self.headless:
firefox_options.add_argument("--headless")
if self.binary_location is not None:
firefox_options.binary_location = self.bin... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
1647622f7ae7-5 | driver = self._get_driver()
for url in self.urls:
try:
driver.get(url)
page_content = driver.page_source
elements = partition_html(text=page_content)
text = "\n\n".join([str(el) for el in elements])
metadata = {"source":... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
a47482d6dab7-0 | Source code for langchain.document_loaders.max_compute
from __future__ import annotations
from typing import Any, Iterator, List, Optional, Sequence
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.utilities.max_compute import MaxComputeAPIWrapper
[d... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/max_compute.html |
a47482d6dab7-1 | Document. If unspecified, all columns will be written to `page_content`.
metadata_columns: The columns to write into the `metadata` of the Document.
If unspecified, all columns not added to `page_content` will be written.
"""
self.query = query
self.api_wrapper = api_... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/max_compute.html |
a47482d6dab7-2 | query: SQL query to execute.
endpoint: MaxCompute endpoint.
project: A project is a basic organizational unit of MaxCompute, which is
similar to a database.
access_id: MaxCompute access ID. Should be passed in directly or set as the
environment variabl... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/max_compute.html |
a47482d6dab7-3 | page_content_data = {
k: v for k, v in row.items() if k in self.page_content_columns
}
else:
page_content_data = row
page_content = "\n".join(f"{k}: {v}" for k, v in page_content_data.items())
if self.metadata_columns:
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/max_compute.html |
a2e620899152-0 | Source code for langchain.document_loaders.pyspark_dataframe
"""Load from a Spark Dataframe object"""
import itertools
import logging
import sys
from typing import TYPE_CHECKING, Any, Iterator, List, Optional, Tuple
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/pyspark_dataframe.html |
a2e620899152-1 | except ImportError:
raise ImportError(
"pyspark is not installed. "
"Please install it with `pip install pyspark`"
)
self.spark = (
spark_session if spark_session else SparkSession.builder.getOrCreate()
)
if not isinstance(df, D... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/pyspark_dataframe.html |
a2e620899152-2 | try:
import psutil
except ImportError as e:
raise ImportError(
"psutil not installed. Please install it with `pip install psutil`."
) from e
row = self.df.limit(1).collect()[0]
estimated_row_size = sys.getsizeof(row)
mem_info = psutil.v... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/pyspark_dataframe.html |
a2e620899152-3 | text = metadata[self.page_content_column]
metadata.pop(self.page_content_column)
yield Document(page_content=text, metadata=metadata)
[docs] def load(self) -> List[Document]:
"""Load from the dataframe."""
if self.df.count() > self.max_num_rows:
logger.warning(
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/pyspark_dataframe.html |
b18ba7925d47-0 | Source code for langchain.document_loaders.docugami
"""Loader that loads processed documents from Docugami."""
import io
import logging
import os
import re
from pathlib import Path
from typing import Any, Dict, List, Mapping, Optional, Sequence, Union
import requests
from pydantic import BaseModel, root_validator
from ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-1 | logger = logging.getLogger(__name__)
[docs]class DocugamiLoader(BaseLoader, BaseModel):
"""Loader that loads processed docs from Docugami.
To use, you should have the ``lxml`` python package installed.
"""
api: str = DEFAULT_API_ENDPOINT
access_token: Optional[str] = os.environ.get("DOCUGAMI_API_KEY... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-2 | if values.get("file_paths") and values.get("docset_id"):
raise ValueError("Cannot specify both file_paths and remote API docset_id")
if not values.get("file_paths") and not values.get("docset_id"):
raise ValueError("Must specify either file_paths or remote API docset_id")
if valu... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-3 | "Please install it with `pip install lxml`."
)
# helpers
def _xpath_qname_for_chunk(chunk: Any) -> str:
"""Get the xpath qname for a chunk."""
qname = f"{chunk.prefix}:{chunk.tag.split('}')[-1]}"
parent = chunk.getparent()
if parent is not None... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-4 | return "/" + "/".join(_xpath_qname_for_chunk(x) for x in ancestor_chain)
def _structure_value(node: Any) -> str:
"""Get the structure value for a node."""
structure = (
"table"
if node.tag == TABLE_NAME
else node.attrib["structure"]
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-5 | """Get the text of a node."""
return " ".join(node.itertext()).strip()
def _has_structural_descendant(node: Any) -> bool:
"""Check if a node has a structural descendant."""
for child in node:
if _is_structural(child) or _has_structural_descendant(child):
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-6 | metadata = {
XPATH_KEY: _xpath_for_chunk(node),
DOCUMENT_ID_KEY: document["id"],
DOCUMENT_NAME_KEY: document["name"],
STRUCTURE_KEY: node.attrib.get("structure", ""),
TAG_KEY: re.sub(r"\{.*\}", "", node.tag),
}
if do... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-7 | prev_small_chunk_text = None
if _is_heading(node) or len(text) < self.min_chunk_size:
# Save headings or other small chunks to be appended to the next chunk
prev_small_chunk_text = text
else:
chunks.append(_create_doc(node, text))
if prev_s... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-8 | url,
headers={"Authorization": f"Bearer {self.access_token}"},
)
if response.ok:
data = response.json()
all_documents.extend(data["documents"])
url = data.get("next", None)
else:
raise Exception(
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-9 | data={},
)
if response.ok:
data = response.json()
all_projects.extend(data["projects"])
url = data.get("next", None)
else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-10 | data = response.json()
all_artifacts.extend(data["artifacts"])
url = data.get("next", None)
else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"
)
per_file_metadata = {}
for art... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-11 | data={},
)
if response.ok:
try:
from lxml import etree
except ImportError:
raise ImportError(
"Could not import lxml python package. "
"Please i... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-12 | else:
raise Exception(
f"Failed to download {artifact_url}/content "
+ "(status: {response.status_code})"
)
return per_file_metadata
def _load_chunks_for_document(
self, docset_id: str, document: Dict, doc_metada... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-13 | else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"
)
[docs] def load(self) -> List[Document]:
"""Load documents."""
chunks: List[Document] = []
if self.access_token and self.docset_id:
# remote mode
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
b18ba7925d47-14 | for project in _project_details:
metadata = self._metadata_for_project(project)
combined_project_metadata.update(metadata)
for doc in _document_details:
doc_metadata = combined_project_metadata.get(doc["id"])
chunks += self._load_chunks... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/docugami.html |
c1439cca58c4-0 | Source code for langchain.document_loaders.gcs_file
"""Loading logic for loading documents from a GCS file."""
import os
import tempfile
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.unstructured import Uns... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/gcs_file.html |
c1439cca58c4-1 | "Please install it with `pip install google-cloud-storage`."
)
# Initialise a client
storage_client = storage.Client(self.project_name)
# Create a bucket object for our bucket
bucket = storage_client.get_bucket(self.bucket)
# Create a blob object from the filepath
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/gcs_file.html |
94886d86efe6-0 | Source code for langchain.document_loaders.facebook_chat
"""Loader that loads Facebook chat json dump."""
import datetime
import json
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def concatenate_rows(row: dict) -... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/facebook_chat.html |
94886d86efe6-1 | """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(
concatenate_rows(message)
for mess... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/facebook_chat.html |
36fcad30e2f3-0 | Source code for langchain.document_loaders.modern_treasury
"""Loader that fetches data from Modern Treasury"""
import json
import urllib.request
from base64 import b64encode
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from lan... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/modern_treasury.html |
36fcad30e2f3-1 | "internal_accounts": "https://app.moderntreasury.com/api/internal_accounts",
"external_accounts": "https://app.moderntreasury.com/api/external_accounts",
"transactions": "https://app.moderntreasury.com/api/transactions",
"ledgers": "https://app.moderntreasury.com/api/ledgers",
"ledger_accounts": "https:... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/modern_treasury.html |
36fcad30e2f3-2 | def __init__(
self,
resource: str,
organization_id: Optional[str] = None,
api_key: Optional[str] = None,
) -> None:
self.resource = resource
organization_id = organization_id or get_from_env(
"organization_id", "MODERN_TREASURY_ORGANIZATION_ID"
)
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/modern_treasury.html |
36fcad30e2f3-3 | with urllib.request.urlopen(request) as response:
json_data = json.loads(response.read().decode())
text = stringify_value(json_data)
metadata = {"source": url}
return [Document(page_content=text, metadata=metadata)]
def _get_resource(self) -> List[Document]:
e... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/modern_treasury.html |
e02d090dd07c-0 | Source code for langchain.document_loaders.s3_file
"""Loading logic for loading documents from an s3 file."""
import os
import tempfile
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.unstructured import Unst... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_file.html |
e02d090dd07c-1 | )
s3 = boto3.client("s3")
with tempfile.TemporaryDirectory() as temp_dir:
file_path = f"{temp_dir}/{self.key}"
os.makedirs(os.path.dirname(file_path), exist_ok=True)
s3.download_file(self.bucket, self.key, file_path)
loader = UnstructuredFileLoader(file_pa... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_file.html |
396108ba147d-0 | Source code for langchain.document_loaders.github
from abc import ABC
from datetime import datetime
from typing import Dict, Iterator, List, Literal, Optional, Union
import requests
from pydantic import BaseModel, root_validator, validator
from langchain.docstore.document import Document
from langchain.document_loaders... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-1 | values, "access_token", "GITHUB_PERSONAL_ACCESS_TOKEN"
)
return values
@property
def headers(self) -> Dict[str, str]:
return {
"Accept": "application/vnd.github+json",
"Authorization": f"Bearer {self.access_token}",
}
[docs]class GitHubIssuesLoader(BaseGit... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-2 | """Filter on issue state. Can be one of: 'open', 'closed', 'all'."""
assignee: Optional[str] = None
"""Filter on assigned user. Pass 'none' for no user and '*' for any user."""
creator: Optional[str] = None
"""Filter on the user that created the issue."""
mentioned: Optional[str] = None
"""Filte... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-3 | """The direction to sort the results by. Can be one of: 'asc', 'desc'."""
since: Optional[str] = None
"""Only show notifications updated after the given time.
This is a timestamp in ISO 8601 format: YYYY-MM-DDTHH:MM:SSZ."""
@validator("since")
def validate_since(cls, v: Optional[str]) -> Optiona... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-4 | Get issues of a GitHub repository.
Returns:
A list of Documents with attributes:
- page_content
- metadata
- url
- title
- creator
- created_at
- last_update_time
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-5 | url = response.links["next"]["url"]
else:
url = None
[docs] def load(self) -> List[Document]:
"""
Get issues of a GitHub repository.
Returns:
A list of Documents with attributes:
- page_content
- metadata
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-6 | "url": issue["html_url"],
"title": issue["title"],
"creator": issue["user"]["login"],
"created_at": issue["created_at"],
"comments": issue["comments"],
"state": issue["state"],
"labels": [label["name"] for label in issue["labels"]],
"as... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-7 | @property
def query_params(self) -> str:
labels = ",".join(self.labels) if self.labels else self.labels
query_params_dict = {
"milestone": self.milestone,
"state": self.state,
"assignee": self.assignee,
"creator": self.creator,
"mentioned":... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
396108ba147d-8 | def url(self) -> str:
return f"https://api.github.com/repos/{self.repo}/issues?{self.query_params}" | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/github.html |
a1c5531e06a2-0 | Source code for langchain.document_loaders.discord
"""Load from Discord chat dump"""
from __future__ import annotations
from typing import TYPE_CHECKING, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
if TYPE_CHECKING:
import pandas as pd
[docs]class Dis... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/discord.html |
a1c5531e06a2-1 | """Load all chat messages."""
result = []
for _, row in self.chat_log.iterrows():
user_id = row[self.user_id_col]
metadata = row.to_dict()
metadata.pop(self.user_id_col)
result.append(Document(page_content=user_id, metadata=metadata))
return result | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/discord.html |
da4d30de0644-0 | Source code for langchain.document_loaders.fauna
from typing import Iterator, List, Optional, Sequence
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class FaunaLoader(BaseLoader):
"""FaunaDB Loader.
Attributes:
query (str): The FQL query st... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/fauna.html |
da4d30de0644-1 | ):
self.query = query
self.page_content_field = page_content_field
self.secret = secret
self.metadata_fields = metadata_fields
[docs] def load(self) -> List[Document]:
return list(self.lazy_load())
[docs] def lazy_load(self) -> Iterator[Document]:
try:
f... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/fauna.html |
da4d30de0644-2 | if result is not None:
document_dict = dict(result.items())
page_content = ""
for key, value in document_dict.items():
if key == self.page_content_field:
page_content = value
document: Document = Document(
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/fauna.html |
eb7663f455a4-0 | Source code for langchain.document_loaders.arxiv
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.utilities.arxiv import ArxivAPIWrapper
[docs]class ArxivLoader(BaseLoader):
"""Loads a query result from arxiv.org... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/arxiv.html |
eb7663f455a4-1 | load_max_docs=self.load_max_docs,
load_all_available_meta=self.load_all_available_meta,
)
docs = arxiv_client.load(self.query)
return docs | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/arxiv.html |
d387aa4d6136-0 | Source code for langchain.document_loaders.python
import tokenize
from langchain.document_loaders.text import TextLoader
[docs]class PythonLoader(TextLoader):
"""
Load Python files, respecting any non-default encoding if specified.
"""
def __init__(self, file_path: str):
with open(file_path, "rb... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/python.html |
a825d785a87c-0 | Source code for langchain.document_loaders.bigquery
from __future__ import annotations
from typing import TYPE_CHECKING, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
if TYPE_CHECKING:
from google.auth.credentials import Credentials
[docs]clas... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/bigquery.html |
a825d785a87c-1 | project: Optional[str] = None,
page_content_columns: Optional[List[str]] = None,
metadata_columns: Optional[List[str]] = None,
credentials: Optional[Credentials] = None,
):
"""Initialize BigQuery document loader.
Args:
query: The query to run in BigQuery.
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/bigquery.html |
a825d785a87c-2 | """
self.query = query
self.project = project
self.page_content_columns = page_content_columns
self.metadata_columns = metadata_columns
self.credentials = credentials
[docs] def load(self) -> List[Document]:
try:
from google.cloud import bigquery
ex... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/bigquery.html |
a825d785a87c-3 | if metadata_columns is None:
metadata_columns = []
for row in query_result:
page_content = "\n".join(
f"{k}: {v}" for k, v in row.items() if k in page_content_columns
)
metadata = {k: v for k, v in row.items() if k in metadata_columns}
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/bigquery.html |
5167d9be408c-0 | Source code for langchain.document_loaders.azure_blob_storage_file
"""Loading logic for loading documents from an Azure Blob Storage file."""
import os
import tempfile
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_file.html |
5167d9be408c-1 | raise ValueError(
"Could not import azure storage blob python package. "
"Please install it with `pip install azure-storage-blob`."
) from exc
client = BlobClient.from_connection_string(
conn_str=self.conn_str, container_name=self.container, blob_name=self... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_file.html |
f9dc9c2584c5-0 | Source code for langchain.document_loaders.duckdb_loader
from typing import Dict, List, Optional, cast
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class DuckDBLoader(BaseLoader):
"""Loads a query result from DuckDB into a list of documents.
Each ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html |
f9dc9c2584c5-1 | page_content_columns: Optional[List[str]] = None,
metadata_columns: Optional[List[str]] = None,
):
self.query = query
self.database = database
self.read_only = read_only
self.config = config or {}
self.page_content_columns = page_content_columns
self.metadata_... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html |
f9dc9c2584c5-2 | field_names = [c[0] for c in description]
if self.page_content_columns is None:
page_content_columns = field_names
else:
page_content_columns = self.page_content_columns
if self.metadata_columns is None:
metadata_columns = []
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/duckdb_loader.html |
d1903859bbbe-0 | Source code for langchain.document_loaders.notion
"""Loader that loads Notion directory dump."""
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class NotionDirectoryLoader(BaseLoader):
"""Loader that load... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/notion.html |
f7fe4891e53e-0 | Source code for langchain.document_loaders.psychic
"""Loader that loads documents from Psychic.dev."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class PsychicLoader(BaseLoader):
"""Loader that loads documents from Psychic.de... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/psychic.html |
f7fe4891e53e-1 | self.connection_id = connection_id
[docs] def load(self) -> List[Document]:
"""Load documents."""
psychic_docs = self.psychic.get_documents(self.connector_id, self.connection_id)
return [
Document(
page_content=doc["content"],
metadata={"title": doc... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/psychic.html |
23eea75afe70-0 | Source code for langchain.document_loaders.apify_dataset
"""Logic for loading documents from Apify datasets."""
from typing import Any, Callable, Dict, List
from pydantic import BaseModel, root_validator
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/apify_dataset.html |
23eea75afe70-1 | ):
"""Initialize the loader with an Apify dataset ID and a mapping function.
Args:
dataset_id (str): The ID of the dataset on the Apify platform.
dataset_mapping_function (Callable): A function that takes a single
dictionary (an Apify dataset item) and converts it... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/apify_dataset.html |
23eea75afe70-2 | )
return values
[docs] def load(self) -> List[Document]:
"""Load documents."""
dataset_items = self.apify_client.dataset(self.dataset_id).list_items().items
return list(map(self.dataset_mapping_function, dataset_items)) | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/apify_dataset.html |
6347ff6b9b8c-0 | Source code for langchain.document_loaders.html
"""Loader that uses unstructured to load HTML files."""
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredHTMLLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load HTML files."... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/html.html |
0203c8694f84-0 | Source code for langchain.document_loaders.s3_directory
"""Loading logic for loading documents from an s3 directory."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
from langchain.document_loaders.s3_file import S3FileLoader
[docs]class ... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_directory.html |
0203c8694f84-1 | )
s3 = boto3.resource("s3")
bucket = s3.Bucket(self.bucket)
docs = []
for obj in bucket.objects.filter(Prefix=self.prefix):
loader = S3FileLoader(self.bucket, obj.key)
docs.extend(loader.load())
return docs | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_directory.html |
4b91829d9f71-0 | Source code for langchain.document_loaders.url
"""Loader that uses unstructured to load HTML files."""
import logging
from typing import Any, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = logging.getLogger(__name__)
[docs]class UnstructuredURLLoade... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
4b91829d9f71-1 | except ImportError:
raise ValueError(
"unstructured package not found, please install it with "
"`pip install unstructured`"
)
self._validate_mode(mode)
self.mode = mode
headers = unstructured_kwargs.pop("headers", {})
if len(header... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
4b91829d9f71-2 | self.unstructured_kwargs = unstructured_kwargs
self.show_progress_bar = show_progress_bar
def _validate_mode(self, mode: str) -> None:
_valid_modes = {"single", "elements"}
if mode not in _valid_modes:
raise ValueError(
f"Got {mode} for `mode`, but should be one o... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
4b91829d9f71-3 | unstructured_version = tuple([int(x) for x in _unstructured_version.split(".")])
return unstructured_version >= (0, 5, 13)
def __is_non_html_available(self) -> bool:
_unstructured_version = self.__version.split("-")[0]
unstructured_version = tuple([int(x) for x in _unstructured_version.split... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
4b91829d9f71-4 | "Please install with 'pip install tqdm' or set "
"show_progress_bar=False."
) from e
urls = tqdm(self.urls)
else:
urls = self.urls
for url in urls:
try:
if self.__is_non_html_available():
if self.... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
4b91829d9f71-5 | if self.continue_on_failure:
logger.error(f"Error fetching or processing {url}, exeption: {e}")
continue
else:
raise e
if self.mode == "single":
text = "\n\n".join([str(el) for el in elements])
metada... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
bdef7a48fbfd-0 | Source code for langchain.document_loaders.onedrive
"""Loader that loads data from OneDrive"""
from __future__ import annotations
import logging
import os
import tempfile
from enum import Enum
from pathlib import Path
from typing import TYPE_CHECKING, Dict, List, Optional, Type, Union
from pydantic import BaseModel, Ba... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-1 | client_secret: SecretStr = Field(..., env="O365_CLIENT_SECRET")
class Config:
env_prefix = ""
case_sentive = False
env_file = ".env"
class _OneDriveTokenStorage(BaseSettings):
token_path: FilePath = Field(Path.home() / ".credentials" / "o365_token.txt")
class _FileType(str, Enum):
DO... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-2 | mime_types_mapping[
file_type.value
] = "application/vnd.openxmlformats-officedocument.wordprocessingml.document" # noqa: E501
elif file_type.value == "pdf":
mime_types_mapping[file_type.value] = "application/pdf"
return mime_types_mapping
[docs]c... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-3 | """
try:
from O365 import FileSystemTokenBackend
except ImportError:
raise ImportError(
"O365 package not found, please install it with `pip install o365`"
)
if self.auth_with_token:
token_storage = _OneDriveTokenStorage()
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-4 | )
account = Account(
credentials=(
self.settings.client_id,
self.settings.client_secret.get_secret_value(),
),
scopes=SCOPES,
token_backend=token_backend,
**{"raise_http_errors": False},
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-5 | """
subfolder_drive = drive
if self.folder_path is None:
return subfolder_drive
subfolders = [f for f in self.folder_path.split("/") if f != ""]
if len(subfolders) == 0:
return subfolder_drive
items = subfolder_drive.get_items()
for subfolder in su... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-6 | Args:
folder (Type[Folder]): The folder object to load the documents from.
Returns:
List[Document]: A list of Document objects representing
the loaded documents.
"""
docs = []
file_types = _SupportedFileTypes(file_types=["doc", "docx", "pdf"])
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-7 | """
Loads all supported document files from the specified OneDrive
drive based on their object IDs and returns a list
of Document objects.
Args:
drive (Type[Drive]): The OneDrive drive object
to load the documents from.
Returns:
List[Document]:... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-8 | logging.warning(
"There isn't a file with "
f"object_id {object_id} in drive {drive}."
)
continue
if file.is_file:
if file.mime_type in list(file_mime_types.values()):
load... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
bdef7a48fbfd-9 | docs: List[Document] = []
if not drive:
raise ValueError(f"There isn't a drive with id {self.drive_id}.")
if self.folder_path:
folder = self._get_folder_from_path(drive=drive)
docs.extend(self._load_from_folder(folder=folder))
elif self.object_ids:
... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/onedrive.html |
1d62b8110dcb-0 | Source code for langchain.document_loaders.rst
"""Loader that loads RST files."""
from typing import Any, List
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
validate_unstructured_version,
)
[docs]class UnstructuredRSTLoader(UnstructuredFileLoader):
"""Loader that uses unstruc... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/rst.html |
cf6bacdcfbce-0 | Source code for langchain.document_loaders.open_city_data
from typing import Iterator, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class OpenCityDataLoader(BaseLoader):
"""Loader that loads Open city data."""
def __init__(self, city_id: str,... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/open_city_data.html |
cf6bacdcfbce-1 | """Lazy load records."""
from sodapy import Socrata
client = Socrata(self.city_id, None)
results = client.get(self.dataset_id, limit=self.limit)
for record in results:
yield Document(
page_content=str(record),
metadata={
"so... | https://api.python.langchain.com/en/latest/_modules/langchain/document_loaders/open_city_data.html |
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