id stringlengths 14 16 | text stringlengths 44 2.73k | source stringlengths 49 115 |
|---|---|---|
f60d51e2772a-1 | self._id_key = id_key
self._text_key = text_key
[docs] def add_texts(
self,
texts: Iterable[str],
metadatas: Optional[List[dict]] = None,
ids: Optional[List[str]] = None,
**kwargs: Any,
) -> List[str]:
"""Turn texts into embedding and add it to the database... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/lancedb.html |
f60d51e2772a-2 | """
embedding = self._embedding.embed_query(query)
docs = self._connection.search(embedding).limit(k).to_df()
return [
Document(
page_content=row[self._text_key],
metadata=row[docs.columns != self._text_key],
)
for _, row in doc... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/lancedb.html |
8018e2a6d584-0 | Source code for langchain.vectorstores.atlas
"""Wrapper around Atlas by Nomic."""
from __future__ import annotations
import logging
import uuid
from typing import Any, Iterable, List, Optional, Type
import numpy as np
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-1 | is_public (bool): Whether your project is publicly accessible.
True by default.
reset_project_if_exists (bool): Whether to reset this project if it
already exists. Default False.
Generally userful during development and testing.
"""
try:
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-2 | metadatas (Optional[List[dict]], optional): Optional list of metadatas.
ids (Optional[List[str]]): An optional list of ids.
refresh(bool): Whether or not to refresh indices with the updated data.
Default True.
Returns:
List[str]: List of IDs of the added texts... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-3 | else:
if metadatas is None:
data = [
{"text": text, AtlasDB._ATLAS_DEFAULT_ID_FIELD: ids[i]}
for i, text in enumerate(texts)
]
else:
for i, text in enumerate(texts):
metadatas[i]["text"] =... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-4 | """
if self._embedding_function is None:
raise NotImplementedError(
"AtlasDB requires an embedding_function for text similarity search!"
)
_embedding = self._embedding_function.embed_documents([query])[0]
embedding = np.array(_embedding).reshape(1, -1)
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-5 | ids (Optional[List[str]]): Optional list of document IDs. If None,
ids will be auto created
description (str): A description for your project.
is_public (bool): Whether your project is publicly accessible.
True by default.
reset_project_if_exists (bool... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-6 | ids: Optional[List[str]] = None,
name: Optional[str] = None,
api_key: Optional[str] = None,
persist_directory: Optional[str] = None,
description: str = "A description for your project",
is_public: bool = True,
reset_project_if_exists: bool = False,
index_kwargs: O... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
8018e2a6d584-7 | return cls.from_texts(
name=name,
api_key=api_key,
texts=texts,
embedding=embedding,
metadatas=metadatas,
ids=ids,
description=description,
is_public=is_public,
reset_project_if_exists=reset_project_if_exists,
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/atlas.html |
7d9702e234ad-0 | Source code for langchain.vectorstores.opensearch_vector_search
"""Wrapper around OpenSearch vector database."""
from __future__ import annotations
import uuid
from typing import Any, Dict, Iterable, List, Optional
from langchain.docstore.document import Document
from langchain.embeddings.base import Embeddings
from la... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-1 | try:
opensearch = _import_opensearch()
client = opensearch(opensearch_url, **kwargs)
except ValueError as e:
raise ValueError(
f"OpenSearch client string provided is not in proper format. "
f"Got error: {e} "
)
return client
def _validate_embeddings_and_bu... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-2 | request = {
"_op_type": "index",
"_index": index_name,
vector_field: embeddings[i],
text_field: text,
"metadata": metadata,
"_id": _id,
}
requests.append(request)
ids.append(_id)
bulk(client, requests)
client.indices... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-3 | "parameters": {"ef_construction": ef_construction, "m": m},
},
}
}
},
}
def _default_approximate_search_query(
query_vector: List[float],
size: int = 4,
k: int = 4,
vector_field: str = "vector_field",
) -> Dict:
"""For Approximate k-NN Sear... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-4 | query_vector, size, k, vector_field
)
search_query["query"]["knn"][vector_field]["filter"] = lucene_filter
return search_query
def _default_script_query(
query_vector: List[float],
space_type: str = "l2",
pre_filter: Dict = MATCH_ALL_QUERY,
vector_field: str = "vector_field",
) -> Dict:
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-5 | vector_field: str = "vector_field",
) -> Dict:
"""For Painless Scripting Search, this is the default query."""
source = __get_painless_scripting_source(space_type, query_vector)
return {
"query": {
"script_score": {
"query": pre_filter,
"script": {
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-6 | bulk_size: int = 500,
**kwargs: Any,
) -> List[str]:
"""Run more texts through the embeddings and add to the vectorstore.
Args:
texts: Iterable of strings to add to the vectorstore.
metadatas: Optional list of metadatas associated with the texts.
bulk_size... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-7 | texts,
metadatas,
vector_field,
text_field,
mapping,
)
[docs] def similarity_search(
self, query: str, k: int = 4, **kwargs: Any
) -> List[Document]:
"""Return docs most similar to query.
By default supports Approximate Search.
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-8 | search_type: "script_scoring"; default: "approximate_search"
space_type: "l2", "l1", "linf", "cosinesimil", "innerproduct",
"hammingbit"; default: "l2"
pre_filter: script_score query to pre-filter documents before identifying
nearest neighbors; default: {"match_all": {}}
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-9 | "is invalid"
)
if boolean_filter != {}:
search_query = _approximate_search_query_with_boolean_filter(
embedding, boolean_filter, size, k, vector_field, subquery_clause
)
elif lucene_filter != {}:
search_query = _... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-10 | for hit in hits
]
return documents
[docs] @classmethod
def from_texts(
cls,
texts: List[str],
embedding: Embeddings,
metadatas: Optional[List[dict]] = None,
bulk_size: int = 500,
**kwargs: Any,
) -> OpenSearchVectorSearch:
"""Construct O... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-11 | ef_construction: Size of the dynamic list used during k-NN graph creation.
Higher values lead to more accurate graph but slower indexing speed;
default: 512
m: Number of bidirectional links created for each new element. Large impact
on memory consumption. Between 2 and 10... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
7d9702e234ad-12 | if is_appx_search:
engine = _get_kwargs_value(kwargs, "engine", "nmslib")
space_type = _get_kwargs_value(kwargs, "space_type", "l2")
ef_search = _get_kwargs_value(kwargs, "ef_search", 512)
ef_construction = _get_kwargs_value(kwargs, "ef_construction", 512)
m =... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/opensearch_vector_search.html |
1c013a9ce4d2-0 | Source code for langchain.vectorstores.qdrant
"""Wrapper around Qdrant vector database."""
from __future__ import annotations
import uuid
from hashlib import md5
from operator import itemgetter
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Type, Union
from langchain.docstore.document import D... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-1 | if not isinstance(client, qdrant_client.QdrantClient):
raise ValueError(
f"client should be an instance of qdrant_client.QdrantClient, "
f"got {type(client)}"
)
self.client: qdrant_client.QdrantClient = client
self.collection_name = collection_name... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-2 | k: int = 4,
filter: Optional[MetadataFilter] = None,
**kwargs: Any,
) -> List[Document]:
"""Return docs most similar to query.
Args:
query: Text to look up documents similar to.
k: Number of Documents to return. Defaults to 4.
filter: Filter by met... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-3 | self,
query: str,
k: int = 4,
fetch_k: int = 20,
lambda_mult: float = 0.5,
**kwargs: Any,
) -> List[Document]:
"""Return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity
amon... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-4 | embedding: Embeddings,
metadatas: Optional[List[dict]] = None,
location: Optional[str] = None,
url: Optional[str] = None,
port: Optional[int] = 6333,
grpc_port: int = 6334,
prefer_grpc: bool = False,
https: Optional[bool] = None,
api_key: Optional[str] = N... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-5 | grpc_port: Port of the gRPC interface. Default: 6334
prefer_grpc:
If true - use gPRC interface whenever possible in custom methods.
Default: False
https: If true - use HTTPS(SSL) protocol. Default: None
api_key: API key for authentication in Qdrant Clo... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-6 | 2. Initializes the Qdrant database as an in-memory docstore by default
(and overridable to a remote docstore)
3. Adds the text embeddings to the Qdrant database
This is intended to be a quick way to get started.
Example:
.. code-block:: python
from ... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-7 | ),
)
# Now generate the embeddings for all the texts
embeddings = embedding.embed_documents(texts)
client.upsert(
collection_name=collection_name,
points=rest.Batch.construct(
ids=[md5(text.encode("utf-8")).hexdigest() for text in texts],
... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
1c013a9ce4d2-8 | metadata_payload_key: str,
) -> Document:
return Document(
page_content=scored_point.payload.get(content_payload_key),
metadata=scored_point.payload.get(metadata_payload_key) or {},
)
def _qdrant_filter_from_dict(self, filter: Optional[MetadataFilter]) -> Any:
if ... | https://python.langchain.com/en/latest/_modules/langchain/vectorstores/qdrant.html |
17f93c1e05ef-0 | Source code for langchain.document_loaders.evernote
"""Load documents from Evernote.
https://gist.github.com/foxmask/7b29c43a161e001ff04afdb2f181e31c
"""
import hashlib
from base64 import b64decode
from time import strptime
from typing import Any, Dict, List
from langchain.docstore.document import Document
from langcha... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
17f93c1e05ef-1 | else:
note_dict[elem.tag] = elem.text
note_dict["resource"] = resources
return note_dict
def _parse_note_xml(xml_file: str) -> str:
"""Parse Evernote xml."""
# Without huge_tree set to True, parser may complain about huge text node
# Try to recover, because there may be " ", which w... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/evernote.html |
c19a0bb25641-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/notion.html |
05336f7adec2-0 | Source code for langchain.document_loaders.markdown
"""Loader that loads Markdown files."""
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredMarkdownLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load markdown files."""
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/markdown.html |
39508037cfde-0 | Source code for langchain.document_loaders.text
from typing import List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class TextLoader(BaseLoader):
"""Load text files."""
def __init__(self, file_path: str, encoding: Optional[str] = None):... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/text.html |
9d608f3ebe7c-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://python.langchain.com/en/latest/_modules/langchain/document_loaders/arxiv.html |
e16babed833e-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://python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_file.html |
abebceab4031-0 | Source code for langchain.document_loaders.whatsapp_chat
import re
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def concatenate_rows(date: str, sender: str, text: str) -> str:
"""Combine message information i... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/whatsapp_chat.html |
ff548d8eebc5-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/python.html |
1f4c171cac80-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/gcs_file.html |
d5849b59431c-0 | Source code for langchain.document_loaders.airbyte_json
"""Loader that loads local airbyte json files."""
import json
from typing import Any, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def _stringify_value(val: Any) -> str:
if isinstance(val, str):
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/airbyte_json.html |
e8c7533d7d1f-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://python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
e8c7533d7d1f-1 | 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 of `{_valid_modes}`"
)
def __is_headers_available_for_html(self) -> bool:
_unst... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
e8c7533d7d1f-2 | elements = partition(url=url, **self.unstructured_kwargs)
else:
if self.__is_headers_available_for_html():
elements = partition_html(
url=url, headers=self.headers, **self.unstructured_kwargs
)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/url.html |
3847bc66b708-0 | Source code for langchain.document_loaders.sitemap
"""Loader that fetches a sitemap and loads those URLs."""
import re
from typing import Any, Callable, List, Optional
from langchain.document_loaders.web_base import WebBaseLoader
from langchain.schema import Document
def _default_parsing_function(content: Any) -> str:
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
3847bc66b708-1 | re.match(r, loc.text) for r in self.filter_urls
):
continue
els.append(
{
tag: prop.text
for tag in ["loc", "lastmod", "changefreq", "priority"]
if (prop := url.find(tag))
}
)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/sitemap.html |
94fdca5c0fea-0 | Source code for langchain.document_loaders.csv_loader
from csv import DictReader
from typing import Dict, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class CSVLoader(BaseLoader):
"""Loads a CSV file into a list of documents.
Each d... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/csv_loader.html |
94fdca5c0fea-1 | with open(self.file_path, newline="", encoding=self.encoding) as csvfile:
csv = DictReader(csvfile, **self.csv_args) # type: ignore
for i, row in enumerate(csv):
content = "\n".join(f"{k.strip()}: {v.strip()}" for k, v in row.items())
if self.source_column is not... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/csv_loader.html |
cedbe13aa256-0 | Source code for langchain.document_loaders.dataframe
"""Load from Dataframe object"""
from typing import Any, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class DataFrameLoader(BaseLoader):
"""Load Pandas DataFrames."""
def __init__(self, dat... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/dataframe.html |
f3cd578f9989-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/apify_dataset.html |
f3cd578f9989-1 | )
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))
By Harrison Chase
© Copyright 2023, Harrison Chase.
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/apify_dataset.html |
759af0d3e7d8-0 | Source code for langchain.document_loaders.unstructured
"""Loader that uses unstructured to load files."""
from abc import ABC, abstractmethod
from typing import IO, Any, List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def satisfies_min_unstructured_version(m... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
759af0d3e7d8-1 | )
self.mode = mode
if not satisfies_min_unstructured_version("0.5.4"):
if "strategy" in unstructured_kwargs:
unstructured_kwargs.pop("strategy")
self.unstructured_kwargs = unstructured_kwargs
@abstractmethod
def _get_elements(self) -> List:
"""Get elem... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
759af0d3e7d8-2 | ):
"""Initialize with file path."""
self.file_path = file_path
super().__init__(mode=mode, **unstructured_kwargs)
def _get_elements(self) -> List:
from unstructured.partition.auto import partition
return partition(filename=self.file_path, **self.unstructured_kwargs)
def _... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/unstructured.html |
a2050ad13397-0 | Source code for langchain.document_loaders.obsidian
"""Loader that loads Obsidian directory dump."""
import re
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class ObsidianLoader(BaseLoader):
"""Loader th... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/obsidian.html |
a2050ad13397-1 | """Load documents."""
ps = list(Path(self.file_path).glob("**/*.md"))
docs = []
for p in ps:
with open(p, encoding=self.encoding) as f:
text = f.read()
front_matter = self._parse_front_matter(text)
text = self._remove_front_matter(text)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/obsidian.html |
ce9083fff54f-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://python.langchain.com/en/latest/_modules/langchain/document_loaders/discord.html |
c9ab401eb059-0 | Source code for langchain.document_loaders.telegram
"""Loader that loads Telegram chat json dump."""
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) -> str:
"""Combine... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
c9ab401eb059-1 | metadata = {"source": str(p)}
return [Document(page_content=text, metadata=metadata)]
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/telegram.html |
942dd9cedf04-0 | Source code for langchain.document_loaders.powerpoint
"""Loader that loads powerpoint files."""
import os
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredPowerPointLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load powe... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/powerpoint.html |
942dd9cedf04-1 | return partition_pptx(filename=self.file_path, **self.unstructured_kwargs)
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/powerpoint.html |
1e9823940722-0 | Source code for langchain.document_loaders.readthedocs
"""Loader that loads ReadTheDocs documentation directory dump."""
from pathlib import Path
from typing import Any, List, Optional
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
[docs]class ReadTheDocsLoader(B... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/readthedocs.html |
1e9823940722-1 | text = text[0].get_text()
else:
text = ""
return "\n".join([t for t in text.split("\n") if t])
docs = []
for p in Path(self.file_path).rglob("*"):
if p.is_dir():
continue
with open(p, encoding=self.encoding, errors=self.erro... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/readthedocs.html |
f6ebf3e5e386-0 | Source code for langchain.document_loaders.roam
"""Loader that loads Roam 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 RoamLoader(BaseLoader):
"""Loader that loads Roam files fr... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/roam.html |
456aab56c934-0 | Source code for langchain.document_loaders.image_captions
"""
Loader that loads image captions
By default, the loader utilizes the pre-trained BLIP image captioning model.
https://huggingface.co/Salesforce/blip-image-captioning-base
"""
from typing import Any, List, Tuple, Union
import requests
from langchain.docstore.... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/image_captions.html |
456aab56c934-1 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/image_captions.html |
b0d9f3504d21-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/s3_directory.html |
5a158bbe62c4-0 | Source code for langchain.document_loaders.rtf
"""Loader that loads rich text files."""
from typing import Any, List
from langchain.document_loaders.unstructured import (
UnstructuredFileLoader,
satisfies_min_unstructured_version,
)
[docs]class UnstructuredRTFLoader(UnstructuredFileLoader):
"""Loader that u... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/rtf.html |
7f6e9ceb48ad-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://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
7f6e9ceb48ad-1 | ):
"""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://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
7f6e9ceb48ad-2 | """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://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
7f6e9ceb48ad-3 | )
# 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
7f6e9ceb48ad-4 | Path(self.folder_path).mkdir(parents=True, exist_ok=True)
# 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.
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
7f6e9ceb48ad-5 | """Parse the filename from a url.
Args:
url: Url to parse the filename from.
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)
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
7f6e9ceb48ad-6 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Apr 28, 2023. | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/blackboard.html |
67a542012787-0 | Source code for langchain.document_loaders.diffbot
"""Loader that uses Diffbot to load webpages in text format."""
import logging
from typing import Any, List
import requests
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
logger = logging.getLogger(__name__)
[doc... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/diffbot.html |
67a542012787-1 | text = data["objects"][0]["text"] if "objects" in data else ""
metadata = {"source": url}
docs.append(Document(page_content=text, metadata=metadata))
except Exception as e:
if self.continue_on_failure:
logger.error(f"Error fetching or proce... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/diffbot.html |
6de138ff9ec1-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
6de138ff9ec1-1 | raise ValueError(
"unstructured package not found, please install it with "
"`pip install unstructured`"
)
self.urls = urls
self.continue_on_failure = continue_on_failure
self.browser = browser
self.executable_path = executable_path
sel... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
6de138ff9ec1-2 | """Load the specified URLs using Selenium and create Document instances.
Returns:
List[Document]: A list of Document instances with loaded content.
"""
from unstructured.partition.html import partition_html
docs: List[Document] = list()
driver = self._get_driver()
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/url_selenium.html |
23f014420cd3-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/email.html |
23f014420cd3-1 | "`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://python.langchain.com/en/latest/_modules/langchain/document_loaders/email.html |
de329f50aedb-0 | Source code for langchain.document_loaders.azure_blob_storage_container
"""Loading logic for loading documents from an Azure Blob Storage container."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.azure_blob_storage_file import (
AzureBlobStorageFileLoader... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/azure_blob_storage_container.html |
b111c74f66f9-0 | 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://python.langchain.com/en/latest/_modules/langchain/document_loaders/html.html |
82559b1a43bd-0 | Source code for langchain.document_loaders.confluence
"""Load Data from a Confluence Space"""
import logging
from typing import Any, Callable, List, Optional, Union
from tenacity import (
before_sleep_log,
retry,
stop_after_attempt,
wait_exponential,
)
from langchain.docstore.document import Document
fr... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-1 | :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 cloud: _de... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-2 | 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_retry_seconds
self.max_retry_seconds = max_retry_seconds
try:
from atlassian import Conflu... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-3 | "`username` and provide a value for `oauth2`"
)
if oauth2 and oauth2.keys() != [
"access_token",
"access_token_secret",
"consumer_key",
"key_cert",
]:
errors.append(
"You have either ommited require keys or added ext... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-4 | :param include_comments: defaults to False
:type include_comments: bool, optional
:param limit: Maximum number of pages to retrieve per request, defaults to 50
:type limit: int, optional
:param max_pages: Maximum number of pages to retrieve in total, defaults 1000
:type max_pages... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-5 | max_pages=max_pages,
expand="body.storage.value",
)
for page in pages:
doc = self.process_page(page, include_attachments, include_comments)
docs.append(doc)
if page_ids:
for page_id in page_ids:
get_page = retry(... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-6 | of pages with each request. We have to manually check if there
are more docs based on the length of the returned list of pages, rather than
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/p... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-7 | " `pip install beautifulsoup4`"
)
if include_attachments:
attachment_texts = self.process_attachment(page["id"])
else:
attachment_texts = []
text = BeautifulSoup(
page["body"]["storage"]["value"], "lxml"
).get_text() + "".join(attachment_te... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-8 | title = attachment["title"]
if media_type == "application/pdf":
text = title + self.process_pdf(absolute_url)
elif (
media_type == "image/png"
or media_type == "image/jpg"
or media_type == "image/jpeg"
):
... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-9 | except ValueError:
return text
for i, image in enumerate(images):
image_text = pytesseract.image_to_string(image)
text += f"Page {i + 1}:\n{image_text}\n\n"
return text
[docs] def process_image(self, link: str) -> str:
try:
from io import BytesI... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-10 | ):
return text
file_data = BytesIO(response.content)
return docx2txt.process(file_data)
[docs] def process_xls(self, link: str) -> str:
try:
import xlrd # noqa: F401
except ImportError:
raise ImportError("`xlrd` package not found, please run `pip i... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
82559b1a43bd-11 | )
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
drawing = svg2rlg(BytesIO(response.content))
img... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/confluence.html |
5a4b2526934d-0 | Source code for langchain.document_loaders.imsdb
"""Loader that loads IMSDb."""
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.web_base import WebBaseLoader
[docs]class IMSDbLoader(WebBaseLoader):
"""Loader that loads IMSDb webpages."""
[docs] def load(se... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/imsdb.html |
a6cd8d7b5856-0 | Source code for langchain.document_loaders.image
"""Loader that loads image files."""
from typing import List
from langchain.document_loaders.unstructured import UnstructuredFileLoader
[docs]class UnstructuredImageLoader(UnstructuredFileLoader):
"""Loader that uses unstructured to load image files, such as PNGs and... | https://python.langchain.com/en/latest/_modules/langchain/document_loaders/image.html |
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