id stringlengths 14 16 | text stringlengths 31 2.41k | source stringlengths 53 121 |
|---|---|---|
4c9e56a69292-28 | file_loader_kwargs (Dict[str, Any]) β
Return type
None
attribute credentials_path: pathlib.Path = PosixPath('/home/docs/.credentials/credentials.json')ο
attribute document_ids: Optional[List[str]] = Noneο
attribute file_ids: Optional[List[str]] = Noneο
attribute file_loader_cls: Any = Noneο
attribute file_loader_kwarg... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-29 | Get important HN webpage information.
Components are:
title
content
source url,
time of post
author of the post
number of comments
rank of the post
Return type
List[langchain.schema.Document]
load_comments(soup_info)[source]ο
Load comments from a HN post.
Parameters
soup_info (Any) β
Return type
List[langchain.schema.... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-30 | Bases: langchain.document_loaders.base.BaseLoader
Load iFixit repair guides, device wikis and answers.
iFixit is the largest, open repair community on the web. The site contains nearly
100k repair manuals, 200k Questions & Answers on 42k devices, and all the data is
licensed under CC-BY.
This loader will allow you to d... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-31 | header_template (Optional[dict]) β
verify (Optional[bool]) β
proxies (Optional[dict]) β
load()[source]ο
Load webpage.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.ImageCaptionLoader(path_images, blip_processor='Salesforce/blip-image-captioning-base', blip_model='Salesforce/blip-image-... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-32 | [ββ, ββ, ββ] -> schema = .[]
Parameters
file_path (Union[str, pathlib.Path]) β
jq_schema (str) β
content_key (Optional[str]) β
metadata_func (Optional[Callable[[Dict, Dict], Dict]]) β
text_content (bool) β
load()[source]ο
Load and return documents from the JSON file.
Return type
List[langchain.schema.Document]
cla... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-33 | access_token (str) β
document_id (str) β
lazy_load()[source]ο
Lazy load LarkSuite (FeiShu) document.
Return type
Iterator[langchain.schema.Document]
load()[source]ο
Load LarkSuite (FeiShu) document.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.MWDumpLoader(file_path, encoding='utf8')[s... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-34 | api_base_url (str) β
load()[source]ο
Load toots into documents.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.MathpixPDFLoader(file_path, processed_file_format='mmd', max_wait_time_seconds=500, should_clean_pdf=False, **kwargs)[source]ο
Bases: langchain.document_loaders.pdf.BasePDFLoader... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-35 | Convenience constructor that builds the MaxCompute API wrapper fromgiven parameters.
Parameters
query (str) β SQL query to execute.
endpoint (str) β MaxCompute endpoint.
project (str) β A project is a basic organizational unit of MaxCompute, which is
similar to a database.
access_id (Optional[str]) β MaxCompute access ... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-36 | get_text_separator (str) β
Return type
None
load()[source]ο
Load data into document objects.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.ModernTreasuryLoader(resource, organization_id=None, api_key=None)[source]ο
Bases: langchain.document_loaders.base.BaseLoader
Loader that fetches dat... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-37 | Parameters
integration_token (str) β
database_id (str) β
request_timeout_sec (Optional[int]) β
Return type
None
load()[source]ο
Load documents from the Notion database.
:returns: List of documents.
:rtype: List[Document]
Return type
List[langchain.schema.Document]
load_page(page_summary)[source]ο
Read a page.
Parame... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-38 | Load Documents
Return type
List[langchain.schema.Document]
class langchain.document_loaders.OneDriveLoader(*, settings=None, drive_id, folder_path=None, object_ids=None, auth_with_token=False)[source]ο
Bases: langchain.document_loaders.base.BaseLoader, pydantic.main.BaseModel
Parameters
settings (langchain.document_loa... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-39 | https://github.com/TeamMsgExtractor/msg-extractor
Parameters
file_path (str) β
load()[source]ο
Load data into document objects.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.OpenCityDataLoader(city_id, dataset_id, limit)[source]ο
Bases: langchain.document_loaders.base.BaseLoader
Loader t... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-40 | Bases: langchain.document_loaders.pdf.BasePDFLoader
Loader that uses pdfplumber to load PDF files.
Parameters
file_path (str) β
text_kwargs (Optional[Mapping[str, Any]]) β
Return type
None
load()[source]ο
Load file.
Return type
List[langchain.schema.Document]
langchain.document_loaders.PagedPDFSplitterο
alias of lang... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-41 | connector_id (Optional[str]) β
load()[source]ο
Load documents.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.PyMuPDFLoader(file_path)[source]ο
Bases: langchain.document_loaders.pdf.BasePDFLoader
Loader that uses PyMuPDF to load PDF files.
Parameters
file_path (str) β
Return type
None
lo... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-42 | Lazy load given path as pages.
Return type
Iterator[langchain.schema.Document]
class langchain.document_loaders.PyPDFium2Loader(file_path)[source]ο
Bases: langchain.document_loaders.pdf.BasePDFLoader
Loads a PDF with pypdfium2 and chunks at character level.
Parameters
file_path (str) β
load()[source]ο
Load given path ... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-43 | Bases: langchain.document_loaders.base.BaseLoader
Loader that loads ReadTheDocs documentation directory dump.
Parameters
path (Union[str, pathlib.Path]) β
encoding (Optional[str]) β
errors (Optional[str]) β
custom_html_tag (Optional[Tuple[str, dict]]) β
kwargs (Optional[Any]) β
load()[source]ο
Load documents.
Retu... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-44 | search_queries (Sequence[str]) β
mode (str) β
categories (Sequence[str]) β
number_posts (Optional[int]) β
load()[source]ο
Load reddits.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.RoamLoader(path)[source]ο
Bases: langchain.document_loaders.base.BaseLoader
Loader that loads Roam file... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-45 | Bases: langchain.document_loaders.base.BaseLoader
Loader that uses Selenium and to load a page and unstructured to load the html.
This is useful for loading pages that require javascript to render.
Parameters
urls (List[str]) β
continue_on_failure (bool) β
browser (Literal['chrome', 'firefox']) β
binary_location (Op... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-46 | blocksize (Optional[int]) β
blocknum (int) β
meta_function (Optional[Callable]) β
is_local (bool) β
parse_sitemap(soup)[source]ο
Parse sitemap xml and load into a list of dicts.
Parameters
soup (Any) β
Return type
List[dict]
load()[source]ο
Load sitemap.
Return type
List[langchain.schema.Document]
class langchain.... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-47 | page_content_columns (Optional[List[str]]) β
metadata_columns (Optional[List[str]]) β
lazy_load()[source]ο
A lazy loader for document content.
Return type
Iterator[langchain.schema.Document]
load()[source]ο
Load data into document objects.
Return type
List[langchain.schema.Document]
class langchain.document_loaders.S... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-48 | Bases: langchain.document_loaders.base.BaseLoader
Loading logic for loading documents from Tencent Cloud COS.
Parameters
conf (Any) β
bucket (str) β
key (str) β
load()[source]ο
Load data into document objects.
Return type
List[langchain.schema.Document]
lazy_load()[source]ο
Load documents.
Return type
Iterator[langc... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-49 | Bases: langchain.document_loaders.base.BaseLoader
Load text files.
Parameters
file_path (str) β Path to the file to load.
encoding (Optional[str]) β File encoding to use. If None, the file will be loaded
encoding. (with the default system) β
autodetect_encoding (bool) β Whether to try to autodetect the file encoding
i... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-50 | Return type
Iterator[langchain.schema.Document]
class langchain.document_loaders.TrelloLoader(client, board_name, *, include_card_name=True, include_comments=True, include_checklist=True, card_filter='all', extra_metadata=('due_date', 'labels', 'list', 'closed'))[source]ο
Bases: langchain.document_loaders.base.BaseLoad... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-51 | Return type
langchain.document_loaders.trello.TrelloLoader
load()[source]ο
Loads all cards from the specified Trello board.
You can filter the cards, metadata and text included by using the optional
parameters.
Returns:A list of documents, one for each card in the board.
Return type
List[langchain.schema.Document]
clas... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-52 | consumer_secret (str) β
twitter_users (Sequence[str]) β
number_tweets (Optional[int]) β
Return type
langchain.document_loaders.twitter.TwitterTweetLoader
class langchain.document_loaders.UnstructuredAPIFileIOLoader(file, mode='single', url='https://api.unstructured.io/general/v0/general', api_key='', **unstructured_... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-53 | Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader
Loader that uses unstructured to load epub files.
Parameters
file_path (Union[str, List[str]]) β
mode (str) β
unstructured_kwargs (Any) β
class langchain.document_loaders.UnstructuredEmailLoader(file_path, mode='single', **unstructured_kwargs)[sou... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-54 | mode (str) β
unstructured_kwargs (Any) β
class langchain.document_loaders.UnstructuredHTMLLoader(file_path, mode='single', **unstructured_kwargs)[source]ο
Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader
Loader that uses unstructured to load HTML files.
Parameters
file_path (Union[str, List[str]]... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-55 | Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader
Loader that uses unstructured to load Org-Mode files.
Parameters
file_path (str) β
mode (str) β
unstructured_kwargs (Any) β
class langchain.document_loaders.UnstructuredPDFLoader(file_path, mode='single', **unstructured_kwargs)[source]ο
Bases: lan... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-56 | mode (str) β
unstructured_kwargs (Any) β
class langchain.document_loaders.UnstructuredURLLoader(urls, continue_on_failure=True, mode='single', show_progress_bar=False, **unstructured_kwargs)[source]ο
Bases: langchain.document_loaders.base.BaseLoader
Loader that uses unstructured to load HTML files.
Parameters
urls (L... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-57 | OpenWeatherMap API.
Parameters
client (OpenWeatherMapAPIWrapper) β
places (Sequence[str]) β
Return type
None
classmethod from_params(places, *, openweathermap_api_key=None)[source]ο
Parameters
places (Sequence[str]) β
openweathermap_api_key (Optional[str]) β
Return type
langchain.document_loaders.weather.WeatherDat... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-58 | Parameters
urls (List[str]) β
Return type
Any
scrape_all(urls, parser=None)[source]ο
Fetch all urls, then return soups for all results.
Parameters
urls (List[str]) β
parser (Optional[str]) β
Return type
List[Any]
scrape(parser=None)[source]ο
Scrape data from webpage and return it in BeautifulSoup format.
Parameters
... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
4c9e56a69292-59 | load_all_available_meta (Optional[bool]) β
doc_content_chars_max (Optional[int]) β
load()[source]ο
Loads the query result from Wikipedia into a list of Documents.
Returns
A list of Document objects representing the loadedWikipedia pages.
Return type
List[Document]
class langchain.document_loaders.YoutubeAudioLoader(u... | https://api.python.langchain.com/en/stable/modules/document_loaders.html |
7fccba7e9300-0 | Document Transformersο
Transform documents
langchain.document_transformers.get_stateful_documents(documents)[source]ο
Convert a list of documents to a list of documents with state.
Parameters
documents (Sequence[langchain.schema.Document]) β The documents to convert.
Returns
A list of documents with state.
Return type
... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
7fccba7e9300-1 | kwargs (Any) β
Return type
Sequence[langchain.schema.Document]
Text Splittersο
Functionality for splitting text.
class langchain.text_splitter.TextSplitter(chunk_size=4000, chunk_overlap=200, length_function=<built-in function len>, keep_separator=False, add_start_index=False)[source]ο
Bases: langchain.schema.BaseDocu... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
7fccba7e9300-2 | Parameters
encoding_name (str) β
model_name (Optional[str]) β
allowed_special (Union[Literal['all'], typing.AbstractSet[str]]) β
disallowed_special (Union[Literal['all'], typing.Collection[str]]) β
kwargs (Any) β
Return type
langchain.text_splitter.TS
transform_documents(documents, **kwargs)[source]ο
Transform seq... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
7fccba7e9300-3 | Bases: object
Implementation of splitting markdown files based on specified headers.
Parameters
headers_to_split_on (List[Tuple[str, str]]) β
return_each_line (bool) β
aggregate_lines_to_chunks(lines)[source]ο
Combine lines with common metadata into chunks
:param lines: Line of text / associated header metadata
Param... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
7fccba7e9300-4 | Implementation of splitting text that looks at tokens.
Parameters
encoding_name (str) β
model_name (Optional[str]) β
allowed_special (Union[Literal['all'], AbstractSet[str]]) β
disallowed_special (Union[Literal['all'], Collection[str]]) β
kwargs (Any) β
Return type
None
split_text(text)[source]ο
Split text into mu... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
7fccba7e9300-5 | RUBY = 'ruby'ο
RUST = 'rust'ο
SCALA = 'scala'ο
SWIFT = 'swift'ο
MARKDOWN = 'markdown'ο
LATEX = 'latex'ο
HTML = 'html'ο
SOL = 'sol'ο
class langchain.text_splitter.RecursiveCharacterTextSplitter(separators=None, keep_separator=True, **kwargs)[source]ο
Bases: langchain.text_splitter.TextSplitter
Implementation of splittin... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
7fccba7e9300-6 | Parameters
text (str) β
Return type
List[str]
class langchain.text_splitter.SpacyTextSplitter(separator='\n\n', pipeline='en_core_web_sm', **kwargs)[source]ο
Bases: langchain.text_splitter.TextSplitter
Implementation of splitting text that looks at sentences using Spacy.
Parameters
separator (str) β
pipeline (str) β ... | https://api.python.langchain.com/en/stable/modules/document_transformers.html |
e6d866776567-0 | All modules for which code is available
langchain.agents.agent
langchain.agents.agent_toolkits.azure_cognitive_services.toolkit
langchain.agents.agent_toolkits.csv.base
langchain.agents.agent_toolkits.file_management.toolkit
langchain.agents.agent_toolkits.gmail.toolkit
langchain.agents.agent_toolkits.jira.toolkit
lang... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-1 | langchain.callbacks.argilla_callback
langchain.callbacks.arize_callback
langchain.callbacks.clearml_callback
langchain.callbacks.comet_ml_callback
langchain.callbacks.file
langchain.callbacks.human
langchain.callbacks.infino_callback
langchain.callbacks.manager
langchain.callbacks.mlflow_callback
langchain.callbacks.op... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-2 | langchain.chains.openai_functions.qa_with_structure
langchain.chains.openai_functions.tagging
langchain.chains.pal.base
langchain.chains.qa_generation.base
langchain.chains.qa_with_sources.base
langchain.chains.qa_with_sources.retrieval
langchain.chains.qa_with_sources.vector_db
langchain.chains.retrieval_qa.base
langc... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-3 | langchain.document_loaders.dataframe
langchain.document_loaders.diffbot
langchain.document_loaders.directory
langchain.document_loaders.discord
langchain.document_loaders.docugami
langchain.document_loaders.duckdb_loader
langchain.document_loaders.email
langchain.document_loaders.embaas
langchain.document_loaders.epub
... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-4 | langchain.document_loaders.onedrive
langchain.document_loaders.onedrive_file
langchain.document_loaders.open_city_data
langchain.document_loaders.org_mode
langchain.document_loaders.pdf
langchain.document_loaders.powerpoint
langchain.document_loaders.psychic
langchain.document_loaders.pyspark_dataframe
langchain.docume... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-5 | langchain.embeddings.deepinfra
langchain.embeddings.elasticsearch
langchain.embeddings.embaas
langchain.embeddings.fake
langchain.embeddings.huggingface
langchain.embeddings.huggingface_hub
langchain.embeddings.llamacpp
langchain.embeddings.minimax
langchain.embeddings.modelscope_hub
langchain.embeddings.mosaicml
langc... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-6 | langchain.llms.llamacpp
langchain.llms.manifest
langchain.llms.modal
langchain.llms.mosaicml
langchain.llms.nlpcloud
langchain.llms.octoai_endpoint
langchain.llms.openai
langchain.llms.openllm
langchain.llms.openlm
langchain.llms.petals
langchain.llms.pipelineai
langchain.llms.predictionguard
langchain.llms.promptlayer... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-7 | langchain.output_parsers.fix
langchain.output_parsers.list
langchain.output_parsers.pydantic
langchain.output_parsers.rail_parser
langchain.output_parsers.regex
langchain.output_parsers.regex_dict
langchain.output_parsers.retry
langchain.output_parsers.structured
langchain.prompts.base
langchain.prompts.chat
langchain.... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-8 | langchain.retrievers.tfidf
langchain.retrievers.time_weighted_retriever
langchain.retrievers.vespa_retriever
langchain.retrievers.weaviate_hybrid_search
langchain.retrievers.wikipedia
langchain.retrievers.zep
langchain.retrievers.zilliz
langchain.schema
langchain.text_splitter
langchain.tools.arxiv.tool
langchain.tools... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-9 | langchain.tools.playwright.navigate
langchain.tools.playwright.navigate_back
langchain.tools.plugin
langchain.tools.powerbi.tool
langchain.tools.pubmed.tool
langchain.tools.python.tool
langchain.tools.requests.tool
langchain.tools.scenexplain.tool
langchain.tools.searx_search.tool
langchain.tools.shell.tool
langchain.t... | https://api.python.langchain.com/en/stable/_modules/index.html |
e6d866776567-10 | langchain.vectorstores.chroma
langchain.vectorstores.clarifai
langchain.vectorstores.clickhouse
langchain.vectorstores.deeplake
langchain.vectorstores.docarray.hnsw
langchain.vectorstores.docarray.in_memory
langchain.vectorstores.elastic_vector_search
langchain.vectorstores.faiss
langchain.vectorstores.hologres
langcha... | https://api.python.langchain.com/en/stable/_modules/index.html |
b51f8900a521-0 | Source code for langchain.text_splitter
"""Functionality for splitting text."""
from __future__ import annotations
import copy
import logging
import re
from abc import ABC, abstractmethod
from dataclasses import dataclass
from enum import Enum
from typing import (
AbstractSet,
Any,
Callable,
Collection,... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-1 | """Interface for splitting text into chunks."""
def __init__(
self,
chunk_size: int = 4000,
chunk_overlap: int = 200,
length_function: Callable[[str], int] = len,
keep_separator: bool = False,
add_start_index: bool = False,
) -> None:
"""Create a new TextS... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-2 | metadata = copy.deepcopy(_metadatas[i])
if self._add_start_index:
index = text.find(chunk, index + 1)
metadata["start_index"] = index
new_doc = Document(page_content=chunk, metadata=metadata)
documents.append(new_doc)
return... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-3 | )
if len(current_doc) > 0:
doc = self._join_docs(current_doc, separator)
if doc is not None:
docs.append(doc)
# Keep on popping if:
# - we have a larger chunk than in the chunk overlap
... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-4 | "Please install it with `pip install transformers`."
)
return cls(length_function=_huggingface_tokenizer_length, **kwargs)
[docs] @classmethod
def from_tiktoken_encoder(
cls: Type[TS],
encoding_name: str = "gpt2",
model_name: Optional[str] = None,
allowed_speci... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-5 | [docs] def transform_documents(
self, documents: Sequence[Document], **kwargs: Any
) -> Sequence[Document]:
"""Transform sequence of documents by splitting them."""
return self.split_documents(list(documents))
[docs] async def atransform_documents(
self, documents: Sequence[Doc... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-6 | ):
"""Create a new MarkdownHeaderTextSplitter.
Args:
headers_to_split_on: Headers we want to track
return_each_line: Return each line w/ associated headers
"""
# Output line-by-line or aggregated into chunks w/ common headers
self.return_each_line = return... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-7 | lines = text.split("\n")
# Final output
lines_with_metadata: List[LineType] = []
# Content and metadata of the chunk currently being processed
current_content: List[str] = []
current_metadata: Dict[str, str] = {}
# Keep track of the nested header structure
# heade... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-8 | # Push the current header to the stack
header: HeaderType = {
"level": current_header_level,
"name": name,
"data": stripped_line[len(sep) :].strip(),
}
header_stack... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-9 | class Tokenizer:
chunk_overlap: int
tokens_per_chunk: int
decode: Callable[[list[int]], str]
encode: Callable[[str], List[int]]
[docs]def split_text_on_tokens(*, text: str, tokenizer: Tokenizer) -> List[str]:
"""Split incoming text and return chunks."""
splits: List[str] = []
input_ids = tok... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-10 | )
if model_name is not None:
enc = tiktoken.encoding_for_model(model_name)
else:
enc = tiktoken.get_encoding(encoding_name)
self._tokenizer = enc
self._allowed_special = allowed_special
self._disallowed_special = disallowed_special
[docs] def split_text... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-11 | )
self.model_name = model_name
self._model = SentenceTransformer(self.model_name)
self.tokenizer = self._model.tokenizer
self._initialize_chunk_configuration(tokens_per_chunk=tokens_per_chunk)
def _initialize_chunk_configuration(
self, *, tokens_per_chunk: Optional[int]
)... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-12 | token_ids_with_start_and_end_token_ids = self.tokenizer.encode(
text,
max_length=self._max_length_equal_32_bit_integer,
truncation="do_not_truncate",
)
return token_ids_with_start_and_end_token_ids
[docs]class Language(str, Enum):
CPP = "cpp"
GO = "go"
JAV... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-13 | for i, _s in enumerate(separators):
if _s == "":
separator = _s
break
if re.search(_s, text):
separator = _s
new_separators = separators[i + 1 :]
break
splits = _split_text_with_regex(text, separator, self._k... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-14 | if language == Language.CPP:
return [
# Split along class definitions
"\nclass ",
# Split along function definitions
"\nvoid ",
"\nint ",
"\nfloat ",
"\ndouble ",
# Split along con... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-15 | "\nfunction ",
"\nconst ",
"\nlet ",
"\nvar ",
"\nclass ",
# Split along control flow statements
"\nif ",
"\nfor ",
"\nwhile ",
"\nswitch ",
"\ncase ",
... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-16 | # Now split by the normal type of lines
"\n\n",
"\n",
" ",
"",
]
elif language == Language.RST:
return [
# Split along section titles
"\n=+\n",
"\n-+\n",
"\n\*+... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-17 | "\nobject ",
# Split along method definitions
"\ndef ",
"\nval ",
"\nvar ",
# Split along control flow statements
"\nif ",
"\nfor ",
"\nwhile ",
"\nmatch ",
"\n... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-18 | "\n",
" ",
"",
]
elif language == Language.LATEX:
return [
# First, try to split along Latex sections
"\n\\\chapter{",
"\n\\\section{",
"\n\\\subsection{",
"\n\\\subsubsection{... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-19 | return [
# Split along compiler informations definitions
"\npragma ",
"\nusing ",
# Split along contract definitions
"\ncontract ",
"\ninterface ",
"\nlibrary ",
# Split along method definitio... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-20 | splits = self._tokenizer(text)
return self._merge_splits(splits, self._separator)
[docs]class SpacyTextSplitter(TextSplitter):
"""Implementation of splitting text that looks at sentences using Spacy."""
def __init__(
self, separator: str = "\n\n", pipeline: str = "en_core_web_sm", **kwargs: Any
... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
b51f8900a521-21 | separators = self.get_separators_for_language(Language.MARKDOWN)
super().__init__(separators=separators, **kwargs)
[docs]class LatexTextSplitter(RecursiveCharacterTextSplitter):
"""Attempts to split the text along Latex-formatted layout elements."""
def __init__(self, **kwargs: Any) -> None:
"""... | https://api.python.langchain.com/en/stable/_modules/langchain/text_splitter.html |
4f6982c1328d-0 | Source code for langchain.requests
"""Lightweight wrapper around requests library, with async support."""
from contextlib import asynccontextmanager
from typing import Any, AsyncGenerator, Dict, Optional
import aiohttp
import requests
from pydantic import BaseModel, Extra
class Requests(BaseModel):
"""Wrapper aroun... | https://api.python.langchain.com/en/stable/_modules/langchain/requests.html |
4f6982c1328d-1 | def delete(self, url: str, **kwargs: Any) -> requests.Response:
"""DELETE the URL and return the text."""
return requests.delete(url, headers=self.headers, **kwargs)
@asynccontextmanager
async def _arequest(
self, method: str, url: str, **kwargs: Any
) -> AsyncGenerator[aiohttp.Clien... | https://api.python.langchain.com/en/stable/_modules/langchain/requests.html |
4f6982c1328d-2 | """PATCH the URL and return the text asynchronously."""
async with self._arequest("PATCH", url, **kwargs) as response:
yield response
@asynccontextmanager
async def aput(
self, url: str, data: Dict[str, Any], **kwargs: Any
) -> AsyncGenerator[aiohttp.ClientResponse, None]:
... | https://api.python.langchain.com/en/stable/_modules/langchain/requests.html |
4f6982c1328d-3 | """POST to the URL and return the text."""
return self.requests.post(url, data, **kwargs).text
[docs] def patch(self, url: str, data: Dict[str, Any], **kwargs: Any) -> str:
"""PATCH the URL and return the text."""
return self.requests.patch(url, data, **kwargs).text
[docs] def put(self, ur... | https://api.python.langchain.com/en/stable/_modules/langchain/requests.html |
4f6982c1328d-4 | """PUT the URL and return the text asynchronously."""
async with self.requests.aput(url, **kwargs) as response:
return await response.text()
[docs] async def adelete(self, url: str, **kwargs: Any) -> str:
"""DELETE the URL and return the text asynchronously."""
async with self.req... | https://api.python.langchain.com/en/stable/_modules/langchain/requests.html |
cf9fa59b406b-0 | Source code for langchain.schema
"""Common schema objects."""
from __future__ import annotations
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import (
Any,
Dict,
Generic,
List,
NamedTuple,
Optional,
Sequence,
TypeVar,
Union,
)
from uuid import UUI... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-1 | """Agent's return value."""
return_values: dict
log: str
[docs]class Generation(Serializable):
"""Output of a single generation."""
text: str
"""Generated text output."""
generation_info: Optional[Dict[str, Any]] = None
"""Raw generation info response from the provider"""
"""May include ... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-2 | """Type of the message, used for serialization."""
return "system"
[docs]class FunctionMessage(BaseMessage):
name: str
@property
def type(self) -> str:
"""Type of the message, used for serialization."""
return "function"
[docs]class ChatMessage(BaseMessage):
"""Type of message wi... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-3 | Returns:
List of messages (BaseMessages).
"""
return [_message_from_dict(m) for m in messages]
[docs]class ChatGeneration(Generation):
"""Output of a single generation."""
text = ""
message: BaseMessage
@root_validator
def set_text(cls, values: Dict[str, Any]) -> Dict[str, Any]:
... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-4 | llm_output=self.llm_output,
)
)
else:
if self.llm_output is not None:
llm_output = self.llm_output.copy()
llm_output["token_usage"] = dict()
else:
llm_output = None
... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-5 | """Save the context of this model run to memory."""
[docs] @abstractmethod
def clear(self) -> None:
"""Clear memory contents."""
[docs]class BaseChatMessageHistory(ABC):
"""Base interface for chat message history
See `ChatMessageHistory` for default implementation.
"""
"""
Example:
... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-6 | raise NotImplementedError
[docs] @abstractmethod
def clear(self) -> None:
"""Remove all messages from the store"""
[docs]class Document(Serializable):
"""Interface for interacting with a document."""
page_content: str
metadata: dict = Field(default_factory=dict)
[docs]class BaseRetriever(ABC)... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-7 | """Parse the output of an LLM call.
A method which takes in a string (assumed output of a language model )
and parses it into some structure.
Args:
text: output of language model
Returns:
structured output
"""
[docs] def parse_with_prompt(self, completi... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
cf9fa59b406b-8 | @property
def _type(self) -> str:
return "default"
[docs] def parse(self, text: str) -> str:
return text
[docs]class OutputParserException(ValueError):
"""Exception that output parsers should raise to signify a parsing error.
This exists to differentiate parsing errors from other code or ... | https://api.python.langchain.com/en/stable/_modules/langchain/schema.html |
53bae54580e6-0 | Source code for langchain.document_transformers
"""Transform documents"""
from typing import Any, Callable, List, Sequence
import numpy as np
from pydantic import BaseModel, Field
from langchain.embeddings.base import Embeddings
from langchain.math_utils import cosine_similarity
from langchain.schema import BaseDocumen... | https://api.python.langchain.com/en/stable/_modules/langchain/document_transformers.html |
53bae54580e6-1 | redundant_stacked = np.column_stack(redundant)
redundant_sorted = np.argsort(similarity[redundant])[::-1]
included_idxs = set(range(len(embedded_documents)))
for first_idx, second_idx in redundant_stacked[redundant_sorted]:
if first_idx in included_idxs and second_idx in included_idxs:
#... | https://api.python.langchain.com/en/stable/_modules/langchain/document_transformers.html |
53bae54580e6-2 | arbitrary_types_allowed = True
[docs] def transform_documents(
self, documents: Sequence[Document], **kwargs: Any
) -> Sequence[Document]:
"""Filter down documents."""
stateful_documents = get_stateful_documents(documents)
embedded_documents = _get_embeddings_from_stateful_docs(
... | https://api.python.langchain.com/en/stable/_modules/langchain/document_transformers.html |
6efe031c7c9b-0 | Source code for langchain.agents.loading
"""Functionality for loading agents."""
import json
import logging
from pathlib import Path
from typing import Any, List, Optional, Union
import yaml
from langchain.agents.agent import BaseMultiActionAgent, BaseSingleActionAgent
from langchain.agents.tools import Tool
from langc... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/loading.html |
6efe031c7c9b-1 | if load_from_tools:
if llm is None:
raise ValueError(
"If `load_from_llm_and_tools` is set to True, "
"then LLM must be provided"
)
if tools is None:
raise ValueError(
"If `load_from_llm_and_tools` is set to True, "
... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/loading.html |
6efe031c7c9b-2 | if hub_result := try_load_from_hub(
path, _load_agent_from_file, "agents", {"json", "yaml"}
):
return hub_result
else:
return _load_agent_from_file(path, **kwargs)
def _load_agent_from_file(
file: Union[str, Path], **kwargs: Any
) -> Union[BaseSingleActionAgent, BaseMultiActionAgent]... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/loading.html |
1886b3951db2-0 | Source code for langchain.agents.agent_types
from enum import Enum
[docs]class AgentType(str, Enum):
"""Enumerator with the Agent types."""
ZERO_SHOT_REACT_DESCRIPTION = "zero-shot-react-description"
REACT_DOCSTORE = "react-docstore"
SELF_ASK_WITH_SEARCH = "self-ask-with-search"
CONVERSATIONAL_REACT... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/agent_types.html |
3626c117023e-0 | Source code for langchain.agents.initialize
"""Load agent."""
from typing import Any, Optional, Sequence
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_types import AgentType
from langchain.agents.loading import AGENT_TO_CLASS, load_agent
from langchain.base_language import BaseLanguageMod... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/initialize.html |
3626c117023e-1 | agent = AgentType.ZERO_SHOT_REACT_DESCRIPTION
if agent is not None and agent_path is not None:
raise ValueError(
"Both `agent` and `agent_path` are specified, "
"but at most only one should be."
)
if agent is not None:
if agent not in AGENT_TO_CLASS:
r... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/initialize.html |
9e3e8c0b73e3-0 | Source code for langchain.agents.agent
"""Chain that takes in an input and produces an action and action input."""
from __future__ import annotations
import asyncio
import json
import logging
import time
from abc import abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Sequ... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/agent.html |
9e3e8c0b73e3-1 | return None
[docs] @abstractmethod
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Ste... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/agent.html |
9e3e8c0b73e3-2 | # `force` just returns a constant string
return AgentFinish(
{"output": "Agent stopped due to iteration limit or time limit."}, ""
)
else:
raise ValueError(
f"Got unsupported early_stopping_method `{early_stopping_method}`"
)
[docs]... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/agent.html |
9e3e8c0b73e3-3 | directory_path.mkdir(parents=True, exist_ok=True)
# Fetch dictionary to save
agent_dict = self.dict()
if save_path.suffix == ".json":
with open(file_path, "w") as f:
json.dump(agent_dict, f, indent=4)
elif save_path.suffix == ".yaml":
with open(fil... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/agent.html |
9e3e8c0b73e3-4 | **kwargs: Any,
) -> Union[List[AgentAction], AgentFinish]:
"""Given input, decided what to do.
Args:
intermediate_steps: Steps the LLM has taken to date,
along with observations
callbacks: Callbacks to run.
**kwargs: User inputs.
Returns:
... | https://api.python.langchain.com/en/stable/_modules/langchain/agents/agent.html |
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