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community[patch]: import flattening fix (#20110)

Browse Source 
This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code.

See #20050 as a template for this PR.
- As a byproduct: Added 3 missed `test_imports`.
- Added missed `SolarChat` in to __init___.py Added it into test_import
ut.
- Added `# type: ignore` to fix linting. It is not clear, why linting
errors appear after ^ changes.

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
This commit is contained in:
Leonid Ganeline 2024-04-10 10:01:19 -07:00 committed by GitHub
parent 12190ad728
commit 4cb5f4c353
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GPG Key ID: B5690EEEBB952194
60 changed files with 2973 additions and 163 deletions
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124
libs/community/langchain_community/agent_toolkits/__init__.py
View File

@ -3,7 +3,129 @@ various services and APIs.
"""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.agent_toolkits.ainetwork.toolkit import (
AINetworkToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.amadeus.toolkit import (
AmadeusToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.azure_ai_services import (
AzureAiServicesToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.azure_cognitive_services import (
AzureCognitiveServicesToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.cogniswitch.toolkit import (
CogniswitchToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.connery import (
ConneryToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.file_management.toolkit import (
FileManagementToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.gmail.toolkit import (
GmailToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.jira.toolkit import (
JiraToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.json.base import (
create_json_agent, # noqa: F401
)
from langchain_community.agent_toolkits.json.toolkit import (
JsonToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.multion.toolkit import (
MultionToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.nasa.toolkit import (
NasaToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.nla.toolkit import (
NLAToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.office365.toolkit import (
O365Toolkit, # noqa: F401
)
from langchain_community.agent_toolkits.openapi.base import (
create_openapi_agent, # noqa: F401
)
from langchain_community.agent_toolkits.openapi.toolkit import (
OpenAPIToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.playwright.toolkit import (
PlayWrightBrowserToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.polygon.toolkit import (
PolygonToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.powerbi.base import (
create_pbi_agent, # noqa: F401
)
from langchain_community.agent_toolkits.powerbi.chat_base import (
create_pbi_chat_agent, # noqa: F401
)
from langchain_community.agent_toolkits.powerbi.toolkit import (
PowerBIToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.slack.toolkit import (
SlackToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.spark_sql.base import (
create_spark_sql_agent, # noqa: F401
)
from langchain_community.agent_toolkits.spark_sql.toolkit import (
SparkSQLToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.sql.base import (
create_sql_agent, # noqa: F401
)
from langchain_community.agent_toolkits.sql.toolkit import (
SQLDatabaseToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.steam.toolkit import (
SteamToolkit, # noqa: F401
)
from langchain_community.agent_toolkits.zapier.toolkit import (
ZapierToolkit, # noqa: F401
)
__all__ = [
"AINetworkToolkit",
"AmadeusToolkit",
"AzureAiServicesToolkit",
"AzureCognitiveServicesToolkit",
"CogniswitchToolkit",
"ConneryToolkit",
"FileManagementToolkit",
"GmailToolkit",
"JiraToolkit",
"JsonToolkit",
"MultionToolkit",
"NLAToolkit",
"NasaToolkit",
"O365Toolkit",
"OpenAPIToolkit",
"PlayWrightBrowserToolkit",
"PolygonToolkit",
"PowerBIToolkit",
"SQLDatabaseToolkit",
"SlackToolkit",
"SparkSQLToolkit",
"SteamToolkit",
"ZapierToolkit",
"create_json_agent",
"create_openapi_agent",
"create_pbi_agent",
"create_pbi_chat_agent",
"create_spark_sql_agent",
"create_sql_agent",
]
_module_lookup = {
"AINetworkToolkit": "langchain_community.agent_toolkits.ainetwork.toolkit",

2
libs/community/langchain_community/cache.py
View File

@ -1998,7 +1998,7 @@ class AzureCosmosDBSemanticCache(BaseCache):
k=1,
kind=self.kind,
ef_search=self.ef_search,
score_threshold=self.score_threshold,
score_threshold=self.score_threshold, # type: ignore[arg-type]
)
if results:
for document in results:

43
libs/community/langchain_community/chat_loaders/__init__.py
View File

@ -19,7 +19,48 @@ WhatsApp. The loaded chat messages can be used for fine-tuning models.
""" # noqa: E501
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.chat_loaders.base import (
BaseChatLoader, # noqa: F401
)
from langchain_community.chat_loaders.facebook_messenger import (
FolderFacebookMessengerChatLoader, # noqa: F401
SingleFileFacebookMessengerChatLoader, # noqa: F401
)
from langchain_community.chat_loaders.gmail import (
GMailLoader, # noqa: F401
)
from langchain_community.chat_loaders.imessage import (
IMessageChatLoader, # noqa: F401
)
from langchain_community.chat_loaders.langsmith import (
LangSmithDatasetChatLoader, # noqa: F401
LangSmithRunChatLoader, # noqa: F401
)
from langchain_community.chat_loaders.slack import (
SlackChatLoader, # noqa: F401
)
from langchain_community.chat_loaders.telegram import (
TelegramChatLoader, # noqa: F401
)
from langchain_community.chat_loaders.whatsapp import (
WhatsAppChatLoader, # noqa: F401
)
__all__ = [
"BaseChatLoader",
"FolderFacebookMessengerChatLoader",
"GMailLoader",
"IMessageChatLoader",
"LangSmithDatasetChatLoader",
"LangSmithRunChatLoader",
"SingleFileFacebookMessengerChatLoader",
"SlackChatLoader",
"TelegramChatLoader",
"WhatsAppChatLoader",
]
_module_lookup = {
"BaseChatLoader": "langchain_community.chat_loaders.base",

91
libs/community/langchain_community/chat_message_histories/__init__.py
View File

@ -16,7 +16,96 @@
""" # noqa: E501
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.chat_message_histories.astradb import (
AstraDBChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.cassandra import (
CassandraChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.cosmos_db import (
CosmosDBChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.dynamodb import (
DynamoDBChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.elasticsearch import (
ElasticsearchChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.file import (
FileChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.firestore import (
FirestoreChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.in_memory import (
ChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.momento import (
MomentoChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.mongodb import (
MongoDBChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.neo4j import (
Neo4jChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.postgres import (
PostgresChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.redis import (
RedisChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.rocksetdb import (
RocksetChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.singlestoredb import (
SingleStoreDBChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.sql import (
SQLChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.streamlit import (
StreamlitChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.tidb import (
TiDBChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.upstash_redis import (
UpstashRedisChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.xata import (
XataChatMessageHistory, # noqa: F401
)
from langchain_community.chat_message_histories.zep import (
ZepChatMessageHistory, # noqa: F401
)
__all__ = [
"AstraDBChatMessageHistory",
"CassandraChatMessageHistory",
"ChatMessageHistory",
"CosmosDBChatMessageHistory",
"DynamoDBChatMessageHistory",
"ElasticsearchChatMessageHistory",
"FileChatMessageHistory",
"FirestoreChatMessageHistory",
"MomentoChatMessageHistory",
"MongoDBChatMessageHistory",
"Neo4jChatMessageHistory",
"PostgresChatMessageHistory",
"RedisChatMessageHistory",
"RocksetChatMessageHistory",
"SQLChatMessageHistory",
"SingleStoreDBChatMessageHistory",
"StreamlitChatMessageHistory",
"TiDBChatMessageHistory",
"UpstashRedisChatMessageHistory",
"XataChatMessageHistory",
"ZepChatMessageHistory",
]
_module_lookup = {
"AstraDBChatMessageHistory": "langchain_community.chat_message_histories.astradb",

193
libs/community/langchain_community/chat_models/__init__.py
View File

@ -18,7 +18,197 @@ an interface where "chat messages" are the inputs and outputs.
""" # noqa: E501
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.chat_models.anthropic import (
ChatAnthropic, # noqa: F401
)
from langchain_community.chat_models.anyscale import (
ChatAnyscale, # noqa: F401
)
from langchain_community.chat_models.azure_openai import (
AzureChatOpenAI, # noqa: F401
)
from langchain_community.chat_models.baichuan import (
ChatBaichuan, # noqa: F401
)
from langchain_community.chat_models.baidu_qianfan_endpoint import (
QianfanChatEndpoint, # noqa: F401
)
from langchain_community.chat_models.bedrock import (
BedrockChat, # noqa: F401
)
from langchain_community.chat_models.cohere import (
ChatCohere, # noqa: F401
)
from langchain_community.chat_models.databricks import (
ChatDatabricks, # noqa: F401
)
from langchain_community.chat_models.deepinfra import (
ChatDeepInfra, # noqa: F401
)
from langchain_community.chat_models.ernie import (
ErnieBotChat, # noqa: F401
)
from langchain_community.chat_models.everlyai import (
ChatEverlyAI, # noqa: F401
)
from langchain_community.chat_models.fake import (
FakeListChatModel, # noqa: F401
)
from langchain_community.chat_models.fireworks import (
ChatFireworks, # noqa: F401
)
from langchain_community.chat_models.friendli import (
ChatFriendli, # noqa: F401
)
from langchain_community.chat_models.gigachat import (
GigaChat, # noqa: F401
)
from langchain_community.chat_models.google_palm import (
ChatGooglePalm, # noqa: F401
)
from langchain_community.chat_models.gpt_router import (
GPTRouter, # noqa: F401
)
from langchain_community.chat_models.huggingface import (
ChatHuggingFace, # noqa: F401
)
from langchain_community.chat_models.human import (
HumanInputChatModel, # noqa: F401
)
from langchain_community.chat_models.hunyuan import (
ChatHunyuan, # noqa: F401
)
from langchain_community.chat_models.javelin_ai_gateway import (
ChatJavelinAIGateway, # noqa: F401
)
from langchain_community.chat_models.jinachat import (
JinaChat, # noqa: F401
)
from langchain_community.chat_models.kinetica import (
ChatKinetica, # noqa: F401
)
from langchain_community.chat_models.konko import (
ChatKonko, # noqa: F401
)
from langchain_community.chat_models.litellm import (
ChatLiteLLM, # noqa: F401
)
from langchain_community.chat_models.litellm_router import (
ChatLiteLLMRouter, # noqa: F401
)
from langchain_community.chat_models.llama_edge import (
LlamaEdgeChatService, # noqa: F401
)
from langchain_community.chat_models.maritalk import (
ChatMaritalk, # noqa: F401
)
from langchain_community.chat_models.minimax import (
MiniMaxChat, # noqa: F401
)
from langchain_community.chat_models.mlflow import (
ChatMlflow, # noqa: F401
)
from langchain_community.chat_models.mlflow_ai_gateway import (
ChatMLflowAIGateway, # noqa: F401
)
from langchain_community.chat_models.mlx import (
ChatMLX, # noqa: F401
)
from langchain_community.chat_models.ollama import (
ChatOllama, # noqa: F401
)
from langchain_community.chat_models.openai import (
ChatOpenAI, # noqa: F401
)
from langchain_community.chat_models.pai_eas_endpoint import (
PaiEasChatEndpoint, # noqa: F401
)
from langchain_community.chat_models.perplexity import (
ChatPerplexity, # noqa: F401
)
from langchain_community.chat_models.premai import (
ChatPremAI, # noqa: F401
)
from langchain_community.chat_models.promptlayer_openai import (
PromptLayerChatOpenAI, # noqa: F401
)
from langchain_community.chat_models.solar import (
SolarChat, # noqa: F401
)
from langchain_community.chat_models.sparkllm import (
ChatSparkLLM, # noqa: F401
)
from langchain_community.chat_models.tongyi import (
ChatTongyi, # noqa: F401
)
from langchain_community.chat_models.vertexai import (
ChatVertexAI, # noqa: F401
)
from langchain_community.chat_models.volcengine_maas import (
VolcEngineMaasChat, # noqa: F401
)
from langchain_community.chat_models.yandex import (
ChatYandexGPT, # noqa: F401
)
from langchain_community.chat_models.yuan2 import (
ChatYuan2, # noqa: F401
)
from langchain_community.chat_models.zhipuai import (
ChatZhipuAI, # noqa: F401
)
__all__ = [
"AzureChatOpenAI",
"BedrockChat",
"ChatAnthropic",
"ChatAnyscale",
"ChatBaichuan",
"ChatCohere",
"ChatDatabricks",
"ChatDeepInfra",
"ChatEverlyAI",
"ChatFireworks",
"ChatFriendli",
"ChatGooglePalm",
"ChatHuggingFace",
"ChatHunyuan",
"ChatJavelinAIGateway",
"ChatKinetica",
"ChatKonko",
"ChatLiteLLM",
"ChatLiteLLMRouter",
"ChatMLX",
"ChatMLflowAIGateway",
"ChatMaritalk",
"ChatMlflow",
"ChatOllama",
"ChatOpenAI",
"ChatPerplexity",
"ChatPremAI",
"ChatSparkLLM",
"ChatTongyi",
"ChatVertexAI",
"ChatYandexGPT",
"ChatYuan2",
"ChatZhipuAI",
"ErnieBotChat",
"FakeListChatModel",
"GPTRouter",
"GigaChat",
"HumanInputChatModel",
"JinaChat",
"LlamaEdgeChatService",
"MiniMaxChat",
"PaiEasChatEndpoint",
"PromptLayerChatOpenAI",
"QianfanChatEndpoint",
"SolarChat",
"VolcEngineMaasChat",
]
_module_lookup = {
"AzureChatOpenAI": "langchain_community.chat_models.azure_openai",
@ -63,6 +253,7 @@ _module_lookup = {
"MiniMaxChat": "langchain_community.chat_models.minimax",
"PaiEasChatEndpoint": "langchain_community.chat_models.pai_eas_endpoint",
"PromptLayerChatOpenAI": "langchain_community.chat_models.promptlayer_openai",
"SolarChat": "langchain_community.chat_models.solar",
"QianfanChatEndpoint": "langchain_community.chat_models.baidu_qianfan_endpoint",
"VolcEngineMaasChat": "langchain_community.chat_models.volcengine_maas",
"ChatPremAI": "langchain_community.chat_models.premai",

2
libs/community/langchain_community/chat_models/moonshot.py
View File

@ -8,7 +8,7 @@ from langchain_community.chat_models import ChatOpenAI
from langchain_community.llms.moonshot import MOONSHOT_SERVICE_URL_BASE, MoonshotCommon
class MoonshotChat(MoonshotCommon, ChatOpenAI):
class MoonshotChat(MoonshotCommon, ChatOpenAI): # type: ignore[misc]
"""Wrapper around Moonshot large language models.
To use, you should have the ``openai`` python package installed, and the

3
libs/community/langchain_community/chat_models/solar.py
View File

@ -9,8 +9,9 @@ from langchain_community.chat_models import ChatOpenAI
from langchain_community.llms.solar import SOLAR_SERVICE_URL_BASE, SolarCommon
class SolarChat(SolarCommon, ChatOpenAI):
class SolarChat(SolarCommon, ChatOpenAI): # type: ignore[misc]
"""Wrapper around Solar large language models.
To use, you should have the ``openai`` python package installed, and the
environment variable ``SOLAR_API_KEY`` set with your API key.
(Solar's chat API is compatible with OpenAI's SDK.)

15
libs/community/langchain_community/docstore/__init__.py
View File

@ -16,7 +16,20 @@ The **Docstore** is a simplified version of the Document Loader.
"""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.docstore.arbitrary_fn import (
DocstoreFn, # noqa: F401
)
from langchain_community.docstore.in_memory import (
InMemoryDocstore, # noqa: F401
)
from langchain_community.docstore.wikipedia import (
Wikipedia, # noqa: F401
)
__all__ = ["DocstoreFn", "InMemoryDocstore", "Wikipedia"]
_module_lookup = {
"DocstoreFn": "langchain_community.docstore.arbitrary_fn",

12
libs/community/langchain_community/document_compressors/__init__.py
View File

@ -1,5 +1,15 @@
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.document_compressors.llmlingua_filter import (
LLMLinguaCompressor, # noqa: F401
)
from langchain_community.document_compressors.openvino_rerank import (
OpenVINOReranker, # noqa: F401
)
__all__ = ["LLMLinguaCompressor", "OpenVINOReranker"]
_module_lookup = {
"LLMLinguaCompressor": "langchain_community.document_compressors.llmlingua_filter",

669
libs/community/langchain_community/document_loaders/__init__.py
View File

@ -15,7 +15,674 @@
Document, <name>TextSplitter
"""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.document_loaders.acreom import (
AcreomLoader, # noqa: F401
)
from langchain_community.document_loaders.airbyte import (
AirbyteCDKLoader, # noqa: F401
AirbyteGongLoader, # noqa: F401
AirbyteHubspotLoader, # noqa: F401
AirbyteSalesforceLoader, # noqa: F401
AirbyteShopifyLoader, # noqa: F401
AirbyteStripeLoader, # noqa: F401
AirbyteTypeformLoader, # noqa: F401
AirbyteZendeskSupportLoader, # noqa: F401
)
from langchain_community.document_loaders.airbyte_json import (
AirbyteJSONLoader, # noqa: F401
)
from langchain_community.document_loaders.airtable import (
AirtableLoader, # noqa: F401
)
from langchain_community.document_loaders.apify_dataset import (
ApifyDatasetLoader, # noqa: F401
)
from langchain_community.document_loaders.arcgis_loader import (
ArcGISLoader, # noqa: F401
)
from langchain_community.document_loaders.arxiv import (
ArxivLoader, # noqa: F401
)
from langchain_community.document_loaders.assemblyai import (
AssemblyAIAudioLoaderById, # noqa: F401
AssemblyAIAudioTranscriptLoader, # noqa: F401
)
from langchain_community.document_loaders.astradb import (
AstraDBLoader, # noqa: F401
)
from langchain_community.document_loaders.async_html import (
AsyncHtmlLoader, # noqa: F401
)
from langchain_community.document_loaders.athena import (
AthenaLoader, # noqa: F401
)
from langchain_community.document_loaders.azlyrics import (
AZLyricsLoader, # noqa: F401
)
from langchain_community.document_loaders.azure_ai_data import (
AzureAIDataLoader, # noqa: F401
)
from langchain_community.document_loaders.azure_blob_storage_container import (
AzureBlobStorageContainerLoader, # noqa: F401
)
from langchain_community.document_loaders.azure_blob_storage_file import (
AzureBlobStorageFileLoader, # noqa: F401
)
from langchain_community.document_loaders.bibtex import (
BibtexLoader, # noqa: F401
)
from langchain_community.document_loaders.bigquery import (
BigQueryLoader, # noqa: F401
)
from langchain_community.document_loaders.bilibili import (
BiliBiliLoader, # noqa: F401
)
from langchain_community.document_loaders.blackboard import (
BlackboardLoader, # noqa: F401
)
from langchain_community.document_loaders.blob_loaders import (
Blob, # noqa: F401
BlobLoader, # noqa: F401
FileSystemBlobLoader, # noqa: F401
YoutubeAudioLoader, # noqa: F401
)
from langchain_community.document_loaders.blockchain import (
BlockchainDocumentLoader, # noqa: F401
)
from langchain_community.document_loaders.brave_search import (
BraveSearchLoader, # noqa: F401
)
from langchain_community.document_loaders.browserless import (
BrowserlessLoader, # noqa: F401
)
from langchain_community.document_loaders.cassandra import (
CassandraLoader, # noqa: F401
)
from langchain_community.document_loaders.chatgpt import (
ChatGPTLoader, # noqa: F401
)
from langchain_community.document_loaders.chm import (
UnstructuredCHMLoader, # noqa: F401
)
from langchain_community.document_loaders.chromium import (
AsyncChromiumLoader, # noqa: F401
)
from langchain_community.document_loaders.college_confidential import (
CollegeConfidentialLoader, # noqa: F401
)
from langchain_community.document_loaders.concurrent import (
ConcurrentLoader, # noqa: F401
)
from langchain_community.document_loaders.confluence import (
ConfluenceLoader, # noqa: F401
)
from langchain_community.document_loaders.conllu import (
CoNLLULoader, # noqa: F401
)
from langchain_community.document_loaders.couchbase import (
CouchbaseLoader, # noqa: F401
)
from langchain_community.document_loaders.csv_loader import (
CSVLoader, # noqa: F401
UnstructuredCSVLoader, # noqa: F401
)
from langchain_community.document_loaders.cube_semantic import (
CubeSemanticLoader, # noqa: F401
)
from langchain_community.document_loaders.datadog_logs import (
DatadogLogsLoader, # noqa: F401
)
from langchain_community.document_loaders.dataframe import (
DataFrameLoader, # noqa: F401
)
from langchain_community.document_loaders.diffbot import (
DiffbotLoader, # noqa: F401
)
from langchain_community.document_loaders.directory import (
DirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.discord import (
DiscordChatLoader, # noqa: F401
)
from langchain_community.document_loaders.doc_intelligence import (
AzureAIDocumentIntelligenceLoader, # noqa: F401
)
from langchain_community.document_loaders.docugami import (
DocugamiLoader, # noqa: F401
)
from langchain_community.document_loaders.docusaurus import (
DocusaurusLoader, # noqa: F401
)
from langchain_community.document_loaders.dropbox import (
DropboxLoader, # noqa: F401
)
from langchain_community.document_loaders.duckdb_loader import (
DuckDBLoader, # noqa: F401
)
from langchain_community.document_loaders.email import (
OutlookMessageLoader, # noqa: F401
UnstructuredEmailLoader, # noqa: F401
)
from langchain_community.document_loaders.epub import (
UnstructuredEPubLoader, # noqa: F401
)
from langchain_community.document_loaders.etherscan import (
EtherscanLoader, # noqa: F401
)
from langchain_community.document_loaders.evernote import (
EverNoteLoader, # noqa: F401
)
from langchain_community.document_loaders.excel import (
UnstructuredExcelLoader, # noqa: F401
)
from langchain_community.document_loaders.facebook_chat import (
FacebookChatLoader, # noqa: F401
)
from langchain_community.document_loaders.fauna import (
FaunaLoader, # noqa: F401
)
from langchain_community.document_loaders.figma import (
FigmaFileLoader, # noqa: F401
)
from langchain_community.document_loaders.gcs_directory import (
GCSDirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.gcs_file import (
GCSFileLoader, # noqa: F401
)
from langchain_community.document_loaders.geodataframe import (
GeoDataFrameLoader, # noqa: F401
)
from langchain_community.document_loaders.git import (
GitLoader, # noqa: F401
)
from langchain_community.document_loaders.gitbook import (
GitbookLoader, # noqa: F401
)
from langchain_community.document_loaders.github import (
GithubFileLoader, # noqa: F401
GitHubIssuesLoader, # noqa: F401
)
from langchain_community.document_loaders.google_speech_to_text import (
GoogleSpeechToTextLoader, # noqa: F401
)
from langchain_community.document_loaders.googledrive import (
GoogleDriveLoader, # noqa: F401
)
from langchain_community.document_loaders.gutenberg import (
GutenbergLoader, # noqa: F401
)
from langchain_community.document_loaders.hn import (
HNLoader, # noqa: F401
)
from langchain_community.document_loaders.html import (
UnstructuredHTMLLoader, # noqa: F401
)
from langchain_community.document_loaders.html_bs import (
BSHTMLLoader, # noqa: F401
)
from langchain_community.document_loaders.hugging_face_dataset import (
HuggingFaceDatasetLoader, # noqa: F401
)
from langchain_community.document_loaders.hugging_face_model import (
HuggingFaceModelLoader, # noqa: F401
)
from langchain_community.document_loaders.ifixit import (
IFixitLoader, # noqa: F401
)
from langchain_community.document_loaders.image import (
UnstructuredImageLoader, # noqa: F401
)
from langchain_community.document_loaders.image_captions import (
ImageCaptionLoader, # noqa: F401
)
from langchain_community.document_loaders.imsdb import (
IMSDbLoader, # noqa: F401
)
from langchain_community.document_loaders.iugu import (
IuguLoader, # noqa: F401
)
from langchain_community.document_loaders.joplin import (
JoplinLoader, # noqa: F401
)
from langchain_community.document_loaders.json_loader import (
JSONLoader, # noqa: F401
)
from langchain_community.document_loaders.lakefs import (
LakeFSLoader, # noqa: F401
)
from langchain_community.document_loaders.larksuite import (
LarkSuiteDocLoader, # noqa: F401
)
from langchain_community.document_loaders.llmsherpa import (
LLMSherpaFileLoader, # noqa: F401
)
from langchain_community.document_loaders.markdown import (
UnstructuredMarkdownLoader, # noqa: F401
)
from langchain_community.document_loaders.mastodon import (
MastodonTootsLoader, # noqa: F401
)
from langchain_community.document_loaders.max_compute import (
MaxComputeLoader, # noqa: F401
)
from langchain_community.document_loaders.mediawikidump import (
MWDumpLoader, # noqa: F401
)
from langchain_community.document_loaders.merge import (
MergedDataLoader, # noqa: F401
)
from langchain_community.document_loaders.mhtml import (
MHTMLLoader, # noqa: F401
)
from langchain_community.document_loaders.modern_treasury import (
ModernTreasuryLoader, # noqa: F401
)
from langchain_community.document_loaders.mongodb import (
MongodbLoader, # noqa: F401
)
from langchain_community.document_loaders.news import (
NewsURLLoader, # noqa: F401
)
from langchain_community.document_loaders.notebook import (
NotebookLoader, # noqa: F401
)
from langchain_community.document_loaders.notion import (
NotionDirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.notiondb import (
NotionDBLoader, # noqa: F401
)
from langchain_community.document_loaders.obs_directory import (
OBSDirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.obs_file import (
OBSFileLoader, # noqa: F401
)
from langchain_community.document_loaders.obsidian import (
ObsidianLoader, # noqa: F401
)
from langchain_community.document_loaders.odt import (
UnstructuredODTLoader, # noqa: F401
)
from langchain_community.document_loaders.onedrive import (
OneDriveLoader, # noqa: F401
)
from langchain_community.document_loaders.onedrive_file import (
OneDriveFileLoader, # noqa: F401
)
from langchain_community.document_loaders.open_city_data import (
OpenCityDataLoader, # noqa: F401
)
from langchain_community.document_loaders.oracleadb_loader import (
OracleAutonomousDatabaseLoader, # noqa: F401
)
from langchain_community.document_loaders.org_mode import (
UnstructuredOrgModeLoader, # noqa: F401
)
from langchain_community.document_loaders.pdf import (
AmazonTextractPDFLoader, # noqa: F401
MathpixPDFLoader, # noqa: F401
OnlinePDFLoader, # noqa: F401
PagedPDFSplitter, # noqa: F401
PDFMinerLoader, # noqa: F401
PDFMinerPDFasHTMLLoader, # noqa: F401
PDFPlumberLoader, # noqa: F401
PyMuPDFLoader, # noqa: F401
PyPDFDirectoryLoader, # noqa: F401
PyPDFium2Loader, # noqa: F401
PyPDFLoader, # noqa: F401
UnstructuredPDFLoader, # noqa: F401
)
from langchain_community.document_loaders.pebblo import (
PebbloSafeLoader, # noqa: F401
)
from langchain_community.document_loaders.polars_dataframe import (
PolarsDataFrameLoader, # noqa: F401
)
from langchain_community.document_loaders.powerpoint import (
UnstructuredPowerPointLoader, # noqa: F401
)
from langchain_community.document_loaders.psychic import (
PsychicLoader, # noqa: F401
)
from langchain_community.document_loaders.pubmed import (
PubMedLoader, # noqa: F401
)
from langchain_community.document_loaders.pyspark_dataframe import (
PySparkDataFrameLoader, # noqa: F401
)
from langchain_community.document_loaders.python import (
PythonLoader, # noqa: F401
)
from langchain_community.document_loaders.readthedocs import (
ReadTheDocsLoader, # noqa: F401
)
from langchain_community.document_loaders.recursive_url_loader import (
RecursiveUrlLoader, # noqa: F401
)
from langchain_community.document_loaders.reddit import (
RedditPostsLoader, # noqa: F401
)
from langchain_community.document_loaders.roam import (
RoamLoader, # noqa: F401
)
from langchain_community.document_loaders.rocksetdb import (
RocksetLoader, # noqa: F401
)
from langchain_community.document_loaders.rss import (
RSSFeedLoader, # noqa: F401
)
from langchain_community.document_loaders.rst import (
UnstructuredRSTLoader, # noqa: F401
)
from langchain_community.document_loaders.rtf import (
UnstructuredRTFLoader, # noqa: F401
)
from langchain_community.document_loaders.s3_directory import (
S3DirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.s3_file import (
S3FileLoader, # noqa: F401
)
from langchain_community.document_loaders.sharepoint import (
SharePointLoader, # noqa: F401
)
from langchain_community.document_loaders.sitemap import (
SitemapLoader, # noqa: F401
)
from langchain_community.document_loaders.slack_directory import (
SlackDirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.snowflake_loader import (
SnowflakeLoader, # noqa: F401
)
from langchain_community.document_loaders.spreedly import (
SpreedlyLoader, # noqa: F401
)
from langchain_community.document_loaders.sql_database import (
SQLDatabaseLoader, # noqa: F401
)
from langchain_community.document_loaders.srt import (
SRTLoader, # noqa: F401
)
from langchain_community.document_loaders.stripe import (
StripeLoader, # noqa: F401
)
from langchain_community.document_loaders.surrealdb import (
SurrealDBLoader, # noqa: F401
)
from langchain_community.document_loaders.telegram import (
TelegramChatApiLoader, # noqa: F401
TelegramChatFileLoader, # noqa: F401
TelegramChatLoader, # noqa: F401
)
from langchain_community.document_loaders.tencent_cos_directory import (
TencentCOSDirectoryLoader, # noqa: F401
)
from langchain_community.document_loaders.tencent_cos_file import (
TencentCOSFileLoader, # noqa: F401
)
from langchain_community.document_loaders.tensorflow_datasets import (
TensorflowDatasetLoader, # noqa: F401
)
from langchain_community.document_loaders.text import (
TextLoader, # noqa: F401
)
from langchain_community.document_loaders.tidb import (
TiDBLoader, # noqa: F401
)
from langchain_community.document_loaders.tomarkdown import (
ToMarkdownLoader, # noqa: F401
)
from langchain_community.document_loaders.toml import (
TomlLoader, # noqa: F401
)
from langchain_community.document_loaders.trello import (
TrelloLoader, # noqa: F401
)
from langchain_community.document_loaders.tsv import (
UnstructuredTSVLoader, # noqa: F401
)
from langchain_community.document_loaders.twitter import (
TwitterTweetLoader, # noqa: F401
)
from langchain_community.document_loaders.unstructured import (
UnstructuredAPIFileIOLoader, # noqa: F401
UnstructuredAPIFileLoader, # noqa: F401
UnstructuredFileIOLoader, # noqa: F401
UnstructuredFileLoader, # noqa: F401
)
from langchain_community.document_loaders.url import (
UnstructuredURLLoader, # noqa: F401
)
from langchain_community.document_loaders.url_playwright import (
PlaywrightURLLoader, # noqa: F401
)
from langchain_community.document_loaders.url_selenium import (
SeleniumURLLoader, # noqa: F401
)
from langchain_community.document_loaders.vsdx import (
VsdxLoader, # noqa: F401
)
from langchain_community.document_loaders.weather import (
WeatherDataLoader, # noqa: F401
)
from langchain_community.document_loaders.web_base import (
WebBaseLoader, # noqa: F401
)
from langchain_community.document_loaders.whatsapp_chat import (
WhatsAppChatLoader, # noqa: F401
)
from langchain_community.document_loaders.wikipedia import (
WikipediaLoader, # noqa: F401
)
from langchain_community.document_loaders.word_document import (
Docx2txtLoader, # noqa: F401
UnstructuredWordDocumentLoader, # noqa: F401
)
from langchain_community.document_loaders.xml import (
UnstructuredXMLLoader, # noqa: F401
)
from langchain_community.document_loaders.xorbits import (
XorbitsLoader, # noqa: F401
)
from langchain_community.document_loaders.youtube import (
GoogleApiClient, # noqa: F401
GoogleApiYoutubeLoader, # noqa: F401
YoutubeLoader, # noqa: F401
)
from langchain_community.document_loaders.yuque import (
YuqueLoader, # noqa: F401
)
__all__ = [
"AZLyricsLoader",
"AcreomLoader",
"AirbyteCDKLoader",
"AirbyteGongLoader",
"AirbyteHubspotLoader",
"AirbyteJSONLoader",
"AirbyteSalesforceLoader",
"AirbyteShopifyLoader",
"AirbyteStripeLoader",
"AirbyteTypeformLoader",
"AirbyteZendeskSupportLoader",
"AirtableLoader",
"AmazonTextractPDFLoader",
"ApifyDatasetLoader",
"ArcGISLoader",
"ArxivLoader",
"AssemblyAIAudioLoaderById",
"AssemblyAIAudioTranscriptLoader",
"AstraDBLoader",
"AsyncChromiumLoader",
"AsyncHtmlLoader",
"AthenaLoader",
"AzureAIDataLoader",
"AzureAIDocumentIntelligenceLoader",
"AzureBlobStorageContainerLoader",
"AzureBlobStorageFileLoader",
"BSHTMLLoader",
"BibtexLoader",
"BigQueryLoader",
"BiliBiliLoader",
"BlackboardLoader",
"Blob",
"BlobLoader",
"BlockchainDocumentLoader",
"BraveSearchLoader",
"BrowserlessLoader",
"CSVLoader",
"CassandraLoader",
"ChatGPTLoader",
"CoNLLULoader",
"CollegeConfidentialLoader",
"ConcurrentLoader",
"ConfluenceLoader",
"CouchbaseLoader",
"CubeSemanticLoader",
"DataFrameLoader",
"DatadogLogsLoader",
"DiffbotLoader",
"DirectoryLoader",
"DiscordChatLoader",
"DocugamiLoader",
"DocusaurusLoader",
"Docx2txtLoader",
"DropboxLoader",
"DuckDBLoader",
"EtherscanLoader",
"EverNoteLoader",
"FacebookChatLoader",
"FaunaLoader",
"FigmaFileLoader",
"FileSystemBlobLoader",
"GCSDirectoryLoader",
"GCSFileLoader",
"GeoDataFrameLoader",
"GitHubIssuesLoader",
"GitLoader",
"GitbookLoader",
"GithubFileLoader",
"GoogleApiClient",
"GoogleApiYoutubeLoader",
"GoogleDriveLoader",
"GoogleSpeechToTextLoader",
"GutenbergLoader",
"HNLoader",
"HuggingFaceDatasetLoader",
"HuggingFaceModelLoader",
"IFixitLoader",
"IMSDbLoader",
"ImageCaptionLoader",
"IuguLoader",
"JSONLoader",
"JoplinLoader",
"LLMSherpaFileLoader",
"LakeFSLoader",
"LarkSuiteDocLoader",
"MHTMLLoader",
"MWDumpLoader",
"MastodonTootsLoader",
"MathpixPDFLoader",
"MaxComputeLoader",
"MergedDataLoader",
"ModernTreasuryLoader",
"MongodbLoader",
"NewsURLLoader",
"NotebookLoader",
"NotionDBLoader",
"NotionDirectoryLoader",
"OBSDirectoryLoader",
"OBSFileLoader",
"ObsidianLoader",
"OneDriveFileLoader",
"OneDriveLoader",
"OnlinePDFLoader",
"OpenCityDataLoader",
"OracleAutonomousDatabaseLoader",
"OutlookMessageLoader",
"PDFMinerLoader",
"PDFMinerPDFasHTMLLoader",
"PDFPlumberLoader",
"PagedPDFSplitter",
"PebbloSafeLoader",
"PlaywrightURLLoader",
"PolarsDataFrameLoader",
"PsychicLoader",
"PubMedLoader",
"PyMuPDFLoader",
"PyPDFDirectoryLoader",
"PyPDFLoader",
"PyPDFium2Loader",
"PySparkDataFrameLoader",
"PythonLoader",
"RSSFeedLoader",
"ReadTheDocsLoader",
"RecursiveUrlLoader",
"RedditPostsLoader",
"RoamLoader",
"RocksetLoader",
"S3DirectoryLoader",
"S3FileLoader",
"SQLDatabaseLoader",
"SRTLoader",
"SeleniumURLLoader",
"SharePointLoader",
"SitemapLoader",
"SlackDirectoryLoader",
"SnowflakeLoader",
"SpreedlyLoader",
"StripeLoader",
"SurrealDBLoader",
"TelegramChatApiLoader",
"TelegramChatFileLoader",
"TelegramChatLoader",
"TencentCOSDirectoryLoader",
"TencentCOSFileLoader",
"TensorflowDatasetLoader",
"TextLoader",
"TiDBLoader",
"ToMarkdownLoader",
"TomlLoader",
"TrelloLoader",
"TwitterTweetLoader",
"UnstructuredAPIFileIOLoader",
"UnstructuredAPIFileLoader",
"UnstructuredCHMLoader",
"UnstructuredCSVLoader",
"UnstructuredEPubLoader",
"UnstructuredEmailLoader",
"UnstructuredExcelLoader",
"UnstructuredFileIOLoader",
"UnstructuredFileLoader",
"UnstructuredHTMLLoader",
"UnstructuredImageLoader",
"UnstructuredMarkdownLoader",
"UnstructuredODTLoader",
"UnstructuredOrgModeLoader",
"UnstructuredPDFLoader",
"UnstructuredPowerPointLoader",
"UnstructuredRSTLoader",
"UnstructuredRTFLoader",
"UnstructuredTSVLoader",
"UnstructuredURLLoader",
"UnstructuredWordDocumentLoader",
"UnstructuredXMLLoader",
"VsdxLoader",
"WeatherDataLoader",
"WebBaseLoader",
"WhatsAppChatLoader",
"WikipediaLoader",
"XorbitsLoader",
"YoutubeAudioLoader",
"YoutubeLoader",
"YuqueLoader",
]
_module_lookup = {
"AZLyricsLoader": "langchain_community.document_loaders.azlyrics",

9
libs/community/langchain_community/document_loaders/concurrent.py
View File

@ -23,7 +23,10 @@ class ConcurrentLoader(GenericLoader):
"""Load and pars Documents concurrently."""
def __init__(
self, blob_loader: BlobLoader, blob_parser: BaseBlobParser, num_workers: int = 4
self,
blob_loader: BlobLoader, # type: ignore[valid-type]
blob_parser: BaseBlobParser,
num_workers: int = 4, # type: ignore[valid-type]
) -> None:
super().__init__(blob_loader, blob_parser)
self.num_workers = num_workers
@ -37,7 +40,7 @@ class ConcurrentLoader(GenericLoader):
) as executor:
futures = {
executor.submit(self.blob_parser.lazy_parse, blob)
for blob in self.blob_loader.yield_blobs()
for blob in self.blob_loader.yield_blobs() # type: ignore[attr-defined]
}
for future in concurrent.futures.as_completed(futures):
yield from future.result()
@ -69,7 +72,7 @@ class ConcurrentLoader(GenericLoader):
num_workers: Max number of concurrent workers to use.
parser_kwargs: Keyword arguments to pass to the parser.
"""
blob_loader = FileSystemBlobLoader(
blob_loader = FileSystemBlobLoader( # type: ignore[attr-defined, misc]
path,
glob=glob,
exclude=exclude,

4
libs/community/langchain_community/document_loaders/doc_intelligence.py
View File

@ -78,7 +78,7 @@ class AzureAIDocumentIntelligenceLoader(BaseLoader):
self.file_path = file_path
self.url_path = url_path
self.parser = AzureAIDocumentIntelligenceParser(
self.parser = AzureAIDocumentIntelligenceParser( # type: ignore[misc]
api_endpoint=api_endpoint,
api_key=api_key,
api_version=api_version,
@ -92,7 +92,7 @@ class AzureAIDocumentIntelligenceLoader(BaseLoader):
) -> Iterator[Document]:
"""Lazy load given path as pages."""
if self.file_path is not None:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
yield from self.parser.parse(blob)
else:
yield from self.parser.parse_url(self.url_path) # type: ignore[arg-type]

6
libs/community/langchain_community/document_loaders/generic.py
View File

@ -96,7 +96,7 @@ class GenericLoader(BaseLoader):
def __init__(
self,
blob_loader: BlobLoader,
blob_loader: BlobLoader, # type: ignore[valid-type]
blob_parser: BaseBlobParser,
) -> None:
"""A generic document loader.
@ -112,7 +112,7 @@ class GenericLoader(BaseLoader):
self,
) -> Iterator[Document]:
"""Load documents lazily. Use this when working at a large scale."""
for blob in self.blob_loader.yield_blobs():
for blob in self.blob_loader.yield_blobs(): # type: ignore[attr-defined]
yield from self.blob_parser.lazy_parse(blob)
def load_and_split(
@ -159,7 +159,7 @@ class GenericLoader(BaseLoader):
Returns:
A generic document loader.
"""
blob_loader = FileSystemBlobLoader(
blob_loader = FileSystemBlobLoader( # type: ignore[attr-defined, misc]
path,
glob=glob,
exclude=exclude,

10
libs/community/langchain_community/document_loaders/parsers/msword.py
View File

@ -9,7 +9,7 @@ from langchain_community.document_loaders.blob_loaders import Blob
class MsWordParser(BaseBlobParser):
"""Parse the Microsoft Word documents from a blob."""
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Parse a Microsoft Word document into the Document iterator.
Args:
@ -33,13 +33,13 @@ class MsWordParser(BaseBlobParser):
partition_docx
),
}
if blob.mimetype not in (
if blob.mimetype not in ( # type: ignore[attr-defined]
"application/msword",
"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
):
raise ValueError("This blob type is not supported for this parser.")
with blob.as_bytes_io() as word_document:
elements = mime_type_parser[blob.mimetype](file=word_document)
with blob.as_bytes_io() as word_document: # type: ignore[attr-defined]
elements = mime_type_parser[blob.mimetype](file=word_document) # type: ignore[attr-defined]
text = "\n\n".join([str(el) for el in elements])
metadata = {"source": blob.source}
metadata = {"source": blob.source} # type: ignore[attr-defined]
yield Document(page_content=text, metadata=metadata)

60
libs/community/langchain_community/document_loaders/parsers/pdf.py
View File

@ -87,17 +87,17 @@ class PyPDFParser(BaseBlobParser):
self.password = password
self.extract_images = extract_images
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
import pypdf
with blob.as_bytes_io() as pdf_file_obj:
with blob.as_bytes_io() as pdf_file_obj: # type: ignore[attr-defined]
pdf_reader = pypdf.PdfReader(pdf_file_obj, password=self.password)
yield from [
Document(
page_content=page.extract_text()
+ self._extract_images_from_page(page),
metadata={"source": blob.source, "page": page_number},
metadata={"source": blob.source, "page": page_number}, # type: ignore[attr-defined]
)
for page_number, page in enumerate(pdf_reader.pages)
]
@ -140,16 +140,16 @@ class PDFMinerParser(BaseBlobParser):
self.extract_images = extract_images
self.concatenate_pages = concatenate_pages
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
if not self.extract_images:
from pdfminer.high_level import extract_text
with blob.as_bytes_io() as pdf_file_obj:
with blob.as_bytes_io() as pdf_file_obj: # type: ignore[attr-defined]
if self.concatenate_pages:
text = extract_text(pdf_file_obj)
metadata = {"source": blob.source}
metadata = {"source": blob.source} # type: ignore[attr-defined]
yield Document(page_content=text, metadata=metadata)
else:
from pdfminer.pdfpage import PDFPage
@ -157,7 +157,7 @@ class PDFMinerParser(BaseBlobParser):
pages = PDFPage.get_pages(pdf_file_obj)
for i, _ in enumerate(pages):
text = extract_text(pdf_file_obj, page_numbers=[i])
metadata = {"source": blob.source, "page": str(i)}
metadata = {"source": blob.source, "page": str(i)} # type: ignore[attr-defined]
yield Document(page_content=text, metadata=metadata)
else:
import io
@ -168,7 +168,7 @@ class PDFMinerParser(BaseBlobParser):
from pdfminer.pdfpage import PDFPage
text_io = io.StringIO()
with blob.as_bytes_io() as pdf_file_obj:
with blob.as_bytes_io() as pdf_file_obj: # type: ignore[attr-defined]
pages = PDFPage.get_pages(pdf_file_obj)
rsrcmgr = PDFResourceManager()
device_for_text = TextConverter(rsrcmgr, text_io, laparams=LAParams())
@ -183,7 +183,7 @@ class PDFMinerParser(BaseBlobParser):
)
text_io.truncate(0)
text_io.seek(0)
metadata = {"source": blob.source, "page": str(i)}
metadata = {"source": blob.source, "page": str(i)} # type: ignore[attr-defined]
yield Document(page_content=content, metadata=metadata)
def _extract_images_from_page(self, page: pdfminer.layout.LTPage) -> str:
@ -231,12 +231,12 @@ class PyMuPDFParser(BaseBlobParser):
self.text_kwargs = text_kwargs or {}
self.extract_images = extract_images
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
import fitz
with blob.as_bytes_io() as file_path:
if blob.data is None:
with blob.as_bytes_io() as file_path: # type: ignore[attr-defined]
if blob.data is None: # type: ignore[attr-defined]
doc = fitz.open(file_path)
else:
doc = fitz.open(stream=file_path, filetype="pdf")
@ -247,8 +247,8 @@ class PyMuPDFParser(BaseBlobParser):
+ self._extract_images_from_page(doc, page),
metadata=dict(
{
"source": blob.source,
"file_path": blob.source,
"source": blob.source, # type: ignore[attr-defined]
"file_path": blob.source, # type: ignore[attr-defined]
"page": page.number,
"total_pages": len(doc),
},
@ -297,13 +297,13 @@ class PyPDFium2Parser(BaseBlobParser):
)
self.extract_images = extract_images
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
import pypdfium2
# pypdfium2 is really finicky with respect to closing things,
# if done incorrectly creates seg faults.
with blob.as_bytes_io() as file_path:
with blob.as_bytes_io() as file_path: # type: ignore[attr-defined]
pdf_reader = pypdfium2.PdfDocument(file_path, autoclose=True)
try:
for page_number, page in enumerate(pdf_reader):
@ -312,7 +312,7 @@ class PyPDFium2Parser(BaseBlobParser):
text_page.close()
content += "\n" + self._extract_images_from_page(page)
page.close()
metadata = {"source": blob.source, "page": page_number}
metadata = {"source": blob.source, "page": page_number} # type: ignore[attr-defined]
yield Document(page_content=content, metadata=metadata)
finally:
pdf_reader.close()
@ -349,11 +349,11 @@ class PDFPlumberParser(BaseBlobParser):
self.dedupe = dedupe
self.extract_images = extract_images
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
import pdfplumber
with blob.as_bytes_io() as file_path:
with blob.as_bytes_io() as file_path: # type: ignore[attr-defined]
doc = pdfplumber.open(file_path) # open document
yield from [
@ -363,8 +363,8 @@ class PDFPlumberParser(BaseBlobParser):
+ self._extract_images_from_page(page),
metadata=dict(
{
"source": blob.source,
"file_path": blob.source,
"source": blob.source, # type: ignore[attr-defined]
"file_path": blob.source, # type: ignore[attr-defined]
"page": page.page_number - 1,
"total_pages": len(doc.pages),
},
@ -514,14 +514,14 @@ class AmazonTextractPDFParser(BaseBlobParser):
else:
self.boto3_textract_client = client
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Iterates over the Blob pages and returns an Iterator with a Document
for each page, like the other parsers If multi-page document, blob.path
has to be set to the S3 URI and for single page docs
the blob.data is taken
"""
url_parse_result = urlparse(str(blob.path)) if blob.path else None
url_parse_result = urlparse(str(blob.path)) if blob.path else None # type: ignore[attr-defined]
# Either call with S3 path (multi-page) or with bytes (single-page)
if (
url_parse_result
@ -529,13 +529,13 @@ class AmazonTextractPDFParser(BaseBlobParser):
and url_parse_result.netloc
):
textract_response_json = self.tc.call_textract(
input_document=str(blob.path),
input_document=str(blob.path), # type: ignore[attr-defined]
features=self.textract_features,
boto3_textract_client=self.boto3_textract_client,
)
else:
textract_response_json = self.tc.call_textract(
input_document=blob.as_bytes(),
input_document=blob.as_bytes(), # type: ignore[attr-defined]
features=self.textract_features,
call_mode=self.tc.Textract_Call_Mode.FORCE_SYNC,
boto3_textract_client=self.boto3_textract_client,
@ -546,7 +546,7 @@ class AmazonTextractPDFParser(BaseBlobParser):
for idx, page in enumerate(document.pages):
yield Document(
page_content=page.get_text(config=self.linearization_config),
metadata={"source": blob.source, "page": idx + 1},
metadata={"source": blob.source, "page": idx + 1}, # type: ignore[attr-defined]
)
@ -566,23 +566,23 @@ class DocumentIntelligenceParser(BaseBlobParser):
self.client = client
self.model = model
def _generate_docs(self, blob: Blob, result: Any) -> Iterator[Document]:
def _generate_docs(self, blob: Blob, result: Any) -> Iterator[Document]: # type: ignore[valid-type]
for p in result.pages:
content = " ".join([line.content for line in p.lines])
d = Document(
page_content=content,
metadata={
"source": blob.source,
"source": blob.source, # type: ignore[attr-defined]
"page": p.page_number,
},
)
yield d
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
with blob.as_bytes_io() as file_obj:
with blob.as_bytes_io() as file_obj: # type: ignore[attr-defined]
poller = self.client.begin_analyze_document(self.model, file_obj)
result = poller.result()

4
libs/community/langchain_community/document_loaders/parsers/txt.py
View File

@ -10,6 +10,6 @@ from langchain_community.document_loaders.blob_loaders import Blob
class TextParser(BaseBlobParser):
"""Parser for text blobs."""
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
def lazy_parse(self, blob: Blob) -> Iterator[Document]: # type: ignore[valid-type]
"""Lazily parse the blob."""
yield Document(page_content=blob.as_string(), metadata={"source": blob.source})
yield Document(page_content=blob.as_string(), metadata={"source": blob.source}) # type: ignore[attr-defined]

40
libs/community/langchain_community/document_loaders/pdf.py
View File

@ -187,9 +187,9 @@ class PyPDFLoader(BasePDFLoader):
) -> Iterator[Document]:
"""Lazy load given path as pages."""
if self.web_path:
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path)
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path) # type: ignore[attr-defined]
else:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
yield from self.parser.parse(blob)
@ -212,9 +212,9 @@ class PyPDFium2Loader(BasePDFLoader):
) -> Iterator[Document]:
"""Lazy load given path as pages."""
if self.web_path:
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path)
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path) # type: ignore[attr-defined]
else:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
yield from self.parser.parse(blob)
@ -301,9 +301,9 @@ class PDFMinerLoader(BasePDFLoader):
) -> Iterator[Document]:
"""Lazily load documents."""
if self.web_path:
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path)
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path) # type: ignore[attr-defined]
else:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
yield from self.parser.parse(blob)
@ -378,9 +378,9 @@ class PyMuPDFLoader(BasePDFLoader):
text_kwargs=text_kwargs, extract_images=self.extract_images
)
if self.web_path:
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path)
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path) # type: ignore[attr-defined]
else:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
yield from parser.lazy_parse(blob)
def load(self, **kwargs: Any) -> List[Document]:
@ -574,9 +574,9 @@ class PDFPlumberLoader(BasePDFLoader):
extract_images=self.extract_images,
)
if self.web_path:
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path)
blob = Blob.from_data(open(self.file_path, "rb").read(), path=self.web_path) # type: ignore[attr-defined]
else:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
return parser.parse(blob)
@ -691,9 +691,9 @@ class AmazonTextractPDFLoader(BasePDFLoader):
# raises ValueError when multi-page and not on S3"""
if self.web_path and self._is_s3_url(self.web_path):
blob = Blob(path=self.web_path)
blob = Blob(path=self.web_path) # type: ignore[misc]
else:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
if AmazonTextractPDFLoader._get_number_of_pages(blob) > 1:
raise ValueError(
f"the file {blob.path} is a multi-page document, \
@ -704,7 +704,7 @@ class AmazonTextractPDFLoader(BasePDFLoader):
yield from self.parser.parse(blob)
@staticmethod
def _get_number_of_pages(blob: Blob) -> int:
def _get_number_of_pages(blob: Blob) -> int: # type: ignore[valid-type]
try:
import pypdf
from PIL import Image, ImageSequence
@ -714,20 +714,20 @@ class AmazonTextractPDFLoader(BasePDFLoader):
"Could not import pypdf or Pilloe python package. "
"Please install it with `pip install pypdf Pillow`."
)
if blob.mimetype == "application/pdf":
with blob.as_bytes_io() as input_pdf_file:
if blob.mimetype == "application/pdf": # type: ignore[attr-defined]
with blob.as_bytes_io() as input_pdf_file: # type: ignore[attr-defined]
pdf_reader = pypdf.PdfReader(input_pdf_file)
return len(pdf_reader.pages)
elif blob.mimetype == "image/tiff":
elif blob.mimetype == "image/tiff": # type: ignore[attr-defined]
num_pages = 0
img = Image.open(blob.as_bytes())
img = Image.open(blob.as_bytes()) # type: ignore[attr-defined]
for _, _ in enumerate(ImageSequence.Iterator(img)):
num_pages += 1
return num_pages
elif blob.mimetype in ["image/png", "image/jpeg"]:
elif blob.mimetype in ["image/png", "image/jpeg"]: # type: ignore[attr-defined]
return 1
else:
raise ValueError(f"unsupported mime type: {blob.mimetype}")
raise ValueError(f"unsupported mime type: {blob.mimetype}") # type: ignore[attr-defined]
class DocumentIntelligenceLoader(BasePDFLoader):
@ -778,7 +778,7 @@ class DocumentIntelligenceLoader(BasePDFLoader):
self,
) -> Iterator[Document]:
"""Lazy load given path as pages."""
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
yield from self.parser.parse(blob)

4
libs/community/langchain_community/document_loaders/vsdx.py
View File

@ -37,7 +37,7 @@ class VsdxLoader(BaseLoader, ABC):
elif not os.path.isfile(self.file_path):
raise ValueError("File path %s is not a valid file or url" % self.file_path)
self.parser = VsdxParser()
self.parser = VsdxParser() # type: ignore[misc]
def __del__(self) -> None:
if hasattr(self, "temp_file"):
@ -50,5 +50,5 @@ class VsdxLoader(BaseLoader, ABC):
return bool(parsed.netloc) and bool(parsed.scheme)
def load(self) -> List[Document]:
blob = Blob.from_path(self.file_path)
blob = Blob.from_path(self.file_path) # type: ignore[attr-defined]
return list(self.parser.parse(blob))

51
libs/community/langchain_community/document_transformers/__init__.py
View File

@ -16,7 +16,56 @@
""" # noqa: E501
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.document_transformers.beautiful_soup_transformer import (
BeautifulSoupTransformer, # noqa: F401
)
from langchain_community.document_transformers.doctran_text_extract import (
DoctranPropertyExtractor, # noqa: F401
)
from langchain_community.document_transformers.doctran_text_qa import (
DoctranQATransformer, # noqa: F401
)
from langchain_community.document_transformers.doctran_text_translate import (
DoctranTextTranslator, # noqa: F401
)
from langchain_community.document_transformers.embeddings_redundant_filter import (
EmbeddingsClusteringFilter, # noqa: F401
EmbeddingsRedundantFilter, # noqa: F401
get_stateful_documents, # noqa: F401
)
from langchain_community.document_transformers.google_translate import (
GoogleTranslateTransformer, # noqa: F401
)
from langchain_community.document_transformers.html2text import (
Html2TextTransformer, # noqa: F401
)
from langchain_community.document_transformers.long_context_reorder import (
LongContextReorder, # noqa: F401
)
from langchain_community.document_transformers.nuclia_text_transform import (
NucliaTextTransformer, # noqa: F401
)
from langchain_community.document_transformers.openai_functions import (
OpenAIMetadataTagger, # noqa: F401
)
__all__ = [
"BeautifulSoupTransformer",
"DoctranPropertyExtractor",
"DoctranQATransformer",
"DoctranTextTranslator",
"EmbeddingsClusteringFilter",
"EmbeddingsRedundantFilter",
"GoogleTranslateTransformer",
"Html2TextTransformer",
"LongContextReorder",
"NucliaTextTransformer",
"OpenAIMetadataTagger",
"get_stateful_documents",
]
_module_lookup = {
"BeautifulSoupTransformer": "langchain_community.document_transformers.beautiful_soup_transformer", # noqa: E501

276
libs/community/langchain_community/embeddings/__init__.py
View File

@ -10,10 +10,282 @@ from different APIs and services.
Embeddings --> <name>Embeddings # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings
"""
import importlib
import logging
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.embeddings.aleph_alpha import (
AlephAlphaAsymmetricSemanticEmbedding, # noqa: F401
AlephAlphaSymmetricSemanticEmbedding, # noqa: F401
)
from langchain_community.embeddings.anyscale import (
AnyscaleEmbeddings, # noqa: F401
)
from langchain_community.embeddings.awa import (
AwaEmbeddings, # noqa: F401
)
from langchain_community.embeddings.azure_openai import (
AzureOpenAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.baichuan import (
BaichuanTextEmbeddings, # noqa: F401
)
from langchain_community.embeddings.baidu_qianfan_endpoint import (
QianfanEmbeddingsEndpoint, # noqa: F401
)
from langchain_community.embeddings.bedrock import (
BedrockEmbeddings, # noqa: F401
)
from langchain_community.embeddings.bookend import (
BookendEmbeddings, # noqa: F401
)
from langchain_community.embeddings.clarifai import (
ClarifaiEmbeddings, # noqa: F401
)
from langchain_community.embeddings.cohere import (
CohereEmbeddings, # noqa: F401
)
from langchain_community.embeddings.dashscope import (
DashScopeEmbeddings, # noqa: F401
)
from langchain_community.embeddings.databricks import (
DatabricksEmbeddings, # noqa: F401
)
from langchain_community.embeddings.deepinfra import (
DeepInfraEmbeddings, # noqa: F401
)
from langchain_community.embeddings.edenai import (
EdenAiEmbeddings, # noqa: F401
)
from langchain_community.embeddings.elasticsearch import (
ElasticsearchEmbeddings, # noqa: F401
)
from langchain_community.embeddings.embaas import (
EmbaasEmbeddings, # noqa: F401
)
from langchain_community.embeddings.ernie import (
ErnieEmbeddings, # noqa: F401
)
from langchain_community.embeddings.fake import (
DeterministicFakeEmbedding, # noqa: F401
FakeEmbeddings, # noqa: F401
)
from langchain_community.embeddings.fastembed import (
FastEmbedEmbeddings, # noqa: F401
)
from langchain_community.embeddings.gigachat import (
GigaChatEmbeddings, # noqa: F401
)
from langchain_community.embeddings.google_palm import (
GooglePalmEmbeddings, # noqa: F401
)
from langchain_community.embeddings.gpt4all import (
GPT4AllEmbeddings, # noqa: F401
)
from langchain_community.embeddings.gradient_ai import (
GradientEmbeddings, # noqa: F401
)
from langchain_community.embeddings.huggingface import (
HuggingFaceBgeEmbeddings, # noqa: F401
HuggingFaceEmbeddings, # noqa: F401
HuggingFaceInferenceAPIEmbeddings, # noqa: F401
HuggingFaceInstructEmbeddings, # noqa: F401
)
from langchain_community.embeddings.huggingface_hub import (
HuggingFaceHubEmbeddings, # noqa: F401
)
from langchain_community.embeddings.infinity import (
InfinityEmbeddings, # noqa: F401
)
from langchain_community.embeddings.infinity_local import (
InfinityEmbeddingsLocal, # noqa: F401
)
from langchain_community.embeddings.itrex import (
QuantizedBgeEmbeddings, # noqa: F401
)
from langchain_community.embeddings.javelin_ai_gateway import (
JavelinAIGatewayEmbeddings, # noqa: F401
)
from langchain_community.embeddings.jina import (
JinaEmbeddings, # noqa: F401
)
from langchain_community.embeddings.johnsnowlabs import (
JohnSnowLabsEmbeddings, # noqa: F401
)
from langchain_community.embeddings.laser import (
LaserEmbeddings, # noqa: F401
)
from langchain_community.embeddings.llamacpp import (
LlamaCppEmbeddings, # noqa: F401
)
from langchain_community.embeddings.llamafile import (
LlamafileEmbeddings, # noqa: F401
)
from langchain_community.embeddings.llm_rails import (
LLMRailsEmbeddings, # noqa: F401
)
from langchain_community.embeddings.localai import (
LocalAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.minimax import (
MiniMaxEmbeddings, # noqa: F401
)
from langchain_community.embeddings.mlflow import (
MlflowCohereEmbeddings, # noqa: F401
MlflowEmbeddings, # noqa: F401
)
from langchain_community.embeddings.mlflow_gateway import (
MlflowAIGatewayEmbeddings, # noqa: F401
)
from langchain_community.embeddings.modelscope_hub import (
ModelScopeEmbeddings, # noqa: F401
)
from langchain_community.embeddings.mosaicml import (
MosaicMLInstructorEmbeddings, # noqa: F401
)
from langchain_community.embeddings.nemo import (
NeMoEmbeddings, # noqa: F401
)
from langchain_community.embeddings.nlpcloud import (
NLPCloudEmbeddings, # noqa: F401
)
from langchain_community.embeddings.oci_generative_ai import (
OCIGenAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.octoai_embeddings import (
OctoAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.ollama import (
OllamaEmbeddings, # noqa: F401
)
from langchain_community.embeddings.openai import (
OpenAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.openvino import (
OpenVINOBgeEmbeddings, # noqa: F401
OpenVINOEmbeddings, # noqa: F401
)
from langchain_community.embeddings.optimum_intel import (
QuantizedBiEncoderEmbeddings, # noqa: F401
)
from langchain_community.embeddings.premai import (
PremAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.sagemaker_endpoint import (
SagemakerEndpointEmbeddings, # noqa: F401
)
from langchain_community.embeddings.self_hosted import (
SelfHostedEmbeddings, # noqa: F401
)
from langchain_community.embeddings.self_hosted_hugging_face import (
SelfHostedHuggingFaceEmbeddings, # noqa: F401
SelfHostedHuggingFaceInstructEmbeddings, # noqa: F401
)
from langchain_community.embeddings.sentence_transformer import (
SentenceTransformerEmbeddings, # noqa: F401
)
from langchain_community.embeddings.solar import (
SolarEmbeddings, # noqa: F401
)
from langchain_community.embeddings.spacy_embeddings import (
SpacyEmbeddings, # noqa: F401
)
from langchain_community.embeddings.sparkllm import (
SparkLLMTextEmbeddings, # noqa: F401
)
from langchain_community.embeddings.tensorflow_hub import (
TensorflowHubEmbeddings, # noqa: F401
)
from langchain_community.embeddings.vertexai import (
VertexAIEmbeddings, # noqa: F401
)
from langchain_community.embeddings.volcengine import (
VolcanoEmbeddings, # noqa: F401
)
from langchain_community.embeddings.voyageai import (
VoyageEmbeddings, # noqa: F401
)
from langchain_community.embeddings.xinference import (
XinferenceEmbeddings, # noqa: F401
)
from langchain_community.embeddings.yandex import (
YandexGPTEmbeddings, # noqa: F401
)
__all__ = [
"AlephAlphaAsymmetricSemanticEmbedding",
"AlephAlphaSymmetricSemanticEmbedding",
"AnyscaleEmbeddings",
"AwaEmbeddings",
"AzureOpenAIEmbeddings",
"BaichuanTextEmbeddings",
"BedrockEmbeddings",
"BookendEmbeddings",
"ClarifaiEmbeddings",
"CohereEmbeddings",
"DashScopeEmbeddings",
"DatabricksEmbeddings",
"DeepInfraEmbeddings",
"DeterministicFakeEmbedding",
"EdenAiEmbeddings",
"ElasticsearchEmbeddings",
"EmbaasEmbeddings",
"ErnieEmbeddings",
"FakeEmbeddings",
"FastEmbedEmbeddings",
"GPT4AllEmbeddings",
"GigaChatEmbeddings",
"GooglePalmEmbeddings",
"GradientEmbeddings",
"HuggingFaceBgeEmbeddings",
"HuggingFaceEmbeddings",
"HuggingFaceHubEmbeddings",
"HuggingFaceInferenceAPIEmbeddings",
"HuggingFaceInstructEmbeddings",
"InfinityEmbeddings",
"InfinityEmbeddingsLocal",
"JavelinAIGatewayEmbeddings",
"JinaEmbeddings",
"JohnSnowLabsEmbeddings",
"LLMRailsEmbeddings",
"LaserEmbeddings",
"LlamaCppEmbeddings",
"LlamafileEmbeddings",
"LocalAIEmbeddings",
"MiniMaxEmbeddings",
"MlflowAIGatewayEmbeddings",
"MlflowCohereEmbeddings",
"MlflowEmbeddings",
"ModelScopeEmbeddings",
"MosaicMLInstructorEmbeddings",
"NLPCloudEmbeddings",
"NeMoEmbeddings",
"OCIGenAIEmbeddings",
"OctoAIEmbeddings",
"OllamaEmbeddings",
"OpenAIEmbeddings",
"OpenVINOBgeEmbeddings",
"OpenVINOEmbeddings",
"PremAIEmbeddings",
"QianfanEmbeddingsEndpoint",
"QuantizedBgeEmbeddings",
"QuantizedBiEncoderEmbeddings",
"SagemakerEndpointEmbeddings",
"SelfHostedEmbeddings",
"SelfHostedHuggingFaceEmbeddings",
"SelfHostedHuggingFaceInstructEmbeddings",
"SentenceTransformerEmbeddings",
"SolarEmbeddings",
"SpacyEmbeddings",
"SparkLLMTextEmbeddings",
"TensorflowHubEmbeddings",
"VertexAIEmbeddings",
"VolcanoEmbeddings",
"VoyageEmbeddings",
"XinferenceEmbeddings",
"YandexGPTEmbeddings",
]
_module_lookup = {
"AlephAlphaAsymmetricSemanticEmbedding": "langchain_community.embeddings.aleph_alpha", # noqa: E501

63
libs/community/langchain_community/graphs/__init__.py
View File

@ -1,7 +1,68 @@
"""**Graphs** provide a natural language interface to graph databases."""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.graphs.arangodb_graph import (
ArangoGraph, # noqa: F401
)
from langchain_community.graphs.falkordb_graph import (
FalkorDBGraph, # noqa: F401
)
from langchain_community.graphs.gremlin_graph import (
GremlinGraph, # noqa: F401
)
from langchain_community.graphs.hugegraph import (
HugeGraph, # noqa: F401
)
from langchain_community.graphs.kuzu_graph import (
KuzuGraph, # noqa: F401
)
from langchain_community.graphs.memgraph_graph import (
MemgraphGraph, # noqa: F401
)
from langchain_community.graphs.nebula_graph import (
NebulaGraph, # noqa: F401
)
from langchain_community.graphs.neo4j_graph import (
Neo4jGraph, # noqa: F401
)
from langchain_community.graphs.neptune_graph import (
NeptuneGraph, # noqa: F401
)
from langchain_community.graphs.neptune_rdf_graph import (
NeptuneRdfGraph, # noqa: F401
)
from langchain_community.graphs.networkx_graph import (
NetworkxEntityGraph, # noqa: F401
)
from langchain_community.graphs.ontotext_graphdb_graph import (
OntotextGraphDBGraph, # noqa: F401
)
from langchain_community.graphs.rdf_graph import (
RdfGraph, # noqa: F401
)
from langchain_community.graphs.tigergraph_graph import (
TigerGraph, # noqa: F401
)
__all__ = [
"ArangoGraph",
"FalkorDBGraph",
"GremlinGraph",
"HugeGraph",
"KuzuGraph",
"MemgraphGraph",
"NebulaGraph",
"Neo4jGraph",
"NeptuneGraph",
"NeptuneRdfGraph",
"NetworkxEntityGraph",
"OntotextGraphDBGraph",
"RdfGraph",
"TigerGraph",
]
_module_lookup = {
"ArangoGraph": "langchain_community.graphs.arangodb_graph",

3
libs/community/langchain_community/llms/solar.py
View File

@ -32,6 +32,8 @@ class _SolarClient(BaseModel):
class SolarCommon(BaseModel):
"""Common configuration for Solar LLMs."""
_client: _SolarClient
base_url: str = SOLAR_SERVICE_URL_BASE
solar_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
@ -92,6 +94,7 @@ class SolarCommon(BaseModel):
class Solar(SolarCommon, LLM):
"""Solar large language models.
To use, you should have the environment variable
``SOLAR_API_KEY`` set with your API key.
Referenced from https://console.upstage.ai/services/solar

153
libs/community/langchain_community/retrievers/__init__.py
View File

@ -19,7 +19,158 @@ the backbone of a retriever, but there are other types of retrievers as well.
"""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.retrievers.arcee import (
ArceeRetriever, # noqa: F401
)
from langchain_community.retrievers.arxiv import (
ArxivRetriever, # noqa: F401
)
from langchain_community.retrievers.azure_cognitive_search import (
AzureCognitiveSearchRetriever, # noqa: F401
)
from langchain_community.retrievers.bedrock import (
AmazonKnowledgeBasesRetriever, # noqa: F401
)
from langchain_community.retrievers.bm25 import (
BM25Retriever, # noqa: F401
)
from langchain_community.retrievers.breebs import (
BreebsRetriever, # noqa: F401
)
from langchain_community.retrievers.chaindesk import (
ChaindeskRetriever, # noqa: F401
)
from langchain_community.retrievers.chatgpt_plugin_retriever import (
ChatGPTPluginRetriever, # noqa: F401
)
from langchain_community.retrievers.cohere_rag_retriever import (
CohereRagRetriever, # noqa: F401
)
from langchain_community.retrievers.docarray import (
DocArrayRetriever, # noqa: F401
)
from langchain_community.retrievers.dria_index import (
DriaRetriever, # noqa: F401
)
from langchain_community.retrievers.elastic_search_bm25 import (
ElasticSearchBM25Retriever, # noqa: F401
)
from langchain_community.retrievers.embedchain import (
EmbedchainRetriever, # noqa: F401
)
from langchain_community.retrievers.google_cloud_documentai_warehouse import (
GoogleDocumentAIWarehouseRetriever, # noqa: F401
)
from langchain_community.retrievers.google_vertex_ai_search import (
GoogleCloudEnterpriseSearchRetriever, # noqa: F401
GoogleVertexAIMultiTurnSearchRetriever, # noqa: F401
GoogleVertexAISearchRetriever, # noqa: F401
)
from langchain_community.retrievers.kay import (
KayAiRetriever, # noqa: F401
)
from langchain_community.retrievers.kendra import (
AmazonKendraRetriever, # noqa: F401
)
from langchain_community.retrievers.knn import (
KNNRetriever, # noqa: F401
)
from langchain_community.retrievers.llama_index import (
LlamaIndexGraphRetriever, # noqa: F401
LlamaIndexRetriever, # noqa: F401
)
from langchain_community.retrievers.metal import (
MetalRetriever, # noqa: F401
)
from langchain_community.retrievers.milvus import (
MilvusRetriever, # noqa: F401
)
from langchain_community.retrievers.outline import (
OutlineRetriever, # noqa: F401
)
from langchain_community.retrievers.pinecone_hybrid_search import (
PineconeHybridSearchRetriever, # noqa: F401
)
from langchain_community.retrievers.pubmed import (
PubMedRetriever, # noqa: F401
)
from langchain_community.retrievers.qdrant_sparse_vector_retriever import (
QdrantSparseVectorRetriever, # noqa: F401
)
from langchain_community.retrievers.remote_retriever import (
RemoteLangChainRetriever, # noqa: F401
)
from langchain_community.retrievers.svm import (
SVMRetriever, # noqa: F401
)
from langchain_community.retrievers.tavily_search_api import (
TavilySearchAPIRetriever, # noqa: F401
)
from langchain_community.retrievers.tfidf import (
TFIDFRetriever, # noqa: F401
)
from langchain_community.retrievers.vespa_retriever import (
VespaRetriever, # noqa: F401
)
from langchain_community.retrievers.weaviate_hybrid_search import (
WeaviateHybridSearchRetriever, # noqa: F401
)
from langchain_community.retrievers.wikipedia import (
WikipediaRetriever, # noqa: F401
)
from langchain_community.retrievers.you import (
YouRetriever, # noqa: F401
)
from langchain_community.retrievers.zep import (
ZepRetriever, # noqa: F401
)
from langchain_community.retrievers.zilliz import (
ZillizRetriever, # noqa: F401
)
__all__ = [
"AmazonKendraRetriever",
"AmazonKnowledgeBasesRetriever",
"ArceeRetriever",
"ArxivRetriever",
"AzureCognitiveSearchRetriever",
"BM25Retriever",
"BreebsRetriever",
"ChaindeskRetriever",
"ChatGPTPluginRetriever",
"CohereRagRetriever",
"DocArrayRetriever",
"DriaRetriever",
"ElasticSearchBM25Retriever",
"EmbedchainRetriever",
"GoogleCloudEnterpriseSearchRetriever",
"GoogleDocumentAIWarehouseRetriever",
"GoogleVertexAIMultiTurnSearchRetriever",
"GoogleVertexAISearchRetriever",
"KNNRetriever",
"KayAiRetriever",
"LlamaIndexGraphRetriever",
"LlamaIndexRetriever",
"MetalRetriever",
"MilvusRetriever",
"OutlineRetriever",
"PineconeHybridSearchRetriever",
"PubMedRetriever",
"QdrantSparseVectorRetriever",
"RemoteLangChainRetriever",
"SVMRetriever",
"TFIDFRetriever",
"TavilySearchAPIRetriever",
"VespaRetriever",
"WeaviateHybridSearchRetriever",
"WikipediaRetriever",
"YouRetriever",
"ZepRetriever",
"ZillizRetriever",
]
_module_lookup = {
"AmazonKendraRetriever": "langchain_community.retrievers.kendra",

27
libs/community/langchain_community/storage/__init__.py
View File

@ -15,7 +15,32 @@ The primary goal of these storages is to support caching.
""" # noqa: E501
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.storage.astradb import (
AstraDBByteStore, # noqa: F401
AstraDBStore, # noqa: F401
)
from langchain_community.storage.mongodb import (
MongoDBStore, # noqa: F401
)
from langchain_community.storage.redis import (
RedisStore, # noqa: F401
)
from langchain_community.storage.upstash_redis import (
UpstashRedisByteStore, # noqa: F401
UpstashRedisStore, # noqa: F401
)
__all__ = [
"AstraDBByteStore",
"AstraDBStore",
"MongoDBStore",
"RedisStore",
"UpstashRedisByteStore",
"UpstashRedisStore",
]
_module_lookup = {
"AstraDBByteStore": "langchain_community.storage.astradb",

428
libs/community/langchain_community/tools/__init__.py
View File

@ -18,7 +18,433 @@ tool for the job.
"""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_core.tools import (
BaseTool, # noqa: F401
StructuredTool, # noqa: F401
Tool, # noqa: F401
tool, # noqa: F401
)
from langchain_community.tools.ainetwork.app import (
AINAppOps, # noqa: F401
)
from langchain_community.tools.ainetwork.owner import (
AINOwnerOps, # noqa: F401
)
from langchain_community.tools.ainetwork.rule import (
AINRuleOps, # noqa: F401
)
from langchain_community.tools.ainetwork.transfer import (
AINTransfer, # noqa: F401
)
from langchain_community.tools.ainetwork.value import (
AINValueOps, # noqa: F401
)
from langchain_community.tools.arxiv.tool import (
ArxivQueryRun, # noqa: F401
)
from langchain_community.tools.azure_ai_services import (
AzureAiServicesDocumentIntelligenceTool, # noqa: F401
AzureAiServicesImageAnalysisTool, # noqa: F401
AzureAiServicesSpeechToTextTool, # noqa: F401
AzureAiServicesTextAnalyticsForHealthTool, # noqa: F401
AzureAiServicesTextToSpeechTool, # noqa: F401
)
from langchain_community.tools.azure_cognitive_services import (
AzureCogsFormRecognizerTool, # noqa: F401
AzureCogsImageAnalysisTool, # noqa: F401
AzureCogsSpeech2TextTool, # noqa: F401
AzureCogsText2SpeechTool, # noqa: F401
AzureCogsTextAnalyticsHealthTool, # noqa: F401
)
from langchain_community.tools.bearly.tool import (
BearlyInterpreterTool, # noqa: F401
)
from langchain_community.tools.bing_search.tool import (
BingSearchResults, # noqa: F401
BingSearchRun, # noqa: F401
)
from langchain_community.tools.brave_search.tool import (
BraveSearch, # noqa: F401
)
from langchain_community.tools.cogniswitch.tool import (
CogniswitchKnowledgeRequest, # noqa: F401
CogniswitchKnowledgeSourceFile, # noqa: F401
CogniswitchKnowledgeSourceURL, # noqa: F401
CogniswitchKnowledgeStatus, # noqa: F401
)
from langchain_community.tools.connery import (
ConneryAction, # noqa: F401
)
from langchain_community.tools.convert_to_openai import (
format_tool_to_openai_function, # noqa: F401
)
from langchain_community.tools.ddg_search.tool import (
DuckDuckGoSearchResults, # noqa: F401
DuckDuckGoSearchRun, # noqa: F401
)
from langchain_community.tools.e2b_data_analysis.tool import (
E2BDataAnalysisTool, # noqa: F401
)
from langchain_community.tools.edenai import (
EdenAiExplicitImageTool, # noqa: F401
EdenAiObjectDetectionTool, # noqa: F401
EdenAiParsingIDTool, # noqa: F401
EdenAiParsingInvoiceTool, # noqa: F401
EdenAiSpeechToTextTool, # noqa: F401
EdenAiTextModerationTool, # noqa: F401
EdenAiTextToSpeechTool, # noqa: F401
EdenaiTool, # noqa: F401
)
from langchain_community.tools.eleven_labs.text2speech import (
ElevenLabsText2SpeechTool, # noqa: F401
)
from langchain_community.tools.file_management import (
CopyFileTool, # noqa: F401
DeleteFileTool, # noqa: F401
FileSearchTool, # noqa: F401
ListDirectoryTool, # noqa: F401
MoveFileTool, # noqa: F401
ReadFileTool, # noqa: F401
WriteFileTool, # noqa: F401
)
from langchain_community.tools.gmail import (
GmailCreateDraft, # noqa: F401
GmailGetMessage, # noqa: F401
GmailGetThread, # noqa: F401
GmailSearch, # noqa: F401
GmailSendMessage, # noqa: F401
)
from langchain_community.tools.google_cloud.texttospeech import (
GoogleCloudTextToSpeechTool, # noqa: F401
)
from langchain_community.tools.google_places.tool import (
GooglePlacesTool, # noqa: F401
)
from langchain_community.tools.google_search.tool import (
GoogleSearchResults, # noqa: F401
GoogleSearchRun, # noqa: F401
)
from langchain_community.tools.google_serper.tool import (
GoogleSerperResults, # noqa: F401
GoogleSerperRun, # noqa: F401
)
from langchain_community.tools.graphql.tool import (
BaseGraphQLTool, # noqa: F401
)
from langchain_community.tools.human.tool import (
HumanInputRun, # noqa: F401
)
from langchain_community.tools.ifttt import (
IFTTTWebhook, # noqa: F401
)
from langchain_community.tools.interaction.tool import (
StdInInquireTool, # noqa: F401
)
from langchain_community.tools.jira.tool import (
JiraAction, # noqa: F401
)
from langchain_community.tools.json.tool import (
JsonGetValueTool, # noqa: F401
JsonListKeysTool, # noqa: F401
)
from langchain_community.tools.merriam_webster.tool import (
MerriamWebsterQueryRun, # noqa: F401
)
from langchain_community.tools.metaphor_search import (
MetaphorSearchResults, # noqa: F401
)
from langchain_community.tools.nasa.tool import (
NasaAction, # noqa: F401
)
from langchain_community.tools.office365.create_draft_message import (
O365CreateDraftMessage, # noqa: F401
)
from langchain_community.tools.office365.events_search import (
O365SearchEvents, # noqa: F401
)
from langchain_community.tools.office365.messages_search import (
O365SearchEmails, # noqa: F401
)
from langchain_community.tools.office365.send_event import (
O365SendEvent, # noqa: F401
)
from langchain_community.tools.office365.send_message import (
O365SendMessage, # noqa: F401
)
from langchain_community.tools.office365.utils import (
authenticate, # noqa: F401
)
from langchain_community.tools.openapi.utils.api_models import (
APIOperation, # noqa: F401
)
from langchain_community.tools.openapi.utils.openapi_utils import (
OpenAPISpec, # noqa: F401
)
from langchain_community.tools.openweathermap.tool import (
OpenWeatherMapQueryRun, # noqa: F401
)
from langchain_community.tools.playwright import (
ClickTool, # noqa: F401
CurrentWebPageTool, # noqa: F401
ExtractHyperlinksTool, # noqa: F401
ExtractTextTool, # noqa: F401
GetElementsTool, # noqa: F401
NavigateBackTool, # noqa: F401
NavigateTool, # noqa: F401
)
from langchain_community.tools.plugin import (
AIPluginTool, # noqa: F401
)
from langchain_community.tools.polygon.aggregates import (
PolygonAggregates, # noqa: F401
)
from langchain_community.tools.polygon.financials import (
PolygonFinancials, # noqa: F401
)
from langchain_community.tools.polygon.last_quote import (
PolygonLastQuote, # noqa: F401
)
from langchain_community.tools.polygon.ticker_news import (
PolygonTickerNews, # noqa: F401
)
from langchain_community.tools.powerbi.tool import (
InfoPowerBITool, # noqa: F401
ListPowerBITool, # noqa: F401
QueryPowerBITool, # noqa: F401
)
from langchain_community.tools.pubmed.tool import (
PubmedQueryRun, # noqa: F401
)
from langchain_community.tools.reddit_search.tool import (
RedditSearchRun, # noqa: F401
RedditSearchSchema, # noqa: F401
)
from langchain_community.tools.requests.tool import (
BaseRequestsTool, # noqa: F401
RequestsDeleteTool, # noqa: F401
RequestsGetTool, # noqa: F401
RequestsPatchTool, # noqa: F401
RequestsPostTool, # noqa: F401
RequestsPutTool, # noqa: F401
)
from langchain_community.tools.scenexplain.tool import (
SceneXplainTool, # noqa: F401
)
from langchain_community.tools.searchapi.tool import (
SearchAPIResults, # noqa: F401
SearchAPIRun, # noqa: F401
)
from langchain_community.tools.searx_search.tool import (
SearxSearchResults, # noqa: F401
SearxSearchRun, # noqa: F401
)
from langchain_community.tools.shell.tool import (
ShellTool, # noqa: F401
)
from langchain_community.tools.slack.get_channel import (
SlackGetChannel, # noqa: F401
)
from langchain_community.tools.slack.get_message import (
SlackGetMessage, # noqa: F401
)
from langchain_community.tools.slack.schedule_message import (
SlackScheduleMessage, # noqa: F401
)
from langchain_community.tools.slack.send_message import (
SlackSendMessage, # noqa: F401
)
from langchain_community.tools.sleep.tool import (
SleepTool, # noqa: F401
)
from langchain_community.tools.spark_sql.tool import (
BaseSparkSQLTool, # noqa: F401
InfoSparkSQLTool, # noqa: F401
ListSparkSQLTool, # noqa: F401
QueryCheckerTool, # noqa: F401
QuerySparkSQLTool, # noqa: F401
)
from langchain_community.tools.sql_database.tool import (
BaseSQLDatabaseTool, # noqa: F401
InfoSQLDatabaseTool, # noqa: F401
ListSQLDatabaseTool, # noqa: F401
QuerySQLCheckerTool, # noqa: F401
QuerySQLDataBaseTool, # noqa: F401
)
from langchain_community.tools.stackexchange.tool import (
StackExchangeTool, # noqa: F401
)
from langchain_community.tools.steam.tool import (
SteamWebAPIQueryRun, # noqa: F401
)
from langchain_community.tools.steamship_image_generation import (
SteamshipImageGenerationTool, # noqa: F401
)
from langchain_community.tools.vectorstore.tool import (
VectorStoreQATool, # noqa: F401
VectorStoreQAWithSourcesTool, # noqa: F401
)
from langchain_community.tools.wikipedia.tool import (
WikipediaQueryRun, # noqa: F401
)
from langchain_community.tools.wolfram_alpha.tool import (
WolframAlphaQueryRun, # noqa: F401
)
from langchain_community.tools.yahoo_finance_news import (
YahooFinanceNewsTool, # noqa: F401
)
from langchain_community.tools.you.tool import (
YouSearchTool, # noqa: F401
)
from langchain_community.tools.youtube.search import (
YouTubeSearchTool, # noqa: F401
)
from langchain_community.tools.zapier.tool import (
ZapierNLAListActions, # noqa: F401
ZapierNLARunAction, # noqa: F401
)
__all__ = [
"AINAppOps",
"AINOwnerOps",
"AINRuleOps",
"AINTransfer",
"AINValueOps",
"AIPluginTool",
"APIOperation",
"ArxivQueryRun",
"AzureAiServicesDocumentIntelligenceTool",
"AzureAiServicesImageAnalysisTool",
"AzureAiServicesSpeechToTextTool",
"AzureAiServicesTextAnalyticsForHealthTool",
"AzureAiServicesTextToSpeechTool",
"AzureCogsFormRecognizerTool",
"AzureCogsImageAnalysisTool",
"AzureCogsSpeech2TextTool",
"AzureCogsText2SpeechTool",
"AzureCogsTextAnalyticsHealthTool",
"BaseGraphQLTool",
"BaseRequestsTool",
"BaseSQLDatabaseTool",
"BaseSparkSQLTool",
"BaseTool",
"BearlyInterpreterTool",
"BingSearchResults",
"BingSearchRun",
"BraveSearch",
"ClickTool",
"CogniswitchKnowledgeRequest",
"CogniswitchKnowledgeSourceFile",
"CogniswitchKnowledgeSourceURL",
"CogniswitchKnowledgeStatus",
"ConneryAction",
"CopyFileTool",
"CurrentWebPageTool",
"DeleteFileTool",
"DuckDuckGoSearchResults",
"DuckDuckGoSearchRun",
"E2BDataAnalysisTool",
"EdenAiExplicitImageTool",
"EdenAiObjectDetectionTool",
"EdenAiParsingIDTool",
"EdenAiParsingInvoiceTool",
"EdenAiSpeechToTextTool",
"EdenAiTextModerationTool",
"EdenAiTextToSpeechTool",
"EdenaiTool",
"ElevenLabsText2SpeechTool",
"ExtractHyperlinksTool",
"ExtractTextTool",
"FileSearchTool",
"GetElementsTool",
"GmailCreateDraft",
"GmailGetMessage",
"GmailGetThread",
"GmailSearch",
"GmailSendMessage",
"GoogleCloudTextToSpeechTool",
"GooglePlacesTool",
"GoogleSearchResults",
"GoogleSearchRun",
"GoogleSerperResults",
"GoogleSerperRun",
"HumanInputRun",
"IFTTTWebhook",
"InfoPowerBITool",
"InfoSQLDatabaseTool",
"InfoSparkSQLTool",
"JiraAction",
"JsonGetValueTool",
"JsonListKeysTool",
"ListDirectoryTool",
"ListPowerBITool",
"ListSQLDatabaseTool",
"ListSparkSQLTool",
"MerriamWebsterQueryRun",
"MetaphorSearchResults",
"MoveFileTool",
"NasaAction",
"NavigateBackTool",
"NavigateTool",
"O365CreateDraftMessage",
"O365SearchEmails",
"O365SearchEvents",
"O365SendEvent",
"O365SendMessage",
"OpenAPISpec",
"OpenWeatherMapQueryRun",
"PolygonAggregates",
"PolygonFinancials",
"PolygonLastQuote",
"PolygonTickerNews",
"PubmedQueryRun",
"QueryCheckerTool",
"QueryPowerBITool",
"QuerySQLCheckerTool",
"QuerySQLDataBaseTool",
"QuerySparkSQLTool",
"ReadFileTool",
"RedditSearchRun",
"RedditSearchSchema",
"RequestsDeleteTool",
"RequestsGetTool",
"RequestsPatchTool",
"RequestsPostTool",
"RequestsPutTool",
"SceneXplainTool",
"SearchAPIResults",
"SearchAPIRun",
"SearxSearchResults",
"SearxSearchRun",
"ShellTool",
"SlackGetChannel",
"SlackGetMessage",
"SlackScheduleMessage",
"SlackSendMessage",
"SleepTool",
"StackExchangeTool",
"StdInInquireTool",
"SteamWebAPIQueryRun",
"SteamshipImageGenerationTool",
"StructuredTool",
"Tool",
"VectorStoreQATool",
"VectorStoreQAWithSourcesTool",
"WikipediaQueryRun",
"WolframAlphaQueryRun",
"WriteFileTool",
"YahooFinanceNewsTool",
"YouSearchTool",
"YouTubeSearchTool",
"ZapierNLAListActions",
"ZapierNLARunAction",
"authenticate",
"format_tool_to_openai_function",
"tool",
]
# Used for internal purposes
_DEPRECATED_TOOLS = {"PythonAstREPLTool", "PythonREPLTool"}

217
libs/community/langchain_community/utilities/__init__.py
View File

@ -4,7 +4,222 @@ Other LangChain classes use **Utilities** to interact with third-part systems
and packages.
"""
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_community.utilities.alpha_vantage import (
AlphaVantageAPIWrapper, # noqa: F401
)
from langchain_community.utilities.apify import (
ApifyWrapper, # noqa: F401
)
from langchain_community.utilities.arcee import (
ArceeWrapper, # noqa: F401
)
from langchain_community.utilities.arxiv import (
ArxivAPIWrapper, # noqa: F401
)
from langchain_community.utilities.awslambda import (
LambdaWrapper, # noqa: F401
)
from langchain_community.utilities.bibtex import (
BibtexparserWrapper, # noqa: F401
)
from langchain_community.utilities.bing_search import (
BingSearchAPIWrapper, # noqa: F401
)
from langchain_community.utilities.brave_search import (
BraveSearchWrapper, # noqa: F401
)
from langchain_community.utilities.dria_index import (
DriaAPIWrapper, # noqa: F401
)
from langchain_community.utilities.duckduckgo_search import (
DuckDuckGoSearchAPIWrapper, # noqa: F401
)
from langchain_community.utilities.golden_query import (
GoldenQueryAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_finance import (
GoogleFinanceAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_jobs import (
GoogleJobsAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_lens import (
GoogleLensAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_places_api import (
GooglePlacesAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_scholar import (
GoogleScholarAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_search import (
GoogleSearchAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_serper import (
GoogleSerperAPIWrapper, # noqa: F401
)
from langchain_community.utilities.google_trends import (
GoogleTrendsAPIWrapper, # noqa: F401
)
from langchain_community.utilities.graphql import (
GraphQLAPIWrapper, # noqa: F401
)
from langchain_community.utilities.infobip import (
InfobipAPIWrapper, # noqa: F401
)
from langchain_community.utilities.jira import (
JiraAPIWrapper, # noqa: F401
)
from langchain_community.utilities.max_compute import (
MaxComputeAPIWrapper, # noqa: F401
)
from langchain_community.utilities.merriam_webster import (
MerriamWebsterAPIWrapper, # noqa: F401
)
from langchain_community.utilities.metaphor_search import (
MetaphorSearchAPIWrapper, # noqa: F401
)
from langchain_community.utilities.nasa import (
NasaAPIWrapper, # noqa: F401
)
from langchain_community.utilities.nvidia_riva import (
AudioStream, # noqa: F401
NVIDIARivaASR, # noqa: F401
NVIDIARivaStream, # noqa: F401
NVIDIARivaTTS, # noqa: F401
RivaASR, # noqa: F401
RivaTTS, # noqa: F401
)
from langchain_community.utilities.openweathermap import (
OpenWeatherMapAPIWrapper, # noqa: F401
)
from langchain_community.utilities.outline import (
OutlineAPIWrapper, # noqa: F401
)
from langchain_community.utilities.passio_nutrition_ai import (
NutritionAIAPI, # noqa: F401
)
from langchain_community.utilities.portkey import (
Portkey, # noqa: F401
)
from langchain_community.utilities.powerbi import (
PowerBIDataset, # noqa: F401
)
from langchain_community.utilities.pubmed import (
PubMedAPIWrapper, # noqa: F401
)
from langchain_community.utilities.python import (
PythonREPL, # noqa: F401
)
from langchain_community.utilities.requests import (
Requests, # noqa: F401
RequestsWrapper, # noqa: F401
TextRequestsWrapper, # noqa: F401
)
from langchain_community.utilities.scenexplain import (
SceneXplainAPIWrapper, # noqa: F401
)
from langchain_community.utilities.searchapi import (
SearchApiAPIWrapper, # noqa: F401
)
from langchain_community.utilities.searx_search import (
SearxSearchWrapper, # noqa: F401
)
from langchain_community.utilities.serpapi import (
SerpAPIWrapper, # noqa: F401
)
from langchain_community.utilities.spark_sql import (
SparkSQL, # noqa: F401
)
from langchain_community.utilities.sql_database import (
SQLDatabase, # noqa: F401
)
from langchain_community.utilities.stackexchange import (
StackExchangeAPIWrapper, # noqa: F401
)
from langchain_community.utilities.steam import (
SteamWebAPIWrapper, # noqa: F401
)
from langchain_community.utilities.tensorflow_datasets import (
TensorflowDatasets, # noqa: F401
)
from langchain_community.utilities.twilio import (
TwilioAPIWrapper, # noqa: F401
)
from langchain_community.utilities.wikipedia import (
WikipediaAPIWrapper, # noqa: F401
)
from langchain_community.utilities.wolfram_alpha import (
WolframAlphaAPIWrapper, # noqa: F401
)
from langchain_community.utilities.you import (
YouSearchAPIWrapper, # noqa: F401
)
from langchain_community.utilities.zapier import (
ZapierNLAWrapper, # noqa: F401
)
__all__ = [
"AlphaVantageAPIWrapper",
"ApifyWrapper",
"ArceeWrapper",
"ArxivAPIWrapper",
"AudioStream",
"BibtexparserWrapper",
"BingSearchAPIWrapper",
"BraveSearchWrapper",
"DriaAPIWrapper",
"DuckDuckGoSearchAPIWrapper",
"GoldenQueryAPIWrapper",
"GoogleFinanceAPIWrapper",
"GoogleJobsAPIWrapper",
"GoogleLensAPIWrapper",
"GooglePlacesAPIWrapper",
"GoogleScholarAPIWrapper",
"GoogleSearchAPIWrapper",
"GoogleSerperAPIWrapper",
"GoogleTrendsAPIWrapper",
"GraphQLAPIWrapper",
"InfobipAPIWrapper",
"JiraAPIWrapper",
"LambdaWrapper",
"MaxComputeAPIWrapper",
"MerriamWebsterAPIWrapper",
"MetaphorSearchAPIWrapper",
"NVIDIARivaASR",
"NVIDIARivaStream",
"NVIDIARivaTTS",
"NasaAPIWrapper",
"NutritionAIAPI",
"OpenWeatherMapAPIWrapper",
"OutlineAPIWrapper",
"Portkey",
"PowerBIDataset",
"PubMedAPIWrapper",
"PythonREPL",
"Requests",
"RequestsWrapper",
"RivaASR",
"RivaTTS",
"SQLDatabase",
"SceneXplainAPIWrapper",
"SearchApiAPIWrapper",
"SearxSearchWrapper",
"SerpAPIWrapper",
"SparkSQL",
"StackExchangeAPIWrapper",
"SteamWebAPIWrapper",
"TensorflowDatasets",
"TextRequestsWrapper",
"TwilioAPIWrapper",
"WikipediaAPIWrapper",
"WolframAlphaAPIWrapper",
"YouSearchAPIWrapper",
"ZapierNLAWrapper",
]
_module_lookup = {
"AlphaVantageAPIWrapper": "langchain_community.utilities.alpha_vantage",

350
libs/community/langchain_community/vectorstores/__init__.py
View File

@ -20,7 +20,355 @@ and retrieve the data that are 'most similar' to the embedded query.
""" # noqa: E501
import importlib
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from langchain_core.vectorstores import (
VectorStore, # noqa: F401
)
from langchain_community.vectorstores.alibabacloud_opensearch import (
AlibabaCloudOpenSearch, # noqa: F401
AlibabaCloudOpenSearchSettings, # noqa: F401
)
from langchain_community.vectorstores.analyticdb import (
AnalyticDB, # noqa: F401
)
from langchain_community.vectorstores.annoy import (
Annoy, # noqa: F401
)
from langchain_community.vectorstores.apache_doris import (
ApacheDoris, # noqa: F401
)
from langchain_community.vectorstores.astradb import (
AstraDB, # noqa: F401
)
from langchain_community.vectorstores.atlas import (
AtlasDB, # noqa: F401
)
from langchain_community.vectorstores.awadb import (
AwaDB, # noqa: F401
)
from langchain_community.vectorstores.azure_cosmos_db import (
AzureCosmosDBVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.azuresearch import (
AzureSearch, # noqa: F401
)
from langchain_community.vectorstores.bageldb import (
Bagel, # noqa: F401
)
from langchain_community.vectorstores.baiducloud_vector_search import (
BESVectorStore, # noqa: F401
)
from langchain_community.vectorstores.baiduvectordb import (
BaiduVectorDB, # noqa: F401
)
from langchain_community.vectorstores.bigquery_vector_search import (
BigQueryVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.cassandra import (
Cassandra, # noqa: F401
)
from langchain_community.vectorstores.chroma import (
Chroma, # noqa: F401
)
from langchain_community.vectorstores.clarifai import (
Clarifai, # noqa: F401
)
from langchain_community.vectorstores.clickhouse import (
Clickhouse, # noqa: F401
ClickhouseSettings, # noqa: F401
)
from langchain_community.vectorstores.couchbase import (
CouchbaseVectorStore, # noqa: F401
)
from langchain_community.vectorstores.dashvector import (
DashVector, # noqa: F401
)
from langchain_community.vectorstores.databricks_vector_search import (
DatabricksVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.deeplake import (
DeepLake, # noqa: F401
)
from langchain_community.vectorstores.dingo import (
Dingo, # noqa: F401
)
from langchain_community.vectorstores.docarray import (
DocArrayHnswSearch, # noqa: F401
DocArrayInMemorySearch, # noqa: F401
)
from langchain_community.vectorstores.documentdb import (
DocumentDBVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.duckdb import (
DuckDB, # noqa: F401
)
from langchain_community.vectorstores.ecloud_vector_search import (
EcloudESVectorStore, # noqa: F401
)
from langchain_community.vectorstores.elastic_vector_search import (
ElasticKnnSearch, # noqa: F401
ElasticVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.elasticsearch import (
ElasticsearchStore, # noqa: F401
)
from langchain_community.vectorstores.epsilla import (
Epsilla, # noqa: F401
)
from langchain_community.vectorstores.faiss import (
FAISS, # noqa: F401
)
from langchain_community.vectorstores.hanavector import (
HanaDB, # noqa: F401
)
from langchain_community.vectorstores.hologres import (
Hologres, # noqa: F401
)
from langchain_community.vectorstores.infinispanvs import (
InfinispanVS, # noqa: F401
)
from langchain_community.vectorstores.inmemory import (
InMemoryVectorStore, # noqa: F401
)
from langchain_community.vectorstores.kdbai import (
KDBAI, # noqa: F401
)
from langchain_community.vectorstores.kinetica import (
DistanceStrategy, # noqa: F401
Kinetica, # noqa: F401
KineticaSettings, # noqa: F401
)
from langchain_community.vectorstores.lancedb import (
LanceDB, # noqa: F401
)
from langchain_community.vectorstores.lantern import (
Lantern, # noqa: F401
)
from langchain_community.vectorstores.llm_rails import (
LLMRails, # noqa: F401
)
from langchain_community.vectorstores.marqo import (
Marqo, # noqa: F401
)
from langchain_community.vectorstores.matching_engine import (
MatchingEngine, # noqa: F401
)
from langchain_community.vectorstores.meilisearch import (
Meilisearch, # noqa: F401
)
from langchain_community.vectorstores.milvus import (
Milvus, # noqa: F401
)
from langchain_community.vectorstores.momento_vector_index import (
MomentoVectorIndex, # noqa: F401
)
from langchain_community.vectorstores.mongodb_atlas import (
MongoDBAtlasVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.myscale import (
MyScale, # noqa: F401
MyScaleSettings, # noqa: F401
)
from langchain_community.vectorstores.neo4j_vector import (
Neo4jVector, # noqa: F401
)
from langchain_community.vectorstores.opensearch_vector_search import (
OpenSearchVectorSearch, # noqa: F401
)
from langchain_community.vectorstores.pathway import (
PathwayVectorClient, # noqa: F401
)
from langchain_community.vectorstores.pgembedding import (
PGEmbedding, # noqa: F401
)
from langchain_community.vectorstores.pgvector import (
PGVector, # noqa: F401
)
from langchain_community.vectorstores.pinecone import (
Pinecone, # noqa: F401
)
from langchain_community.vectorstores.qdrant import (
Qdrant, # noqa: F401
)
from langchain_community.vectorstores.redis import (
Redis, # noqa: F401
)
from langchain_community.vectorstores.rocksetdb import (
Rockset, # noqa: F401
)
from langchain_community.vectorstores.scann import (
ScaNN, # noqa: F401
)
from langchain_community.vectorstores.semadb import (
SemaDB, # noqa: F401
)
from langchain_community.vectorstores.singlestoredb import (
SingleStoreDB, # noqa: F401
)
from langchain_community.vectorstores.sklearn import (
SKLearnVectorStore, # noqa: F401
)
from langchain_community.vectorstores.sqlitevss import (
SQLiteVSS, # noqa: F401
)
from langchain_community.vectorstores.starrocks import (
StarRocks, # noqa: F401
)
from langchain_community.vectorstores.supabase import (
SupabaseVectorStore, # noqa: F401
)
from langchain_community.vectorstores.surrealdb import (
SurrealDBStore, # noqa: F401
)
from langchain_community.vectorstores.tair import (
Tair, # noqa: F401
)
from langchain_community.vectorstores.tencentvectordb import (
TencentVectorDB, # noqa: F401
)
from langchain_community.vectorstores.thirdai_neuraldb import (
NeuralDBVectorStore, # noqa: F401
)
from langchain_community.vectorstores.tidb_vector import (
TiDBVectorStore, # noqa: F401
)
from langchain_community.vectorstores.tigris import (
Tigris, # noqa: F401
)
from langchain_community.vectorstores.tiledb import (
TileDB, # noqa: F401
)
from langchain_community.vectorstores.timescalevector import (
TimescaleVector, # noqa: F401
)
from langchain_community.vectorstores.typesense import (
Typesense, # noqa: F401
)
from langchain_community.vectorstores.usearch import (
USearch, # noqa: F401
)
from langchain_community.vectorstores.vald import (
Vald, # noqa: F401
)
from langchain_community.vectorstores.vdms import (
VDMS, # noqa: F401
)
from langchain_community.vectorstores.vearch import (
Vearch, # noqa: F401
)
from langchain_community.vectorstores.vectara import (
Vectara, # noqa: F401
)
from langchain_community.vectorstores.vespa import (
VespaStore, # noqa: F401
)
from langchain_community.vectorstores.weaviate import (
Weaviate, # noqa: F401
)
from langchain_community.vectorstores.yellowbrick import (
Yellowbrick, # noqa: F401
)
from langchain_community.vectorstores.zep import (
ZepVectorStore, # noqa: F401
)
from langchain_community.vectorstores.zilliz import (
Zilliz, # noqa: F401
)
__all__ = [
"AlibabaCloudOpenSearch",
"AlibabaCloudOpenSearchSettings",
"AnalyticDB",
"Annoy",
"ApacheDoris",
"AstraDB",
"AtlasDB",
"AwaDB",
"AzureCosmosDBVectorSearch",
"AzureSearch",
"BESVectorStore",
"Bagel",
"BaiduVectorDB",
"BigQueryVectorSearch",
"Cassandra",
"Chroma",
"Clarifai",
"Clickhouse",
"ClickhouseSettings",
"CouchbaseVectorStore",
"DashVector",
"DatabricksVectorSearch",
"DeepLake",
"Dingo",
"DistanceStrategy",
"DocArrayHnswSearch",
"DocArrayInMemorySearch",
"DocumentDBVectorSearch",
"DuckDB",
"EcloudESVectorStore",
"ElasticKnnSearch",
"ElasticVectorSearch",
"ElasticsearchStore",
"Epsilla",
"FAISS",
"HanaDB",
"Hologres",
"InMemoryVectorStore",
"InfinispanVS",
"KDBAI",
"Kinetica",
"KineticaSettings",
"LLMRails",
"LanceDB",
"Lantern",
"Marqo",
"MatchingEngine",
"Meilisearch",
"Milvus",
"MomentoVectorIndex",
"MongoDBAtlasVectorSearch",
"MyScale",
"MyScaleSettings",
"Neo4jVector",
"NeuralDBVectorStore",
"OpenSearchVectorSearch",
"PGEmbedding",
"PGVector",
"PathwayVectorClient",
"Pinecone",
"Qdrant",
"Redis",
"Rockset",
"SKLearnVectorStore",
"SQLiteVSS",
"ScaNN",
"SemaDB",
"SingleStoreDB",
"StarRocks",
"SupabaseVectorStore",
"SurrealDBStore",
"Tair",
"TencentVectorDB",
"TiDBVectorStore",
"Tigris",
"TileDB",
"TimescaleVector",
"Typesense",
"USearch",
"VDMS",
"Vald",
"Vearch",
"Vectara",
"VectorStore",
"VespaStore",
"Weaviate",
"Yellowbrick",
"ZepVectorStore",
"Zilliz",
]
_module_lookup = {
"AlibabaCloudOpenSearch": "langchain_community.vectorstores.alibabacloud_opensearch", # noqa: E501

2
libs/community/tests/integration_tests/chat_models/test_bedrock.py
View File

@ -108,7 +108,7 @@ def test_bedrock_streaming(chat: BedrockChat) -> None:
full = None
for token in chat.stream("I'm Pickle Rick"):
full = token if full is None else full + token
full = token if full is None else full + token # type: ignore[operator]
assert isinstance(token.content, str)
assert isinstance(cast(AIMessageChunk, full).content, str)

8
libs/community/tests/integration_tests/utilities/test_outline.py
View File

@ -66,7 +66,7 @@ def assert_docs(docs: List[Document], all_meta: bool = False) -> None:
def test_run_success(api_client: OutlineAPIWrapper) -> None:
responses.add(
responses.POST,
api_client.outline_instance_url + api_client.outline_search_endpoint,
api_client.outline_instance_url + api_client.outline_search_endpoint, # type: ignore[operator]
json=OUTLINE_SUCCESS_RESPONSE,
status=200,
)
@ -80,7 +80,7 @@ def test_run_success_all_meta(api_client: OutlineAPIWrapper) -> None:
api_client.load_all_available_meta = True
responses.add(
responses.POST,
api_client.outline_instance_url + api_client.outline_search_endpoint,
api_client.outline_instance_url + api_client.outline_search_endpoint, # type: ignore[operator]
json=OUTLINE_SUCCESS_RESPONSE,
status=200,
)
@ -93,7 +93,7 @@ def test_run_success_all_meta(api_client: OutlineAPIWrapper) -> None:
def test_run_no_result(api_client: OutlineAPIWrapper) -> None:
responses.add(
responses.POST,
api_client.outline_instance_url + api_client.outline_search_endpoint,
api_client.outline_instance_url + api_client.outline_search_endpoint, # type: ignore[operator]
json=OUTLINE_EMPTY_RESPONSE,
status=200,
)
@ -106,7 +106,7 @@ def test_run_no_result(api_client: OutlineAPIWrapper) -> None:
def test_run_error(api_client: OutlineAPIWrapper) -> None:
responses.add(
responses.POST,
api_client.outline_instance_url + api_client.outline_search_endpoint,
api_client.outline_instance_url + api_client.outline_search_endpoint, # type: ignore[operator]
json=OUTLINE_ERROR_RESPONSE,
status=401,
)

2
libs/community/tests/integration_tests/vectorstores/test_deeplake.py
View File

@ -8,7 +8,7 @@ from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
@pytest.fixture
def deeplake_datastore() -> DeepLake:
def deeplake_datastore() -> DeepLake: # type: ignore[misc]
texts = ["foo", "bar", "baz"]
metadatas = [{"page": str(i)} for i in range(len(texts))]
docsearch = DeepLake.from_texts(

2
libs/community/tests/integration_tests/vectorstores/test_lantern.py
View File

@ -85,7 +85,7 @@ def test_lantern_embeddings_distance_strategy() -> None:
collection_name="test_collection",
embedding=FakeEmbeddingsWithAdaDimension(),
connection_string=CONNECTION_STRING,
distance_strategy="hamming",
distance_strategy="hamming", # type: ignore[arg-type]
pre_delete_collection=True,
)
output = docsearch.similarity_search("foo", k=1)

6
libs/community/tests/integration_tests/vectorstores/test_milvus.py
View File

@ -26,7 +26,7 @@ def _milvus_from_texts(
def _get_pks(expr: str, docsearch: Milvus) -> List[Any]:
return docsearch.get_pks(expr)
return docsearch.get_pks(expr) # type: ignore[return-value]
def test_milvus() -> None:
@ -51,7 +51,7 @@ def test_milvus_with_id() -> None:
assert output == [Document(page_content="foo")]
output = docsearch.delete(ids=ids)
assert output.delete_count == len(fake_texts)
assert output.delete_count == len(fake_texts) # type: ignore[attr-defined]
try:
ids = ["dup_id" for _ in fake_texts]
@ -146,7 +146,7 @@ def test_milvus_upsert_entities() -> None:
Document(page_content="test_2", metadata={"id": 3}),
]
ids = docsearch.upsert(pks, documents)
assert len(ids) == 2
assert len(ids) == 2 # type: ignore[arg-type]
# if __name__ == "__main__":

2
libs/community/tests/integration_tests/vectorstores/test_tidb_vector.py
View File

@ -320,7 +320,7 @@ def test_relevance_score() -> None:
except ValueError:
pass
docsearch_l2.drop_vectorstore()
docsearch_l2.drop_vectorstore() # type: ignore[attr-defined]
def test_retriever_search_threshold() -> None:

6
libs/community/tests/integration_tests/vectorstores/test_vdms.py
View File

@ -37,7 +37,7 @@ def vdms_client() -> vdms.vdms:
@pytest.mark.requires("vdms")
def test_init_from_client(vdms_client: vdms.vdms) -> None:
embedding_function = FakeEmbeddings()
_ = VDMS(
_ = VDMS( # type: ignore[call-arg]
embedding_function=embedding_function,
client=vdms_client,
)
@ -331,7 +331,7 @@ def test_with_relevance_score(vdms_client: vdms.vdms) -> None:
def test_add_documents_no_metadata(vdms_client: vdms.vdms) -> None:
collection_name = "test_add_documents_no_metadata"
embedding_function = FakeEmbeddings()
db = VDMS(
db = VDMS( # type: ignore[call-arg]
collection_name=collection_name,
embedding_function=embedding_function,
client=vdms_client,
@ -343,7 +343,7 @@ def test_add_documents_no_metadata(vdms_client: vdms.vdms) -> None:
def test_add_documents_mixed_metadata(vdms_client: vdms.vdms) -> None:
collection_name = "test_add_documents_mixed_metadata"
embedding_function = FakeEmbeddings()
db = VDMS(
db = VDMS( # type: ignore[call-arg]
collection_name=collection_name,
embedding_function=embedding_function,
client=vdms_client,

3
libs/community/tests/unit_tests/agent_toolkits/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.agent_toolkits import __all__
from langchain_community.agent_toolkits import __all__, _module_lookup
EXPECTED_ALL = [
"AINetworkToolkit",
@ -35,3 +35,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

6
libs/community/tests/unit_tests/chat_loaders/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.chat_loaders import _module_lookup
from langchain_community.chat_loaders import __all__, _module_lookup
EXPECTED_ALL = [
"BaseChatLoader",
@ -15,4 +15,6 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(_module_lookup.keys()) == set(EXPECTED_ALL)
"""Test that __all__ is correctly set."""
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

6
libs/community/tests/unit_tests/chat_message_histories/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.chat_message_histories import _module_lookup
from langchain_community.chat_message_histories import __all__, _module_lookup
EXPECTED_ALL = [
"AstraDBChatMessageHistory",
@ -26,4 +26,6 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(_module_lookup.keys()) == set(EXPECTED_ALL)
"""Test that __all__ is correctly set."""
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

2
libs/community/tests/unit_tests/chat_models/test_bedrock.py
View File

@ -82,7 +82,7 @@ def test_bedrock_combine_llm_output() -> None:
},
]
model = BedrockChat(model_id=model_id, client=client)
final_output = model._combine_llm_outputs(llm_outputs)
final_output = model._combine_llm_outputs(llm_outputs) # type: ignore[arg-type]
assert final_output["model_id"] == model_id
assert final_output["usage"]["completion_tokens"] == 2
assert final_output["usage"]["prompt_tokens"] == 4

65
libs/community/tests/unit_tests/chat_models/test_imports.py
View File

@ -1,53 +1,56 @@
from langchain_community.chat_models import __all__
from langchain_community.chat_models import __all__, _module_lookup
EXPECTED_ALL = [
"ChatOpenAI",
"BedrockChat",
"AzureChatOpenAI",
"FakeListChatModel",
"PromptLayerChatOpenAI",
"ChatEverlyAI",
"BedrockChat",
"ChatAnthropic",
"ChatAnyscale",
"ChatBaichuan",
"ChatCohere",
"ChatDatabricks",
"ChatDeepInfra",
"ChatEverlyAI",
"ChatFireworks",
"ChatFriendli",
"ChatGooglePalm",
"ChatHuggingFace",
"ChatHunyuan",
"ChatJavelinAIGateway",
"ChatKinetica",
"ChatKonko",
"ChatLiteLLM",
"ChatLiteLLMRouter",
"ChatMLflowAIGateway",
"ChatMaritalk",
"ChatMlflow",
"ChatMLflowAIGateway",
"ChatMLX",
"ChatOllama",
"ChatVertexAI",
"JinaChat",
"HumanInputChatModel",
"MiniMaxChat",
"ChatAnyscale",
"ChatLiteLLM",
"ChatLiteLLMRouter",
"ErnieBotChat",
"ChatJavelinAIGateway",
"ChatKonko",
"PaiEasChatEndpoint",
"QianfanChatEndpoint",
"ChatTongyi",
"ChatFireworks",
"ChatYandexGPT",
"ChatBaichuan",
"ChatHunyuan",
"GigaChat",
"ChatOpenAI",
"ChatPerplexity",
"ChatPremAI",
"ChatSparkLLM",
"VolcEngineMaasChat",
"LlamaEdgeChatService",
"GPTRouter",
"ChatTongyi",
"ChatVertexAI",
"ChatYandexGPT",
"ChatYuan2",
"ChatZhipuAI",
"ChatPerplexity",
"ChatKinetica",
"ChatFriendli",
"ChatPremAI",
"ErnieBotChat",
"FakeListChatModel",
"GPTRouter",
"GigaChat",
"HumanInputChatModel",
"JinaChat",
"LlamaEdgeChatService",
"MiniMaxChat",
"PaiEasChatEndpoint",
"PromptLayerChatOpenAI",
"SolarChat",
"QianfanChatEndpoint",
"VolcEngineMaasChat",
]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/docstore/test_imports.py
View File

@ -1,7 +1,8 @@
from langchain_community.docstore import __all__
from langchain_community.docstore import __all__, _module_lookup
EXPECTED_ALL = ["DocstoreFn", "InMemoryDocstore", "Wikipedia"]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

8
libs/community/tests/unit_tests/document_compressors/test_imports.py Normal file
View File

@ -0,0 +1,8 @@
from langchain_community.document_compressors import __all__, _module_lookup
EXPECTED_ALL = ["LLMLinguaCompressor", "OpenVINOReranker"]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/document_loaders/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.document_loaders import __all__
from langchain_community.document_loaders import __all__, _module_lookup
EXPECTED_ALL = [
"AcreomLoader",
@ -190,3 +190,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/document_transformers/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.document_transformers import __all__
from langchain_community.document_transformers import __all__, _module_lookup
EXPECTED_ALL = [
"BeautifulSoupTransformer",
@ -18,3 +18,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/embeddings/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.embeddings import __all__
from langchain_community.embeddings import __all__, _module_lookup
EXPECTED_ALL = [
"OpenAIEmbeddings",
@ -77,3 +77,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/graphs/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.graphs import __all__
from langchain_community.graphs import __all__, _module_lookup
EXPECTED_ALL = [
"MemgraphGraph",
@ -22,3 +22,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/retrievers/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.retrievers import __all__
from langchain_community.retrievers import __all__, _module_lookup
EXPECTED_ALL = [
"AmazonKendraRetriever",
@ -45,3 +45,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/storage/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.storage import __all__
from langchain_community.storage import __all__, _module_lookup
EXPECTED_ALL = [
"AstraDBStore",
@ -12,3 +12,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/tools/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.tools import __all__
from langchain_community.tools import __all__, _module_lookup
EXPECTED_ALL = [
"AINAppOps",
@ -142,3 +142,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

3
libs/community/tests/unit_tests/utilities/test_imports.py
View File

@ -1,4 +1,4 @@
from langchain_community.utilities import __all__
from langchain_community.utilities import __all__, _module_lookup
EXPECTED_ALL = [
"AlphaVantageAPIWrapper",
@ -62,3 +62,4 @@ EXPECTED_ALL = [
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

4
libs/community/tests/unit_tests/vectorstores/test_databricks_vector_search.py
View File

@ -219,7 +219,7 @@ def test_init_direct_access_index() -> None:
@pytest.mark.requires("databricks", "databricks.vector_search")
def test_init_fail_no_index() -> None:
with pytest.raises(TypeError):
DatabricksVectorSearch()
DatabricksVectorSearch() # type: ignore[call-arg]
@pytest.mark.requires("databricks", "databricks.vector_search")
@ -420,7 +420,7 @@ def test_add_texts_with_metadata() -> None:
DEFAULT_PRIMARY_KEY: id_,
DEFAULT_TEXT_COLUMN: text,
DEFAULT_VECTOR_COLUMN: vector,
**metadata,
**metadata, # type: ignore[arg-type]
}
for text, vector, id_, metadata in zip(
fake_texts, vectors, added_ids, metadatas

100
libs/community/tests/unit_tests/vectorstores/test_imports.py
View File

@ -1,9 +1,102 @@
from langchain_core.vectorstores import VectorStore
from langchain_community import vectorstores
from langchain_community.vectorstores import __all__, _module_lookup
EXPECTED_ALL = [
"AlibabaCloudOpenSearch",
"AlibabaCloudOpenSearchSettings",
"AnalyticDB",
"Annoy",
"ApacheDoris",
"AstraDB",
"AtlasDB",
"AwaDB",
"AzureCosmosDBVectorSearch",
"AzureSearch",
"BESVectorStore",
"Bagel",
"BaiduVectorDB",
"BigQueryVectorSearch",
"Cassandra",
"Chroma",
"Clarifai",
"Clickhouse",
"ClickhouseSettings",
"CouchbaseVectorStore",
"DashVector",
"DatabricksVectorSearch",
"DeepLake",
"Dingo",
"DistanceStrategy",
"DocArrayHnswSearch",
"DocArrayInMemorySearch",
"DocumentDBVectorSearch",
"DuckDB",
"EcloudESVectorStore",
"ElasticKnnSearch",
"ElasticVectorSearch",
"ElasticsearchStore",
"Epsilla",
"FAISS",
"HanaDB",
"Hologres",
"InMemoryVectorStore",
"InfinispanVS",
"KDBAI",
"Kinetica",
"KineticaSettings",
"LLMRails",
"LanceDB",
"Lantern",
"Marqo",
"MatchingEngine",
"Meilisearch",
"Milvus",
"MomentoVectorIndex",
"MongoDBAtlasVectorSearch",
"MyScale",
"MyScaleSettings",
"Neo4jVector",
"NeuralDBVectorStore",
"OpenSearchVectorSearch",
"PGEmbedding",
"PGVector",
"PathwayVectorClient",
"Pinecone",
"Qdrant",
"Redis",
"Rockset",
"SKLearnVectorStore",
"SQLiteVSS",
"ScaNN",
"SemaDB",
"SingleStoreDB",
"StarRocks",
"SupabaseVectorStore",
"SurrealDBStore",
"Tair",
"TencentVectorDB",
"TiDBVectorStore",
"Tigris",
"TileDB",
"TimescaleVector",
"Typesense",
"USearch",
"VDMS",
"Vald",
"Vearch",
"Vectara",
"VectorStore",
"VespaStore",
"Weaviate",
"Yellowbrick",
"ZepVectorStore",
"Zilliz",
]
def test_all_imports() -> None:
def test_all_imports_exclusive() -> None:
"""Simple test to make sure all things can be imported."""
for cls in vectorstores.__all__:
if cls not in [
@ -15,3 +108,8 @@ def test_all_imports() -> None:
"KineticaSettings",
]:
assert issubclass(getattr(vectorstores, cls), VectorStore)
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
assert set(__all__) == set(_module_lookup.keys())

2
libs/langchain/langchain/agents/conversational/base.py
View File

@ -116,7 +116,7 @@ class ConversationalAgent(Agent):
format_instructions=format_instructions,
input_variables=input_variables,
)
llm_chain = LLMChain(
llm_chain = LLMChain( # type: ignore[misc]
llm=llm,
prompt=prompt,
callback_manager=callback_manager,

2
libs/langchain/langchain/agents/conversational_chat/base.py
View File

@ -125,7 +125,7 @@ class ConversationalChatAgent(Agent):
input_variables=input_variables,
output_parser=_output_parser,
)
llm_chain = LLMChain(
llm_chain = LLMChain( # type: ignore[misc]
llm=llm,
prompt=prompt,
callback_manager=callback_manager,

2
libs/langchain/langchain/agents/mrkl/base.py
View File

@ -110,7 +110,7 @@ class ZeroShotAgent(Agent):
format_instructions=format_instructions,
input_variables=input_variables,
)
llm_chain = LLMChain(
llm_chain = LLMChain( # type: ignore[misc]
llm=llm,
prompt=prompt,
callback_manager=callback_manager,

4
libs/langchain/langchain/chains/llm_requests.py
View File

@ -27,7 +27,7 @@ class LLMRequestsChain(Chain):
See https://python.langchain.com/docs/security for more information.
"""
llm_chain: LLMChain
llm_chain: LLMChain # type: ignore[valid-type]
requests_wrapper: TextRequestsWrapper = Field(
default_factory=lambda: TextRequestsWrapper(headers=DEFAULT_HEADERS),
exclude=True,
@ -87,7 +87,7 @@ class LLMRequestsChain(Chain):
# extract the text from the html
soup = BeautifulSoup(res, "html.parser")
other_keys[self.requests_key] = soup.get_text()[: self.text_length]
result = self.llm_chain.predict(
result = self.llm_chain.predict( # type: ignore[attr-defined]
callbacks=_run_manager.get_child(), **other_keys
)
return {self.output_key: result}

4
libs/langchain/langchain/chains/loading.py
View File

@ -134,7 +134,7 @@ def _load_map_reduce_documents_chain(
)
def _load_reduce_documents_chain(config: dict, **kwargs: Any) -> ReduceDocumentsChain:
def _load_reduce_documents_chain(config: dict, **kwargs: Any) -> ReduceDocumentsChain: # type: ignore[valid-type]
combine_documents_chain = None
collapse_documents_chain = None
@ -187,7 +187,7 @@ def _load_reduce_documents_chain(config: dict, **kwargs: Any) -> ReduceDocuments
config.pop("collapse_document_chain_path"), **kwargs
)
return ReduceDocumentsChain(
return ReduceDocumentsChain( # type: ignore[misc]
combine_documents_chain=combine_documents_chain,
collapse_documents_chain=collapse_documents_chain,
**config,

6
libs/langchain/langchain/chains/openai_functions/base.py
View File

@ -52,7 +52,7 @@ def create_openai_fn_chain(
output_key: str = "function",
output_parser: Optional[BaseLLMOutputParser] = None,
**kwargs: Any,
) -> LLMChain:
) -> LLMChain: # type: ignore[valid-type]
"""[Legacy] Create an LLM chain that uses OpenAI functions.
Args:
@ -132,7 +132,7 @@ def create_openai_fn_chain(
}
if len(openai_functions) == 1 and enforce_single_function_usage:
llm_kwargs["function_call"] = {"name": openai_functions[0]["name"]}
llm_chain = LLMChain(
llm_chain = LLMChain( # type: ignore[misc]
llm=llm,
prompt=prompt,
output_parser=output_parser,
@ -154,7 +154,7 @@ def create_structured_output_chain(
output_key: str = "function",
output_parser: Optional[BaseLLMOutputParser] = None,
**kwargs: Any,
) -> LLMChain:
) -> LLMChain: # type: ignore[valid-type]
"""[Legacy] Create an LLMChain that uses an OpenAI function to get a structured output.
Args:

2
libs/langchain/langchain/chains/qa_with_sources/base.py
View File

@ -59,7 +59,7 @@ class BaseQAWithSourcesChain(Chain, ABC):
document_prompt=document_prompt,
document_variable_name="summaries",
)
reduce_documents_chain = ReduceDocumentsChain(
reduce_documents_chain = ReduceDocumentsChain( # type: ignore[misc]
combine_documents_chain=combine_results_chain
)
combine_documents_chain = MapReduceDocumentsChain(

2
libs/langchain/langchain/chains/question_answering/__init__.py
View File

@ -153,7 +153,7 @@ def _load_map_reduce_chain(
verbose=verbose, # type: ignore[arg-type]
callback_manager=callback_manager,
)
reduce_documents_chain = ReduceDocumentsChain(
reduce_documents_chain = ReduceDocumentsChain( # type: ignore[misc]
combine_documents_chain=combine_documents_chain,
collapse_documents_chain=collapse_chain,
token_max=token_max,

4
libs/langchain/tests/integration_tests/agent/test_powerbi_agent.py
View File

@ -27,10 +27,10 @@ def test_daxquery() -> None:
fast_llm = ChatOpenAI(
temperature=0.5, max_tokens=1000, model_name="gpt-3.5-turbo", verbose=True
)
) # type: ignore[call-arg]
smart_llm = ChatOpenAI(
temperature=0, max_tokens=100, model_name="gpt-4", verbose=True
)
) # type: ignore[call-arg]
toolkit = PowerBIToolkit(
powerbi=PowerBIDataset(