lint tests

libs/community/tests/integration_tests/agent/test_ainetwork_agent.py

@@ -8,12 +8,12 @@ from typing import Any
 from urllib.error import HTTPError
 
 import pytest
+from langchain.agents import AgentType, initialize_agent
+
 from langchain_community.agent_toolkits.ainetwork.toolkit import AINetworkToolkit
 from langchain_community.chat_models import ChatOpenAI
 from langchain_community.tools.ainetwork.utils import authenticate
 
-from langchain.agents import AgentType, initialize_agent
-
 
 class Match(Enum):
     __test__ = False

libs/community/tests/integration_tests/agent/test_powerbi_agent.py

@@ -1,8 +1,9 @@
 import pytest
+from langchain_core.utils import get_from_env
+
 from langchain_community.agent_toolkits import PowerBIToolkit, create_pbi_agent
 from langchain_community.chat_models import ChatOpenAI
 from langchain_community.utilities.powerbi import PowerBIDataset
-from langchain_core.utils import get_from_env
 
 
 def azure_installed() -> bool:

libs/community/tests/integration_tests/cache/test_astradb.py

@@ -15,13 +15,13 @@ import os
 from typing import AsyncIterator, Iterator
 
 import pytest
-from langchain_community.cache import AstraDBCache, AstraDBSemanticCache
-from langchain_community.utilities.astradb import SetupMode
+from langchain.globals import get_llm_cache, set_llm_cache
 from langchain_core.caches import BaseCache
 from langchain_core.language_models import LLM
 from langchain_core.outputs import Generation, LLMResult
 
-from langchain.globals import get_llm_cache, set_llm_cache
+from langchain_community.cache import AstraDBCache, AstraDBSemanticCache
+from langchain_community.utilities.astradb import SetupMode
 from tests.integration_tests.cache.fake_embeddings import FakeEmbeddings
 from tests.unit_tests.llms.fake_llm import FakeLLM
 

libs/community/tests/integration_tests/cache/test_azure_cosmosdb_cache.py

@@ -10,14 +10,14 @@ import os
 import uuid
 
 import pytest
+from langchain.globals import get_llm_cache, set_llm_cache
+from langchain_core.outputs import Generation
+
 from langchain_community.cache import AzureCosmosDBSemanticCache
 from langchain_community.vectorstores.azure_cosmos_db import (
     CosmosDBSimilarityType,
     CosmosDBVectorSearchType,
 )
-from langchain_core.outputs import Generation
-
-from langchain.globals import get_llm_cache, set_llm_cache
 from tests.integration_tests.cache.fake_embeddings import (
     FakeEmbeddings,
 )

libs/community/tests/integration_tests/cache/test_cassandra.py

@@ -5,11 +5,11 @@ import time
 from typing import Any, Iterator, Tuple
 
 import pytest
-from langchain_community.cache import CassandraCache, CassandraSemanticCache
-from langchain_community.utilities.cassandra import SetupMode
+from langchain.globals import get_llm_cache, set_llm_cache
 from langchain_core.outputs import Generation, LLMResult
 
-from langchain.globals import get_llm_cache, set_llm_cache
+from langchain_community.cache import CassandraCache, CassandraSemanticCache
+from langchain_community.utilities.cassandra import SetupMode
 from tests.integration_tests.cache.fake_embeddings import FakeEmbeddings
 from tests.unit_tests.llms.fake_llm import FakeLLM
 

libs/community/tests/integration_tests/cache/test_gptcache.py

@@ -2,10 +2,10 @@ import os
 from typing import Any, Callable, Union
 
 import pytest
-from langchain_community.cache import GPTCache
+from langchain.globals import get_llm_cache, set_llm_cache
 from langchain_core.outputs import Generation
 
-from langchain.globals import get_llm_cache, set_llm_cache
+from langchain_community.cache import GPTCache
 from tests.unit_tests.llms.fake_llm import FakeLLM
 
 try:

libs/community/tests/integration_tests/cache/test_momento_cache.py

@@ -11,10 +11,10 @@ from datetime import timedelta
 from typing import Iterator
 
 import pytest
-from langchain_community.cache import MomentoCache
+from langchain.globals import set_llm_cache
 from langchain_core.outputs import Generation, LLMResult
 
-from langchain.globals import set_llm_cache
+from langchain_community.cache import MomentoCache
 from tests.unit_tests.llms.fake_llm import FakeLLM
 
 

libs/community/tests/integration_tests/cache/test_opensearch_cache.py

@@ -1,7 +1,7 @@
-from langchain_community.cache import OpenSearchSemanticCache
+from langchain.globals import get_llm_cache, set_llm_cache
 from langchain_core.outputs import Generation
 
-from langchain.globals import get_llm_cache, set_llm_cache
+from langchain_community.cache import OpenSearchSemanticCache
 from tests.integration_tests.cache.fake_embeddings import (
     FakeEmbeddings,
 )

libs/community/tests/integration_tests/cache/test_redis_cache.py

@@ -5,13 +5,13 @@ from contextlib import asynccontextmanager, contextmanager
 from typing import AsyncGenerator, Generator, List, Optional, cast
 
 import pytest
-from langchain_community.cache import AsyncRedisCache, RedisCache, RedisSemanticCache
+from langchain.globals import get_llm_cache, set_llm_cache
 from langchain_core.embeddings import Embeddings
 from langchain_core.load.dump import dumps
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
 from langchain_core.outputs import ChatGeneration, Generation, LLMResult
 
-from langchain.globals import get_llm_cache, set_llm_cache
+from langchain_community.cache import AsyncRedisCache, RedisCache, RedisSemanticCache
 from tests.integration_tests.cache.fake_embeddings import (
     ConsistentFakeEmbeddings,
     FakeEmbeddings,

libs/community/tests/integration_tests/cache/test_upstash_redis_cache.py

@@ -1,11 +1,11 @@
 """Test Upstash Redis cache functionality."""
 import uuid
 
+import langchain
 import pytest
-from langchain_community.cache import UpstashRedisCache
 from langchain_core.outputs import Generation, LLMResult
 
-import langchain
+from langchain_community.cache import UpstashRedisCache
 from tests.unit_tests.llms.fake_chat_model import FakeChatModel
 from tests.unit_tests.llms.fake_llm import FakeLLM
 

libs/community/tests/integration_tests/chains/test_dalle_agent.py

@@ -1,9 +1,9 @@
 """Integration test for Dall-E image generator agent."""
+from langchain.agents import AgentType, initialize_agent
+
 from langchain_community.agent_toolkits.load_tools import load_tools
 from langchain_community.llms import OpenAI
 
-from langchain.agents import AgentType, initialize_agent
-
 
 def test_call() -> None:
     """Test that the agent runs and returns output."""

libs/community/tests/integration_tests/chains/test_graph_database.py

@@ -1,12 +1,12 @@
 """Test Graph Database Chain."""
 import os
 
+from langchain.chains.loading import load_chain
+
 from langchain_community.chains.graph_qa.cypher import GraphCypherQAChain
 from langchain_community.graphs import Neo4jGraph
 from langchain_community.llms.openai import OpenAI
 
-from langchain.chains.loading import load_chain
-
 
 def test_connect_neo4j() -> None:
     """Test that Neo4j database is correctly instantiated and connected."""

libs/community/tests/integration_tests/chains/test_graph_database_sparql.py

@@ -3,11 +3,11 @@ import pathlib
 import re
 from unittest.mock import MagicMock, Mock
 
+from langchain.chains import LLMChain
+
 from langchain_community.chains.graph_qa.sparql import GraphSparqlQAChain
 from langchain_community.graphs import RdfGraph
 
-from langchain.chains import LLMChain
-
 """
 cd libs/langchain/tests/integration_tests/chains/docker-compose-ontotext-graphdb
 ./start.sh

libs/community/tests/integration_tests/chains/test_ontotext_graphdb_qa.py

@@ -1,11 +1,11 @@
 from unittest.mock import MagicMock, Mock
 
 import pytest
+from langchain.chains import LLMChain
+
 from langchain_community.chains.graph_qa.ontotext_graphdb import OntotextGraphDBQAChain
 from langchain_community.graphs import OntotextGraphDBGraph
 
-from langchain.chains import LLMChain
-
 """
 cd libs/langchain/tests/integration_tests/chains/docker-compose-ontotext-graphdb
 ./start.sh

libs/community/tests/integration_tests/chains/test_react.py

@@ -1,10 +1,10 @@
 """Integration test for self ask with search."""
 
+from langchain.agents.react.base import ReActChain
+
 from langchain_community.docstore import Wikipedia
 from langchain_community.llms.openai import OpenAI
 
-from langchain.agents.react.base import ReActChain
-
 
 def test_react() -> None:
     """Test functionality on a prompt."""

libs/community/tests/integration_tests/chains/test_retrieval_qa.py

@@ -1,14 +1,14 @@
 """Test RetrievalQA functionality."""
 from pathlib import Path
 
+from langchain.chains import RetrievalQA
+from langchain.chains.loading import load_chain
+from langchain_text_splitters.character import CharacterTextSplitter
+
 from langchain_community.document_loaders import TextLoader
 from langchain_community.embeddings.openai import OpenAIEmbeddings
 from langchain_community.llms import OpenAI
 from langchain_community.vectorstores import FAISS
-from langchain_text_splitters.character import CharacterTextSplitter
-
-from langchain.chains import RetrievalQA
-from langchain.chains.loading import load_chain
 
 
 def test_retrieval_qa_saving_loading(tmp_path: Path) -> None:

libs/community/tests/integration_tests/chains/test_retrieval_qa_with_sources.py

@@ -1,12 +1,12 @@
 """Test RetrievalQA functionality."""
+from langchain.chains import RetrievalQAWithSourcesChain
+from langchain.chains.loading import load_chain
+from langchain_text_splitters.character import CharacterTextSplitter
+
 from langchain_community.document_loaders import DirectoryLoader
 from langchain_community.embeddings.openai import OpenAIEmbeddings
 from langchain_community.llms import OpenAI
 from langchain_community.vectorstores import FAISS
-from langchain_text_splitters.character import CharacterTextSplitter
-
-from langchain.chains import RetrievalQAWithSourcesChain
-from langchain.chains.loading import load_chain
 
 
 def test_retrieval_qa_with_sources_chain_saving_loading(tmp_path: str) -> None:

libs/community/tests/integration_tests/chains/test_self_ask_with_search.py

@@ -1,9 +1,9 @@
 """Integration test for self ask with search."""
+from langchain.agents.self_ask_with_search.base import SelfAskWithSearchChain
+
 from langchain_community.llms.openai import OpenAI
 from langchain_community.utilities.searchapi import SearchApiAPIWrapper
 
-from langchain.agents.self_ask_with_search.base import SelfAskWithSearchChain
-
 
 def test_self_ask_with_search() -> None:
     """Test functionality on a prompt."""

libs/community/tests/integration_tests/memory/test_astradb.py

@@ -2,13 +2,13 @@ import os
 from typing import AsyncIterable, Iterable
 
 import pytest
+from langchain.memory import ConversationBufferMemory
+from langchain_core.messages import AIMessage, HumanMessage
+
 from langchain_community.chat_message_histories.astradb import (
     AstraDBChatMessageHistory,
 )
 from langchain_community.utilities.astradb import SetupMode
-from langchain_core.messages import AIMessage, HumanMessage
-
-from langchain.memory import ConversationBufferMemory
 
 
 def _has_env_vars() -> bool:

libs/community/tests/integration_tests/memory/test_cassandra.py

@@ -2,12 +2,12 @@ import os
 import time
 from typing import Optional
 
+from langchain.memory import ConversationBufferMemory
+from langchain_core.messages import AIMessage, HumanMessage
+
 from langchain_community.chat_message_histories.cassandra import (
     CassandraChatMessageHistory,
 )
-from langchain_core.messages import AIMessage, HumanMessage
-
-from langchain.memory import ConversationBufferMemory
 
 
 def _chat_message_history(

libs/community/tests/integration_tests/memory/test_cosmos_db.py

@@ -1,10 +1,10 @@
 import json
 import os
 
-from langchain_community.chat_message_histories import CosmosDBChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import CosmosDBChatMessageHistory
 
 # Replace these with your Azure Cosmos DB endpoint and key
 endpoint = os.environ.get("COSMOS_DB_ENDPOINT", "")

libs/community/tests/integration_tests/memory/test_elasticsearch.py

@@ -4,10 +4,10 @@ import uuid
 from typing import Generator, Union
 
 import pytest
-from langchain_community.chat_message_histories import ElasticsearchChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import ElasticsearchChatMessageHistory
 
 """
 cd tests/integration_tests/memory/docker-compose

libs/community/tests/integration_tests/memory/test_firestore.py

@@ -1,9 +1,9 @@
 import json
 
-from langchain_community.chat_message_histories import FirestoreChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import FirestoreChatMessageHistory
 
 
 def test_memory_with_message_store() -> None:

libs/community/tests/integration_tests/memory/test_momento.py

@@ -10,10 +10,10 @@ from datetime import timedelta
 from typing import Iterator
 
 import pytest
-from langchain_community.chat_message_histories import MomentoChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import MomentoChatMessageHistory
 
 
 def random_string() -> str:

libs/community/tests/integration_tests/memory/test_mongodb.py

@@ -1,10 +1,10 @@
 import json
 import os
 
-from langchain_community.chat_message_histories import MongoDBChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import MongoDBChatMessageHistory
 
 # Replace these with your mongodb connection string
 connection_string = os.environ.get("MONGODB_CONNECTION_STRING", "")

libs/community/tests/integration_tests/memory/test_neo4j.py

@@ -1,9 +1,9 @@
 import json
 
-from langchain_community.chat_message_histories import Neo4jChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import Neo4jChatMessageHistory
 
 
 def test_memory_with_message_store() -> None:

libs/community/tests/integration_tests/memory/test_redis.py

@@ -1,9 +1,9 @@
 import json
 
-from langchain_community.chat_message_histories import RedisChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import RedisChatMessageHistory
 
 
 def test_memory_with_message_store() -> None:

libs/community/tests/integration_tests/memory/test_rockset.py

@@ -8,10 +8,10 @@ and ROCKSET_REGION environment variables set.
 import json
 import os
 
-from langchain_community.chat_message_histories import RocksetChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import RocksetChatMessageHistory
 
 collection_name = "langchain_demo"
 session_id = "MySession"

libs/community/tests/integration_tests/memory/test_singlestoredb.py

@@ -1,9 +1,9 @@
 import json
 
-from langchain_community.chat_message_histories import SingleStoreDBChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import SingleStoreDBChatMessageHistory
 
 # Replace these with your mongodb connection string
 TEST_SINGLESTOREDB_URL = "root:pass@localhost:3306/db"

libs/community/tests/integration_tests/memory/test_upstash_redis.py

@@ -1,12 +1,12 @@
 import json
 
 import pytest
+from langchain.memory import ConversationBufferMemory
+from langchain_core.messages import message_to_dict
+
 from langchain_community.chat_message_histories.upstash_redis import (
     UpstashRedisChatMessageHistory,
 )
-from langchain_core.messages import message_to_dict
-
-from langchain.memory import ConversationBufferMemory
 
 URL = "<UPSTASH_REDIS_REST_URL>"
 TOKEN = "<UPSTASH_REDIS_REST_TOKEN>"

libs/community/tests/integration_tests/memory/test_xata.py

@@ -6,10 +6,10 @@ Before running this test, please create a Xata database.
 import json
 import os
 
-from langchain_community.chat_message_histories import XataChatMessageHistory
+from langchain.memory import ConversationBufferMemory
 from langchain_core.messages import message_to_dict
 
-from langchain.memory import ConversationBufferMemory
+from langchain_community.chat_message_histories import XataChatMessageHistory
 
 
 class TestXata:

libs/community/tests/integration_tests/prompts/test_ngram_overlap_example_selector.py

@@ -1,11 +1,12 @@
 """Test functionality related to ngram overlap based selector."""
 
 import pytest
+from langchain_core.prompts import PromptTemplate
+
 from langchain_community.example_selectors import (
     NGramOverlapExampleSelector,
     ngram_overlap_score,
 )
-from langchain_core.prompts import PromptTemplate
 
 EXAMPLES = [
     {"input": "See Spot run.", "output": "foo1"},

libs/community/tests/integration_tests/retrievers/document_compressors/test_base.py

@@ -1,13 +1,13 @@
 """Integration test for compression pipelines."""
-from langchain_community.document_transformers import EmbeddingsRedundantFilter
-from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_core.documents import Document
-from langchain_text_splitters.character import CharacterTextSplitter
-
 from langchain.retrievers.document_compressors import (
     DocumentCompressorPipeline,
     EmbeddingsFilter,
 )
+from langchain_core.documents import Document
+from langchain_text_splitters.character import CharacterTextSplitter
+
+from langchain_community.document_transformers import EmbeddingsRedundantFilter
+from langchain_community.embeddings import OpenAIEmbeddings
 
 
 def test_document_compressor_pipeline() -> None:

libs/community/tests/integration_tests/retrievers/document_compressors/test_chain_extract.py

@@ -1,8 +1,8 @@
 """Integration test for LLMChainExtractor."""
-from langchain_community.chat_models import ChatOpenAI
+from langchain.retrievers.document_compressors import LLMChainExtractor
 from langchain_core.documents import Document
 
-from langchain.retrievers.document_compressors import LLMChainExtractor
+from langchain_community.chat_models import ChatOpenAI
 
 
 def test_llm_construction_with_kwargs() -> None:

libs/community/tests/integration_tests/retrievers/document_compressors/test_chain_filter.py

@@ -1,8 +1,8 @@
 """Integration test for llm-based relevant doc filtering."""
-from langchain_community.chat_models import ChatOpenAI
+from langchain.retrievers.document_compressors import LLMChainFilter
 from langchain_core.documents import Document
 
-from langchain.retrievers.document_compressors import LLMChainFilter
+from langchain_community.chat_models import ChatOpenAI
 
 
 def test_llm_chain_filter() -> None:

libs/community/tests/integration_tests/retrievers/document_compressors/test_embeddings_filter.py

@@ -1,12 +1,12 @@
 """Integration test for embedding-based relevant doc filtering."""
 import numpy as np
+from langchain.retrievers.document_compressors import EmbeddingsFilter
+from langchain_core.documents import Document
+
 from langchain_community.document_transformers.embeddings_redundant_filter import (
     _DocumentWithState,
 )
 from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_core.documents import Document
-
-from langchain.retrievers.document_compressors import EmbeddingsFilter
 
 
 def test_embeddings_filter() -> None:

libs/community/tests/integration_tests/retrievers/test_contextual_compression.py

@@ -1,9 +1,9 @@
-from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_community.vectorstores import FAISS
-
 from langchain.retrievers.contextual_compression import ContextualCompressionRetriever
 from langchain.retrievers.document_compressors import EmbeddingsFilter
 
+from langchain_community.embeddings import OpenAIEmbeddings
+from langchain_community.vectorstores import FAISS
+
 
 def test_contextual_compression_retriever_get_relevant_docs() -> None:
     """Test get_relevant_docs."""

libs/community/tests/integration_tests/retrievers/test_merger_retriever.py

@@ -1,8 +1,8 @@
+from langchain.retrievers.merger_retriever import MergerRetriever
+
 from langchain_community.embeddings import OpenAIEmbeddings
 from langchain_community.vectorstores import Chroma
 
-from langchain.retrievers.merger_retriever import MergerRetriever
-
 
 def test_merger_retriever_get_relevant_docs() -> None:
     """Test get_relevant_docs."""

libs/community/tests/integration_tests/smith/evaluation/test_runner_utils.py

@@ -2,19 +2,19 @@ from typing import Iterator, List, Optional
 from uuid import uuid4
 
 import pytest
-from langchain_community.chat_models import ChatOpenAI
-from langchain_community.llms.openai import OpenAI
+from langchain.chains.llm import LLMChain
+from langchain.evaluation import EvaluatorType
+from langchain.smith import RunEvalConfig, run_on_dataset
+from langchain.smith.evaluation import InputFormatError
+from langchain.smith.evaluation.runner_utils import arun_on_dataset
 from langchain_core.messages import BaseMessage, HumanMessage
 from langchain_core.prompts.chat import ChatPromptTemplate
 from langsmith import Client as Client
 from langsmith.evaluation import run_evaluator
 from langsmith.schemas import DataType, Example, Run
 
-from langchain.chains.llm import LLMChain
-from langchain.evaluation import EvaluatorType
-from langchain.smith import RunEvalConfig, run_on_dataset
-from langchain.smith.evaluation import InputFormatError
-from langchain.smith.evaluation.runner_utils import arun_on_dataset
+from langchain_community.chat_models import ChatOpenAI
+from langchain_community.llms.openai import OpenAI
 
 
 def _check_all_feedback_passed(_project_name: str, client: Client) -> None:

libs/community/tests/integration_tests/test_document_transformers.py

@@ -1,12 +1,13 @@
 """Integration test for embedding-based redundant doc filtering."""
 
+from langchain_core.documents import Document
+
 from langchain_community.document_transformers.embeddings_redundant_filter import (
     EmbeddingsClusteringFilter,
     EmbeddingsRedundantFilter,
     _DocumentWithState,
 )
 from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_core.documents import Document
 
 
 def test_embeddings_redundant_filter() -> None:

libs/community/tests/integration_tests/test_nuclia_transformer.py

@@ -3,11 +3,12 @@ import json
 from typing import Any
 from unittest import mock
 
+from langchain_core.documents import Document
+
 from langchain_community.document_transformers.nuclia_text_transform import (
     NucliaTextTransformer,
 )
 from langchain_community.tools.nuclia.tool import NucliaUnderstandingAPI
-from langchain_core.documents import Document
 
 
 def fakerun(**args: Any) -> Any:

libs/community/tests/unit_tests/test_cache.py

@@ -4,6 +4,7 @@ from typing import Dict, Generator, List, Union
 
 import pytest
 from _pytest.fixtures import FixtureRequest
+from langchain.globals import get_llm_cache, set_llm_cache
 from langchain_core.caches import InMemoryCache
 from langchain_core.language_models import FakeListChatModel, FakeListLLM
 from langchain_core.language_models.chat_models import BaseChatModel
@@ -14,8 +15,6 @@ from langchain_core.outputs import ChatGeneration, Generation
 from sqlalchemy import create_engine
 from sqlalchemy.orm import Session
 
-from langchain.globals import get_llm_cache, set_llm_cache
-
 pytest.importorskip("langchain_community")
 
 from langchain_community.cache import SQLAlchemyCache  # noqa: E402