diff --git a/libs/community/langchain_community/agent_toolkits/nla/tool.py b/libs/community/langchain_community/agent_toolkits/nla/tool.py
index 47f25d13b687b8..f097edaa1184d0 100644
--- a/libs/community/langchain_community/agent_toolkits/nla/tool.py
+++ b/libs/community/langchain_community/agent_toolkits/nla/tool.py
@@ -30,7 +30,7 @@ def from_open_api_endpoint_chain(
             The API endpoint tool.
         """
         expanded_name = (
-            f'{api_title.replace(" ", "_")}.{chain.api_operation.operation_id}'
+            f"{api_title.replace(' ', '_')}.{chain.api_operation.operation_id}"
         )
         description = (
             f"I'm an AI from {api_title}. Instruct what you want,"
diff --git a/libs/community/langchain_community/callbacks/fiddler_callback.py b/libs/community/langchain_community/callbacks/fiddler_callback.py
index 95df0851d55d44..0ff6ed894d0b65 100644
--- a/libs/community/langchain_community/callbacks/fiddler_callback.py
+++ b/libs/community/langchain_community/callbacks/fiddler_callback.py
@@ -100,7 +100,7 @@ def __init__(
 
         if self.project not in self.fiddler_client.get_project_names():
             print(  # noqa: T201
-                f"adding project {self.project}." "This only has to be done once."
+                f"adding project {self.project}.This only has to be done once."
             )
             try:
                 self.fiddler_client.add_project(self.project)
diff --git a/libs/community/langchain_community/callbacks/manager.py b/libs/community/langchain_community/callbacks/manager.py
index ba942084953f6c..8e8d0525606020 100644
--- a/libs/community/langchain_community/callbacks/manager.py
+++ b/libs/community/langchain_community/callbacks/manager.py
@@ -61,9 +61,9 @@ def get_openai_callback() -> Generator[OpenAICallbackHandler, None, None]:
 
 
 @contextmanager
-def get_bedrock_anthropic_callback() -> (
-    Generator[BedrockAnthropicTokenUsageCallbackHandler, None, None]
-):
+def get_bedrock_anthropic_callback() -> Generator[
+    BedrockAnthropicTokenUsageCallbackHandler, None, None
+]:
     """Get the Bedrock anthropic callback handler in a context manager.
     which conveniently exposes token and cost information.
 
diff --git a/libs/community/langchain_community/callbacks/streamlit/streamlit_callback_handler.py b/libs/community/langchain_community/callbacks/streamlit/streamlit_callback_handler.py
index 5d5985c039cb75..4747bfc2f690d6 100644
--- a/libs/community/langchain_community/callbacks/streamlit/streamlit_callback_handler.py
+++ b/libs/community/langchain_community/callbacks/streamlit/streamlit_callback_handler.py
@@ -211,9 +211,9 @@ def on_agent_action(
     def complete(self, final_label: Optional[str] = None) -> None:
         """Finish the thought."""
         if final_label is None and self._state == LLMThoughtState.RUNNING_TOOL:
-            assert (
-                self._last_tool is not None
-            ), "_last_tool should never be null when _state == RUNNING_TOOL"
+            assert self._last_tool is not None, (
+                "_last_tool should never be null when _state == RUNNING_TOOL"
+            )
             final_label = self._labeler.get_tool_label(
                 self._last_tool, is_complete=True
             )
diff --git a/libs/community/langchain_community/chains/pebblo_retrieval/utilities.py b/libs/community/langchain_community/chains/pebblo_retrieval/utilities.py
index e6e36a505a9479..0ad9ff3656036b 100644
--- a/libs/community/langchain_community/chains/pebblo_retrieval/utilities.py
+++ b/libs/community/langchain_community/chains/pebblo_retrieval/utilities.py
@@ -467,7 +467,7 @@ async def amake_request(
                         logger.warning(f"Pebblo Server: Error {response.status}")
                     elif response.status >= HTTPStatus.BAD_REQUEST:
                         logger.warning(
-                            f"Pebblo received an invalid payload: " f"{response.text}"
+                            f"Pebblo received an invalid payload: {response.text}"
                         )
                     elif response.status != HTTPStatus.OK:
                         logger.warning(
diff --git a/libs/community/langchain_community/chat_loaders/facebook_messenger.py b/libs/community/langchain_community/chat_loaders/facebook_messenger.py
index 2bf883b0f0fe98..44900e0f84eefc 100644
--- a/libs/community/langchain_community/chat_loaders/facebook_messenger.py
+++ b/libs/community/langchain_community/chat_loaders/facebook_messenger.py
@@ -37,7 +37,7 @@ def lazy_load(self) -> Iterator[ChatSession]:
             if "content" not in m:
                 logger.info(
                     f"""Skipping Message No.
-                    {index+1} as no content is present in the message"""
+                    {index + 1} as no content is present in the message"""
                 )
                 continue
             messages.append(
diff --git a/libs/community/langchain_community/chat_message_histories/neo4j.py b/libs/community/langchain_community/chat_message_histories/neo4j.py
index 5a054c706de258..9d2cb317874cc0 100644
--- a/libs/community/langchain_community/chat_message_histories/neo4j.py
+++ b/libs/community/langchain_community/chat_message_histories/neo4j.py
@@ -87,7 +87,7 @@ def messages(self) -> List[BaseMessage]:
         query = (
             f"MATCH (s:`{self._node_label}`)-[:LAST_MESSAGE]->(last_message) "
             "WHERE s.id = $session_id MATCH p=(last_message)<-[:NEXT*0.."
-            f"{self._window*2}]-() WITH p, length(p) AS length "
+            f"{self._window * 2}]-() WITH p, length(p) AS length "
             "ORDER BY length DESC LIMIT 1 UNWIND reverse(nodes(p)) AS node "
             "RETURN {data:{content: node.content}, type:node.type} AS result"
         )
diff --git a/libs/community/langchain_community/chat_message_histories/sql.py b/libs/community/langchain_community/chat_message_histories/sql.py
index 2c3b2351c471d0..8c0706b7ee0d91 100644
--- a/libs/community/langchain_community/chat_message_histories/sql.py
+++ b/libs/community/langchain_community/chat_message_histories/sql.py
@@ -177,9 +177,9 @@ def __init__(
             engine_args: Additional configuration for creating database engines.
             async_mode: Whether it is an asynchronous connection.
         """
-        assert not (
-            connection_string and connection
-        ), "connection_string and connection are mutually exclusive"
+        assert not (connection_string and connection), (
+            "connection_string and connection are mutually exclusive"
+        )
         if connection_string:
             global _warned_once_already
             if not _warned_once_already:
diff --git a/libs/community/langchain_community/chat_models/bedrock.py b/libs/community/langchain_community/chat_models/bedrock.py
index 6b362083903791..086a4d461301fc 100644
--- a/libs/community/langchain_community/chat_models/bedrock.py
+++ b/libs/community/langchain_community/chat_models/bedrock.py
@@ -110,9 +110,9 @@ def _format_anthropic_messages(
 
         if not isinstance(message.content, str):
             # parse as dict
-            assert isinstance(
-                message.content, list
-            ), "Anthropic message content must be str or list of dicts"
+            assert isinstance(message.content, list), (
+                "Anthropic message content must be str or list of dicts"
+            )
 
             # populate content
             content = []
diff --git a/libs/community/langchain_community/chat_models/deepinfra.py b/libs/community/langchain_community/chat_models/deepinfra.py
index b23402cdc06f05..546171f8762492 100644
--- a/libs/community/langchain_community/chat_models/deepinfra.py
+++ b/libs/community/langchain_community/chat_models/deepinfra.py
@@ -468,8 +468,7 @@ def _handle_status(self, code: int, text: Any) -> None:
             raise ValueError(f"DeepInfra received an invalid payload: {text}")
         elif code != 200:
             raise Exception(
-                f"DeepInfra returned an unexpected response with status "
-                f"{code}: {text}"
+                f"DeepInfra returned an unexpected response with status {code}: {text}"
             )
 
     def _url(self) -> str:
diff --git a/libs/community/langchain_community/chat_models/konko.py b/libs/community/langchain_community/chat_models/konko.py
index 3aec395cf53040..a1164d6d17804e 100644
--- a/libs/community/langchain_community/chat_models/konko.py
+++ b/libs/community/langchain_community/chat_models/konko.py
@@ -179,8 +179,7 @@ def get_available_models(
 
         if models_response.status_code != 200:
             raise ValueError(
-                f"Error getting models from {models_url}: "
-                f"{models_response.status_code}"
+                f"Error getting models from {models_url}: {models_response.status_code}"
             )
 
         return {model["id"] for model in models_response.json()["data"]}
diff --git a/libs/community/langchain_community/chat_models/zhipuai.py b/libs/community/langchain_community/chat_models/zhipuai.py
index 99b58697f1a01c..18dc9dd196046a 100644
--- a/libs/community/langchain_community/chat_models/zhipuai.py
+++ b/libs/community/langchain_community/chat_models/zhipuai.py
@@ -121,7 +121,7 @@ def _get_jwt_token(api_key: str) -> str:
         import jwt
     except ImportError:
         raise ImportError(
-            "jwt package not found, please install it with" "`pip install pyjwt`"
+            "jwt package not found, please install it with`pip install pyjwt`"
         )
 
     try:
diff --git a/libs/community/langchain_community/document_loaders/blob_loaders/youtube_audio.py b/libs/community/langchain_community/document_loaders/blob_loaders/youtube_audio.py
index 8397f32fab89bf..b0b2dc6daa8f4e 100644
--- a/libs/community/langchain_community/document_loaders/blob_loaders/youtube_audio.py
+++ b/libs/community/langchain_community/document_loaders/blob_loaders/youtube_audio.py
@@ -21,8 +21,7 @@ def yield_blobs(self) -> Iterable[Blob]:
             import yt_dlp
         except ImportError:
             raise ImportError(
-                "yt_dlp package not found, please install it with "
-                "`pip install yt_dlp`"
+                "yt_dlp package not found, please install it with `pip install yt_dlp`"
             )
 
         # Use yt_dlp to download audio given a YouTube url
diff --git a/libs/community/langchain_community/document_loaders/confluence.py b/libs/community/langchain_community/document_loaders/confluence.py
index 225488c9ceb556..8b4f55078febe9 100644
--- a/libs/community/langchain_community/document_loaders/confluence.py
+++ b/libs/community/langchain_community/document_loaders/confluence.py
@@ -649,7 +649,7 @@ def process_attachment(
             from PIL import Image  # noqa: F401
         except ImportError:
             raise ImportError(
-                "`Pillow` package not found, " "please run `pip install Pillow`"
+                "`Pillow` package not found, please run `pip install Pillow`"
             )
 
         # depending on setup you may also need to set the correct path for
diff --git a/libs/community/langchain_community/document_loaders/csv_loader.py b/libs/community/langchain_community/document_loaders/csv_loader.py
index 1e126709d4add5..59927920569b0a 100644
--- a/libs/community/langchain_community/document_loaders/csv_loader.py
+++ b/libs/community/langchain_community/document_loaders/csv_loader.py
@@ -164,9 +164,13 @@ def __read_file(self, csvfile: TextIOWrapper) -> Iterator[Document]:
                     f"Source column '{self.source_column}' not found in CSV file."
                 )
             content = "\n".join(
-                f"""{k.strip() if k is not None else k}: {v.strip()
-                if isinstance(v, str) else ','.join(map(str.strip, v))
-                if isinstance(v, list) else v}"""
+                f"""{k.strip() if k is not None else k}: {
+                    v.strip()
+                    if isinstance(v, str)
+                    else ",".join(map(str.strip, v))
+                    if isinstance(v, list)
+                    else v
+                }"""
                 for k, v in row.items()
                 if (
                     k in self.content_columns
diff --git a/libs/community/langchain_community/document_loaders/dropbox.py b/libs/community/langchain_community/document_loaders/dropbox.py
index c689e3a455633c..a0350914536f5d 100644
--- a/libs/community/langchain_community/document_loaders/dropbox.py
+++ b/libs/community/langchain_community/document_loaders/dropbox.py
@@ -54,7 +54,7 @@ def _create_dropbox_client(self) -> Any:
         try:
             from dropbox import Dropbox, exceptions
         except ImportError:
-            raise ImportError("You must run " "`pip install dropbox")
+            raise ImportError("You must run `pip install dropbox")
 
         try:
             dbx = Dropbox(self.dropbox_access_token)
@@ -73,7 +73,7 @@ def _load_documents_from_folder(self, folder_path: str) -> List[Document]:
             from dropbox import exceptions
             from dropbox.files import FileMetadata
         except ImportError:
-            raise ImportError("You must run " "`pip install dropbox")
+            raise ImportError("You must run `pip install dropbox")
 
         try:
             results = dbx.files_list_folder(folder_path, recursive=self.recursive)
@@ -98,7 +98,7 @@ def _load_file_from_path(self, file_path: str) -> Optional[Document]:
         try:
             from dropbox import exceptions
         except ImportError:
-            raise ImportError("You must run " "`pip install dropbox")
+            raise ImportError("You must run `pip install dropbox")
 
         try:
             file_metadata = dbx.files_get_metadata(file_path)
diff --git a/libs/community/langchain_community/document_loaders/mediawikidump.py b/libs/community/langchain_community/document_loaders/mediawikidump.py
index 288312d6c9c61c..a778335646b8eb 100644
--- a/libs/community/langchain_community/document_loaders/mediawikidump.py
+++ b/libs/community/langchain_community/document_loaders/mediawikidump.py
@@ -65,7 +65,7 @@ def _load_dump_file(self):  # type: ignore[no-untyped-def]
             import mwxml
         except ImportError as e:
             raise ImportError(
-                "Unable to import 'mwxml'. Please install with" " `pip install mwxml`."
+                "Unable to import 'mwxml'. Please install with `pip install mwxml`."
             ) from e
 
         return mwxml.Dump.from_file(open(self.file_path, encoding=self.encoding))
diff --git a/libs/community/langchain_community/document_loaders/notiondb.py b/libs/community/langchain_community/document_loaders/notiondb.py
index 3e43a3fd811a12..37c367dcb486d7 100644
--- a/libs/community/langchain_community/document_loaders/notiondb.py
+++ b/libs/community/langchain_community/document_loaders/notiondb.py
@@ -126,7 +126,7 @@ def load_page(self, page_summary: Dict[str, Any]) -> Document:
                 value = prop_data["url"]
             elif prop_type == "unique_id":
                 value = (
-                    f'{prop_data["unique_id"]["prefix"]}-{prop_data["unique_id"]["number"]}'
+                    f"{prop_data['unique_id']['prefix']}-{prop_data['unique_id']['number']}"
                     if prop_data["unique_id"]
                     else None
                 )
diff --git a/libs/community/langchain_community/document_loaders/oracleadb_loader.py b/libs/community/langchain_community/document_loaders/oracleadb_loader.py
index 35da49c9affe9b..ebf0c446c44852 100644
--- a/libs/community/langchain_community/document_loaders/oracleadb_loader.py
+++ b/libs/community/langchain_community/document_loaders/oracleadb_loader.py
@@ -82,8 +82,7 @@ def _run_query(self) -> List[Dict[str, Any]]:
             import oracledb
         except ImportError as e:
             raise ImportError(
-                "Could not import oracledb, "
-                "please install with 'pip install oracledb'"
+                "Could not import oracledb, please install with 'pip install oracledb'"
             ) from e
         connect_param = {"user": self.user, "password": self.password, "dsn": self.dsn}
         if self.dsn == self.tns_name:
diff --git a/libs/community/langchain_community/document_loaders/parsers/audio.py b/libs/community/langchain_community/document_loaders/parsers/audio.py
index 32ced082601879..6d98e9667ce40c 100644
--- a/libs/community/langchain_community/document_loaders/parsers/audio.py
+++ b/libs/community/langchain_community/document_loaders/parsers/audio.py
@@ -148,8 +148,7 @@ def __init__(
             import openai
         except ImportError:
             raise ImportError(
-                "openai package not found, please install it with "
-                "`pip install openai`"
+                "openai package not found, please install it with `pip install openai`"
             )
 
         if is_openai_v1():
@@ -278,14 +277,13 @@ def lazy_parse(self, blob: Blob) -> Iterator[Document]:
             import openai
         except ImportError:
             raise ImportError(
-                "openai package not found, please install it with "
-                "`pip install openai`"
+                "openai package not found, please install it with `pip install openai`"
             )
         try:
             from pydub import AudioSegment
         except ImportError:
             raise ImportError(
-                "pydub package not found, please install it with " "`pip install pydub`"
+                "pydub package not found, please install it with `pip install pydub`"
             )
 
         if is_openai_v1():
@@ -402,7 +400,7 @@ def __init__(
             import torch
         except ImportError:
             raise ImportError(
-                "torch package not found, please install it with " "`pip install torch`"
+                "torch package not found, please install it with `pip install torch`"
             )
 
         # Determine the device to use
@@ -533,7 +531,7 @@ def lazy_parse(self, blob: Blob) -> Iterator[Document]:
             from pydub import AudioSegment
         except ImportError:
             raise ImportError(
-                "pydub package not found, please install it with " "`pip install pydub`"
+                "pydub package not found, please install it with `pip install pydub`"
             )
 
         if self.api_key:
diff --git a/libs/community/langchain_community/document_loaders/parsers/docai.py b/libs/community/langchain_community/document_loaders/parsers/docai.py
index 517ea0140aacf0..74b80f6af35cc5 100644
--- a/libs/community/langchain_community/document_loaders/parsers/docai.py
+++ b/libs/community/langchain_community/document_loaders/parsers/docai.py
@@ -230,7 +230,7 @@ def batch_parse(
             time_elapsed += check_in_interval_sec
             if time_elapsed > timeout_sec:
                 raise TimeoutError(
-                    "Timeout exceeded! Check operations " f"{operation_names} later!"
+                    f"Timeout exceeded! Check operations {operation_names} later!"
                 )
             logger.debug(".")
 
diff --git a/libs/community/langchain_community/document_loaders/parsers/grobid.py b/libs/community/langchain_community/document_loaders/parsers/grobid.py
index 2ffe2998fa37f7..ee287cade6e710 100644
--- a/libs/community/langchain_community/document_loaders/parsers/grobid.py
+++ b/libs/community/langchain_community/document_loaders/parsers/grobid.py
@@ -44,7 +44,7 @@ def process_xml(
             from bs4 import BeautifulSoup
         except ImportError:
             raise ImportError(
-                "`bs4` package not found, please install it with " "`pip install bs4`"
+                "`bs4` package not found, please install it with `pip install bs4`"
             )
         soup = BeautifulSoup(xml_data, "xml")
         sections = soup.find_all("div")
diff --git a/libs/community/langchain_community/document_loaders/parsers/pdf.py b/libs/community/langchain_community/document_loaders/parsers/pdf.py
index 00b4510ee660d1..632b3a09801a26 100644
--- a/libs/community/langchain_community/document_loaders/parsers/pdf.py
+++ b/libs/community/langchain_community/document_loaders/parsers/pdf.py
@@ -100,8 +100,7 @@ def lazy_parse(self, blob: Blob) -> Iterator[Document]:  # type: ignore[valid-ty
             import pypdf
         except ImportError:
             raise ImportError(
-                "`pypdf` package not found, please install it with "
-                "`pip install pypdf`"
+                "`pypdf` package not found, please install it with `pip install pypdf`"
             )
 
         def _extract_text_from_page(page: pypdf.PageObject) -> str:
@@ -425,8 +424,7 @@ def __init__(
             import PIL  # noqa:F401
         except ImportError:
             raise ImportError(
-                "pillow package not found, please install it with"
-                " `pip install pillow`"
+                "pillow package not found, please install it with `pip install pillow`"
             )
         self.text_kwargs = text_kwargs or {}
         self.dedupe = dedupe
diff --git a/libs/community/langchain_community/document_loaders/pyspark_dataframe.py b/libs/community/langchain_community/document_loaders/pyspark_dataframe.py
index 410b7d07afc20c..ff1c7fc7ee8555 100644
--- a/libs/community/langchain_community/document_loaders/pyspark_dataframe.py
+++ b/libs/community/langchain_community/document_loaders/pyspark_dataframe.py
@@ -36,8 +36,7 @@ def __init__(
             from pyspark.sql import DataFrame, SparkSession
         except ImportError:
             raise ImportError(
-                "pyspark is not installed. "
-                "Please install it with `pip install pyspark`"
+                "pyspark is not installed. Please install it with `pip install pyspark`"
             )
 
         self.spark = (
diff --git a/libs/community/langchain_community/document_loaders/quip.py b/libs/community/langchain_community/document_loaders/quip.py
index 540ef8f945c797..bb3a002912bd64 100644
--- a/libs/community/langchain_community/document_loaders/quip.py
+++ b/libs/community/langchain_community/document_loaders/quip.py
@@ -40,7 +40,7 @@ def __init__(
             from quip_api.quip import QuipClient
         except ImportError:
             raise ImportError(
-                "`quip_api` package not found, please run " "`pip install quip_api`"
+                "`quip_api` package not found, please run `pip install quip_api`"
             )
 
         self.quip_client = QuipClient(
diff --git a/libs/community/langchain_community/document_loaders/rspace.py b/libs/community/langchain_community/document_loaders/rspace.py
index cb12c6d6c848bd..244b92bb4f1599 100644
--- a/libs/community/langchain_community/document_loaders/rspace.py
+++ b/libs/community/langchain_community/document_loaders/rspace.py
@@ -58,7 +58,7 @@ def _create_rspace_client(self) -> Any:
             from rspace_client.eln import eln, field_content
 
         except ImportError:
-            raise ImportError("You must run " "`pip install rspace_client`")
+            raise ImportError("You must run `pip install rspace_client`")
 
         try:
             eln = eln.ELNClient(self.url, self.api_key)
@@ -66,8 +66,7 @@ def _create_rspace_client(self) -> Any:
 
         except Exception:
             raise Exception(
-                f"Unable to initialize client - is url {self.url} or "
-                f"api key  correct?"
+                f"Unable to initialize client - is url {self.url} or api key  correct?"
             )
 
         return eln, field_content.FieldContent
diff --git a/libs/community/langchain_community/embeddings/ascend.py b/libs/community/langchain_community/embeddings/ascend.py
index d01f7967491d85..c8cb059177b193 100644
--- a/libs/community/langchain_community/embeddings/ascend.py
+++ b/libs/community/langchain_community/embeddings/ascend.py
@@ -89,7 +89,7 @@ def encode(self, sentences: Any) -> Any:
             import torch
         except ImportError as e:
             raise ImportError(
-                "Unable to import torch, please install with " "`pip install -U torch`."
+                "Unable to import torch, please install with `pip install -U torch`."
             ) from e
         last_hidden_state = self.model(
             inputs.input_ids.npu(), inputs.attention_mask.npu(), return_dict=True
@@ -103,7 +103,7 @@ def pooling(self, last_hidden_state: Any, attention_mask: Any = None) -> Any:
             import torch
         except ImportError as e:
             raise ImportError(
-                "Unable to import torch, please install with " "`pip install -U torch`."
+                "Unable to import torch, please install with `pip install -U torch`."
             ) from e
         if self.pooling_method == "cls":
             return last_hidden_state[:, 0]
diff --git a/libs/community/langchain_community/embeddings/openvino.py b/libs/community/langchain_community/embeddings/openvino.py
index 3dbbdef45f1a6f..930453247c3491 100644
--- a/libs/community/langchain_community/embeddings/openvino.py
+++ b/libs/community/langchain_community/embeddings/openvino.py
@@ -166,19 +166,19 @@ def encode(
             import numpy as np
         except ImportError as e:
             raise ImportError(
-                "Unable to import numpy, please install with " "`pip install -U numpy`."
+                "Unable to import numpy, please install with `pip install -U numpy`."
             ) from e
         try:
             from tqdm import trange
         except ImportError as e:
             raise ImportError(
-                "Unable to import tqdm, please install with " "`pip install -U tqdm`."
+                "Unable to import tqdm, please install with `pip install -U tqdm`."
             ) from e
         try:
             import torch
         except ImportError as e:
             raise ImportError(
-                "Unable to import torch, please install with " "`pip install -U torch`."
+                "Unable to import torch, please install with `pip install -U torch`."
             ) from e
 
         def run_mean_pooling(model_output: Any, attention_mask: Any) -> Any:
diff --git a/libs/community/langchain_community/embeddings/spacy_embeddings.py b/libs/community/langchain_community/embeddings/spacy_embeddings.py
index 1d7c6ed4e95adf..cd862d3ba901f0 100644
--- a/libs/community/langchain_community/embeddings/spacy_embeddings.py
+++ b/libs/community/langchain_community/embeddings/spacy_embeddings.py
@@ -48,8 +48,7 @@ def validate_environment(cls, values: Dict) -> Any:
         # Check if the spaCy package is installed
         if importlib.util.find_spec("spacy") is None:
             raise ValueError(
-                "SpaCy package not found. "
-                "Please install it with `pip install spacy`."
+                "SpaCy package not found. Please install it with `pip install spacy`."
             )
         try:
             # Try to load the spaCy model
diff --git a/libs/community/langchain_community/graphs/falkordb_graph.py b/libs/community/langchain_community/graphs/falkordb_graph.py
index 99e3e4592b3e95..56ce03c1f9a090 100644
--- a/libs/community/langchain_community/graphs/falkordb_graph.py
+++ b/libs/community/langchain_community/graphs/falkordb_graph.py
@@ -167,7 +167,7 @@ def query(self, query: str, params: dict = {}) -> List[Dict[str, Any]]:
             data = self._graph.query(query, params)
             return data.result_set
         except Exception as e:
-            raise ValueError("Generated Cypher Statement is not valid\n" f"{e}")
+            raise ValueError(f"Generated Cypher Statement is not valid\n{e}")
 
     def add_graph_documents(
         self, graph_documents: List[GraphDocument], include_source: bool = False
diff --git a/libs/community/langchain_community/graphs/gremlin_graph.py b/libs/community/langchain_community/graphs/gremlin_graph.py
index 934ccb3f53c990..d2c1a1725dce2e 100644
--- a/libs/community/langchain_community/graphs/gremlin_graph.py
+++ b/libs/community/langchain_community/graphs/gremlin_graph.py
@@ -57,7 +57,7 @@ def __init__(
                 asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
         except ImportError:
             raise ImportError(
-                "Please install gremlin-python first: " "`pip3 install gremlinpython"
+                "Please install gremlin-python first: `pip3 install gremlinpython"
             )
 
         self.client = client.Client(
diff --git a/libs/community/langchain_community/graphs/memgraph_graph.py b/libs/community/langchain_community/graphs/memgraph_graph.py
index fa829a0e5db813..4180b49ce3d49e 100644
--- a/libs/community/langchain_community/graphs/memgraph_graph.py
+++ b/libs/community/langchain_community/graphs/memgraph_graph.py
@@ -488,8 +488,7 @@ def add_graph_documents(
 
         if baseEntityLabel:
             self.query(
-                f"CREATE CONSTRAINT ON (b:{BASE_ENTITY_LABEL}) "
-                "ASSERT b.id IS UNIQUE;"
+                f"CREATE CONSTRAINT ON (b:{BASE_ENTITY_LABEL}) ASSERT b.id IS UNIQUE;"
             )
             self.query(f"CREATE INDEX ON :{BASE_ENTITY_LABEL}(id);")
             self.query(f"CREATE INDEX ON :{BASE_ENTITY_LABEL};")
diff --git a/libs/community/langchain_community/graphs/neo4j_graph.py b/libs/community/langchain_community/graphs/neo4j_graph.py
index dd2a7937f7f819..f96cd276967d15 100644
--- a/libs/community/langchain_community/graphs/neo4j_graph.py
+++ b/libs/community/langchain_community/graphs/neo4j_graph.py
@@ -204,7 +204,7 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str:
                         example = (
                             (
                                 "Available options: "
-                                f'{[clean_string_values(el) for el in prop["values"]]}'
+                                f"{[clean_string_values(el) for el in prop['values']]}"
                             )
                             if prop["values"]
                             else ""
@@ -218,7 +218,7 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str:
                     "LOCAL_DATE_TIME",
                 ]:
                     if prop.get("min") is not None:
-                        example = f'Min: {prop["min"]}, Max: {prop["max"]}'
+                        example = f"Min: {prop['min']}, Max: {prop['max']}"
                     else:
                         example = (
                             f'Example: "{prop["values"][0]}"'
@@ -230,7 +230,7 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str:
                     if not prop.get("min_size") or prop["min_size"] > LIST_LIMIT:
                         continue
                     example = (
-                        f'Min Size: {prop["min_size"]}, Max Size: {prop["max_size"]}'
+                        f"Min Size: {prop['min_size']}, Max Size: {prop['max_size']}"
                     )
                 formatted_node_props.append(
                     f"  - `{prop['property']}`: {prop['type']} {example}"
@@ -252,7 +252,7 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str:
                         example = (
                             (
                                 "Available options: "
-                                f'{[clean_string_values(el) for el in prop["values"]]}'
+                                f"{[clean_string_values(el) for el in prop['values']]}"
                             )
                             if prop["values"]
                             else ""
@@ -265,7 +265,7 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str:
                     "LOCAL_DATE_TIME",
                 ]:
                     if prop.get("min"):  # If we have min/max
-                        example = f'Min: {prop["min"]}, Max:  {prop["max"]}'
+                        example = f"Min: {prop['min']}, Max:  {prop['max']}"
                     else:  # return a single value
                         example = (
                             f'Example: "{prop["values"][0]}"' if prop["values"] else ""
@@ -275,7 +275,7 @@ def _format_schema(schema: Dict, is_enhanced: bool) -> str:
                     if not prop.get("min_size") or prop["min_size"] > LIST_LIMIT:
                         continue
                     example = (
-                        f'Min Size: {prop["min_size"]}, Max Size: {prop["max_size"]}'
+                        f"Min Size: {prop['min_size']}, Max Size: {prop['max_size']}"
                     )
                 formatted_rel_props.append(
                     f"  - `{prop['property']}: {prop['type']}` {example}"
diff --git a/libs/community/langchain_community/graphs/neptune_rdf_graph.py b/libs/community/langchain_community/graphs/neptune_rdf_graph.py
index f560768a15ccc0..7f2aefac96ed21 100644
--- a/libs/community/langchain_community/graphs/neptune_rdf_graph.py
+++ b/libs/community/langchain_community/graphs/neptune_rdf_graph.py
@@ -249,7 +249,7 @@ def _get_local_name(self, iri: str) -> Sequence[str]:
             return [f"{tokens[0]}#", tokens[-1]]
         elif "/" in iri:
             tokens = iri.split("/")
-            return [f"{'/'.join(tokens[0:len(tokens)-1])}/", tokens[-1]]
+            return [f"{'/'.join(tokens[0 : len(tokens) - 1])}/", tokens[-1]]
         else:
             raise ValueError(f"Unexpected IRI '{iri}', contains neither '#' nor '/'.")
 
diff --git a/libs/community/langchain_community/graphs/rdf_graph.py b/libs/community/langchain_community/graphs/rdf_graph.py
index edc46d5d18d6d1..ca8595c1620ff1 100644
--- a/libs/community/langchain_community/graphs/rdf_graph.py
+++ b/libs/community/langchain_community/graphs/rdf_graph.py
@@ -217,7 +217,7 @@ def query(
         try:
             res = self.graph.query(query)
         except ParserError as e:
-            raise ValueError("Generated SPARQL statement is invalid\n" f"{e}")
+            raise ValueError(f"Generated SPARQL statement is invalid\n{e}")
         return [r for r in res if isinstance(r, ResultRow)]
 
     def update(
@@ -232,7 +232,7 @@ def update(
         try:
             self.graph.update(query)
         except ParserError as e:
-            raise ValueError("Generated SPARQL statement is invalid\n" f"{e}")
+            raise ValueError(f"Generated SPARQL statement is invalid\n{e}")
         if self.local_copy:
             self.graph.serialize(
                 destination=self.local_copy, format=self.local_copy.split(".")[-1]
@@ -274,9 +274,9 @@ def _rdf_s_schema(
                 f"In the following, each IRI is followed by the local name and "
                 f"optionally its description in parentheses. \n"
                 f"The RDF graph supports the following node types:\n"
-                f'{", ".join([self._res_to_str(r, "cls") for r in classes])}\n'
+                f"{', '.join([self._res_to_str(r, 'cls') for r in classes])}\n"
                 f"The RDF graph supports the following relationships:\n"
-                f'{", ".join([self._res_to_str(r, "rel") for r in relationships])}\n'
+                f"{', '.join([self._res_to_str(r, 'rel') for r in relationships])}\n"
             )
 
         if self.standard == "rdf":
@@ -295,13 +295,13 @@ def _rdf_s_schema(
                 f"In the following, each IRI is followed by the local name and "
                 f"optionally its description in parentheses. \n"
                 f"The OWL graph supports the following node types:\n"
-                f'{", ".join([self._res_to_str(r, "cls") for r in clss])}\n'
+                f"{', '.join([self._res_to_str(r, 'cls') for r in clss])}\n"
                 f"The OWL graph supports the following object properties, "
                 f"i.e., relationships between objects:\n"
-                f'{", ".join([self._res_to_str(r, "op") for r in ops])}\n'
+                f"{', '.join([self._res_to_str(r, 'op') for r in ops])}\n"
                 f"The OWL graph supports the following data properties, "
                 f"i.e., relationships between objects and literals:\n"
-                f'{", ".join([self._res_to_str(r, "dp") for r in dps])}\n'
+                f"{', '.join([self._res_to_str(r, 'dp') for r in dps])}\n"
             )
         else:
             raise ValueError(f"Mode '{self.standard}' is currently not supported.")
diff --git a/libs/community/langchain_community/indexes/_document_manager.py b/libs/community/langchain_community/indexes/_document_manager.py
index 64fbe1b94616e7..e36f3d832b3598 100644
--- a/libs/community/langchain_community/indexes/_document_manager.py
+++ b/libs/community/langchain_community/indexes/_document_manager.py
@@ -27,7 +27,7 @@ def _get_pymongo_client(mongodb_url: str, **kwargs: Any) -> Any:
         client = pymongo(mongodb_url, **kwargs)
     except ValueError as e:
         raise ImportError(
-            f"MongoClient string provided is not in proper format. " f"Got error: {e} "
+            f"MongoClient string provided is not in proper format. Got error: {e} "
         )
     return client
 
diff --git a/libs/community/langchain_community/llms/bedrock.py b/libs/community/langchain_community/llms/bedrock.py
index 4c5fbdc476d665..e1b6570cf30835 100644
--- a/libs/community/langchain_community/llms/bedrock.py
+++ b/libs/community/langchain_community/llms/bedrock.py
@@ -454,8 +454,7 @@ def _get_provider(self) -> str:
             return self.provider
         if self.model_id.startswith("arn"):
             raise ValueError(
-                "Model provider should be supplied when passing a model ARN as "
-                "model_id"
+                "Model provider should be supplied when passing a model ARN as model_id"
             )
 
         return self.model_id.split(".")[0]
diff --git a/libs/community/langchain_community/llms/databricks.py b/libs/community/langchain_community/llms/databricks.py
index 3f7aa42f2fda68..4b656192e2b51c 100644
--- a/libs/community/langchain_community/llms/databricks.py
+++ b/libs/community/langchain_community/llms/databricks.py
@@ -457,12 +457,12 @@ def set_cluster_id(cls, values: Dict[str, Any]) -> dict:
             pass
 
         if model_kwargs := values.get("model_kwargs"):
-            assert (
-                "prompt" not in model_kwargs
-            ), "model_kwargs must not contain key 'prompt'"
-            assert (
-                "stop" not in model_kwargs
-            ), "model_kwargs must not contain key 'stop'"
+            assert "prompt" not in model_kwargs, (
+                "model_kwargs must not contain key 'prompt'"
+            )
+            assert "stop" not in model_kwargs, (
+                "model_kwargs must not contain key 'stop'"
+            )
         return values
 
     def __init__(self, **data: Any):
diff --git a/libs/community/langchain_community/llms/deepinfra.py b/libs/community/langchain_community/llms/deepinfra.py
index 47551dd4e65205..bd0e21df5260b7 100644
--- a/libs/community/langchain_community/llms/deepinfra.py
+++ b/libs/community/langchain_community/llms/deepinfra.py
@@ -97,8 +97,7 @@ def _handle_status(self, code: int, text: Any) -> None:
             raise ValueError(f"DeepInfra received an invalid payload: {text}")
         elif code != 200:
             raise Exception(
-                f"DeepInfra returned an unexpected response with status "
-                f"{code}: {text}"
+                f"DeepInfra returned an unexpected response with status {code}: {text}"
             )
 
     def _call(
diff --git a/libs/community/langchain_community/llms/oci_generative_ai.py b/libs/community/langchain_community/llms/oci_generative_ai.py
index a9f48a97528bab..ee355867e9631a 100644
--- a/libs/community/langchain_community/llms/oci_generative_ai.py
+++ b/libs/community/langchain_community/llms/oci_generative_ai.py
@@ -274,8 +274,7 @@ def _prepare_invocation_object(
 
         if self.model_id is None:
             raise ValueError(
-                "model_id is required to call the model, "
-                "please provide the model_id."
+                "model_id is required to call the model, please provide the model_id."
             )
 
         if self.model_id.startswith(CUSTOM_ENDPOINT_PREFIX):
diff --git a/libs/community/langchain_community/llms/sambanova.py b/libs/community/langchain_community/llms/sambanova.py
index 994fb7888c8753..18f2810262a21f 100644
--- a/libs/community/langchain_community/llms/sambanova.py
+++ b/libs/community/langchain_community/llms/sambanova.py
@@ -711,7 +711,7 @@ def _handle_request(
         }
         data = {key: value for key, value in data.items() if value is not None}
         headers = {
-            "Authorization": f"Bearer " f"{self.sambanova_api_key.get_secret_value()}",
+            "Authorization": f"Bearer {self.sambanova_api_key.get_secret_value()}",
             "Content-Type": "application/json",
         }
 
diff --git a/libs/community/langchain_community/llms/self_hosted_hugging_face.py b/libs/community/langchain_community/llms/self_hosted_hugging_face.py
index 016da2e48f9be9..e43ca9e312454e 100644
--- a/libs/community/langchain_community/llms/self_hosted_hugging_face.py
+++ b/libs/community/langchain_community/llms/self_hosted_hugging_face.py
@@ -69,8 +69,7 @@ def _load_transformer(
             model = AutoModelForSeq2SeqLM.from_pretrained(model_id, **_model_kwargs)
         else:
             raise ValueError(
-                f"Got invalid task {task}, "
-                f"currently only {VALID_TASKS} are supported"
+                f"Got invalid task {task}, currently only {VALID_TASKS} are supported"
             )
     except ImportError as e:
         raise ImportError(
diff --git a/libs/community/langchain_community/retrievers/nanopq.py b/libs/community/langchain_community/retrievers/nanopq.py
index ca4162240d0980..274ad4b42e15f9 100644
--- a/libs/community/langchain_community/retrievers/nanopq.py
+++ b/libs/community/langchain_community/retrievers/nanopq.py
@@ -86,7 +86,7 @@ def _get_relevant_documents(
             from nanopq import PQ
         except ImportError:
             raise ImportError(
-                "Could not import nanopq, please install with `pip install " "nanopq`."
+                "Could not import nanopq, please install with `pip install nanopq`."
             )
 
         query_embeds = np.array(self.embeddings.embed_query(query))
diff --git a/libs/community/langchain_community/tools/azure_ai_services/text_analytics_for_health.py b/libs/community/langchain_community/tools/azure_ai_services/text_analytics_for_health.py
index b47b29210fde64..b7fcd310e9cdf1 100644
--- a/libs/community/langchain_community/tools/azure_ai_services/text_analytics_for_health.py
+++ b/libs/community/langchain_community/tools/azure_ai_services/text_analytics_for_health.py
@@ -83,7 +83,7 @@ def _format_text_analysis_result(self, text_analysis_result: Dict) -> str:
         if "entities" in text_analysis_result:
             formatted_result.append(
                 f"""The text contains the following healthcare entities: {
-                        ', '.join(text_analysis_result['entities'])
+                    ", ".join(text_analysis_result["entities"])
                 }""".replace("\n", " ")
             )
 
diff --git a/libs/community/langchain_community/tools/azure_cognitive_services/text_analytics_health.py b/libs/community/langchain_community/tools/azure_cognitive_services/text_analytics_health.py
index 0827cb9b93c188..53463f4d592abc 100644
--- a/libs/community/langchain_community/tools/azure_cognitive_services/text_analytics_health.py
+++ b/libs/community/langchain_community/tools/azure_cognitive_services/text_analytics_health.py
@@ -83,7 +83,7 @@ def _format_text_analysis_result(self, text_analysis_result: Dict) -> str:
         if "entities" in text_analysis_result:
             formatted_result.append(
                 f"""The text contains the following healthcare entities: {
-                        ', '.join(text_analysis_result['entities'])
+                    ", ".join(text_analysis_result["entities"])
                 }""".replace("\n", " ")
             )
 
diff --git a/libs/community/langchain_community/tools/databricks/_execution.py b/libs/community/langchain_community/tools/databricks/_execution.py
index 62e8414fe49a37..09693e55107541 100644
--- a/libs/community/langchain_community/tools/databricks/_execution.py
+++ b/libs/community/langchain_community/tools/databricks/_execution.py
@@ -66,9 +66,9 @@ def get_execute_function_sql_stmt(
     else:
         parts.append(f"SELECT * FROM {function.full_name}(")
     if function.input_params is None or function.input_params.parameters is None:
-        assert (
-            not json_params
-        ), "Function has no parameters but parameters were provided."
+        assert not json_params, (
+            "Function has no parameters but parameters were provided."
+        )
     else:
         args = []
         use_named_args = False
@@ -213,17 +213,17 @@ def execute_function(
     assert response.status is not None, f"Statement execution failed: {response}"
     if response.status.state != StatementState.SUCCEEDED:
         error = response.status.error
-        assert (
-            error is not None
-        ), f"Statement execution failed but no error message was provided: {response}"
+        assert error is not None, (
+            f"Statement execution failed but no error message was provided: {response}"
+        )
         return FunctionExecutionResult(error=f"{error.error_code}: {error.message}")
     manifest = response.manifest
     assert manifest is not None
     truncated = manifest.truncated
     result = response.result
-    assert (
-        result is not None
-    ), "Statement execution succeeded but no result was provided."
+    assert result is not None, (
+        "Statement execution succeeded but no result was provided."
+    )
     data_array = result.data_array
     if is_scalar(function):
         value = None
@@ -234,9 +234,9 @@ def execute_function(
         )
     else:
         schema = manifest.schema
-        assert (
-            schema is not None and schema.columns is not None
-        ), "Statement execution succeeded but no schema was provided."
+        assert schema is not None and schema.columns is not None, (
+            "Statement execution succeeded but no schema was provided."
+        )
         columns = [c.name for c in schema.columns]
         if data_array is None:
             data_array = []
diff --git a/libs/community/langchain_community/tools/edenai/audio_speech_to_text.py b/libs/community/langchain_community/tools/edenai/audio_speech_to_text.py
index b4a218dc3daa69..b3a70d4e6424a2 100644
--- a/libs/community/langchain_community/tools/edenai/audio_speech_to_text.py
+++ b/libs/community/langchain_community/tools/edenai/audio_speech_to_text.py
@@ -70,7 +70,7 @@ def _wait_processing(self, url: str) -> requests.Response:
                 if temp["results"][self.providers[0]]["error"] is not None:
                     raise Exception(
                         f"""EdenAI returned an unexpected response 
-                        {temp['results'][self.providers[0]]['error']}"""
+                        {temp["results"][self.providers[0]]["error"]}"""
                     )
                 else:
                     return audio_analysis_result
diff --git a/libs/community/langchain_community/tools/financial_datasets/balance_sheets.py b/libs/community/langchain_community/tools/financial_datasets/balance_sheets.py
index 0b02b549ad6c21..4be8125cb5a444 100644
--- a/libs/community/langchain_community/tools/financial_datasets/balance_sheets.py
+++ b/libs/community/langchain_community/tools/financial_datasets/balance_sheets.py
@@ -20,7 +20,7 @@ class BalanceSheetsSchema(BaseModel):
         "Default is 'annual'.",
     )
     limit: int = Field(
-        description="The number of balance sheets to return. " "Default is 10.",
+        description="The number of balance sheets to return. Default is 10.",
     )
 
 
diff --git a/libs/community/langchain_community/tools/financial_datasets/cash_flow_statements.py b/libs/community/langchain_community/tools/financial_datasets/cash_flow_statements.py
index a627300a3a4339..5f621085a1838c 100644
--- a/libs/community/langchain_community/tools/financial_datasets/cash_flow_statements.py
+++ b/libs/community/langchain_community/tools/financial_datasets/cash_flow_statements.py
@@ -20,7 +20,7 @@ class CashFlowStatementsSchema(BaseModel):
         "Default is 'annual'.",
     )
     limit: int = Field(
-        description="The number of cash flow statements to return. " "Default is 10.",
+        description="The number of cash flow statements to return. Default is 10.",
     )
 
 
diff --git a/libs/community/langchain_community/tools/financial_datasets/income_statements.py b/libs/community/langchain_community/tools/financial_datasets/income_statements.py
index dc06d358df1178..d181ef7a1c1f6d 100644
--- a/libs/community/langchain_community/tools/financial_datasets/income_statements.py
+++ b/libs/community/langchain_community/tools/financial_datasets/income_statements.py
@@ -20,7 +20,7 @@ class IncomeStatementsSchema(BaseModel):
         "Default is 'annual'.",
     )
     limit: int = Field(
-        description="The number of income statements to return. " "Default is 10.",
+        description="The number of income statements to return. Default is 10.",
     )
 
 
diff --git a/libs/community/langchain_community/tools/gmail/create_draft.py b/libs/community/langchain_community/tools/gmail/create_draft.py
index b35b0f8758025e..a1cb44cd3cf9a7 100644
--- a/libs/community/langchain_community/tools/gmail/create_draft.py
+++ b/libs/community/langchain_community/tools/gmail/create_draft.py
@@ -81,7 +81,7 @@ def _run(
                 .create(userId="me", body=create_message)
                 .execute()
             )
-            output = f'Draft created. Draft Id: {draft["id"]}'
+            output = f"Draft created. Draft Id: {draft['id']}"
             return output
         except Exception as e:
             raise Exception(f"An error occurred: {e}")
diff --git a/libs/community/langchain_community/tools/gmail/send_message.py b/libs/community/langchain_community/tools/gmail/send_message.py
index 0d9ab4634993b3..fadab49014434d 100644
--- a/libs/community/langchain_community/tools/gmail/send_message.py
+++ b/libs/community/langchain_community/tools/gmail/send_message.py
@@ -41,7 +41,7 @@ class GmailSendMessage(GmailBaseTool):  # type: ignore[override, override]
 
     name: str = "send_gmail_message"
     description: str = (
-        "Use this tool to send email messages." " The input is the message, recipients"
+        "Use this tool to send email messages. The input is the message, recipients"
     )
     args_schema: Type[SendMessageSchema] = SendMessageSchema
 
@@ -86,6 +86,6 @@ def _run(
                 .send(userId="me", body=create_message)
             )
             sent_message = send_message.execute()
-            return f'Message sent. Message Id: {sent_message["id"]}'
+            return f"Message sent. Message Id: {sent_message['id']}"
         except Exception as error:
             raise Exception(f"An error occurred: {error}")
diff --git a/libs/community/langchain_community/tools/nuclia/tool.py b/libs/community/langchain_community/tools/nuclia/tool.py
index 02cb335367a532..8bae0929a744c5 100644
--- a/libs/community/langchain_community/tools/nuclia/tool.py
+++ b/libs/community/langchain_community/tools/nuclia/tool.py
@@ -161,7 +161,7 @@ def _pushField(self, id: str, field: Any) -> str:
         )
         if response.status_code != 200:
             logger.info(
-                f"Error pushing field {id}:" f"{response.status_code} {response.text}"
+                f"Error pushing field {id}:{response.status_code} {response.text}"
             )
             raise ValueError("Error pushing field")
         else:
@@ -177,7 +177,7 @@ def _pull(self, id: str) -> str:
             logger.info(f"{id} not in queue")
             return ""
         elif result["status"] == "pending":
-            logger.info(f'Waiting for {result["uuid"]} to be processed')
+            logger.info(f"Waiting for {result['uuid']} to be processed")
             return ""
         else:
             return result["data"]
diff --git a/libs/community/langchain_community/tools/office365/send_event.py b/libs/community/langchain_community/tools/office365/send_event.py
index e7513025ac1f41..052fc19c0e3d2b 100644
--- a/libs/community/langchain_community/tools/office365/send_event.py
+++ b/libs/community/langchain_community/tools/office365/send_event.py
@@ -6,10 +6,10 @@
 
 from datetime import datetime as dt
 from typing import List, Optional, Type
+from zoneinfo import ZoneInfo
 
 from langchain_core.callbacks import CallbackManagerForToolRun
 from pydantic import BaseModel, Field
-from zoneinfo import ZoneInfo
 
 from langchain_community.tools.office365.base import O365BaseTool
 from langchain_community.tools.office365.utils import UTC_FORMAT
diff --git a/libs/community/langchain_community/tools/openapi/utils/api_models.py b/libs/community/langchain_community/tools/openapi/utils/api_models.py
index fef0b849ae37dc..8358305464d7f1 100644
--- a/libs/community/langchain_community/tools/openapi/utils/api_models.py
+++ b/libs/community/langchain_community/tools/openapi/utils/api_models.py
@@ -576,8 +576,7 @@ def _format_nested_properties(
                 prop_type = f"{{\n{nested_props}\n{' ' * indent}}}"
 
             formatted_props.append(
-                f"{prop_desc}\n{' ' * indent}{prop_name}"
-                f"{prop_required}: {prop_type},"
+                f"{prop_desc}\n{' ' * indent}{prop_name}{prop_required}: {prop_type},"
             )
 
         return "\n".join(formatted_props)
diff --git a/libs/community/langchain_community/utilities/bibtex.py b/libs/community/langchain_community/utilities/bibtex.py
index a3bf82ab738896..050b3b61025090 100644
--- a/libs/community/langchain_community/utilities/bibtex.py
+++ b/libs/community/langchain_community/utilities/bibtex.py
@@ -70,7 +70,7 @@ def get_metadata(
         if "url" in entry:
             url = entry["url"]
         elif "doi" in entry:
-            url = f'https://doi.org/{entry["doi"]}'
+            url = f"https://doi.org/{entry['doi']}"
         else:
             url = None
         meta = {
diff --git a/libs/community/langchain_community/utilities/cassandra_database.py b/libs/community/langchain_community/utilities/cassandra_database.py
index 4ec1973b1668ed..cd1c0f01964380 100644
--- a/libs/community/langchain_community/utilities/cassandra_database.py
+++ b/libs/community/langchain_community/utilities/cassandra_database.py
@@ -433,7 +433,7 @@ def _resolve_session(
             import cassio.config
         except ImportError:
             raise ValueError(
-                "cassio package not found, please install with" " `pip install cassio`"
+                "cassio package not found, please install with `pip install cassio`"
             )
 
         # Use pre-existing session on cassio
diff --git a/libs/community/langchain_community/utilities/clickup.py b/libs/community/langchain_community/utilities/clickup.py
index f5f00b22a0884c..ef4d6140998bad 100644
--- a/libs/community/langchain_community/utilities/clickup.py
+++ b/libs/community/langchain_community/utilities/clickup.py
@@ -460,7 +460,7 @@ def get_task_attribute(self, query: str) -> Dict:
 
         if params["attribute_name"] not in task:
             return {
-                "Error": f"""attribute_name = {params['attribute_name']} was not 
+                "Error": f"""attribute_name = {params["attribute_name"]} was not 
 found in task keys {task.keys()}. Please call again with one of the key names."""
             }
 
diff --git a/libs/community/langchain_community/utilities/github.py b/libs/community/langchain_community/utilities/github.py
index 2674b749de8f10..fab79012ed8568 100644
--- a/libs/community/langchain_community/utilities/github.py
+++ b/libs/community/langchain_community/utilities/github.py
@@ -20,8 +20,7 @@ def _import_tiktoken() -> Any:
         import tiktoken
     except ImportError:
         raise ImportError(
-            "tiktoken is not installed. "
-            "Please install it with `pip install tiktoken`"
+            "tiktoken is not installed. Please install it with `pip install tiktoken`"
         )
     return tiktoken
 
@@ -90,8 +89,7 @@ def validate_environment(cls, values: Dict) -> Any:
             installation = installation[0]
         except ValueError as e:
             raise ValueError(
-                "Please make sure to give correct github parameters "
-                f"Error message: {e}"
+                f"Please make sure to give correct github parameters Error message: {e}"
             )
         # create a GitHub instance:
         g = installation.get_github_for_installation()
@@ -257,8 +255,7 @@ def list_branches_in_repo(self) -> str:
             if branches:
                 branches_str = "\n".join(branches)
                 return (
-                    f"Found {len(branches)} branches in the repository:"
-                    f"\n{branches_str}"
+                    f"Found {len(branches)} branches in the repository:\n{branches_str}"
                 )
             else:
                 return "No branches found in the repository"
@@ -774,8 +771,7 @@ def search_code(self, query: str) -> str:
                 code.path, ref=self.active_branch
             ).decoded_content.decode()
             results.append(
-                f"Filepath: `{code.path}`\nFile contents: "
-                f"{file_content}\n<END OF FILE>"
+                f"Filepath: `{code.path}`\nFile contents: {file_content}\n<END OF FILE>"
             )
             count += 1
         return "\n".join(results)
diff --git a/libs/community/langchain_community/utilities/google_places_api.py b/libs/community/langchain_community/utilities/google_places_api.py
index b0c6f152bd26b4..423aeee6ec02fc 100644
--- a/libs/community/langchain_community/utilities/google_places_api.py
+++ b/libs/community/langchain_community/utilities/google_places_api.py
@@ -84,7 +84,7 @@ def run(self, query: str) -> str:
             if details is not None:
                 places.append(details)
 
-        return "\n".join([f"{i+1}. {item}" for i, item in enumerate(places)])
+        return "\n".join([f"{i + 1}. {item}" for i, item in enumerate(places)])
 
     def fetch_place_details(self, place_id: str) -> Optional[str]:
         try:
diff --git a/libs/community/langchain_community/utilities/google_scholar.py b/libs/community/langchain_community/utilities/google_scholar.py
index ffc94848a61a56..2285f086891c99 100644
--- a/libs/community/langchain_community/utilities/google_scholar.py
+++ b/libs/community/langchain_community/utilities/google_scholar.py
@@ -121,10 +121,10 @@ def run(self, query: str) -> str:
         if not total_results:
             return "No good Google Scholar Result was found"
         docs = [
-            f"Title: {result.get('title','')}\n"
-            f"Authors: {','.join([author.get('name') for author in result.get('publication_info',{}).get('authors',[])])}\n"  # noqa: E501
-            f"Summary: {result.get('publication_info',{}).get('summary','')}\n"
-            f"Total-Citations: {result.get('inline_links',{}).get('cited_by',{}).get('total','')}"  # noqa: E501
+            f"Title: {result.get('title', '')}\n"
+            f"Authors: {','.join([author.get('name') for author in result.get('publication_info', {}).get('authors', [])])}\n"  # noqa: E501
+            f"Summary: {result.get('publication_info', {}).get('summary', '')}\n"
+            f"Total-Citations: {result.get('inline_links', {}).get('cited_by', {}).get('total', '')}"  # noqa: E501
             for result in total_results
         ]
         return "\n\n".join(docs)
diff --git a/libs/community/langchain_community/utilities/merriam_webster.py b/libs/community/langchain_community/utilities/merriam_webster.py
index 8cf9e18a107e80..94268556d02b56 100644
--- a/libs/community/langchain_community/utilities/merriam_webster.py
+++ b/libs/community/langchain_community/utilities/merriam_webster.py
@@ -84,7 +84,7 @@ def _format_definitions(self, query: str, definitions: List[Dict]) -> str:
             formatted_definitions.extend(self._format_definition(definition))
 
         if len(formatted_definitions) == 1:
-            return f"Definition of '{query}':\n" f"{formatted_definitions[0]}"
+            return f"Definition of '{query}':\n{formatted_definitions[0]}"
 
         result = f"Definitions of '{query}':\n\n"
         for i, formatted_definition in enumerate(formatted_definitions, 1):
diff --git a/libs/community/langchain_community/utilities/openapi.py b/libs/community/langchain_community/utilities/openapi.py
index 1d99f7e182301c..9e6ff44cf12a25 100644
--- a/libs/community/langchain_community/utilities/openapi.py
+++ b/libs/community/langchain_community/utilities/openapi.py
@@ -211,8 +211,7 @@ def _alert_unsupported_spec(obj: dict) -> None:
             )
         else:
             raise ValueError(
-                "Attempting to load an unsupported spec:"
-                f"\n\n{obj}\n{warning_message}"
+                f"Attempting to load an unsupported spec:\n\n{obj}\n{warning_message}"
             )
 
     @classmethod
diff --git a/libs/community/langchain_community/utilities/portkey.py b/libs/community/langchain_community/utilities/portkey.py
index dbaf41840f072e..5eb16f7af518b0 100644
--- a/libs/community/langchain_community/utilities/portkey.py
+++ b/libs/community/langchain_community/utilities/portkey.py
@@ -26,9 +26,9 @@ def Config(
         cache_force_refresh: Optional[str] = None,
         cache_age: Optional[int] = None,
     ) -> Dict[str, str]:
-        assert retry_count is None or retry_count in range(
-            1, 6
-        ), "retry_count must be an integer and in range [1, 2, 3, 4, 5]"
+        assert retry_count is None or retry_count in range(1, 6), (
+            "retry_count must be an integer and in range [1, 2, 3, 4, 5]"
+        )
         assert cache is None or cache in [
             "simple",
             "semantic",
@@ -37,9 +37,9 @@ def Config(
             isinstance(cache_force_refresh, str)
             and cache_force_refresh in ["True", "False"]
         ), "cache_force_refresh must be 'True' or 'False'"
-        assert cache_age is None or isinstance(
-            cache_age, int
-        ), "cache_age must be an integer"
+        assert cache_age is None or isinstance(cache_age, int), (
+            "cache_age must be an integer"
+        )
 
         os.environ["OPENAI_API_BASE"] = Portkey.base
 
diff --git a/libs/community/langchain_community/utilities/sql_database.py b/libs/community/langchain_community/utilities/sql_database.py
index 85f0a1076770d9..62eec9e472b48e 100644
--- a/libs/community/langchain_community/utilities/sql_database.py
+++ b/libs/community/langchain_community/utilities/sql_database.py
@@ -24,8 +24,8 @@
 
 def _format_index(index: sqlalchemy.engine.interfaces.ReflectedIndex) -> str:
     return (
-        f'Name: {index["name"]}, Unique: {index["unique"]},'
-        f' Columns: {str(index["column_names"])}'
+        f"Name: {index['name']}, Unique: {index['unique']},"
+        f" Columns: {str(index['column_names'])}"
     )
 
 
diff --git a/libs/community/langchain_community/vectorstores/aerospike.py b/libs/community/langchain_community/vectorstores/aerospike.py
index 997646a00f98af..96ef3c659eb68c 100644
--- a/libs/community/langchain_community/vectorstores/aerospike.py
+++ b/libs/community/langchain_community/vectorstores/aerospike.py
@@ -149,7 +149,7 @@ def convert_distance_strategy(
             return DistanceStrategy.EUCLIDEAN_DISTANCE
 
         raise ValueError(
-            "Unknown distance strategy, must be cosine, dot_product" ", or euclidean"
+            "Unknown distance strategy, must be cosine, dot_product, or euclidean"
         )
 
     def add_texts(
@@ -437,8 +437,7 @@ def _select_relevance_score_fn(self) -> Callable[[float], float]:
             return self._euclidean_relevance_score_fn
         else:
             raise ValueError(
-                "Unknown distance strategy, must be cosine, dot_product"
-                ", or euclidean"
+                "Unknown distance strategy, must be cosine, dot_product, or euclidean"
             )
 
     @staticmethod
diff --git a/libs/community/langchain_community/vectorstores/apache_doris.py b/libs/community/langchain_community/vectorstores/apache_doris.py
index 4d25f0a0aeb762..56ee6c0f64ffd8 100644
--- a/libs/community/langchain_community/vectorstores/apache_doris.py
+++ b/libs/community/langchain_community/vectorstores/apache_doris.py
@@ -123,10 +123,10 @@ def __init__(
 
         self.schema = f"""\
 CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(    
-    {self.config.column_map['id']} varchar(50),
-    {self.config.column_map['document']} string,
-    {self.config.column_map['embedding']} array<float>,
-    {self.config.column_map['metadata']} string
+    {self.config.column_map["id"]} varchar(50),
+    {self.config.column_map["document"]} string,
+    {self.config.column_map["embedding"]} array<float>,
+    {self.config.column_map["metadata"]} string
 ) ENGINE = OLAP UNIQUE KEY(id) DISTRIBUTED BY HASH(id) \
   PROPERTIES ("replication_allocation" = "tag.location.default: 1")\
 """
@@ -179,7 +179,7 @@ def _build_insert_sql(self, transac: Iterable, column_names: Iterable[str]) -> s
                 INSERT INTO
                     {self.config.database}.{self.config.table}({ks})
                 VALUES
-                {','.join(_data)}
+                {",".join(_data)}
                 """
         return i_str
 
@@ -310,10 +310,10 @@ def _build_query_sql(
             where_str = ""
 
         q_str = f"""
-            SELECT {self.config.column_map['document']}, 
-                {self.config.column_map['metadata']}, 
+            SELECT {self.config.column_map["document"]}, 
+                {self.config.column_map["metadata"]}, 
                 cosine_distance(array<float>[{q_emb_str}],
-                  {self.config.column_map['embedding']}) as dist
+                  {self.config.column_map["embedding"]}) as dist
             FROM {self.config.database}.{self.config.table}
             {where_str}
             ORDER BY dist {self.dist_order}
diff --git a/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py b/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py
index 8d0d90dd92e9c7..a2d6327d09dcbf 100644
--- a/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py
+++ b/libs/community/langchain_community/vectorstores/azure_cosmos_db_no_sql.py
@@ -617,7 +617,7 @@ def _construct_query(
         ):
             query = f"SELECT {'TOP ' + str(k) + ' ' if not offset_limit else ''}"
         else:
-            query = f"""SELECT {'TOP @limit ' if not offset_limit else ''}"""
+            query = f"""SELECT {"TOP @limit " if not offset_limit else ""}"""
         query += self._generate_projection_fields(
             projection_mapping, query_type, embeddings
         )
@@ -790,7 +790,7 @@ def _build_where_clause(self, pre_filter: PreFilter) -> str:
                     # e.g., for IN clauses
                     value = f"({', '.join(map(str, condition.value))})"
                 clauses.append(f"c.{condition.property} {sql_operator} {value}")
-        return f""" WHERE {' {} '.format(sql_logical_operator).join(clauses)}""".strip()
+        return f""" WHERE {" {} ".format(sql_logical_operator).join(clauses)}""".strip()
 
     def _execute_query(
         self,
diff --git a/libs/community/langchain_community/vectorstores/bigquery_vector_search.py b/libs/community/langchain_community/vectorstores/bigquery_vector_search.py
index 07114924dca6e1..be4596cd148c94 100644
--- a/libs/community/langchain_community/vectorstores/bigquery_vector_search.py
+++ b/libs/community/langchain_community/vectorstores/bigquery_vector_search.py
@@ -122,9 +122,7 @@ def __init__(
         self.text_embedding_field = text_embedding_field
         self.doc_id_field = doc_id_field
         self.distance_strategy = distance_strategy
-        self._full_table_id = (
-            f"{self.project_id}." f"{self.dataset_name}." f"{self.table_name}"
-        )
+        self._full_table_id = f"{self.project_id}.{self.dataset_name}.{self.table_name}"
         self._logger.debug("Using table `%s`", self.full_table_id)
         with _vector_table_lock:
             self.vectors_table = self._initialize_table()
@@ -149,7 +147,7 @@ def _initialize_table(self) -> Any:
             columns[self.doc_id_field].field_type != "STRING"
             or columns[self.doc_id_field].mode == "REPEATED"
         ):
-            raise ValueError(f"Column {self.doc_id_field} must be of " "STRING type")
+            raise ValueError(f"Column {self.doc_id_field} must be of STRING type")
         if self.metadata_field not in columns:
             changed_schema = True
             schema.append(
@@ -171,7 +169,7 @@ def _initialize_table(self) -> Any:
             columns[self.content_field].field_type != "STRING"
             or columns[self.content_field].mode == "REPEATED"
         ):
-            raise ValueError(f"Column {self.content_field} must be of " "STRING type")
+            raise ValueError(f"Column {self.content_field} must be of STRING type")
         if self.text_embedding_field not in columns:
             changed_schema = True
             schema.append(
@@ -186,7 +184,7 @@ def _initialize_table(self) -> Any:
             or columns[self.text_embedding_field].mode != "REPEATED"
         ):
             raise ValueError(
-                f"Column {self.text_embedding_field} must be of " "ARRAY<FLOAT64> type"
+                f"Column {self.text_embedding_field} must be of ARRAY<FLOAT64> type"
             )
         if changed_schema:
             self._logger.debug("Updated table `%s` schema.", self.full_table_id)
@@ -389,9 +387,7 @@ def get_documents(
                     )
                 else:
                     val = str(i[1]).replace('"', '\\"')
-                    expr = (
-                        f"JSON_VALUE(`{self.metadata_field}`,'$.{i[0]}')" f' = "{val}"'
-                    )
+                    expr = f"JSON_VALUE(`{self.metadata_field}`,'$.{i[0]}') = \"{val}\""
                 filter_expressions.append(expr)
             filter_expression_str = " AND ".join(filter_expressions)
             where_filter_expr = f" AND ({filter_expression_str})"
@@ -520,7 +516,7 @@ def _search_with_score_and_embeddings_by_vector(
         elif fraction_lists_to_search:
             if fraction_lists_to_search == 0 or fraction_lists_to_search >= 1.0:
                 raise ValueError(
-                    "`fraction_lists_to_search` must be between " "0.0 and 1.0"
+                    "`fraction_lists_to_search` must be between 0.0 and 1.0"
                 )
             options_string = (
                 ',options => \'{"fraction_lists_to_search":'
diff --git a/libs/community/langchain_community/vectorstores/chroma.py b/libs/community/langchain_community/vectorstores/chroma.py
index 1ab7ddad140d6d..ebf91f718af3a2 100644
--- a/libs/community/langchain_community/vectorstores/chroma.py
+++ b/libs/community/langchain_community/vectorstores/chroma.py
@@ -643,7 +643,7 @@ def max_marginal_relevance_search(
         """
         if self._embedding_function is None:
             raise ValueError(
-                "For MMR search, you must specify an embedding function on" "creation."
+                "For MMR search, you must specify an embedding function oncreation."
             )
 
         embedding = self._embedding_function.embed_query(query)
diff --git a/libs/community/langchain_community/vectorstores/clarifai.py b/libs/community/langchain_community/vectorstores/clarifai.py
index b37b99f02a7064..4cae4bf7cf976e 100644
--- a/libs/community/langchain_community/vectorstores/clarifai.py
+++ b/libs/community/langchain_community/vectorstores/clarifai.py
@@ -115,14 +115,14 @@ def add_texts(
         assert length > 0, "No texts provided to add to the vectorstore."
 
         if metadatas is not None:
-            assert length == len(
-                metadatas
-            ), "Number of texts and metadatas should be the same."
+            assert length == len(metadatas), (
+                "Number of texts and metadatas should be the same."
+            )
 
         if ids is not None:
-            assert len(ltexts) == len(
-                ids
-            ), "Number of text inputs and input ids should be the same."
+            assert len(ltexts) == len(ids), (
+                "Number of text inputs and input ids should be the same."
+            )
 
         input_obj = Inputs.from_auth_helper(auth=self._auth)
         batch_size = 32
diff --git a/libs/community/langchain_community/vectorstores/clickhouse.py b/libs/community/langchain_community/vectorstores/clickhouse.py
index 4246abfc0ddde9..b05898d55cceff 100644
--- a/libs/community/langchain_community/vectorstores/clickhouse.py
+++ b/libs/community/langchain_community/vectorstores/clickhouse.py
@@ -341,27 +341,28 @@ def _schema(self, dim: int, index_params: Optional[str] = "") -> str:
         if self.config.index_type:
             return f"""\
         CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
-            {self.config.column_map['id']} Nullable(String),
-            {self.config.column_map['document']} Nullable(String),
-            {self.config.column_map['embedding']} Array(Float32),
-            {self.config.column_map['metadata']} JSON,
-            {self.config.column_map['uuid']} UUID DEFAULT generateUUIDv4(),
+            {self.config.column_map["id"]} Nullable(String),
+            {self.config.column_map["document"]} Nullable(String),
+            {self.config.column_map["embedding"]} Array(Float32),
+            {self.config.column_map["metadata"]} JSON,
+            {self.config.column_map["uuid"]} UUID DEFAULT generateUUIDv4(),
             CONSTRAINT cons_vec_len CHECK length(
-                {self.config.column_map['embedding']}) = {dim},
-            INDEX vec_idx {self.config.column_map['embedding']} TYPE \
+                {self.config.column_map["embedding"]}) = {dim},
+            INDEX vec_idx {self.config.column_map["embedding"]} TYPE \
         {self.config.index_type}({index_params}) GRANULARITY 1000
         ) ENGINE = MergeTree ORDER BY uuid SETTINGS index_granularity = 8192\
         """
         else:
             return f"""\
                 CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
-                    {self.config.column_map['id']} Nullable(String),
-                    {self.config.column_map['document']} Nullable(String),
-                    {self.config.column_map['embedding']} Array(Float32),
-                    {self.config.column_map['metadata']} JSON,
-                    {self.config.column_map['uuid']} UUID DEFAULT generateUUIDv4(),
+                    {self.config.column_map["id"]} Nullable(String),
+                    {self.config.column_map["document"]} Nullable(String),
+                    {self.config.column_map["embedding"]} Array(Float32),
+                    {self.config.column_map["metadata"]} JSON,
+                    {self.config.column_map["uuid"]} UUID DEFAULT generateUUIDv4(),
                     CONSTRAINT cons_vec_len CHECK length({
-                        self.config.column_map['embedding']}) = {dim}
+                self.config.column_map["embedding"]
+            }) = {dim}
                 ) ENGINE = MergeTree ORDER BY uuid
                 """
 
@@ -418,7 +419,7 @@ def _build_insert_sql(self, transac: Iterable, column_names: Iterable[str]) -> s
                 INSERT INTO TABLE 
                     {self.config.database}.{self.config.table}({ks})
                 VALUES
-                {','.join(_data)}
+                {",".join(_data)}
                 """
         return i_str
 
@@ -574,13 +575,13 @@ def _build_query_sql(
             for k in self.config.index_query_params:
                 settings_strs.append(f"SETTING {k}={self.config.index_query_params[k]}")
         q_str = f"""
-            SELECT {self.config.column_map['document']}, 
-                {self.config.column_map['metadata']}, dist
+            SELECT {self.config.column_map["document"]}, 
+                {self.config.column_map["metadata"]}, dist
             FROM {self.config.database}.{self.config.table}
             {where_str}
-            ORDER BY L2Distance({self.config.column_map['embedding']}, [{q_emb_str}]) 
+            ORDER BY L2Distance({self.config.column_map["embedding"]}, [{q_emb_str}]) 
                 AS dist {self.dist_order}
-            LIMIT {topk} {' '.join(settings_strs)}
+            LIMIT {topk} {" ".join(settings_strs)}
             """
         return q_str
 
diff --git a/libs/community/langchain_community/vectorstores/dashvector.py b/libs/community/langchain_community/vectorstores/dashvector.py
index 64f73630de6935..639856fcbce996 100644
--- a/libs/community/langchain_community/vectorstores/dashvector.py
+++ b/libs/community/langchain_community/vectorstores/dashvector.py
@@ -392,9 +392,7 @@ def from_texts(
             if resp:
                 collection = dashvector_client.get(collection_name)
             else:
-                raise ValueError(
-                    "Fail to create collection. " f"Error: {resp.message}."
-                )
+                raise ValueError(f"Fail to create collection. Error: {resp.message}.")
 
         dashvector_vector_db = cls(collection, embedding, text_field)
         dashvector_vector_db.add_texts(texts, metadatas, ids, batch_size)
diff --git a/libs/community/langchain_community/vectorstores/deeplake.py b/libs/community/langchain_community/vectorstores/deeplake.py
index 0de4c6032a708f..c0163560e31707 100644
--- a/libs/community/langchain_community/vectorstores/deeplake.py
+++ b/libs/community/langchain_community/vectorstores/deeplake.py
@@ -425,8 +425,7 @@ def _search(
         if embedding is None:
             if _embedding_function is None:
                 raise ValueError(
-                    "Either `embedding` or `embedding_function` needs to be"
-                    " specified."
+                    "Either `embedding` or `embedding_function` needs to be specified."
                 )
 
             embedding = _embedding_function(query) if query else None
diff --git a/libs/community/langchain_community/vectorstores/hanavector.py b/libs/community/langchain_community/vectorstores/hanavector.py
index 6c0a8040b255cd..9212c53f5a4caf 100644
--- a/libs/community/langchain_community/vectorstores/hanavector.py
+++ b/libs/community/langchain_community/vectorstores/hanavector.py
@@ -669,7 +669,7 @@ def _process_filter_object(self, filter):  # type: ignore[no-untyped-def]
                     if key in self.specific_metadata_columns
                     else f"JSON_VALUE({self.metadata_column}, '$.{key}')"
                 )
-                where_str += f"{selector} " f"{operator} {sql_param}"
+                where_str += f"{selector} {operator} {sql_param}"
 
         return where_str, query_tuple
 
diff --git a/libs/community/langchain_community/vectorstores/hippo.py b/libs/community/langchain_community/vectorstores/hippo.py
index 328a2f1e992266..373f6a0e06b154 100644
--- a/libs/community/langchain_community/vectorstores/hippo.py
+++ b/libs/community/langchain_community/vectorstores/hippo.py
@@ -118,7 +118,7 @@ def __init__(
                 self.hc.delete_table(self.table_name, self.database_name)
         except Exception as e:
             logging.error(
-                f"An error occurred while deleting the table " f"{self.table_name}: {e}"
+                f"An error occurred while deleting the table {self.table_name}: {e}"
             )
             raise
 
@@ -127,7 +127,7 @@ def __init__(
                 self.col = self.hc.get_table(self.table_name, self.database_name)
         except Exception as e:
             logging.error(
-                f"An error occurred while getting the table " f"{self.table_name}: {e}"
+                f"An error occurred while getting the table {self.table_name}: {e}"
             )
             raise
 
diff --git a/libs/community/langchain_community/vectorstores/infinispanvs.py b/libs/community/langchain_community/vectorstores/infinispanvs.py
index 3f7c34158df15d..c9012e17fbef1f 100644
--- a/libs/community/langchain_community/vectorstores/infinispanvs.py
+++ b/libs/community/langchain_community/vectorstores/infinispanvs.py
@@ -90,7 +90,7 @@ def __init__(
             self._textfield = self._configuration.get("text_field", "text")
         else:
             warnings.warn(
-                "`textfield` is deprecated. Please use `text_field` " "param.",
+                "`textfield` is deprecated. Please use `text_field` param.",
                 DeprecationWarning,
             )
         self._vectorfield = self._configuration.get("vectorfield", "")
@@ -98,7 +98,7 @@ def __init__(
             self._vectorfield = self._configuration.get("vector_field", "vector")
         else:
             warnings.warn(
-                "`vectorfield` is deprecated. Please use `vector_field` " "param.",
+                "`vectorfield` is deprecated. Please use `vector_field` param.",
                 DeprecationWarning,
             )
         self._to_content = self._configuration.get(
@@ -361,16 +361,16 @@ def _query_result_to_docs(
     def configure(self, metadata: dict, dimension: int) -> None:
         schema = self.schema_builder(metadata, dimension)
         output = self.schema_create(schema)
-        assert (
-            output.status_code == self.ispn.Codes.OK
-        ), "Unable to create schema. Already exists? "
+        assert output.status_code == self.ispn.Codes.OK, (
+            "Unable to create schema. Already exists? "
+        )
         "Consider using clear_old=True"
         assert json.loads(output.text)["error"] is None
         if not self.cache_exists():
             output = self.cache_create()
-            assert (
-                output.status_code == self.ispn.Codes.OK
-            ), "Unable to create cache. Already exists? "
+            assert output.status_code == self.ispn.Codes.OK, (
+                "Unable to create cache. Already exists? "
+            )
             "Consider using clear_old=True"
             # Ensure index is clean
             self.cache_index_clear()
diff --git a/libs/community/langchain_community/vectorstores/lancedb.py b/libs/community/langchain_community/vectorstores/lancedb.py
index f08e4380481b1f..11cc955cac40ae 100644
--- a/libs/community/langchain_community/vectorstores/lancedb.py
+++ b/libs/community/langchain_community/vectorstores/lancedb.py
@@ -562,7 +562,7 @@ def max_marginal_relevance_search(
 
         if self._embedding is None:
             raise ValueError(
-                "For MMR search, you must specify an embedding function on" "creation."
+                "For MMR search, you must specify an embedding function oncreation."
             )
 
         embedding = self._embedding.embed_query(query)
diff --git a/libs/community/langchain_community/vectorstores/manticore_search.py b/libs/community/langchain_community/vectorstores/manticore_search.py
index 3743e603da7976..027d4f6adc8c17 100644
--- a/libs/community/langchain_community/vectorstores/manticore_search.py
+++ b/libs/community/langchain_community/vectorstores/manticore_search.py
@@ -150,16 +150,16 @@ def __init__(
         # Initialize the schema
         self.schema = f"""\
 CREATE TABLE IF NOT EXISTS {self.config.table}(
-    {self.config.column_map['id']} bigint,
-    {self.config.column_map['document']} text indexed stored,
-    {self.config.column_map['embedding']} \
+    {self.config.column_map["id"]} bigint,
+    {self.config.column_map["document"]} text indexed stored,
+    {self.config.column_map["embedding"]} \
         float_vector knn_type='{self.config.knn_type}' \
         knn_dims='{self.dim}' \
         hnsw_similarity='{self.config.hnsw_similarity}' \
         hnsw_m='{self.config.hnsw_m}' \
         hnsw_ef_construction='{self.config.hnsw_ef_construction}',
-    {self.config.column_map['metadata']} json,
-    {self.config.column_map['uuid']} text indexed stored
+    {self.config.column_map["metadata"]} json,
+    {self.config.column_map["uuid"]} text indexed stored
 )\
 """
 
diff --git a/libs/community/langchain_community/vectorstores/meilisearch.py b/libs/community/langchain_community/vectorstores/meilisearch.py
index 885d4d5cff4417..c80301f3714bee 100644
--- a/libs/community/langchain_community/vectorstores/meilisearch.py
+++ b/libs/community/langchain_community/vectorstores/meilisearch.py
@@ -33,8 +33,7 @@ def _create_client(
         client = meilisearch.Client(url=url, api_key=api_key)
     elif not isinstance(client, meilisearch.Client):
         raise ValueError(
-            f"client should be an instance of meilisearch.Client, "
-            f"got {type(client)}"
+            f"client should be an instance of meilisearch.Client, got {type(client)}"
         )
     try:
         client.version()
diff --git a/libs/community/langchain_community/vectorstores/milvus.py b/libs/community/langchain_community/vectorstores/milvus.py
index 04bff999913dbd..7dd404999683c8 100644
--- a/libs/community/langchain_community/vectorstores/milvus.py
+++ b/libs/community/langchain_community/vectorstores/milvus.py
@@ -550,15 +550,15 @@ def add_texts(
 
         texts = list(texts)
         if not self.auto_id:
-            assert isinstance(
-                ids, list
-            ), "A list of valid ids are required when auto_id is False."
-            assert len(set(ids)) == len(
-                texts
-            ), "Different lengths of texts and unique ids are provided."
-            assert all(
-                len(x.encode()) <= 65_535 for x in ids
-            ), "Each id should be a string less than 65535 bytes."
+            assert isinstance(ids, list), (
+                "A list of valid ids are required when auto_id is False."
+            )
+            assert len(set(ids)) == len(texts), (
+                "Different lengths of texts and unique ids are provided."
+            )
+            assert all(len(x.encode()) <= 65_535 for x in ids), (
+                "Each id should be a string less than 65535 bytes."
+            )
 
         try:
             embeddings = self.embedding_func.embed_documents(texts)
@@ -953,13 +953,13 @@ def delete(  # type: ignore[no-untyped-def]
         if isinstance(ids, list) and len(ids) > 0:
             if expr is not None:
                 logger.warning(
-                    "Both ids and expr are provided. " "Ignore expr and delete by ids."
+                    "Both ids and expr are provided. Ignore expr and delete by ids."
                 )
             expr = f"{self._primary_field} in {ids}"
         else:
-            assert isinstance(
-                expr, str
-            ), "Either ids list or expr string must be provided."
+            assert isinstance(expr, str), (
+                "Either ids list or expr string must be provided."
+            )
         return self.col.delete(expr=expr, **kwargs)  # type: ignore[union-attr]
 
     @classmethod
diff --git a/libs/community/langchain_community/vectorstores/myscale.py b/libs/community/langchain_community/vectorstores/myscale.py
index d3dec65c8b71e4..711b525e40606f 100644
--- a/libs/community/langchain_community/vectorstores/myscale.py
+++ b/libs/community/langchain_community/vectorstores/myscale.py
@@ -166,16 +166,16 @@ def __init__(
         )
         schema_ = f"""
             CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(
-                {self.config.column_map['id']} String,
-                {self.config.column_map['text']} String,
-                {self.config.column_map['vector']} Array(Float32),
-                {self.config.column_map['metadata']} JSON,
+                {self.config.column_map["id"]} String,
+                {self.config.column_map["text"]} String,
+                {self.config.column_map["vector"]} Array(Float32),
+                {self.config.column_map["metadata"]} JSON,
                 CONSTRAINT cons_vec_len CHECK length(\
-                    {self.config.column_map['vector']}) = {dim},
-                VECTOR INDEX vidx {self.config.column_map['vector']} \
+                    {self.config.column_map["vector"]}) = {dim},
+                VECTOR INDEX vidx {self.config.column_map["vector"]} \
                     TYPE {self.config.index_type}(\
                         'metric_type={self.config.metric}'{index_params})
-            ) ENGINE = MergeTree ORDER BY {self.config.column_map['id']}
+            ) ENGINE = MergeTree ORDER BY {self.config.column_map["id"]}
         """
         self.dim = dim
         self.BS = "\\"
@@ -220,7 +220,7 @@ def _build_istr(self, transac: Iterable, column_names: Iterable[str]) -> str:
                 INSERT INTO TABLE 
                     {self.config.database}.{self.config.table}({ks})
                 VALUES
-                {','.join(_data)}
+                {",".join(_data)}
                 """
         return i_str
 
@@ -345,11 +345,11 @@ def _build_qstr(
             where_str = ""
 
         q_str = f"""
-            SELECT {self.config.column_map['text']}, 
-                {self.config.column_map['metadata']}, dist
+            SELECT {self.config.column_map["text"]}, 
+                {self.config.column_map["metadata"]}, dist
             FROM {self.config.database}.{self.config.table}
             {where_str}
-            ORDER BY distance({self.config.column_map['vector']}, [{q_emb_str}]) 
+            ORDER BY distance({self.config.column_map["vector"]}, [{q_emb_str}]) 
                 AS dist {self.dist_order}
             LIMIT {topk}
             """
@@ -475,9 +475,9 @@ def delete(
             Optional[bool]: True if deletion is successful,
             False otherwise, None if not implemented.
         """
-        assert not (
-            ids is None and where_str is None
-        ), "You need to specify where to be deleted! Either with `ids` or `where_str`"
+        assert not (ids is None and where_str is None), (
+            "You need to specify where to be deleted! Either with `ids` or `where_str`"
+        )
         conds = []
         if ids and len(ids) > 0:
             id_list = ", ".join([f"'{id}'" for id in ids])
@@ -536,11 +536,11 @@ def _build_qstr(
             where_str = ""
 
         q_str = f"""
-            SELECT {self.config.column_map['text']}, dist, 
-                {','.join(self.must_have_cols)}
+            SELECT {self.config.column_map["text"]}, dist, 
+                {",".join(self.must_have_cols)}
             FROM {self.config.database}.{self.config.table}
             {where_str}
-            ORDER BY distance({self.config.column_map['vector']}, [{q_emb_str}]) 
+            ORDER BY distance({self.config.column_map["vector"]}, [{q_emb_str}]) 
                 AS dist {self.dist_order}
             LIMIT {topk}
             """
diff --git a/libs/community/langchain_community/vectorstores/neo4j_vector.py b/libs/community/langchain_community/vectorstores/neo4j_vector.py
index 03d97a5a9d034e..b65f165abad750 100644
--- a/libs/community/langchain_community/vectorstores/neo4j_vector.py
+++ b/libs/community/langchain_community/vectorstores/neo4j_vector.py
@@ -323,8 +323,7 @@ def _handle_field_filter(
 
     if field.startswith("$"):
         raise ValueError(
-            f"Invalid filter condition. Expected a field but got an operator: "
-            f"{field}"
+            f"Invalid filter condition. Expected a field but got an operator: {field}"
         )
 
     # Allow [a-zA-Z0-9_], disallow $ for now until we support escape characters
@@ -344,8 +343,7 @@ def _handle_field_filter(
         # Verify that that operator is an operator
         if operator not in SUPPORTED_OPERATORS:
             raise ValueError(
-                f"Invalid operator: {operator}. "
-                f"Expected one of {SUPPORTED_OPERATORS}"
+                f"Invalid operator: {operator}. Expected one of {SUPPORTED_OPERATORS}"
             )
     else:  # Then we assume an equality operator
         operator = "$eq"
@@ -423,8 +421,7 @@ def construct_metadata_filter(filter: Dict[str, Any]) -> Tuple[str, Dict]:
                 # Then it's an operator
                 if key.lower() not in ["$and", "$or"]:
                     raise ValueError(
-                        f"Invalid filter condition. Expected $and or $or "
-                        f"but got: {key}"
+                        f"Invalid filter condition. Expected $and or $or but got: {key}"
                     )
             else:
                 # Then it's a field
@@ -459,7 +456,7 @@ def construct_metadata_filter(filter: Dict[str, Any]) -> Tuple[str, Dict]:
                     )
             else:
                 raise ValueError(
-                    f"Invalid filter condition. Expected $and or $or " f"but got: {key}"
+                    f"Invalid filter condition. Expected $and or $or but got: {key}"
                 )
         elif len(filter) > 1:
             # Then all keys have to be fields (they cannot be operators)
@@ -1336,8 +1333,7 @@ def from_existing_index(
 
         if search_type == SearchType.HYBRID and not keyword_index_name:
             raise ValueError(
-                "keyword_index name has to be specified "
-                "when using hybrid search option"
+                "keyword_index name has to be specified when using hybrid search option"
             )
 
         store = cls(
diff --git a/libs/community/langchain_community/vectorstores/oraclevs.py b/libs/community/langchain_community/vectorstores/oraclevs.py
index 2ca39e9f6f1b50..6aa767927f5e6b 100644
--- a/libs/community/langchain_community/vectorstores/oraclevs.py
+++ b/libs/community/langchain_community/vectorstores/oraclevs.py
@@ -75,8 +75,7 @@ def _table_exists(client: Connection, table_name: str) -> bool:
         import oracledb
     except ImportError as e:
         raise ImportError(
-            "Unable to import oracledb, please install with "
-            "`pip install -U oracledb`."
+            "Unable to import oracledb, please install with `pip install -U oracledb`."
         ) from e
 
     try:
@@ -775,8 +774,9 @@ def similarity_search_by_vector_returning_embeddings(
         SELECT id,
           text,
           metadata,
-          vector_distance(embedding, :embedding, {_get_distance_function(
-            self.distance_strategy)}) as distance,
+          vector_distance(embedding, :embedding, {
+            _get_distance_function(self.distance_strategy)
+        }) as distance,
           embedding
         FROM {self.table_name}
         ORDER BY distance
@@ -1010,7 +1010,7 @@ def from_texts(
         )
         if not isinstance(distance_strategy, DistanceStrategy):
             raise TypeError(
-                f"Expected DistanceStrategy got " f"{type(distance_strategy).__name__} "
+                f"Expected DistanceStrategy got {type(distance_strategy).__name__} "
             )
 
         query = kwargs.get("query", "What is a Oracle database")
diff --git a/libs/community/langchain_community/vectorstores/pgvector.py b/libs/community/langchain_community/vectorstores/pgvector.py
index 85814bef99488f..111b8da0bba055 100644
--- a/libs/community/langchain_community/vectorstores/pgvector.py
+++ b/libs/community/langchain_community/vectorstores/pgvector.py
@@ -900,8 +900,7 @@ def _create_filter_clause(self, filters: Any) -> Any:
                         )
                 else:
                     raise ValueError(
-                        f"Invalid filter condition. Expected $and or $or "
-                        f"but got: {key}"
+                        f"Invalid filter condition. Expected $and or $or but got: {key}"
                     )
             elif len(filters) > 1:
                 # Then all keys have to be fields (they cannot be operators)
diff --git a/libs/community/langchain_community/vectorstores/pinecone.py b/libs/community/langchain_community/vectorstores/pinecone.py
index 7d960409e6b0fc..7ad40b2c0c889f 100644
--- a/libs/community/langchain_community/vectorstores/pinecone.py
+++ b/libs/community/langchain_community/vectorstores/pinecone.py
@@ -71,7 +71,7 @@ def __init__(
             )
         if not isinstance(index, pinecone.Index):
             raise ValueError(
-                f"client should be an instance of pinecone.Index, " f"got {type(index)}"
+                f"client should be an instance of pinecone.Index, got {type(index)}"
             )
         self._index = index
         self._embedding = embedding
diff --git a/libs/community/langchain_community/vectorstores/rocksetdb.py b/libs/community/langchain_community/vectorstores/rocksetdb.py
index 263a211fba3249..0f5345eda5a8fc 100644
--- a/libs/community/langchain_community/vectorstores/rocksetdb.py
+++ b/libs/community/langchain_community/vectorstores/rocksetdb.py
@@ -271,10 +271,10 @@ def similarity_search_by_vector_with_relevance_scores(
         finalResult: list[Tuple[Document, float]] = []
         for document in query_response.results:
             metadata = {}
-            assert isinstance(
-                document, dict
-            ), "document should be of type `dict[str,Any]`. But found: `{}`".format(
-                type(document)
+            assert isinstance(document, dict), (
+                "document should be of type `dict[str,Any]`. But found: `{}`".format(
+                    type(document)
+                )
             )
             for k, v in document.items():
                 if k == self._text_key:
diff --git a/libs/community/langchain_community/vectorstores/sklearn.py b/libs/community/langchain_community/vectorstores/sklearn.py
index 96953f69ff4529..4c83543276c276 100644
--- a/libs/community/langchain_community/vectorstores/sklearn.py
+++ b/libs/community/langchain_community/vectorstores/sklearn.py
@@ -171,8 +171,7 @@ def embeddings(self) -> Embeddings:
     def persist(self) -> None:
         if self._serializer is None:
             raise SKLearnVectorStoreException(
-                "You must specify a persist_path on creation to persist the "
-                "collection."
+                "You must specify a persist_path on creation to persist the collection."
             )
         data = {
             "ids": self._ids,
@@ -185,7 +184,7 @@ def persist(self) -> None:
     def _load(self) -> None:
         if self._serializer is None:
             raise SKLearnVectorStoreException(
-                "You must specify a persist_path on creation to load the " "collection."
+                "You must specify a persist_path on creation to load the collection."
             )
         data = self._serializer.load()
         self._embeddings = data["embeddings"]
diff --git a/libs/community/langchain_community/vectorstores/sqlitevec.py b/libs/community/langchain_community/vectorstores/sqlitevec.py
index 13a2d5ee9208c0..52da1942f5adb8 100644
--- a/libs/community/langchain_community/vectorstores/sqlitevec.py
+++ b/libs/community/langchain_community/vectorstores/sqlitevec.py
@@ -132,8 +132,7 @@ def add_texts(
             for text, metadata, embed in zip(texts, metadatas, embeds)
         ]
         self._connection.executemany(
-            f"INSERT INTO {self._table}(text, metadata, text_embedding) "
-            f"VALUES (?,?,?)",
+            f"INSERT INTO {self._table}(text, metadata, text_embedding) VALUES (?,?,?)",
             data_input,
         )
         self._connection.commit()
diff --git a/libs/community/langchain_community/vectorstores/sqlitevss.py b/libs/community/langchain_community/vectorstores/sqlitevss.py
index 3ea9f427700b14..7bc394fddefcc0 100644
--- a/libs/community/langchain_community/vectorstores/sqlitevss.py
+++ b/libs/community/langchain_community/vectorstores/sqlitevss.py
@@ -121,8 +121,7 @@ def add_texts(
             for text, metadata, embed in zip(texts, metadatas, embeds)
         ]
         self._connection.executemany(
-            f"INSERT INTO {self._table}(text, metadata, text_embedding) "
-            f"VALUES (?,?,?)",
+            f"INSERT INTO {self._table}(text, metadata, text_embedding) VALUES (?,?,?)",
             data_input,
         )
         self._connection.commit()
diff --git a/libs/community/langchain_community/vectorstores/starrocks.py b/libs/community/langchain_community/vectorstores/starrocks.py
index 80debc09f92cd7..9298f12a78ff38 100644
--- a/libs/community/langchain_community/vectorstores/starrocks.py
+++ b/libs/community/langchain_community/vectorstores/starrocks.py
@@ -176,10 +176,10 @@ def __init__(
 
         self.schema = f"""\
 CREATE TABLE IF NOT EXISTS {self.config.database}.{self.config.table}(    
-    {self.config.column_map['id']} string,
-    {self.config.column_map['document']} string,
-    {self.config.column_map['embedding']} array<float>,
-    {self.config.column_map['metadata']} string
+    {self.config.column_map["id"]} string,
+    {self.config.column_map["document"]} string,
+    {self.config.column_map["embedding"]} array<float>,
+    {self.config.column_map["metadata"]} string
 ) ENGINE = OLAP PRIMARY KEY(id) DISTRIBUTED BY HASH(id) \
   PROPERTIES ("replication_num" = "1")\
 """
@@ -232,7 +232,7 @@ def _build_insert_sql(self, transac: Iterable, column_names: Iterable[str]) -> s
                 INSERT INTO
                     {self.config.database}.{self.config.table}({ks})
                 VALUES
-                {','.join(_data)}
+                {",".join(_data)}
                 """
         return i_str
 
@@ -363,10 +363,10 @@ def _build_query_sql(
             where_str = ""
 
         q_str = f"""
-            SELECT {self.config.column_map['document']}, 
-                {self.config.column_map['metadata']}, 
+            SELECT {self.config.column_map["document"]}, 
+                {self.config.column_map["metadata"]}, 
                 cosine_similarity_norm(array<float>[{q_emb_str}],
-                  {self.config.column_map['embedding']}) as dist
+                  {self.config.column_map["embedding"]}) as dist
             FROM {self.config.database}.{self.config.table}
             {where_str}
             ORDER BY dist {self.dist_order}
diff --git a/libs/community/langchain_community/vectorstores/surrealdb.py b/libs/community/langchain_community/vectorstores/surrealdb.py
index ce05abdc930ce1..3157f48e33b271 100644
--- a/libs/community/langchain_community/vectorstores/surrealdb.py
+++ b/libs/community/langchain_community/vectorstores/surrealdb.py
@@ -323,9 +323,9 @@ def similarity_search_with_relevance_scores(
             List of Documents most similar along with relevance scores
         """
 
-        async def _similarity_search_with_relevance_scores() -> (
-            List[Tuple[Document, float]]
-        ):
+        async def _similarity_search_with_relevance_scores() -> List[
+            Tuple[Document, float]
+        ]:
             await self.initialize()
             return await self.asimilarity_search_with_relevance_scores(
                 query, k, filter=filter, **kwargs
diff --git a/libs/community/langchain_community/vectorstores/typesense.py b/libs/community/langchain_community/vectorstores/typesense.py
index 88d73992d0eea0..19f3499699a68c 100644
--- a/libs/community/langchain_community/vectorstores/typesense.py
+++ b/libs/community/langchain_community/vectorstores/typesense.py
@@ -158,7 +158,7 @@ def similarity_search_with_score(
         embedded_query = [str(x) for x in self._embedding.embed_query(query)]
         query_obj = {
             "q": "*",
-            "vector_query": f'vec:([{",".join(embedded_query)}], k:{k})',
+            "vector_query": f"vec:([{','.join(embedded_query)}], k:{k})",
             "filter_by": filter,
             "collection": self._typesense_collection_name,
         }
diff --git a/libs/community/langchain_community/vectorstores/vdms.py b/libs/community/langchain_community/vectorstores/vdms.py
index ed50d014626230..811c79fccc80b0 100644
--- a/libs/community/langchain_community/vectorstores/vdms.py
+++ b/libs/community/langchain_community/vectorstores/vdms.py
@@ -232,8 +232,7 @@ def _embed_query(self, text: str) -> List[float]:
             return self.embedding.embed_query(text)
         else:
             raise ValueError(
-                "Must provide `embedding` which is expected"
-                " to be an Embeddings object"
+                "Must provide `embedding` which is expected to be an Embeddings object"
             )
 
     def _select_relevance_score_fn(self) -> Callable[[float], float]:
@@ -1099,7 +1098,7 @@ def max_marginal_relevance_search(
         """
         if self.embedding is None:
             raise ValueError(
-                "For MMR search, you must specify an embedding function on" "creation."
+                "For MMR search, you must specify an embedding function oncreation."
             )
 
         # embedding_vector: List[float] = self._embed_query(query)
@@ -1208,7 +1207,7 @@ def max_marginal_relevance_search_with_score(
         """
         if self.embedding is None:
             raise ValueError(
-                "For MMR search, you must specify an embedding function on" "creation."
+                "For MMR search, you must specify an embedding function oncreation."
             )
 
         if not os.path.isfile(query) and hasattr(self.embedding, "embed_query"):
diff --git a/libs/community/langchain_community/vectorstores/vespa.py b/libs/community/langchain_community/vectorstores/vespa.py
index 6fe6585cd86bea..bc9f3736406c74 100644
--- a/libs/community/langchain_community/vectorstores/vespa.py
+++ b/libs/community/langchain_community/vectorstores/vespa.py
@@ -96,7 +96,7 @@ def add_texts(
             embeddings = self._embedding_function.embed_documents(list(texts))
 
         if ids is None:
-            ids = [str(f"{i+1}") for i, _ in enumerate(texts)]
+            ids = [str(f"{i + 1}") for i, _ in enumerate(texts)]
 
         batch = []
         for i, text in enumerate(texts):
diff --git a/libs/community/langchain_community/vectorstores/vikingdb.py b/libs/community/langchain_community/vectorstores/vikingdb.py
index 002db6485be2ba..2e0a9b0c57fc2e 100644
--- a/libs/community/langchain_community/vectorstores/vikingdb.py
+++ b/libs/community/langchain_community/vectorstores/vikingdb.py
@@ -131,8 +131,7 @@ def _create_collection(
                     fields.append(Field(key, FieldType.Text))
                 else:
                     raise ValueError(
-                        "metadatas value is invalid"
-                        "please change the type of metadatas."
+                        "metadatas value is invalidplease change the type of metadatas."
                     )
         # fields.append(Field("text", FieldType.String))
         fields.append(Field("text", FieldType.Text))
diff --git a/libs/community/poetry.lock b/libs/community/poetry.lock
index f9573f4b69e972..0db0bd745f9819 100644
--- a/libs/community/poetry.lock
+++ b/libs/community/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -1883,7 +1883,7 @@ url = "../core"
 
 [[package]]
 name = "langchain-tests"
-version = "0.3.7"
+version = "0.3.8"
 description = "Standard tests for LangChain implementations"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -1908,7 +1908,7 @@ url = "../standard-tests"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.4"
+version = "0.3.5"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -1916,7 +1916,7 @@ files = []
 develop = true
 
 [package.dependencies]
-langchain-core = "^0.3.26"
+langchain-core = "^0.3.29"
 
 [package.source]
 type = "directory"
@@ -2618,30 +2618,41 @@ files = [
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+    {file = "pandas-2.2.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:b8661b0238a69d7aafe156b7fa86c44b881387509653fdf857bebc5e4008ad42"},
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@@ -3784,29 +3795,29 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.5.7"
+version = "0.9.1"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "ruff-0.9.1-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:186c2313de946f2c22bdf5954b8dd083e124bcfb685732cfb0beae0c47233d9b"},
+    {file = "ruff-0.9.1-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3f94942a3bb767675d9a051867c036655fe9f6c8a491539156a6f7e6b5f31831"},
+    {file = "ruff-0.9.1-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:728d791b769cc28c05f12c280f99e8896932e9833fef1dd8756a6af2261fd1ab"},
+    {file = "ruff-0.9.1-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:2f312c86fb40c5c02b44a29a750ee3b21002bd813b5233facdaf63a51d9a85e1"},
+    {file = "ruff-0.9.1-py3-none-musllinux_1_2_i686.whl", hash = "sha256:ae017c3a29bee341ba584f3823f805abbe5fe9cd97f87ed07ecbf533c4c88366"},
+    {file = "ruff-0.9.1-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:5dc40a378a0e21b4cfe2b8a0f1812a6572fc7b230ef12cd9fac9161aa91d807f"},
+    {file = "ruff-0.9.1-py3-none-win32.whl", hash = "sha256:46ebf5cc106cf7e7378ca3c28ce4293b61b449cd121b98699be727d40b79ba72"},
+    {file = "ruff-0.9.1-py3-none-win_amd64.whl", hash = "sha256:342a824b46ddbcdddd3abfbb332fa7fcaac5488bf18073e841236aadf4ad5c19"},
+    {file = "ruff-0.9.1-py3-none-win_arm64.whl", hash = "sha256:1cd76c7f9c679e6e8f2af8f778367dca82b95009bc7b1a85a47f1521ae524fa7"},
+    {file = "ruff-0.9.1.tar.gz", hash = "sha256:fd2b25ecaf907d6458fa842675382c8597b3c746a2dde6717fe3415425df0c17"},
 ]
 
 [[package]]
@@ -4704,4 +4715,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "285e19251cdc78fc8dbde4ccf887f0ca35a0800e757223bb4abefa471a04a33a"
+content-hash = "d4510bf9b5219bf4f11cee251e0856a228dcefa1a9e3cc90452fb36d0ef7bd29"
diff --git a/libs/community/pyproject.toml b/libs/community/pyproject.toml
index dde6e9a1bbb890..343fccbf79109f 100644
--- a/libs/community/pyproject.toml
+++ b/libs/community/pyproject.toml
@@ -12,6 +12,7 @@ readme = "README.md"
 repository = "https://github.com/langchain-ai/langchain"
 
 [tool.ruff]
+target-version = "py39"
 exclude = [
     "tests/examples/non-utf8-encoding.py",
     "tests/integration_tests/examples/non-utf8-encoding.py",
@@ -119,7 +120,7 @@ pytest-vcr = "^1.0.2"
 vcrpy = "^6"
 
 [tool.poetry.group.lint.dependencies]
-ruff = "^0.5"
+ruff = "~0.9.1"
 [[tool.poetry.group.lint.dependencies.cffi]]
 version = "<1.17.1"
 python = "<3.10"
diff --git a/libs/community/tests/integration_tests/callbacks/test_langchain_tracer.py b/libs/community/tests/integration_tests/callbacks/test_langchain_tracer.py
index 51b2552139be4f..a9e128a7dde0a3 100644
--- a/libs/community/tests/integration_tests/callbacks/test_langchain_tracer.py
+++ b/libs/community/tests/integration_tests/callbacks/test_langchain_tracer.py
@@ -28,7 +28,7 @@
         "Who won the US Open women's final in 2019? "
         "What is her age raised to the 0.34 power?"
     ),
-    ("Who is Beyonce's husband? " "What is his age raised to the 0.19 power?"),
+    ("Who is Beyonce's husband? What is his age raised to the 0.19 power?"),
 ]
 
 
diff --git a/libs/community/tests/integration_tests/callbacks/test_wandb_tracer.py b/libs/community/tests/integration_tests/callbacks/test_wandb_tracer.py
index 45c5287b8ec5bc..15152bf075b14c 100644
--- a/libs/community/tests/integration_tests/callbacks/test_wandb_tracer.py
+++ b/libs/community/tests/integration_tests/callbacks/test_wandb_tracer.py
@@ -25,7 +25,7 @@
         "Who won the US Open women's final in 2019? "
         "What is her age raised to the 0.34 power?"
     ),
-    ("Who is Beyonce's husband? " "What is his age raised to the 0.19 power?"),
+    ("Who is Beyonce's husband? What is his age raised to the 0.19 power?"),
 ]
 
 
diff --git a/libs/community/tests/integration_tests/chat_models/test_outlines.py b/libs/community/tests/integration_tests/chat_models/test_outlines.py
index 8f293e6532c512..b0c22981ff53b4 100644
--- a/libs/community/tests/integration_tests/chat_models/test_outlines.py
+++ b/libs/community/tests/integration_tests/chat_models/test_outlines.py
@@ -80,9 +80,9 @@ def test_chat_outlines_regex(chat_model: ChatOutlines) -> None:
     output = chat_model.invoke(messages)
 
     assert isinstance(output, AIMessage)
-    assert re.match(
-        ip_regex, str(output.content)
-    ), f"Generated output '{output.content}' is not a valid IP address"
+    assert re.match(ip_regex, str(output.content)), (
+        f"Generated output '{output.content}' is not a valid IP address"
+    )
 
 
 def test_chat_outlines_type_constraints(chat_model: ChatOutlines) -> None:
@@ -129,14 +129,14 @@ def test_chat_outlines_grammar(chat_model: ChatOutlines) -> None:
     output = chat_model.invoke(messages)
 
     # Validate the output is a non-empty string
-    assert (
-        isinstance(output.content, str) and output.content.strip()
-    ), "Output should be a non-empty string"
+    assert isinstance(output.content, str) and output.content.strip(), (
+        "Output should be a non-empty string"
+    )
 
     # Use a simple regex to check if the output contains basic arithmetic operations and numbers
-    assert re.search(
-        r"[\d\+\-\*/\(\)]+", output.content
-    ), f"Generated output '{output.content}' does not appear to be a valid arithmetic expression"
+    assert re.search(r"[\d\+\-\*/\(\)]+", output.content), (
+        f"Generated output '{output.content}' does not appear to be a valid arithmetic expression"
+    )
 
 
 def test_chat_outlines_with_structured_output(chat_model: ChatOutlines) -> None:
diff --git a/libs/community/tests/integration_tests/chat_models/test_vertexai.py b/libs/community/tests/integration_tests/chat_models/test_vertexai.py
index 5a10353bc2f3b1..37c1a8ecfde4ad 100644
--- a/libs/community/tests/integration_tests/chat_models/test_vertexai.py
+++ b/libs/community/tests/integration_tests/chat_models/test_vertexai.py
@@ -112,8 +112,7 @@ def test_vertexai_single_call_with_context() -> None:
 def test_multimodal() -> None:
     llm = ChatVertexAI(model_name="gemini-ultra-vision")
     gcs_url = (
-        "gs://cloud-samples-data/generative-ai/image/"
-        "320px-Felis_catus-cat_on_snow.jpg"
+        "gs://cloud-samples-data/generative-ai/image/320px-Felis_catus-cat_on_snow.jpg"
     )
     image_message = {
         "type": "image_url",
@@ -131,8 +130,7 @@ def test_multimodal() -> None:
 def test_multimodal_history() -> None:
     llm = ChatVertexAI(model_name="gemini-ultra-vision")
     gcs_url = (
-        "gs://cloud-samples-data/generative-ai/image/"
-        "320px-Felis_catus-cat_on_snow.jpg"
+        "gs://cloud-samples-data/generative-ai/image/320px-Felis_catus-cat_on_snow.jpg"
     )
     image_message = {
         "type": "image_url",
diff --git a/libs/community/tests/integration_tests/graphs/test_neo4j.py b/libs/community/tests/integration_tests/graphs/test_neo4j.py
index 761cbc95e4b8ee..578875a81139b0 100644
--- a/libs/community/tests/integration_tests/graphs/test_neo4j.py
+++ b/libs/community/tests/integration_tests/graphs/test_neo4j.py
@@ -367,7 +367,7 @@ def test_enhanced_schema_exception() -> None:
         url=url, username=username, password=password, enhanced_schema=True
     )
     graph.query("MATCH (n) DETACH DELETE n")
-    graph.query("CREATE (:Node {foo:'bar'})," "(:Node {foo: 1}), (:Node {foo: [1,2]})")
+    graph.query("CREATE (:Node {foo:'bar'}),(:Node {foo: 1}), (:Node {foo: [1,2]})")
     graph.refresh_schema()
     expected_output = {
         "node_props": {"Node": [{"property": "foo", "type": "STRING"}]},
diff --git a/libs/community/tests/integration_tests/llms/test_outlines.py b/libs/community/tests/integration_tests/llms/test_outlines.py
index db0e043723442c..42828db7142cb1 100644
--- a/libs/community/tests/integration_tests/llms/test_outlines.py
+++ b/libs/community/tests/integration_tests/llms/test_outlines.py
@@ -72,9 +72,9 @@ def test_outlines_regex(llm: Outlines) -> None:
 
     assert isinstance(output, str)
 
-    assert re.match(
-        ip_regex, output
-    ), f"Generated output '{output}' is not a valid IP address"
+    assert re.match(ip_regex, output), (
+        f"Generated output '{output}' is not a valid IP address"
+    )
 
 
 def test_outlines_type_constraints(llm: Outlines) -> None:
@@ -113,11 +113,11 @@ def test_outlines_grammar(llm: Outlines) -> None:
     output = llm.invoke("Here is a complex arithmetic expression: ")
 
     # Validate the output is a non-empty string
-    assert (
-        isinstance(output, str) and output.strip()
-    ), "Output should be a non-empty string"
+    assert isinstance(output, str) and output.strip(), (
+        "Output should be a non-empty string"
+    )
 
     # Use a simple regex to check if the output contains basic arithmetic operations and numbers
-    assert re.search(
-        r"[\d\+\-\*/\(\)]+", output
-    ), f"Generated output '{output}' does not appear to be a valid arithmetic expression"
+    assert re.search(r"[\d\+\-\*/\(\)]+", output), (
+        f"Generated output '{output}' does not appear to be a valid arithmetic expression"
+    )
diff --git a/libs/community/tests/integration_tests/retrievers/docarray/fixtures.py b/libs/community/tests/integration_tests/retrievers/docarray/fixtures.py
index ea3a5d4815a3c4..4bfa7b7937fb28 100644
--- a/libs/community/tests/integration_tests/retrievers/docarray/fixtures.py
+++ b/libs/community/tests/integration_tests/retrievers/docarray/fixtures.py
@@ -22,13 +22,11 @@
 
 
 @pytest.fixture
-def init_weaviate() -> (
-    Generator[
-        Tuple[WeaviateDocumentIndex, Dict[str, Any], FakeEmbeddings],
-        None,
-        None,
-    ]
-):
+def init_weaviate() -> Generator[
+    Tuple[WeaviateDocumentIndex, Dict[str, Any], FakeEmbeddings],
+    None,
+    None,
+]:
     """
     cd tests/integration_tests/vectorstores/docker-compose
     docker compose -f weaviate.yml up
@@ -75,9 +73,9 @@ class WeaviateDoc(BaseDoc):
 
 
 @pytest.fixture
-def init_elastic() -> (
-    Generator[Tuple[ElasticDocIndex, Dict[str, Any], FakeEmbeddings], None, None]
-):
+def init_elastic() -> Generator[
+    Tuple[ElasticDocIndex, Dict[str, Any], FakeEmbeddings], None, None
+]:
     """
     cd tests/integration_tests/vectorstores/docker-compose
     docker-compose -f elasticsearch.yml up
diff --git a/libs/community/tests/integration_tests/retrievers/test_dria_index.py b/libs/community/tests/integration_tests/retrievers/test_dria_index.py
index f3e3423bec5222..50104b65b3f667 100644
--- a/libs/community/tests/integration_tests/retrievers/test_dria_index.py
+++ b/libs/community/tests/integration_tests/retrievers/test_dria_index.py
@@ -34,8 +34,8 @@ def test_dria_retriever(dria_retriever: DriaRetriever) -> None:
     doc = docs[0]
     assert isinstance(doc, Document), "Expected a Document instance"
     assert isinstance(doc.page_content, str), (
-        "Expected document content type " "to be string"
+        "Expected document content type to be string"
+    )
+    assert isinstance(doc.metadata, dict), (
+        "Expected document metadata content to be a dictionary"
     )
-    assert isinstance(
-        doc.metadata, dict
-    ), "Expected document metadata content to be a dictionary"
diff --git a/libs/community/tests/integration_tests/retrievers/test_kay.py b/libs/community/tests/integration_tests/retrievers/test_kay.py
index ac6202d89c77db..4dc142769e9863 100644
--- a/libs/community/tests/integration_tests/retrievers/test_kay.py
+++ b/libs/community/tests/integration_tests/retrievers/test_kay.py
@@ -14,8 +14,7 @@ def test_kay_retriever() -> None:
         num_contexts=3,
     )
     docs = retriever.invoke(
-        "What were the biggest strategy changes and partnerships made by Roku "
-        "in 2023?",
+        "What were the biggest strategy changes and partnerships made by Roku in 2023?",
     )
     assert len(docs) == 3
     for doc in docs:
diff --git a/libs/community/tests/integration_tests/tools/zenguard/test_zenguard.py b/libs/community/tests/integration_tests/tools/zenguard/test_zenguard.py
index 238ff93b0bb4d3..c68bc34436f9bc 100644
--- a/libs/community/tests/integration_tests/tools/zenguard/test_zenguard.py
+++ b/libs/community/tests/integration_tests/tools/zenguard/test_zenguard.py
@@ -32,12 +32,12 @@ def assert_detectors_response(
                 if resp["detector"] == detector.value
             )
         )
-        assert (
-            "err" not in common_response
-        ), f"API returned an error: {common_response.get('err')}"  # noqa: E501
-        assert (
-            common_response.get("is_detected") is False
-        ), f"Prompt was detected: {common_response}"  # noqa: E501
+        assert "err" not in common_response, (
+            f"API returned an error: {common_response.get('err')}"
+        )  # noqa: E501
+        assert common_response.get("is_detected") is False, (
+            f"Prompt was detected: {common_response}"
+        )  # noqa: E501
 
 
 def test_prompt_injection(zenguard_tool: ZenGuardTool) -> None:
diff --git a/libs/community/tests/integration_tests/utilities/test_arxiv.py b/libs/community/tests/integration_tests/utilities/test_arxiv.py
index e4fa9e4aa567ad..787724bec0c19c 100644
--- a/libs/community/tests/integration_tests/utilities/test_arxiv.py
+++ b/libs/community/tests/integration_tests/utilities/test_arxiv.py
@@ -152,9 +152,9 @@ def _load_arxiv_from_universal_entry(**kwargs: Any) -> BaseTool:
 def test_load_arxiv_from_universal_entry() -> None:
     arxiv_tool = _load_arxiv_from_universal_entry()
     output = arxiv_tool.invoke("Caprice Stanley")
-    assert (
-        "On Mixing Behavior of a Family of Random Walks" in output
-    ), "failed to fetch a valid result"
+    assert "On Mixing Behavior of a Family of Random Walks" in output, (
+        "failed to fetch a valid result"
+    )
 
 
 def test_load_arxiv_from_universal_entry_with_params() -> None:
@@ -168,6 +168,6 @@ def test_load_arxiv_from_universal_entry_with_params() -> None:
     wp = arxiv_tool.api_wrapper
     assert wp.top_k_results == 1, "failed to assert top_k_results"
     assert wp.load_max_docs == 10, "failed to assert load_max_docs"
-    assert (
-        wp.load_all_available_meta is True
-    ), "failed to assert load_all_available_meta"
+    assert wp.load_all_available_meta is True, (
+        "failed to assert load_all_available_meta"
+    )
diff --git a/libs/community/tests/integration_tests/vectorstores/test_azure_cosmos_db_no_sql.py b/libs/community/tests/integration_tests/vectorstores/test_azure_cosmos_db_no_sql.py
index bbaca0775be7c0..784465d4639b30 100644
--- a/libs/community/tests/integration_tests/vectorstores/test_azure_cosmos_db_no_sql.py
+++ b/libs/community/tests/integration_tests/vectorstores/test_azure_cosmos_db_no_sql.py
@@ -418,8 +418,7 @@ def _get_texts_and_metadata(self) -> Tuple[List[str], List[Dict[str, Any]]]:
             "energetic herders skilled in outdoor activities.",
             "Golden Retrievers are friendly, "
             "loyal companions with excellent retrieving skills.",
-            "Labrador Retrievers are playful, "
-            "eager learners and skilled retrievers.",
+            "Labrador Retrievers are playful, eager learners and skilled retrievers.",
             "Australian Shepherds are agile, "
             "energetic herders excelling in outdoor tasks.",
             "German Shepherds are brave, "
diff --git a/libs/community/tests/integration_tests/vectorstores/test_duckdb.py b/libs/community/tests/integration_tests/vectorstores/test_duckdb.py
index b724dcf0542d90..25ef054812eb60 100644
--- a/libs/community/tests/integration_tests/vectorstores/test_duckdb.py
+++ b/libs/community/tests/integration_tests/vectorstores/test_duckdb.py
@@ -93,18 +93,18 @@ def test_duckdb_add_texts_with_metadata(
 
     # Check if the metadata is correctly associated with the texts
     assert len(result) == 2, "Should return two results"
-    assert (
-        result[0].metadata.get("author") == "Author 1"
-    ), "Metadata for Author 1 should be correctly retrieved"
-    assert (
-        result[0].metadata.get("date") == "2021-01-01"
-    ), "Date for Author 1 should be correctly retrieved"
-    assert (
-        result[1].metadata.get("author") == "Author 2"
-    ), "Metadata for Author 2 should be correctly retrieved"
-    assert (
-        result[1].metadata.get("date") == "2021-02-01"
-    ), "Date for Author 2 should be correctly retrieved"
+    assert result[0].metadata.get("author") == "Author 1", (
+        "Metadata for Author 1 should be correctly retrieved"
+    )
+    assert result[0].metadata.get("date") == "2021-01-01", (
+        "Date for Author 1 should be correctly retrieved"
+    )
+    assert result[1].metadata.get("author") == "Author 2", (
+        "Metadata for Author 2 should be correctly retrieved"
+    )
+    assert result[1].metadata.get("date") == "2021-02-01", (
+        "Date for Author 2 should be correctly retrieved"
+    )
 
 
 @pytest.mark.requires("duckdb")
@@ -127,9 +127,9 @@ def test_duckdb_add_texts_with_predefined_ids(
         result = store.similarity_search(text)
 
         found_texts = [doc.page_content for doc in result]
-        assert (
-            text in found_texts
-        ), f"Text '{text}' was not found in the search results."
+        assert text in found_texts, (
+            f"Text '{text}' was not found in the search results."
+        )
 
 
 @pytest.mark.requires("duckdb")
diff --git a/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py b/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py
index 2842938986c3d8..ecde8eb54748a8 100644
--- a/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py
+++ b/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py
@@ -896,9 +896,9 @@ def test_elasticsearch_with_user_agent(
         pattern = r"^langchain-py-vs/\d+\.\d+\.\d+$"
         match = re.match(pattern, user_agent)
 
-        assert (
-            match is not None
-        ), f"The string '{user_agent}' does not match the expected pattern."
+        assert match is not None, (
+            f"The string '{user_agent}' does not match the expected pattern."
+        )
 
     def test_elasticsearch_with_internal_user_agent(
         self, elasticsearch_connection: Dict, index_name: str
@@ -917,9 +917,9 @@ def test_elasticsearch_with_internal_user_agent(
         pattern = r"^langchain-py-vs/\d+\.\d+\.\d+$"
         match = re.match(pattern, user_agent)
 
-        assert (
-            match is not None
-        ), f"The string '{user_agent}' does not match the expected pattern."
+        assert match is not None, (
+            f"The string '{user_agent}' does not match the expected pattern."
+        )
 
     def test_bulk_args(self, es_client: Any, index_name: str) -> None:
         """Test to make sure the user-agent is set correctly."""
diff --git a/libs/community/tests/integration_tests/vectorstores/test_hanavector.py b/libs/community/tests/integration_tests/vectorstores/test_hanavector.py
index e1ffcd7af0eac2..370fe9b43bec3f 100644
--- a/libs/community/tests/integration_tests/vectorstores/test_hanavector.py
+++ b/libs/community/tests/integration_tests/vectorstores/test_hanavector.py
@@ -1133,7 +1133,7 @@ def test_preexisting_specific_columns_for_metadata_fill(
 
     c = 0
     try:
-        sql_str = f'SELECT COUNT(*) FROM {table_name} WHERE "quality"=' f"'ugly'"
+        sql_str = f"SELECT COUNT(*) FROM {table_name} WHERE \"quality\"='ugly'"
         cur = test_setup.conn.cursor()
         cur.execute(sql_str)
         if cur.has_result_set():
@@ -1195,7 +1195,7 @@ def test_preexisting_specific_columns_for_metadata_via_array(
 
     c = 0
     try:
-        sql_str = f'SELECT COUNT(*) FROM {table_name} WHERE "quality"=' f"'ugly'"
+        sql_str = f"SELECT COUNT(*) FROM {table_name} WHERE \"quality\"='ugly'"
         cur = test_setup.conn.cursor()
         cur.execute(sql_str)
         if cur.has_result_set():
@@ -1206,7 +1206,7 @@ def test_preexisting_specific_columns_for_metadata_via_array(
     assert c == 3
 
     try:
-        sql_str = f'SELECT COUNT(*) FROM {table_name} WHERE "Owner"=' f"'Steve'"
+        sql_str = f"SELECT COUNT(*) FROM {table_name} WHERE \"Owner\"='Steve'"
         cur = test_setup.conn.cursor()
         cur.execute(sql_str)
         if cur.has_result_set():
diff --git a/libs/community/tests/integration_tests/vectorstores/test_lancedb.py b/libs/community/tests/integration_tests/vectorstores/test_lancedb.py
index 615b310629d347..a322d95556aa8b 100644
--- a/libs/community/tests/integration_tests/vectorstores/test_lancedb.py
+++ b/libs/community/tests/integration_tests/vectorstores/test_lancedb.py
@@ -147,8 +147,8 @@ def test_lancedb_no_metadata() -> None:
     result = store.similarity_search("text 1")
     # Verify that the metadata in the Document objects is an empty dictionary
     for doc in result:
-        assert (
-            doc.metadata == {}
-        ), "Expected empty metadata when 'metadata' column is missing"
+        assert doc.metadata == {}, (
+            "Expected empty metadata when 'metadata' column is missing"
+        )
     # Clean up by deleting the table (optional)
     db.drop_table("vectorstore_no_metadata")
diff --git a/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py b/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py
index d8586e089ccf91..ad0fcaacc59268 100644
--- a/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py
+++ b/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py
@@ -471,7 +471,7 @@ def test_neo4jvector_missing_keyword() -> None:
         )
     except ValueError as e:
         assert str(e) == (
-            "keyword_index name has to be specified when " "using hybrid search option"
+            "keyword_index name has to be specified when using hybrid search option"
         )
     drop_vector_indexes(docsearch)
 
@@ -522,7 +522,7 @@ def test_neo4jvector_from_existing_graph() -> None:
 
     graph.query("MATCH (n) DETACH DELETE n")
 
-    graph.query("CREATE (:Test {name:'Foo'})," "(:Test {name:'Bar'})")
+    graph.query("CREATE (:Test {name:'Foo'}),(:Test {name:'Bar'})")
 
     existing = Neo4jVector.from_existing_graph(
         embedding=FakeEmbeddingsWithOsDimension(),
@@ -558,7 +558,7 @@ def test_neo4jvector_from_existing_graph_hybrid() -> None:
 
     graph.query("MATCH (n) DETACH DELETE n")
 
-    graph.query("CREATE (:Test {name:'foo'})," "(:Test {name:'Bar'})")
+    graph.query("CREATE (:Test {name:'foo'}),(:Test {name:'Bar'})")
 
     existing = Neo4jVector.from_existing_graph(
         embedding=FakeEmbeddingsWithOsDimension(),
@@ -594,7 +594,7 @@ def test_neo4jvector_from_existing_graph_multiple_properties() -> None:
     )
     graph.query("MATCH (n) DETACH DELETE n")
 
-    graph.query("CREATE (:Test {name:'Foo', name2: 'Fooz'})," "(:Test {name:'Bar'})")
+    graph.query("CREATE (:Test {name:'Foo', name2: 'Fooz'}),(:Test {name:'Bar'})")
 
     existing = Neo4jVector.from_existing_graph(
         embedding=FakeEmbeddingsWithOsDimension(),
@@ -629,7 +629,7 @@ def test_neo4jvector_from_existing_graph_multiple_properties_hybrid() -> None:
     )
     graph.query("MATCH (n) DETACH DELETE n")
 
-    graph.query("CREATE (:Test {name:'Foo', name2: 'Fooz'})," "(:Test {name:'Bar'})")
+    graph.query("CREATE (:Test {name:'Foo', name2: 'Fooz'}),(:Test {name:'Bar'})")
 
     existing = Neo4jVector.from_existing_graph(
         embedding=FakeEmbeddingsWithOsDimension(),
diff --git a/libs/community/tests/unit_tests/chat_loaders/test_imessage.py b/libs/community/tests/unit_tests/chat_loaders/test_imessage.py
index 4f6bc171730023..2711f64343aed8 100644
--- a/libs/community/tests/unit_tests/chat_loaders/test_imessage.py
+++ b/libs/community/tests/unit_tests/chat_loaders/test_imessage.py
@@ -23,9 +23,9 @@ def test_imessage_chat_loader_upgrade_osx11() -> None:
 
     # time parsed correctly
     expected_message_time = 720845450393148160
-    assert (
-        first_message.additional_kwargs["message_time"] == expected_message_time
-    ), "unexpected time"
+    assert first_message.additional_kwargs["message_time"] == expected_message_time, (
+        "unexpected time"
+    )
 
     expected_parsed_time = datetime.datetime(2023, 11, 5, 2, 50, 50, 393148)
     assert (
@@ -34,9 +34,9 @@ def test_imessage_chat_loader_upgrade_osx11() -> None:
     ), "date failed to parse"
 
     # is_from_me parsed correctly
-    assert (
-        first_message.additional_kwargs["is_from_me"] is False
-    ), "is_from_me failed to parse"
+    assert first_message.additional_kwargs["is_from_me"] is False, (
+        "is_from_me failed to parse"
+    )
 
 
 def test_imessage_chat_loader() -> None:
@@ -57,9 +57,9 @@ def test_imessage_chat_loader() -> None:
 
     # time parsed correctly
     expected_message_time = 720845450393148160
-    assert (
-        first_message.additional_kwargs["message_time"] == expected_message_time
-    ), "unexpected time"
+    assert first_message.additional_kwargs["message_time"] == expected_message_time, (
+        "unexpected time"
+    )
 
     expected_parsed_time = datetime.datetime(2023, 11, 5, 2, 50, 50, 393148)
     assert (
@@ -68,14 +68,14 @@ def test_imessage_chat_loader() -> None:
     ), "date failed to parse"
 
     # is_from_me parsed correctly
-    assert (
-        first_message.additional_kwargs["is_from_me"] is False
-    ), "is_from_me failed to parse"
+    assert first_message.additional_kwargs["is_from_me"] is False, (
+        "is_from_me failed to parse"
+    )
 
     # short message content in attributedBody field
-    assert (
-        "John is the almighty" in chat_sessions[0]["messages"][16].content
-    ), "Chat content mismatch"
+    assert "John is the almighty" in chat_sessions[0]["messages"][16].content, (
+        "Chat content mismatch"
+    )
 
     # long message content in attributedBody field
     long_msg = "aaaaabbbbbaaaaabbbbbaaaaabbbbbaaaaabbbbbaaaaabbbbbaaaaabbbbbaaaaabbbbba"
diff --git a/libs/community/tests/unit_tests/chat_loaders/test_slack.py b/libs/community/tests/unit_tests/chat_loaders/test_slack.py
index 0ab08b679bf88c..62ef8f9085a2f3 100644
--- a/libs/community/tests/unit_tests/chat_loaders/test_slack.py
+++ b/libs/community/tests/unit_tests/chat_loaders/test_slack.py
@@ -14,6 +14,6 @@ def test_slack_chat_loader() -> None:
 
     assert chat_sessions[1]["messages"], "Chat messages should not be empty"
 
-    assert (
-        "Example message" in chat_sessions[1]["messages"][0].content
-    ), "Chat content mismatch"
+    assert "Example message" in chat_sessions[1]["messages"][0].content, (
+        "Chat content mismatch"
+    )
diff --git a/libs/community/tests/unit_tests/document_loaders/parsers/language/test_python.py b/libs/community/tests/unit_tests/document_loaders/parsers/language/test_python.py
index c14154a2842ded..d7142b1091ff5d 100644
--- a/libs/community/tests/unit_tests/document_loaders/parsers/language/test_python.py
+++ b/libs/community/tests/unit_tests/document_loaders/parsers/language/test_python.py
@@ -25,8 +25,8 @@ def __init__(self):
 hello("Hello!")"""
 
         self.expected_extracted_code = [
-            "def hello(text):\n" "    print(text)",
-            "class Simple:\n" "    def __init__(self):\n" "        self.a = 1",
+            "def hello(text):\n    print(text)",
+            "class Simple:\n    def __init__(self):\n        self.a = 1",
         ]
 
     def test_extract_functions_classes(self) -> None:
diff --git a/libs/community/tests/unit_tests/document_loaders/test_csv_loader.py b/libs/community/tests/unit_tests/document_loaders/test_csv_loader.py
index 75a3b08bf79d96..9fd8192335d729 100644
--- a/libs/community/tests/unit_tests/document_loaders/test_csv_loader.py
+++ b/libs/community/tests/unit_tests/document_loaders/test_csv_loader.py
@@ -113,11 +113,11 @@ def test_csv_loader_content_columns(self) -> None:
         file_path = self._get_csv_file_path("test_none_col.csv")
         expected_docs = [
             Document(
-                page_content="column1: value1\n" "column3: value3",
+                page_content="column1: value1\ncolumn3: value3",
                 metadata={"source": file_path, "row": 0},
             ),
             Document(
-                page_content="column1: value6\n" "column3: value8",
+                page_content="column1: value6\ncolumn3: value8",
                 metadata={"source": file_path, "row": 1},
             ),
         ]
diff --git a/libs/community/tests/unit_tests/document_loaders/test_mongodb.py b/libs/community/tests/unit_tests/document_loaders/test_mongodb.py
index 72ed08905f745b..75ae18e6b773e2 100644
--- a/libs/community/tests/unit_tests/document_loaders/test_mongodb.py
+++ b/libs/community/tests/unit_tests/document_loaders/test_mongodb.py
@@ -50,11 +50,12 @@ async def test_load_mocked_with_filters(expected_documents: List[Document]) -> N
     mock_collection.find = mock_find
     mock_collection.count_documents = mock_count_documents
 
-    with patch(
-        "motor.motor_asyncio.AsyncIOMotorClient", return_value=MagicMock()
-    ), patch(
-        "langchain_community.document_loaders.mongodb.MongodbLoader.aload",
-        new=mock_async_load,
+    with (
+        patch("motor.motor_asyncio.AsyncIOMotorClient", return_value=MagicMock()),
+        patch(
+            "langchain_community.document_loaders.mongodb.MongodbLoader.aload",
+            new=mock_async_load,
+        ),
     ):
         loader = MongodbLoader(
             "mongodb://localhost:27017",
diff --git a/libs/community/tests/unit_tests/document_transformers/test_html2text_transformer.py b/libs/community/tests/unit_tests/document_transformers/test_html2text_transformer.py
index f66fee6c0bd4c8..3eea5c48e70552 100644
--- a/libs/community/tests/unit_tests/document_transformers/test_html2text_transformer.py
+++ b/libs/community/tests/unit_tests/document_transformers/test_html2text_transformer.py
@@ -25,10 +25,7 @@ def test_extract_paragraphs() -> None:
     documents = [Document(page_content=paragraphs_html)]
     docs_transformed = html2text_transformer.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# Header\n\n"
-        "First paragraph.\n\n"
-        "Second paragraph.\n\n"
-        "# Ignore at end\n\n"
+        "# Header\n\nFirst paragraph.\n\nSecond paragraph.\n\n# Ignore at end\n\n"
     )
 
 
@@ -78,14 +75,13 @@ def test_ignore_links() -> None:
 
     docs_transformed = html2text_transformer.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# First heading.\n\n"
-        "First paragraph with an [example](http://example.com)\n\n"
+        "# First heading.\n\nFirst paragraph with an [example](http://example.com)\n\n"
     )
 
     html2text_transformer = Html2TextTransformer(ignore_links=True)
     docs_transformed = html2text_transformer.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# First heading.\n\n" "First paragraph with an example\n\n"
+        "# First heading.\n\nFirst paragraph with an example\n\n"
     )
 
 
@@ -101,12 +97,11 @@ def test_ignore_images() -> None:
 
     docs_transformed = html2text_transformer.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# First heading.\n\n"
-        "First paragraph with an ![Example image](example.jpg)\n\n"
+        "# First heading.\n\nFirst paragraph with an ![Example image](example.jpg)\n\n"
     )
 
     html2text_transformer = Html2TextTransformer(ignore_images=True)
     docs_transformed = html2text_transformer.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# First heading.\n\n" "First paragraph with an\n\n"
+        "# First heading.\n\nFirst paragraph with an\n\n"
     )
diff --git a/libs/community/tests/unit_tests/document_transformers/test_markdownify.py b/libs/community/tests/unit_tests/document_transformers/test_markdownify.py
index 1ce407289dd4a2..4b10d94371c131 100644
--- a/libs/community/tests/unit_tests/document_transformers/test_markdownify.py
+++ b/libs/community/tests/unit_tests/document_transformers/test_markdownify.py
@@ -25,7 +25,7 @@ def test_extract_paragraphs() -> None:
     documents = [Document(page_content=paragraphs_html)]
     docs_transformed = markdownify.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# Header\n\n" "First paragraph.\n\n" "Second paragraph.\n\n" "# Ignore at end"
+        "# Header\n\nFirst paragraph.\n\nSecond paragraph.\n\n# Ignore at end"
     )
 
 
@@ -115,10 +115,7 @@ def test_convert_tags() -> None:
     documents = [Document(page_content=paragraphs_html)]
     docs_transformed = markdownify.transform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "Header "
-        "1st paragraph.\n\n "
-        "2nd paragraph. Here is link\n\n "
-        "Ignore at end"
+        "Header 1st paragraph.\n\n 2nd paragraph. Here is link\n\n Ignore at end"
     )
 
 
@@ -161,7 +158,7 @@ async def test_extract_paragraphs_async() -> None:
     documents = [Document(page_content=paragraphs_html)]
     docs_transformed = await markdownify.atransform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "# Header\n\n" "First paragraph.\n\n" "Second paragraph.\n\n" "# Ignore at end"
+        "# Header\n\nFirst paragraph.\n\nSecond paragraph.\n\n# Ignore at end"
     )
 
 
@@ -251,10 +248,7 @@ async def test_convert_tags_async() -> None:
     documents = [Document(page_content=paragraphs_html)]
     docs_transformed = await markdownify.atransform_documents(documents)
     assert docs_transformed[0].page_content == (
-        "Header "
-        "1st paragraph.\n\n "
-        "2nd paragraph. Here is link\n\n "
-        "Ignore at end"
+        "Header 1st paragraph.\n\n 2nd paragraph. Here is link\n\n Ignore at end"
     )
 
 
diff --git a/libs/community/tests/unit_tests/query_constructors/test_milvus.py b/libs/community/tests/unit_tests/query_constructors/test_milvus.py
index 70035628adbe8b..5369e1e04f505b 100644
--- a/libs/community/tests/unit_tests/query_constructors/test_milvus.py
+++ b/libs/community/tests/unit_tests/query_constructors/test_milvus.py
@@ -45,7 +45,7 @@ def test_visit_operation() -> None:
         ],
     )
 
-    expected = '(( foo < 2 ) and ( bar == "baz" ) ' 'and ( abc < "4" ))'
+    expected = '(( foo < 2 ) and ( bar == "baz" ) and ( abc < "4" ))'
     actual = DEFAULT_TRANSLATOR.visit_operation(op)
 
     assert expected == actual
@@ -122,7 +122,7 @@ def test_visit_structured_query() -> None:
 
     expected = (
         query,
-        {"expr": "(( foo < 2 ) " 'and ( bar == "baz" ) ' "and ( abc < 50 ))"},
+        {"expr": '(( foo < 2 ) and ( bar == "baz" ) and ( abc < 50 ))'},
     )
 
     actual = DEFAULT_TRANSLATOR.visit_structured_query(structured_query)
diff --git a/libs/community/tests/unit_tests/test_imports.py b/libs/community/tests/unit_tests/test_imports.py
index 59152b3b0468ed..8d510f7d4928f7 100644
--- a/libs/community/tests/unit_tests/test_imports.py
+++ b/libs/community/tests/unit_tests/test_imports.py
@@ -165,6 +165,6 @@ def test_init_files_properly_defined() -> None:
 
         missing_imports = set(module.__all__) - set(names)
 
-        assert (
-            not missing_imports
-        ), f"Missing imports: {missing_imports} in file path: {path}"
+        assert not missing_imports, (
+            f"Missing imports: {missing_imports} in file path: {path}"
+        )
diff --git a/libs/community/tests/unit_tests/tools/audio/test_tools.py b/libs/community/tests/unit_tests/tools/audio/test_tools.py
index 30cacb7b7b0b59..d5bb6256d45673 100644
--- a/libs/community/tests/unit_tests/tools/audio/test_tools.py
+++ b/libs/community/tests/unit_tests/tools/audio/test_tools.py
@@ -44,11 +44,12 @@ def test_huggingface_tts_constructor() -> None:
 def test_huggingface_tts_run_with_requests_mock() -> None:
     os.environ["HUGGINGFACE_API_KEY"] = "foo"
 
-    with tempfile.TemporaryDirectory() as tmp_dir, patch(
-        "uuid.uuid4"
-    ) as mock_uuid, patch("requests.post") as mock_inference, patch(
-        "builtins.open", mock_open()
-    ) as mock_file:
+    with (
+        tempfile.TemporaryDirectory() as tmp_dir,
+        patch("uuid.uuid4") as mock_uuid,
+        patch("requests.post") as mock_inference,
+        patch("builtins.open", mock_open()) as mock_file,
+    ):
         input_query = "Dummy input"
 
         mock_uuid_value = uuid.UUID("00000000-0000-0000-0000-000000000000")
diff --git a/libs/community/tests/unit_tests/vectorstores/test_azure_search.py b/libs/community/tests/unit_tests/vectorstores/test_azure_search.py
index 0f1ae7356973fc..e7aa37004c4612 100644
--- a/libs/community/tests/unit_tests/vectorstores/test_azure_search.py
+++ b/libs/community/tests/unit_tests/vectorstores/test_azure_search.py
@@ -220,9 +220,10 @@ def mock_upload_documents(self, documents: List[object]) -> List[Response]:  # t
     ]
     ids_provided = [i.metadata.get("id") for i in documents]
 
-    with patch.object(
-        SearchClient, "upload_documents", mock_upload_documents
-    ), patch.object(SearchIndexClient, "get_index", mock_default_index):
+    with (
+        patch.object(SearchClient, "upload_documents", mock_upload_documents),
+        patch.object(SearchIndexClient, "get_index", mock_default_index),
+    ):
         vector_store = create_vector_store()
         ids_used_at_upload = vector_store.add_documents(documents, ids=ids_provided)
         assert len(ids_provided) == len(ids_used_at_upload)
diff --git a/libs/community/tests/unit_tests/vectorstores/test_faiss.py b/libs/community/tests/unit_tests/vectorstores/test_faiss.py
index 739bd243f0eb03..2e749edc49effa 100644
--- a/libs/community/tests/unit_tests/vectorstores/test_faiss.py
+++ b/libs/community/tests/unit_tests/vectorstores/test_faiss.py
@@ -1714,9 +1714,9 @@ def test_ip_score() -> None:
     scores = db.similarity_search_with_relevance_scores("sundays", k=1)
     assert len(scores) == 1, "only one vector should be in db"
     _, score = scores[0]
-    assert (
-        score == 1
-    ), f"expected inner product of equivalent vectors to be 1, not {score}"
+    assert score == 1, (
+        f"expected inner product of equivalent vectors to be 1, not {score}"
+    )
 
 
 @pytest.mark.requires("faiss")
diff --git a/libs/community/tests/unit_tests/vectorstores/test_tencentvectordb.py b/libs/community/tests/unit_tests/vectorstores/test_tencentvectordb.py
index 36a4e959346bc0..5af23b3719defb 100644
--- a/libs/community/tests/unit_tests/vectorstores/test_tencentvectordb.py
+++ b/libs/community/tests/unit_tests/vectorstores/test_tencentvectordb.py
@@ -20,7 +20,7 @@ def test_translate_filter() -> None:
             assert False
     else:
         result = translate_filter(raw_filter)
-        expr = '(artist = "Taylor Swift" or artist = "Katy Perry") ' "and length < 180"
+        expr = '(artist = "Taylor Swift" or artist = "Katy Perry") and length < 180'
         assert expr == result