community[patch]: Add missing annotations (#24890)

This PR adds annotations in comunity package.

Annotations are only strictly needed in subclasses of BaseModel for
pydantic 2 compatibility.

This PR adds some unnecessary annotations, but they're not bad to have
regardless for documentation pages.

libs/community/langchain_community/callbacks/upstash_ratelimit_callback.py

@@ -58,7 +58,7 @@ class UpstashRatelimitHandler(BaseCallbackHandler):
     every time you invoke.
     """
 
-    raise_error = True
+    raise_error: bool = True
     _checked: bool = False
 
     def __init__(

libs/community/langchain_community/chains/pebblo_retrieval/base.py

@@ -76,7 +76,7 @@ class PebbloRetrievalQA(Chain):
     """Classifier endpoint."""
     classifier_location: str = "local"  #: :meta private:
     """Classifier location. It could be either of 'local' or 'pebblo-cloud'."""
-    _discover_sent = False  #: :meta private:
+    _discover_sent: bool = False  #: :meta private:
     """Flag to check if discover payload has been sent."""
     _prompt_sent: bool = False  #: :meta private:
     """Flag to check if prompt payload has been sent."""

libs/community/langchain_community/chat_models/kinetica.py

@@ -9,7 +9,7 @@ import os
 import re
 from importlib.metadata import version
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Pattern, cast
 
 from langchain_core.utils import pre_init
 
@@ -164,7 +164,7 @@ class _KineticaLlmFileContextParser:
     """Parser for Kinetica LLM context datafiles."""
 
     # parse line into a dict containing role and content
-    PARSER = re.compile(r"^<\|(?P<role>\w+)\|>\W*(?P<content>.*)$", re.DOTALL)
+    PARSER: Pattern = re.compile(r"^<\|(?P<role>\w+)\|>\W*(?P<content>.*)$", re.DOTALL)
 
     @classmethod
     def _removesuffix(cls, text: str, suffix: str) -> str:

libs/community/langchain_community/chat_models/oci_generative_ai.py

@@ -135,7 +135,7 @@ class Provider(ABC):
 
 
 class CohereProvider(Provider):
-    stop_sequence_key = "stop_sequences"
+    stop_sequence_key: str = "stop_sequences"
 
     def __init__(self) -> None:
         from oci.generative_ai_inference import models
@@ -364,7 +364,7 @@ class CohereProvider(Provider):
 
 
 class MetaProvider(Provider):
-    stop_sequence_key = "stop"
+    stop_sequence_key: str = "stop"
 
     def __init__(self) -> None:
         from oci.generative_ai_inference import models

libs/community/langchain_community/document_compressors/llmlingua_filter.py

@@ -1,7 +1,7 @@
 # LLM Lingua Document Compressor
 
 import re
-from typing import Any, Dict, List, Optional, Sequence, Tuple
+from typing import Any, Dict, List, Optional, Pattern, Sequence, Tuple
 
 from langchain_core.callbacks import Callbacks
 from langchain_core.documents import Document
@@ -24,8 +24,8 @@ class LLMLinguaCompressor(BaseDocumentCompressor):
 
     # Pattern to match ref tags at the beginning or end of the string,
     # allowing for malformed tags
-    _pattern_beginning = re.compile(r"\A(?:<#)?(?:ref)?(\d+)(?:#>?)?")
-    _pattern_ending = re.compile(r"(?:<#)?(?:ref)?(\d+)(?:#>?)?\Z")
+    _pattern_beginning: Pattern = re.compile(r"\A(?:<#)?(?:ref)?(\d+)(?:#>?)?")
+    _pattern_ending: Pattern = re.compile(r"(?:<#)?(?:ref)?(\d+)(?:#>?)?\Z")
 
     model_name: str = "NousResearch/Llama-2-7b-hf"
     """The hugging face model to use"""

libs/community/langchain_community/document_loaders/acreom.py

@@ -1,6 +1,6 @@
 import re
 from pathlib import Path
-from typing import Iterator, Union
+from typing import Iterator, Pattern, Union
 
 from langchain_core.documents import Document
 
@@ -10,7 +10,9 @@ from langchain_community.document_loaders.base import BaseLoader
 class AcreomLoader(BaseLoader):
     """Load `acreom` vault from a directory."""
 
-    FRONT_MATTER_REGEX = re.compile(r"^---\n(.*?)\n---\n", re.MULTILINE | re.DOTALL)
+    FRONT_MATTER_REGEX: Pattern = re.compile(
+        r"^---\n(.*?)\n---\n", re.MULTILINE | re.DOTALL
+    )
     """Regex to match front matter metadata in markdown files."""
 
     def __init__(

libs/community/langchain_community/document_loaders/docugami.py

@@ -44,13 +44,13 @@ class DocugamiLoader(BaseLoader, BaseModel):
     access_token: Optional[str] = os.environ.get("DOCUGAMI_API_KEY")
     """The Docugami API access token to use."""
 
-    max_text_length = 4096
+    max_text_length: int = 4096
     """Max length of chunk text returned."""
 
     min_text_length: int = 32
     """Threshold under which chunks are appended to next to avoid over-chunking."""
 
-    max_metadata_length = 512
+    max_metadata_length: int = 512
     """Max length of metadata text returned."""
 
     include_xml_tags: bool = False

libs/community/langchain_community/document_loaders/hugging_face_model.py

@@ -36,8 +36,8 @@ class HuggingFaceModelLoader(BaseLoader):
                 print(doc.metadata)      # Metadata of the model
     """
 
-    BASE_URL = "https://huggingface.co/api/models"
-    README_BASE_URL = "https://huggingface.co/{model_id}/raw/main/README.md"
+    BASE_URL: str = "https://huggingface.co/api/models"
+    README_BASE_URL: str = "https://huggingface.co/{model_id}/raw/main/README.md"
 
     def __init__(
         self,

libs/community/langchain_community/document_loaders/obsidian.py

@@ -2,7 +2,7 @@ import functools
 import logging
 import re
 from pathlib import Path
-from typing import Any, Dict, Iterator, Union
+from typing import Any, Dict, Iterator, Pattern, Union
 
 import yaml
 from langchain_core.documents import Document
@@ -15,12 +15,16 @@ logger = logging.getLogger(__name__)
 class ObsidianLoader(BaseLoader):
     """Load `Obsidian` files from directory."""
 
-    FRONT_MATTER_REGEX = re.compile(r"^---\n(.*?)\n---\n", re.DOTALL)
-    TEMPLATE_VARIABLE_REGEX = re.compile(r"{{(.*?)}}", re.DOTALL)
-    TAG_REGEX = re.compile(r"[^\S\/]#([a-zA-Z_]+[-_/\w]*)")
-    DATAVIEW_LINE_REGEX = re.compile(r"^\s*(\w+)::\s*(.*)$", re.MULTILINE)
-    DATAVIEW_INLINE_BRACKET_REGEX = re.compile(r"\[(\w+)::\s*(.*)\]", re.MULTILINE)
-    DATAVIEW_INLINE_PAREN_REGEX = re.compile(r"\((\w+)::\s*(.*)\)", re.MULTILINE)
+    FRONT_MATTER_REGEX: Pattern = re.compile(r"^---\n(.*?)\n---\n", re.DOTALL)
+    TEMPLATE_VARIABLE_REGEX: Pattern = re.compile(r"{{(.*?)}}", re.DOTALL)
+    TAG_REGEX: Pattern = re.compile(r"[^\S\/]#([a-zA-Z_]+[-_/\w]*)")
+    DATAVIEW_LINE_REGEX: Pattern = re.compile(r"^\s*(\w+)::\s*(.*)$", re.MULTILINE)
+    DATAVIEW_INLINE_BRACKET_REGEX: Pattern = re.compile(
+        r"\[(\w+)::\s*(.*)\]", re.MULTILINE
+    )
+    DATAVIEW_INLINE_PAREN_REGEX: Pattern = re.compile(
+        r"\((\w+)::\s*(.*)\)", re.MULTILINE
+    )
 
     def __init__(
         self,

libs/community/langchain_community/document_loaders/onenote.py

@@ -39,7 +39,7 @@ class OneNoteLoader(BaseLoader, BaseModel):
     """Personal access token"""
     onenote_api_base_url: str = "https://graph.microsoft.com/v1.0/me/onenote"
     """URL of Microsoft Graph API for OneNote"""
-    authority_url = "https://login.microsoftonline.com/consumers/"
+    authority_url: str = "https://login.microsoftonline.com/consumers/"
     """A URL that identifies a token authority"""
     token_path: FilePath = Path.home() / ".credentials" / "onenote_graph_token.txt"
     """Path to the file where the access token is stored"""

libs/community/langchain_community/document_loaders/parsers/language/cobol.py

@@ -1,5 +1,5 @@
 import re
-from typing import Callable, List
+from typing import Callable, List, Pattern
 
 from langchain_community.document_loaders.parsers.language.code_segmenter import (
     CodeSegmenter,
@@ -9,11 +9,11 @@ from langchain_community.document_loaders.parsers.language.code_segmenter import
 class CobolSegmenter(CodeSegmenter):
     """Code segmenter for `COBOL`."""
 
-    PARAGRAPH_PATTERN = re.compile(r"^[A-Z0-9\-]+(\s+.*)?\.$", re.IGNORECASE)
-    DIVISION_PATTERN = re.compile(
+    PARAGRAPH_PATTERN: Pattern = re.compile(r"^[A-Z0-9\-]+(\s+.*)?\.$", re.IGNORECASE)
+    DIVISION_PATTERN: Pattern = re.compile(
         r"^\s*(IDENTIFICATION|DATA|PROCEDURE|ENVIRONMENT)\s+DIVISION.*$", re.IGNORECASE
     )
-    SECTION_PATTERN = re.compile(r"^\s*[A-Z0-9\-]+\s+SECTION.$", re.IGNORECASE)
+    SECTION_PATTERN: Pattern = re.compile(r"^\s*[A-Z0-9\-]+\s+SECTION.$", re.IGNORECASE)
 
     def __init__(self, code: str):
         super().__init__(code)

libs/community/langchain_community/embeddings/ernie.py

@@ -27,7 +27,7 @@ class ErnieEmbeddings(BaseModel, Embeddings):
 
     chunk_size: int = 16
 
-    model_name = "ErnieBot-Embedding-V1"
+    model_name: str = "ErnieBot-Embedding-V1"
 
     _lock = threading.Lock()
 

libs/community/langchain_community/graphs/age_graph.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import json
 import re
 from hashlib import md5
-from typing import TYPE_CHECKING, Any, Dict, List, NamedTuple, Tuple, Union
+from typing import TYPE_CHECKING, Any, Dict, List, NamedTuple, Pattern, Tuple, Union
 
 from langchain_community.graphs.graph_document import GraphDocument
 from langchain_community.graphs.graph_store import GraphStore
@@ -63,7 +63,7 @@ class AGEGraph(GraphStore):
     }
 
     # precompiled regex for checking chars in graph labels
-    label_regex = re.compile("[^0-9a-zA-Z]+")
+    label_regex: Pattern = re.compile("[^0-9a-zA-Z]+")
 
     def __init__(
         self, graph_name: str, conf: Dict[str, Any], create: bool = True

libs/community/langchain_community/llms/moonshot.py

@@ -39,9 +39,9 @@ class MoonshotCommon(BaseModel):
     """Moonshot API key. Get it here: https://platform.moonshot.cn/console/api-keys"""
     model_name: str = Field(default="moonshot-v1-8k", alias="model")
     """Model name. Available models listed here: https://platform.moonshot.cn/pricing"""
-    max_tokens = 1024
+    max_tokens: int = 1024
     """Maximum number of tokens to generate."""
-    temperature = 0.3
+    temperature: float = 0.3
     """Temperature parameter (higher values make the model more creative)."""
 
     class Config:

libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py

@@ -244,7 +244,7 @@ class OCIModelDeploymentTGI(OCIModelDeploymentLLM):
     """Watermarking with `A Watermark for Large Language Models <https://arxiv.org/abs/2301.10226>`_.
     Defaults to True."""
 
-    return_full_text = False
+    return_full_text: bool = False
     """Whether to prepend the prompt to the generated text. Defaults to False."""
 
     @property

libs/community/langchain_community/llms/oci_generative_ai.py

@@ -26,7 +26,7 @@ class Provider(ABC):
 
 
 class CohereProvider(Provider):
-    stop_sequence_key = "stop_sequences"
+    stop_sequence_key: str = "stop_sequences"
 
     def __init__(self) -> None:
         from oci.generative_ai_inference import models
@@ -38,7 +38,7 @@ class CohereProvider(Provider):
 
 
 class MetaProvider(Provider):
-    stop_sequence_key = "stop"
+    stop_sequence_key: str = "stop"
 
     def __init__(self) -> None:
         from oci.generative_ai_inference import models

libs/community/langchain_community/llms/sambanova.py

@@ -16,7 +16,7 @@ class SVEndpointHandler:
     :param str host_url: Base URL of the DaaS API service
     """
 
-    API_BASE_PATH = "/api/predict"
+    API_BASE_PATH: str = "/api/predict"
 
     def __init__(self, host_url: str):
         """

libs/community/langchain_community/llms/solar.py

@@ -41,7 +41,7 @@ class SolarCommon(BaseModel):
     model_name: str = Field(default="solar-1-mini-chat", alias="model")
     """Model name. Available models listed here: https://console.upstage.ai/services/solar"""
     max_tokens: int = Field(default=1024)
-    temperature = 0.3
+    temperature: float = 0.3
 
     class Config:
         allow_population_by_field_name = True

libs/community/langchain_community/query_constructors/supabase.py

@@ -27,7 +27,7 @@ class SupabaseVectorTranslator(Visitor):
     ]
     """Subset of allowed logical comparators."""
 
-    metadata_column = "metadata"
+    metadata_column: str = "metadata"
 
     def _map_comparator(self, comparator: Comparator) -> str:
         """

libs/community/langchain_community/tools/bearly/tool.py

@@ -74,8 +74,8 @@ class BearlyInterpreterTool:
     """Tool for evaluating python code in a sandbox environment."""
 
     api_key: str
-    endpoint = "https://exec.bearly.ai/v1/interpreter"
-    name = "bearly_interpreter"
+    endpoint: str = "https://exec.bearly.ai/v1/interpreter"
+    name: str = "bearly_interpreter"
     args_schema: Type[BaseModel] = BearlyInterpreterToolArguments
     files: Dict[str, FileInfo] = {}
 

libs/community/langchain_community/tools/zenguard/tool.py

@@ -51,12 +51,12 @@ class ZenGuardTool(BaseTool):
         "ZenGuard AI integration package. ZenGuard AI - the fastest GenAI guardrails."
     )
     args_schema = ZenGuardInput
-    return_direct = True
+    return_direct: bool = True
 
     zenguard_api_key: Optional[str] = Field(default=None)
 
-    _ZENGUARD_API_URL_ROOT = "https://api.zenguard.ai/"
-    _ZENGUARD_API_KEY_ENV_NAME = "ZENGUARD_API_KEY"
+    _ZENGUARD_API_URL_ROOT: str = "https://api.zenguard.ai/"
+    _ZENGUARD_API_KEY_ENV_NAME: str = "ZENGUARD_API_KEY"
 
     @validator("zenguard_api_key", pre=True, always=True, check_fields=False)
     def set_api_key(cls, v: str) -> str:

libs/community/langchain_community/utilities/portkey.py

@@ -11,7 +11,7 @@ class Portkey:
           Default: "https://api.portkey.ai/v1/proxy"
     """
 
-    base = "https://api.portkey.ai/v1/proxy"
+    base: str = "https://api.portkey.ai/v1/proxy"
 
     @staticmethod
     def Config(

libs/community/langchain_community/utilities/redis.py

@@ -28,7 +28,7 @@ class TokenEscaper:
 
     # Characters that RediSearch requires us to escape during queries.
     # Source: https://redis.io/docs/stack/search/reference/escaping/#the-rules-of-text-field-tokenization
-    DEFAULT_ESCAPED_CHARS = r"[,.<>{}\[\]\\\"\':;!@#$%^&*()\-+=~\/ ]"
+    DEFAULT_ESCAPED_CHARS: str = r"[,.<>{}\[\]\\\"\':;!@#$%^&*()\-+=~\/ ]"
 
     def __init__(self, escape_chars_re: Optional[Pattern] = None):
         if escape_chars_re:

libs/community/langchain_community/vectorstores/atlas.py

@@ -29,7 +29,7 @@ class AtlasDB(VectorStore):
                 vectorstore = AtlasDB("my_project", embeddings.embed_query)
     """
 
-    _ATLAS_DEFAULT_ID_FIELD = "atlas_id"
+    _ATLAS_DEFAULT_ID_FIELD: str = "atlas_id"
 
     def __init__(
         self,

libs/community/langchain_community/vectorstores/awadb.py

@@ -21,7 +21,7 @@ DEFAULT_TOPN = 4
 class AwaDB(VectorStore):
     """`AwaDB` vector store."""
 
-    _DEFAULT_TABLE_NAME = "langchain_awadb"
+    _DEFAULT_TABLE_NAME: str = "langchain_awadb"
 
     def __init__(
         self,

libs/community/langchain_community/vectorstores/bagel.py

@@ -53,7 +53,7 @@ class Bagel(VectorStore):
                 vectorstore = Bagel(cluster_name="langchain_store")
     """
 
-    _LANGCHAIN_DEFAULT_CLUSTER_NAME = "langchain"
+    _LANGCHAIN_DEFAULT_CLUSTER_NAME: str = "langchain"
 
     def __init__(
         self,

libs/community/langchain_community/vectorstores/chroma.py

@@ -66,7 +66,7 @@ class Chroma(VectorStore):
                 vectorstore = Chroma("langchain_store", embeddings)
     """
 
-    _LANGCHAIN_DEFAULT_COLLECTION_NAME = "langchain"
+    _LANGCHAIN_DEFAULT_COLLECTION_NAME: str = "langchain"
 
     def __init__(
         self,

libs/community/langchain_community/vectorstores/couchbase.py

@@ -60,10 +60,10 @@ class CouchbaseVectorStore(VectorStore):
     """
 
     # Default batch size
-    DEFAULT_BATCH_SIZE = 100
-    _metadata_key = "metadata"
-    _default_text_key = "text"
-    _default_embedding_key = "embedding"
+    DEFAULT_BATCH_SIZE: int = 100
+    _metadata_key: str = "metadata"
+    _default_text_key: str = "text"
+    _default_embedding_key: str = "embedding"
 
     def _check_bucket_exists(self) -> bool:
         """Check if the bucket exists in the linked Couchbase cluster"""

libs/community/langchain_community/vectorstores/deeplake.py

@@ -51,7 +51,7 @@ class DeepLake(VectorStore):
                 vectorstore = DeepLake("langchain_store", embeddings.embed_query)
     """
 
-    _LANGCHAIN_DEFAULT_DEEPLAKE_PATH = "./deeplake/"
+    _LANGCHAIN_DEFAULT_DEEPLAKE_PATH: str = "./deeplake/"
     _valid_search_kwargs = ["lambda_mult"]
 
     def __init__(

libs/community/langchain_community/vectorstores/epsilla.py

@@ -45,9 +45,9 @@ class Epsilla(VectorStore):
             epsilla = Epsilla(client, embeddings, db_path, db_name)
     """
 
-    _LANGCHAIN_DEFAULT_DB_NAME = "langchain_store"
-    _LANGCHAIN_DEFAULT_DB_PATH = "/tmp/langchain-epsilla"
-    _LANGCHAIN_DEFAULT_TABLE_NAME = "langchain_collection"
+    _LANGCHAIN_DEFAULT_DB_NAME: str = "langchain_store"
+    _LANGCHAIN_DEFAULT_DB_PATH: str = "/tmp/langchain-epsilla"
+    _LANGCHAIN_DEFAULT_TABLE_NAME: str = "langchain_collection"
 
     def __init__(
         self,

libs/community/langchain_community/vectorstores/hanavector.py

@@ -13,6 +13,7 @@ from typing import (
     Iterable,
     List,
     Optional,
+    Pattern,
     Tuple,
     Type,
 )
@@ -223,7 +224,7 @@ class HanaDB(VectorStore):
         return embedding
 
     # Compile pattern only once, for better performance
-    _compiled_pattern = re.compile("^[_a-zA-Z][_a-zA-Z0-9]*$")
+    _compiled_pattern: Pattern = re.compile("^[_a-zA-Z][_a-zA-Z0-9]*$")
 
     @staticmethod
     def _sanitize_metadata_keys(metadata: dict) -> dict:

libs/community/langchain_community/vectorstores/manticore_search.py

@@ -48,7 +48,7 @@ class ManticoreSearchSettings(BaseSettings):
     hnsw_m: int = 16  # The default is 16.
 
     # An optional setting that defines a construction time/accuracy trade-off.
-    hnsw_ef_construction = 100
+    hnsw_ef_construction: int = 100
 
     def get_connection_string(self) -> str:
         return self.proto + "://" + self.host + ":" + str(self.port)

libs/community/langchain_community/vectorstores/qdrant.py

@@ -85,8 +85,8 @@ class Qdrant(VectorStore):
             qdrant = Qdrant(client, collection_name, embedding_function)
     """
 
-    CONTENT_KEY = "page_content"
-    METADATA_KEY = "metadata"
+    CONTENT_KEY: str = "page_content"
+    METADATA_KEY: str = "metadata"
     VECTOR_NAME = None
 
     def __init__(

libs/community/langchain_community/vectorstores/semadb.py

@@ -25,7 +25,7 @@ class SemaDB(VectorStore):
 
     """
 
-    HOST = "semadb.p.rapidapi.com"
+    HOST: str = "semadb.p.rapidapi.com"
     BASE_URL = "https://" + HOST
 
     def __init__(

libs/community/tests/integration_tests/document_loaders/test_quip.py

@@ -23,9 +23,9 @@ def mock_quip():  # type: ignore
 
 @pytest.mark.requires("quip_api")
 class TestQuipLoader:
-    API_URL = "https://example-api.quip.com"
+    API_URL: str = "https://example-api.quip.com"
     DOC_URL_PREFIX = ("https://example.quip.com",)
-    ACCESS_TOKEN = "api_token"
+    ACCESS_TOKEN: str = "api_token"
 
     MOCK_FOLDER_IDS = ["ABC"]
     MOCK_THREAD_IDS = ["ABC", "DEF"]

libs/community/tests/integration_tests/llms/test_azureml_endpoint.py

@@ -59,8 +59,8 @@ def test_custom_formatter() -> None:
     """Test ability to create a custom content formatter."""
 
     class CustomFormatter(ContentFormatterBase):
-        content_type = "application/json"
-        accepts = "application/json"
+        content_type: str = "application/json"
+        accepts: str = "application/json"
 
         def format_request_payload(self, prompt: str, model_kwargs: Dict) -> bytes:  # type: ignore[override]
             input_str = json.dumps(
@@ -101,8 +101,8 @@ def test_invalid_request_format() -> None:
     """Test invalid request format."""
 
     class CustomContentFormatter(ContentFormatterBase):
-        content_type = "application/json"
-        accepts = "application/json"
+        content_type: str = "application/json"
+        accepts: str = "application/json"
 
         def format_request_payload(self, prompt: str, model_kwargs: Dict) -> bytes:  # type: ignore[override]
             input_str = json.dumps(

libs/community/tests/integration_tests/tools/nuclia/test_nuclia.py

@@ -13,19 +13,19 @@ README_PATH = Path(__file__).parents[4] / "README.md"
 
 
 class FakeUploadResponse:
-    status_code = 200
-    text = "fake_uuid"
+    status_code: int = 200
+    text: str = "fake_uuid"
 
 
 class FakePushResponse:
-    status_code = 200
+    status_code: int = 200
 
     def json(self) -> Any:
         return {"uuid": "fake_uuid"}
 
 
 class FakePullResponse:
-    status_code = 200
+    status_code: int = 200
 
     def json(self) -> Any:
         return {

libs/community/tests/unit_tests/chat_models/test_kinetica.py

@@ -11,7 +11,7 @@ LOG = logging.getLogger(__name__)
 
 
 class TestChatKinetica:
-    test_ctx_json = """
+    test_ctx_json: str = """
     {
         "payload":{
             "context":[

libs/community/tests/unit_tests/document_loaders/test_confluence.py

@@ -20,10 +20,10 @@ def mock_confluence():  # type: ignore
 
 @pytest.mark.requires("atlassian", "bs4", "lxml")
 class TestConfluenceLoader:
-    CONFLUENCE_URL = "https://example.atlassian.com/wiki"
-    MOCK_USERNAME = "user@gmail.com"
-    MOCK_API_TOKEN = "api_token"
-    MOCK_SPACE_KEY = "spaceId123"
+    CONFLUENCE_URL: str = "https://example.atlassian.com/wiki"
+    MOCK_USERNAME: str = "user@gmail.com"
+    MOCK_API_TOKEN: str = "api_token"
+    MOCK_SPACE_KEY: str = "spaceId123"
 
     def test_confluence_loader_initialization(self, mock_confluence: MagicMock) -> None:
         ConfluenceLoader(

libs/community/tests/unit_tests/document_loaders/test_lakefs.py

@@ -57,12 +57,12 @@ def mock_lakefs_client_no_presign_local() -> Any:
 
 
 class TestLakeFSLoader(unittest.TestCase):
-    lakefs_access_key = "lakefs_access_key"
-    lakefs_secret_key = "lakefs_secret_key"
-    endpoint = "endpoint"
-    repo = "repo"
-    ref = "ref"
-    path = "path"
+    lakefs_access_key: str = "lakefs_access_key"
+    lakefs_secret_key: str = "lakefs_secret_key"
+    endpoint: str = "endpoint"
+    repo: str = "repo"
+    ref: str = "ref"
+    path: str = "path"
 
     @requests_mock.Mocker()
     @pytest.mark.usefixtures("mock_lakefs_client_no_presign_not_local")

libs/community/tests/unit_tests/document_loaders/test_psychic.py

@@ -21,9 +21,9 @@ def mock_connector_id():  # type: ignore
 
 @pytest.mark.requires("psychicapi")
 class TestPsychicLoader:
-    MOCK_API_KEY = "api_key"
-    MOCK_CONNECTOR_ID = "notion"
-    MOCK_ACCOUNT_ID = "account_id"
+    MOCK_API_KEY: str = "api_key"
+    MOCK_CONNECTOR_ID: str = "notion"
+    MOCK_ACCOUNT_ID: str = "account_id"
 
     def test_psychic_loader_initialization(
         self, mock_psychic: MagicMock, mock_connector_id: MagicMock

libs/community/tests/unit_tests/document_loaders/test_rspace_loader.py

@@ -4,9 +4,9 @@ from langchain_community.document_loaders.rspace import RSpaceLoader
 
 
 class TestRSpaceLoader(unittest.TestCase):
-    url = "https://community.researchspace.com"
-    api_key = "myapikey"
-    global_id = "SD12345"
+    url: str = "https://community.researchspace.com"
+    api_key: str = "myapikey"
+    global_id: str = "SD12345"
 
     def test_valid_arguments(self) -> None:
         loader = RSpaceLoader(

libs/community/tests/unit_tests/embeddings/test_gradient_ai.py

@@ -70,7 +70,7 @@ class MockGradientaiPackage(MagicMock):
     """Mock Gradientai package."""
 
     Gradient = MockGradient
-    __version__ = "1.4.0"
+    __version__: str = "1.4.0"
 
 
 def test_gradient_llm_sync() -> None:

libs/community/tests/unit_tests/embeddings/test_ollama.py

@@ -5,7 +5,7 @@ from langchain_community.embeddings.ollama import OllamaEmbeddings
 
 
 class MockResponse:
-    status_code = 200
+    status_code: int = 200
 
     def json(self) -> dict:
         return {"embedding": [1, 2, 3]}