langchain: Add ruff rules FBT (#31885)

* Fixed for private functions and in tests
* Added noqa escapes for public functions
See https://docs.astral.sh/ruff/rules/#flake8-boolean-trap-fbt

Co-authored-by: Mason Daugherty <mason@langchain.dev>

libs/langchain/langchain/agents/agent_toolkits/conversational_retrieval/openai_functions.py

@@ -27,10 +27,10 @@ def _get_default_system_message() -> SystemMessage:
 def create_conversational_retrieval_agent(
     llm: BaseLanguageModel,
     tools: list[BaseTool],
-    remember_intermediate_steps: bool = True,
+    remember_intermediate_steps: bool = True,  # noqa: FBT001,FBT002
     memory_key: str = "chat_history",
     system_message: Optional[SystemMessage] = None,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
     max_token_limit: int = 2000,
     **kwargs: Any,
 ) -> AgentExecutor:

libs/langchain/langchain/agents/agent_toolkits/vectorstore/base.py

@@ -35,7 +35,7 @@ def create_vectorstore_agent(
     toolkit: VectorStoreToolkit,
     callback_manager: Optional[BaseCallbackManager] = None,
     prefix: str = PREFIX,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
     agent_executor_kwargs: Optional[dict[str, Any]] = None,
     **kwargs: Any,
 ) -> AgentExecutor:
@@ -128,7 +128,7 @@ def create_vectorstore_router_agent(
     toolkit: VectorStoreRouterToolkit,
     callback_manager: Optional[BaseCallbackManager] = None,
     prefix: str = ROUTER_PREFIX,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
     agent_executor_kwargs: Optional[dict[str, Any]] = None,
     **kwargs: Any,
 ) -> AgentExecutor:

libs/langchain/langchain/agents/json_chat/base.py

@@ -16,7 +16,7 @@ def create_json_chat_agent(
     llm: BaseLanguageModel,
     tools: Sequence[BaseTool],
     prompt: ChatPromptTemplate,
-    stop_sequence: Union[bool, list[str]] = True,
+    stop_sequence: Union[bool, list[str]] = True,  # noqa: FBT001,FBT002
     tools_renderer: ToolsRenderer = render_text_description,
     template_tool_response: str = TEMPLATE_TOOL_RESPONSE,
 ) -> Runnable:

libs/langchain/langchain/agents/openai_functions_agent/base.py

@@ -97,7 +97,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
         self,
         intermediate_steps: list[tuple[AgentAction, str]],
         callbacks: Callbacks = None,
-        with_functions: bool = True,
+        with_functions: bool = True,  # noqa: FBT001,FBT002
         **kwargs: Any,
     ) -> Union[AgentAction, AgentFinish]:
         """Given input, decided what to do.

libs/langchain/langchain/agents/openai_tools/base.py

@@ -17,7 +17,7 @@ def create_openai_tools_agent(
     llm: BaseLanguageModel,
     tools: Sequence[BaseTool],
     prompt: ChatPromptTemplate,
-    strict: Optional[bool] = None,
+    strict: Optional[bool] = None,  # noqa: FBT001
 ) -> Runnable:
     """Create an agent that uses OpenAI tools.
 

libs/langchain/langchain/chains/base.py

@@ -254,7 +254,10 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
 
     @field_validator("verbose", mode="before")
     @classmethod
-    def set_verbose(cls, verbose: Optional[bool]) -> bool:
+    def set_verbose(
+        cls,
+        verbose: Optional[bool],  # noqa: FBT001
+    ) -> bool:
         """Set the chain verbosity.
 
         Defaults to the global setting if not specified by the user.
@@ -353,7 +356,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
     def __call__(
         self,
         inputs: Union[dict[str, Any], Any],
-        return_only_outputs: bool = False,
+        return_only_outputs: bool = False,  # noqa: FBT001,FBT002
         callbacks: Callbacks = None,
         *,
         tags: Optional[list[str]] = None,
@@ -404,7 +407,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
     async def acall(
         self,
         inputs: Union[dict[str, Any], Any],
-        return_only_outputs: bool = False,
+        return_only_outputs: bool = False,  # noqa: FBT001,FBT002
         callbacks: Callbacks = None,
         *,
         tags: Optional[list[str]] = None,
@@ -454,7 +457,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
         self,
         inputs: dict[str, str],
         outputs: dict[str, str],
-        return_only_outputs: bool = False,
+        return_only_outputs: bool = False,  # noqa: FBT001,FBT002
     ) -> dict[str, str]:
         """Validate and prepare chain outputs, and save info about this run to memory.
 
@@ -479,7 +482,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
         self,
         inputs: dict[str, str],
         outputs: dict[str, str],
-        return_only_outputs: bool = False,
+        return_only_outputs: bool = False,  # noqa: FBT001,FBT002
     ) -> dict[str, str]:
         """Validate and prepare chain outputs, and save info about this run to memory.
 

libs/langchain/langchain/chains/conversational_retrieval/base.py

@@ -420,7 +420,7 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
         retriever: BaseRetriever,
         condense_question_prompt: BasePromptTemplate = CONDENSE_QUESTION_PROMPT,
         chain_type: str = "stuff",
-        verbose: bool = False,
+        verbose: bool = False,  # noqa: FBT001,FBT002
         condense_question_llm: Optional[BaseLanguageModel] = None,
         combine_docs_chain_kwargs: Optional[dict] = None,
         callbacks: Callbacks = None,

libs/langchain/langchain/chains/llm_summarization_checker/base.py

@@ -30,6 +30,7 @@ def _load_sequential_chain(
     check_assertions_prompt: PromptTemplate,
     revised_summary_prompt: PromptTemplate,
     are_all_true_prompt: PromptTemplate,
+    *,
     verbose: bool = False,
 ) -> SequentialChain:
     return SequentialChain(
@@ -188,7 +189,7 @@ class LLMSummarizationCheckerChain(Chain):
         check_assertions_prompt: PromptTemplate = CHECK_ASSERTIONS_PROMPT,
         revised_summary_prompt: PromptTemplate = REVISED_SUMMARY_PROMPT,
         are_all_true_prompt: PromptTemplate = ARE_ALL_TRUE_PROMPT,
-        verbose: bool = False,
+        verbose: bool = False,  # noqa: FBT001,FBT002
         **kwargs: Any,
     ) -> LLMSummarizationCheckerChain:
         chain = _load_sequential_chain(

libs/langchain/langchain/chains/openai_functions/extraction.py

@@ -84,7 +84,7 @@ def create_extraction_chain(
     llm: BaseLanguageModel,
     prompt: Optional[BasePromptTemplate] = None,
     tags: Optional[list[str]] = None,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
 ) -> Chain:
     """Creates a chain that extracts information from a passage.
 
@@ -152,7 +152,7 @@ def create_extraction_chain_pydantic(
     pydantic_schema: Any,
     llm: BaseLanguageModel,
     prompt: Optional[BasePromptTemplate] = None,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
 ) -> Chain:
     """Creates a chain that extracts information from a passage using pydantic schema.
 

libs/langchain/langchain/chains/openai_functions/openapi.py

@@ -23,14 +23,6 @@ if TYPE_CHECKING:
     from openapi_pydantic import Parameter
 
 
-def _get_description(o: Any, prefer_short: bool) -> Optional[str]:
-    summary = getattr(o, "summary", None)
-    description = getattr(o, "description", None)
-    if prefer_short:
-        return summary or description
-    return description or summary
-
-
 def _format_url(url: str, path_params: dict) -> str:
     expected_path_param = re.findall(r"{(.*?)}", url)
     new_params = {}
@@ -260,7 +252,7 @@ def get_openapi_chain(
     prompt: Optional[BasePromptTemplate] = None,
     request_chain: Optional[Chain] = None,
     llm_chain_kwargs: Optional[dict] = None,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
     headers: Optional[dict] = None,
     params: Optional[dict] = None,
     **kwargs: Any,

libs/langchain/langchain/chains/openai_functions/qa_with_structure.py

@@ -40,7 +40,7 @@ def create_qa_with_structure_chain(
     schema: Union[dict, type[BaseModel]],
     output_parser: str = "base",
     prompt: Optional[Union[PromptTemplate, ChatPromptTemplate]] = None,
-    verbose: bool = False,
+    verbose: bool = False,  # noqa: FBT001,FBT002
 ) -> LLMChain:
     """Create a question answering chain that returns an answer with sources
      based on schema.
@@ -119,7 +119,9 @@ def create_qa_with_structure_chain(
     ),
 )
 def create_qa_with_sources_chain(
-    llm: BaseLanguageModel, verbose: bool = False, **kwargs: Any
+    llm: BaseLanguageModel,
+    verbose: bool = False,  # noqa: FBT001,FBT002
+    **kwargs: Any,
 ) -> LLMChain:
     """Create a question answering chain that returns an answer with sources.
 

libs/langchain/langchain/chains/qa_with_sources/loading.py

@@ -37,6 +37,7 @@ class LoadingCallable(Protocol):
 
 def _load_map_rerank_chain(
     llm: BaseLanguageModel,
+    *,
     prompt: BasePromptTemplate = MAP_RERANK_PROMPT,
     verbose: bool = False,
     document_variable_name: str = "context",
@@ -56,6 +57,7 @@ def _load_map_rerank_chain(
 
 def _load_stuff_chain(
     llm: BaseLanguageModel,
+    *,
     prompt: BasePromptTemplate = stuff_prompt.PROMPT,
     document_prompt: BasePromptTemplate = stuff_prompt.EXAMPLE_PROMPT,
     document_variable_name: str = "summaries",
@@ -74,6 +76,7 @@ def _load_stuff_chain(
 
 def _load_map_reduce_chain(
     llm: BaseLanguageModel,
+    *,
     question_prompt: BasePromptTemplate = map_reduce_prompt.QUESTION_PROMPT,
     combine_prompt: BasePromptTemplate = map_reduce_prompt.COMBINE_PROMPT,
     document_prompt: BasePromptTemplate = map_reduce_prompt.EXAMPLE_PROMPT,
@@ -131,6 +134,7 @@ def _load_map_reduce_chain(
 
 def _load_refine_chain(
     llm: BaseLanguageModel,
+    *,
     question_prompt: BasePromptTemplate = refine_prompts.DEFAULT_TEXT_QA_PROMPT,
     refine_prompt: BasePromptTemplate = refine_prompts.DEFAULT_REFINE_PROMPT,
     document_prompt: BasePromptTemplate = refine_prompts.EXAMPLE_PROMPT,
@@ -172,7 +176,7 @@ def _load_refine_chain(
 def load_qa_with_sources_chain(
     llm: BaseLanguageModel,
     chain_type: str = "stuff",
-    verbose: Optional[bool] = None,
+    verbose: Optional[bool] = None,  # noqa: FBT001
     **kwargs: Any,
 ) -> BaseCombineDocumentsChain:
     """Load a question answering with sources chain.

libs/langchain/langchain/chains/query_constructor/base.py

@@ -72,7 +72,7 @@ class StructuredQueryOutputParser(BaseOutputParser[StructuredQuery]):
         allowed_comparators: Optional[Sequence[Comparator]] = None,
         allowed_operators: Optional[Sequence[Operator]] = None,
         allowed_attributes: Optional[Sequence[str]] = None,
-        fix_invalid: bool = False,
+        fix_invalid: bool = False,  # noqa: FBT001,FBT002
     ) -> StructuredQueryOutputParser:
         """
         Create a structured query output parser from components.
@@ -269,7 +269,7 @@ def load_query_constructor_chain(
     examples: Optional[list] = None,
     allowed_comparators: Sequence[Comparator] = tuple(Comparator),
     allowed_operators: Sequence[Operator] = tuple(Operator),
-    enable_limit: bool = False,
+    enable_limit: bool = False,  # noqa: FBT001,FBT002
     schema_prompt: Optional[BasePromptTemplate] = None,
     **kwargs: Any,
 ) -> LLMChain:

libs/langchain/langchain/chains/question_answering/chain.py

@@ -36,6 +36,7 @@ class LoadingCallable(Protocol):
 
 def _load_map_rerank_chain(
     llm: BaseLanguageModel,
+    *,
     prompt: BasePromptTemplate = MAP_RERANK_PROMPT,
     verbose: bool = False,
     document_variable_name: str = "context",
@@ -65,6 +66,7 @@ def _load_map_rerank_chain(
 
 def _load_stuff_chain(
     llm: BaseLanguageModel,
+    *,
     prompt: Optional[BasePromptTemplate] = None,
     document_variable_name: str = "context",
     verbose: Optional[bool] = None,
@@ -93,6 +95,7 @@ def _load_stuff_chain(
 
 def _load_map_reduce_chain(
     llm: BaseLanguageModel,
+    *,
     question_prompt: Optional[BasePromptTemplate] = None,
     combine_prompt: Optional[BasePromptTemplate] = None,
     combine_document_variable_name: str = "summaries",
@@ -176,6 +179,7 @@ def _load_map_reduce_chain(
 
 def _load_refine_chain(
     llm: BaseLanguageModel,
+    *,
     question_prompt: Optional[BasePromptTemplate] = None,
     refine_prompt: Optional[BasePromptTemplate] = None,
     document_variable_name: str = "context_str",
@@ -236,7 +240,7 @@ def _load_refine_chain(
 def load_qa_chain(
     llm: BaseLanguageModel,
     chain_type: str = "stuff",
-    verbose: Optional[bool] = None,
+    verbose: Optional[bool] = None,  # noqa: FBT001
     callback_manager: Optional[BaseCallbackManager] = None,
     **kwargs: Any,
 ) -> BaseCombineDocumentsChain:

libs/langchain/langchain/chains/summarize/chain.py

@@ -27,6 +27,7 @@ class LoadingCallable(Protocol):
 
 def _load_stuff_chain(
     llm: BaseLanguageModel,
+    *,
     prompt: BasePromptTemplate = stuff_prompt.PROMPT,
     document_variable_name: str = "text",
     verbose: Optional[bool] = None,
@@ -44,6 +45,7 @@ def _load_stuff_chain(
 
 def _load_map_reduce_chain(
     llm: BaseLanguageModel,
+    *,
     map_prompt: BasePromptTemplate = map_reduce_prompt.PROMPT,
     combine_prompt: BasePromptTemplate = map_reduce_prompt.PROMPT,
     combine_document_variable_name: str = "text",
@@ -54,7 +56,6 @@ def _load_map_reduce_chain(
     verbose: Optional[bool] = None,
     token_max: int = 3000,
     callbacks: Callbacks = None,
-    *,
     collapse_max_retries: Optional[int] = None,
     **kwargs: Any,
 ) -> MapReduceDocumentsChain:
@@ -117,6 +118,7 @@ def _load_map_reduce_chain(
 
 def _load_refine_chain(
     llm: BaseLanguageModel,
+    *,
     question_prompt: BasePromptTemplate = refine_prompts.PROMPT,
     refine_prompt: BasePromptTemplate = refine_prompts.REFINE_PROMPT,
     document_variable_name: str = "text",
@@ -141,7 +143,7 @@ def _load_refine_chain(
 def load_summarize_chain(
     llm: BaseLanguageModel,
     chain_type: str = "stuff",
-    verbose: Optional[bool] = None,
+    verbose: Optional[bool] = None,  # noqa: FBT001
     **kwargs: Any,
 ) -> BaseCombineDocumentsChain:
     """Load summarizing chain.

libs/langchain/langchain/evaluation/string_distance/base.py

@@ -106,7 +106,7 @@ class _RapidFuzzChainMixin(Chain):
         return result
 
     @staticmethod
-    def _get_metric(distance: str, normalize_score: bool = False) -> Callable:
+    def _get_metric(distance: str, *, normalize_score: bool = False) -> Callable:
         """
         Get the distance metric function based on the distance type.
 

libs/langchain/langchain/globals.py

@@ -16,7 +16,9 @@ _debug: bool = False
 _llm_cache: Optional["BaseCache"] = None
 
 
-def set_verbose(value: bool) -> None:
+def set_verbose(
+    value: bool,  # noqa: FBT001
+) -> None:
     """Set a new value for the `verbose` global setting."""
     import langchain
 
@@ -71,7 +73,9 @@ def get_verbose() -> bool:
     return _verbose or old_verbose
 
 
-def set_debug(value: bool) -> None:
+def set_debug(
+    value: bool,  # noqa: FBT001
+) -> None:
     """Set a new value for the `debug` global setting."""
     import langchain
 

libs/langchain/langchain/output_parsers/structured.py

@@ -43,7 +43,10 @@ class StructuredOutputParser(BaseOutputParser[dict[str, Any]]):
     ) -> StructuredOutputParser:
         return cls(response_schemas=response_schemas)
 
-    def get_format_instructions(self, only_json: bool = False) -> str:
+    def get_format_instructions(
+        self,
+        only_json: bool = False,  # noqa: FBT001,FBT002
+    ) -> str:
         """Get format instructions for the output parser.
 
         example:

libs/langchain/langchain/retrievers/multi_query.py

@@ -66,7 +66,7 @@ class MultiQueryRetriever(BaseRetriever):
         llm: BaseLanguageModel,
         prompt: BasePromptTemplate = DEFAULT_QUERY_PROMPT,
         parser_key: Optional[str] = None,
-        include_original: bool = False,
+        include_original: bool = False,  # noqa: FBT001,FBT002
     ) -> "MultiQueryRetriever":
         """Initialize from llm using default template.
 

libs/langchain/langchain/retrievers/parent_document_retriever.py

@@ -74,6 +74,7 @@ class ParentDocumentRetriever(MultiVectorRetriever):
         self,
         documents: list[Document],
         ids: Optional[list[str]] = None,
+        *,
         add_to_docstore: bool = True,
     ) -> tuple[list[Document], list[tuple[str, Document]]]:
         if self.parent_splitter is not None:
@@ -113,7 +114,7 @@ class ParentDocumentRetriever(MultiVectorRetriever):
         self,
         documents: list[Document],
         ids: Optional[list[str]] = None,
-        add_to_docstore: bool = True,
+        add_to_docstore: bool = True,  # noqa: FBT001,FBT002
         **kwargs: Any,
     ) -> None:
         """Adds documents to the docstore and vectorstores.
@@ -130,7 +131,9 @@ class ParentDocumentRetriever(MultiVectorRetriever):
                 to set this to False if the documents are already in the docstore
                 and you don't want to re-add them.
         """
-        docs, full_docs = self._split_docs_for_adding(documents, ids, add_to_docstore)
+        docs, full_docs = self._split_docs_for_adding(
+            documents, ids, add_to_docstore=add_to_docstore
+        )
         self.vectorstore.add_documents(docs, **kwargs)
         if add_to_docstore:
             self.docstore.mset(full_docs)
@@ -139,10 +142,12 @@ class ParentDocumentRetriever(MultiVectorRetriever):
         self,
         documents: list[Document],
         ids: Optional[list[str]] = None,
-        add_to_docstore: bool = True,
+        add_to_docstore: bool = True,  # noqa: FBT001,FBT002
         **kwargs: Any,
     ) -> None:
-        docs, full_docs = self._split_docs_for_adding(documents, ids, add_to_docstore)
+        docs, full_docs = self._split_docs_for_adding(
+            documents, ids, add_to_docstore=add_to_docstore
+        )
         await self.vectorstore.aadd_documents(docs, **kwargs)
         if add_to_docstore:
             await self.docstore.amset(full_docs)

libs/langchain/langchain/retrievers/self_query/base.py

@@ -342,8 +342,8 @@ class SelfQueryRetriever(BaseRetriever):
         metadata_field_info: Sequence[Union[AttributeInfo, dict]],
         structured_query_translator: Optional[Visitor] = None,
         chain_kwargs: Optional[dict] = None,
-        enable_limit: bool = False,
+        enable_limit: bool = False,  # noqa: FBT001,FBT002
-        use_original_query: bool = False,
+        use_original_query: bool = False,  # noqa: FBT001,FBT002
         **kwargs: Any,
     ) -> "SelfQueryRetriever":
         if structured_query_translator is None:

libs/langchain/langchain/smith/evaluation/runner_utils.py

@@ -1146,7 +1146,11 @@ class _DatasetRunContainer:
             aggregate_metrics=aggregate_feedback,
         )
 
-    def finish(self, batch_results: list, verbose: bool = False) -> TestResult:
+    def finish(
+        self,
+        batch_results: list,
+        verbose: bool = False,  # noqa: FBT001,FBT002
+    ) -> TestResult:
         results = self._collect_test_results(batch_results)
         if verbose:
             try:

libs/langchain/pyproject.toml

@@ -143,7 +143,7 @@ ignore-regex = ".*(Stati Uniti|Tense=Pres).*"
 ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure,damon,crate,aadd,symbl,precesses,accademia,nin"
 
 [tool.ruff.lint]
-select = ["A", "C4", "D", "E", "EM", "F", "I", "PGH003", "PIE", "RET", "S", "SIM", "T201", "UP", "W"]
+select = ["A", "C4", "D", "E", "EM", "F", "FBT", "I", "PGH003", "PIE", "RET", "S", "SIM", "T201", "UP", "W"]
 pydocstyle.convention = "google"
 pyupgrade.keep-runtime-typing = true
 

libs/langchain/tests/mock_servers/robot/server.py

@@ -136,7 +136,7 @@ async def get_state(
 
 
 @app.get("/ask_for_passphrase", description="Get the robot's pass phrase")
-async def ask_for_passphrase(said_please: bool) -> dict[str, Any]:
+async def ask_for_passphrase(*, said_please: bool) -> dict[str, Any]:
     if said_please:
         return {"passphrase": f"The passphrase is {PASS_PHRASE}"}
     return {"passphrase": "I won't share the passphrase without saying 'please'."}

libs/langchain/tests/unit_tests/chains/test_sequential.py

@@ -182,7 +182,7 @@ def test_simple_sequential_functionality() -> None:
 
 
 @pytest.mark.parametrize("isAsync", [False, True])
-async def test_simple_sequential_functionality_with_callbacks(isAsync: bool) -> None:
+async def test_simple_sequential_functionality_with_callbacks(*, isAsync: bool) -> None:
     """Test simple sequential functionality."""
     handler_1 = FakeCallbackHandler()
     handler_2 = FakeCallbackHandler()

libs/langchain/tests/unit_tests/evaluation/string_distance/test_base.py

@@ -31,7 +31,7 @@ async def test_zero_distance_async(distance: StringDistance) -> None:
 @pytest.mark.parametrize("distance", list(StringDistance))
 @pytest.mark.parametrize("normalize_score", [True, False])
 def test_zero_distance_pairwise(
-    distance: StringDistance, normalize_score: bool
+    *, distance: StringDistance, normalize_score: bool
 ) -> None:
     eval_chain = PairwiseStringDistanceEvalChain(
         distance=distance, normalize_score=normalize_score
@@ -62,7 +62,7 @@ valid_distances = [
 @pytest.mark.requires("rapidfuzz")
 @pytest.mark.parametrize("distance", valid_distances)
 @pytest.mark.parametrize("normalize_score", [True, False])
-def test_non_zero_distance(distance: StringDistance, normalize_score: bool) -> None:
+def test_non_zero_distance(*, distance: StringDistance, normalize_score: bool) -> None:
     eval_chain = StringDistanceEvalChain(
         distance=distance, normalize_score=normalize_score
     )

libs/langchain/tests/unit_tests/indexes/test_indexing.py

@@ -40,7 +40,7 @@ class ToyLoader(BaseLoader):
 class InMemoryVectorStore(VectorStore):
     """In-memory implementation of VectorStore using a dictionary."""
 
-    def __init__(self, permit_upserts: bool = False) -> None:
+    def __init__(self, *, permit_upserts: bool = False) -> None:
         """Vector store interface for testing things in memory."""
         self.store: dict[str, Document] = {}
         self.permit_upserts = permit_upserts

libs/langchain/tests/unit_tests/test_globals.py

@@ -17,9 +17,9 @@ def test_no_warning() -> None:
         get_verbose()
         set_verbose(False)
         core_get_debug()
-        core_set_debug(False)
+        core_set_debug(value=False)
         core_get_verbose()
-        core_set_verbose(False)
+        core_set_verbose(value=False)
 
 
 def test_debug_is_settable_directly() -> None: