chore(langchain): add ruff rules ARG (#32110)

See https://docs.astral.sh/ruff/rules/#flake8-unused-arguments-arg

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

libs/langchain/langchain/agents/agent.py

@@ -116,8 +116,8 @@ class BaseSingleActionAgent(BaseModel):
     def return_stopped_response(
         self,
         early_stopping_method: str,
-        intermediate_steps: list[tuple[AgentAction, str]],
+        intermediate_steps: list[tuple[AgentAction, str]],  # noqa: ARG002
-        **kwargs: Any,
+        **_: Any,
     ) -> AgentFinish:
         """Return response when agent has been stopped due to max iterations.
 
@@ -125,7 +125,6 @@ class BaseSingleActionAgent(BaseModel):
             early_stopping_method: Method to use for early stopping.
             intermediate_steps: Steps the LLM has taken to date,
                 along with observations.
-            **kwargs: User inputs.
 
         Returns:
             AgentFinish: Agent finish object.
@@ -168,6 +167,7 @@ class BaseSingleActionAgent(BaseModel):
         """Return Identifier of an agent type."""
         raise NotImplementedError
 
+    @override
     def dict(self, **kwargs: Any) -> builtins.dict:
         """Return dictionary representation of agent.
 
@@ -289,8 +289,8 @@ class BaseMultiActionAgent(BaseModel):
     def return_stopped_response(
         self,
         early_stopping_method: str,
-        intermediate_steps: list[tuple[AgentAction, str]],
+        intermediate_steps: list[tuple[AgentAction, str]],  # noqa: ARG002
-        **kwargs: Any,
+        **_: Any,
     ) -> AgentFinish:
         """Return response when agent has been stopped due to max iterations.
 
@@ -298,7 +298,6 @@ class BaseMultiActionAgent(BaseModel):
             early_stopping_method: Method to use for early stopping.
             intermediate_steps: Steps the LLM has taken to date,
                 along with observations.
-            **kwargs: User inputs.
 
         Returns:
             AgentFinish: Agent finish object.
@@ -317,6 +316,7 @@ class BaseMultiActionAgent(BaseModel):
         """Return Identifier of an agent type."""
         raise NotImplementedError
 
+    @override
     def dict(self, **kwargs: Any) -> builtins.dict:
         """Return dictionary representation of agent."""
         _dict = super().model_dump()
@@ -651,6 +651,7 @@ class LLMSingleActionAgent(BaseSingleActionAgent):
         """
         return list(set(self.llm_chain.input_keys) - {"intermediate_steps"})
 
+    @override
     def dict(self, **kwargs: Any) -> builtins.dict:
         """Return dictionary representation of agent."""
         _dict = super().dict()
@@ -735,6 +736,7 @@ class Agent(BaseSingleActionAgent):
     allowed_tools: Optional[list[str]] = None
     """Allowed tools for the agent. If None, all tools are allowed."""
 
+    @override
     def dict(self, **kwargs: Any) -> builtins.dict:
         """Return dictionary representation of agent."""
         _dict = super().dict()
@@ -750,18 +752,6 @@ class Agent(BaseSingleActionAgent):
         """Return values of the agent."""
         return ["output"]
 
-    def _fix_text(self, text: str) -> str:
-        """Fix the text.
-
-        Args:
-            text: Text to fix.
-
-        Returns:
-            str: Fixed text.
-        """
-        msg = "fix_text not implemented for this agent."
-        raise ValueError(msg)
-
     @property
     def _stop(self) -> list[str]:
         return [
@@ -1021,6 +1011,7 @@ class ExceptionTool(BaseTool):
     description: str = "Exception tool"
     """Description of the tool."""
 
+    @override
     def _run(
         self,
         query: str,
@@ -1028,6 +1019,7 @@ class ExceptionTool(BaseTool):
     ) -> str:
         return query
 
+    @override
     async def _arun(
         self,
         query: str,
@@ -1188,6 +1180,7 @@ class AgentExecutor(Chain):
             return cast("RunnableAgentType", self.agent)
         return self.agent
 
+    @override
     def save(self, file_path: Union[Path, str]) -> None:
         """Raise error - saving not supported for Agent Executors.
 
@@ -1218,7 +1211,7 @@ class AgentExecutor(Chain):
         callbacks: Callbacks = None,
         *,
         include_run_info: bool = False,
-        async_: bool = False,  # arg kept for backwards compat, but ignored
+        async_: bool = False,  # noqa: ARG002 arg kept for backwards compat, but ignored
     ) -> AgentExecutorIterator:
         """Enables iteration over steps taken to reach final output.
 

libs/langchain/langchain/agents/chat/base.py

@@ -13,6 +13,7 @@ from langchain_core.prompts.chat import (
 )
 from langchain_core.tools import BaseTool
 from pydantic import Field
+from typing_extensions import override
 
 from langchain._api.deprecation import AGENT_DEPRECATION_WARNING
 from langchain.agents.agent import Agent, AgentOutputParser
@@ -65,6 +66,7 @@ class ChatAgent(Agent):
         return agent_scratchpad
 
     @classmethod
+    @override
     def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
         return ChatOutputParser()
 

libs/langchain/langchain/agents/conversational/base.py

@@ -11,6 +11,7 @@ from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import PromptTemplate
 from langchain_core.tools import BaseTool
 from pydantic import Field
+from typing_extensions import override
 
 from langchain._api.deprecation import AGENT_DEPRECATION_WARNING
 from langchain.agents.agent import Agent, AgentOutputParser
@@ -35,6 +36,7 @@ class ConversationalAgent(Agent):
     """Output parser for the agent."""
 
     @classmethod
+    @override
     def _get_default_output_parser(
         cls,
         ai_prefix: str = "AI",

libs/langchain/langchain/agents/conversational_chat/base.py

@@ -20,6 +20,7 @@ from langchain_core.prompts.chat import (
 )
 from langchain_core.tools import BaseTool
 from pydantic import Field
+from typing_extensions import override
 
 from langchain.agents.agent import Agent, AgentOutputParser
 from langchain.agents.conversational_chat.output_parser import ConvoOutputParser
@@ -42,6 +43,7 @@ class ConversationalChatAgent(Agent):
     """Template for the tool response."""
 
     @classmethod
+    @override
     def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
         return ConvoOutputParser()
 

libs/langchain/langchain/agents/mrkl/base.py

@@ -12,6 +12,7 @@ from langchain_core.prompts import PromptTemplate
 from langchain_core.tools import BaseTool, Tool
 from langchain_core.tools.render import render_text_description
 from pydantic import Field
+from typing_extensions import override
 
 from langchain._api.deprecation import AGENT_DEPRECATION_WARNING
 from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
@@ -51,6 +52,7 @@ class ZeroShotAgent(Agent):
     output_parser: AgentOutputParser = Field(default_factory=MRKLOutputParser)
 
     @classmethod
+    @override
     def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
         return MRKLOutputParser()
 

libs/langchain/langchain/agents/openai_functions_agent/agent_token_buffer_memory.py

@@ -4,6 +4,7 @@ from typing import Any
 
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.messages import BaseMessage, get_buffer_string
+from typing_extensions import override
 
 from langchain.agents.format_scratchpad import (
     format_to_openai_function_messages,
@@ -55,6 +56,7 @@ class AgentTokenBufferMemory(BaseChatMemory):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return history buffer.
 

libs/langchain/langchain/agents/react/base.py

@@ -11,6 +11,7 @@ from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
 from langchain_core.tools import BaseTool, Tool
 from pydantic import Field
+from typing_extensions import override
 
 from langchain._api.deprecation import AGENT_DEPRECATION_WARNING
 from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
@@ -38,6 +39,7 @@ class ReActDocstoreAgent(Agent):
     output_parser: AgentOutputParser = Field(default_factory=ReActOutputParser)
 
     @classmethod
+    @override
     def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
         return ReActOutputParser()
 
@@ -47,6 +49,7 @@ class ReActDocstoreAgent(Agent):
         return AgentType.REACT_DOCSTORE
 
     @classmethod
+    @override
     def create_prompt(cls, tools: Sequence[BaseTool]) -> BasePromptTemplate:
         """Return default prompt."""
         return WIKI_PROMPT
@@ -141,6 +144,7 @@ class ReActTextWorldAgent(ReActDocstoreAgent):
     """Agent for the ReAct TextWorld chain."""
 
     @classmethod
+    @override
     def create_prompt(cls, tools: Sequence[BaseTool]) -> BasePromptTemplate:
         """Return default prompt."""
         return TEXTWORLD_PROMPT

libs/langchain/langchain/agents/self_ask_with_search/base.py

@@ -11,6 +11,7 @@ from langchain_core.prompts import BasePromptTemplate
 from langchain_core.runnables import Runnable, RunnablePassthrough
 from langchain_core.tools import BaseTool, Tool
 from pydantic import Field
+from typing_extensions import override
 
 from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
 from langchain.agents.agent_types import AgentType
@@ -32,6 +33,7 @@ class SelfAskWithSearchAgent(Agent):
     output_parser: AgentOutputParser = Field(default_factory=SelfAskOutputParser)
 
     @classmethod
+    @override
     def _get_default_output_parser(cls, **kwargs: Any) -> AgentOutputParser:
         return SelfAskOutputParser()
 
@@ -41,6 +43,7 @@ class SelfAskWithSearchAgent(Agent):
         return AgentType.SELF_ASK_WITH_SEARCH
 
     @classmethod
+    @override
     def create_prompt(cls, tools: Sequence[BaseTool]) -> BasePromptTemplate:
         """Prompt does not depend on tools."""
         return PROMPT

libs/langchain/langchain/agents/structured_chat/base.py

@@ -71,6 +71,7 @@ class StructuredChatAgent(Agent):
         pass
 
     @classmethod
+    @override
     def _get_default_output_parser(
         cls,
         llm: Optional[BaseLanguageModel] = None,

libs/langchain/langchain/agents/tools.py

@@ -7,6 +7,7 @@ from langchain_core.callbacks import (
     CallbackManagerForToolRun,
 )
 from langchain_core.tools import BaseTool, tool
+from typing_extensions import override
 
 
 class InvalidTool(BaseTool):
@@ -17,6 +18,7 @@ class InvalidTool(BaseTool):
     description: str = "Called when tool name is invalid. Suggests valid tool names."
     """Description of the tool."""
 
+    @override
     def _run(
         self,
         requested_tool_name: str,
@@ -30,6 +32,7 @@ class InvalidTool(BaseTool):
             f"try one of [{available_tool_names_str}]."
         )
 
+    @override
     async def _arun(
         self,
         requested_tool_name: str,

libs/langchain/langchain/callbacks/streaming_stdout_final_only.py

@@ -4,6 +4,7 @@ import sys
 from typing import Any, Optional
 
 from langchain_core.callbacks import StreamingStdOutCallbackHandler
+from typing_extensions import override
 
 DEFAULT_ANSWER_PREFIX_TOKENS = ["Final", "Answer", ":"]
 
@@ -63,6 +64,7 @@ class FinalStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
         self.stream_prefix = stream_prefix
         self.answer_reached = False
 
+    @override
     def on_llm_start(
         self,
         serialized: dict[str, Any],
@@ -72,6 +74,7 @@ class FinalStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
         """Run when LLM starts running."""
         self.answer_reached = False
 
+    @override
     def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
         """Run on new LLM token. Only available when streaming is enabled."""
 

libs/langchain/langchain/chains/api/base.py

@@ -388,7 +388,7 @@ except ImportError:
     class APIChain:  # type: ignore[no-redef]
         """Raise an ImportError if APIChain is used without langchain_community."""
 
-        def __init__(self, *args: Any, **kwargs: Any) -> None:
+        def __init__(self, *_: Any, **__: Any) -> None:
             """Raise an ImportError if APIChain is used without langchain_community."""
             msg = (
                 "To use the APIChain, you must install the langchain_community package."

libs/langchain/langchain/chains/combine_documents/base.py

@@ -83,7 +83,7 @@ class BaseCombineDocumentsChain(Chain, ABC):
         """
         return [self.output_key]
 
-    def prompt_length(self, docs: list[Document], **kwargs: Any) -> Optional[int]:
+    def prompt_length(self, docs: list[Document], **kwargs: Any) -> Optional[int]:  # noqa: ARG002
         """Return the prompt length given the documents passed in.
 
         This can be used by a caller to determine whether passing in a list

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

@@ -402,6 +402,7 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
 
         return docs[:num_docs]
 
+    @override
     def _get_docs(
         self,
         question: str,
@@ -416,6 +417,7 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
         )
         return self._reduce_tokens_below_limit(docs)
 
+    @override
     async def _aget_docs(
         self,
         question: str,
@@ -512,6 +514,7 @@ class ChatVectorDBChain(BaseConversationalRetrievalChain):
         )
         return values
 
+    @override
     def _get_docs(
         self,
         question: str,

libs/langchain/langchain/chains/llm_bash/__init__.py

@@ -1,4 +1,4 @@
-def __getattr__(name: str = "") -> None:
+def __getattr__(_: str = "") -> None:
     """Raise an error on import since is deprecated."""
     msg = (
         "This module has been moved to langchain-experimental. "

libs/langchain/langchain/chains/llm_symbolic_math/__init__.py

@@ -1,4 +1,4 @@
-def __getattr__(name: str = "") -> None:
+def __getattr__(_: str = "") -> None:
     """Raise an error on import since is deprecated."""
     msg = (
         "This module has been moved to langchain-experimental. "

libs/langchain/langchain/chains/loading.py

@@ -39,7 +39,7 @@ try:
     from langchain_community.llms.loading import load_llm, load_llm_from_config
 except ImportError:
 
-    def load_llm(*args: Any, **kwargs: Any) -> None:
+    def load_llm(*_: Any, **__: Any) -> None:
         """Import error for load_llm."""
         msg = (
             "To use this load_llm functionality you must install the "
@@ -48,7 +48,7 @@ except ImportError:
         )
         raise ImportError(msg)
 
-    def load_llm_from_config(*args: Any, **kwargs: Any) -> None:
+    def load_llm_from_config(*_: Any, **__: Any) -> None:
         """Import error for load_llm_from_config."""
         msg = (
             "To use this load_llm_from_config functionality you must install the "

libs/langchain/langchain/chains/moderation.py

@@ -8,6 +8,7 @@ from langchain_core.callbacks import (
 )
 from langchain_core.utils import check_package_version, get_from_dict_or_env
 from pydantic import Field, model_validator
+from typing_extensions import override
 
 from langchain.chains.base import Chain
 
@@ -105,6 +106,7 @@ class OpenAIModerationChain(Chain):
             return error_str
         return text
 
+    @override
     def _call(
         self,
         inputs: dict[str, Any],

libs/langchain/langchain/chains/qa_with_sources/base.py

@@ -16,6 +16,7 @@ from langchain_core.documents import Document
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
 from pydantic import ConfigDict, model_validator
+from typing_extensions import override
 
 from langchain.chains import ReduceDocumentsChain
 from langchain.chains.base import Chain
@@ -240,6 +241,7 @@ class QAWithSourcesChain(BaseQAWithSourcesChain):
         """
         return [self.input_docs_key, self.question_key]
 
+    @override
     def _get_docs(
         self,
         inputs: dict[str, Any],
@@ -249,6 +251,7 @@ class QAWithSourcesChain(BaseQAWithSourcesChain):
         """Get docs to run questioning over."""
         return inputs.pop(self.input_docs_key)
 
+    @override
     async def _aget_docs(
         self,
         inputs: dict[str, Any],

libs/langchain/langchain/chains/qa_with_sources/vector_db.py

@@ -10,6 +10,7 @@ from langchain_core.callbacks import (
 from langchain_core.documents import Document
 from langchain_core.vectorstores import VectorStore
 from pydantic import Field, model_validator
+from typing_extensions import override
 
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.qa_with_sources.base import BaseQAWithSourcesChain
@@ -48,6 +49,7 @@ class VectorDBQAWithSourcesChain(BaseQAWithSourcesChain):
 
         return docs[:num_docs]
 
+    @override
     def _get_docs(
         self,
         inputs: dict[str, Any],

libs/langchain/langchain/chains/query_constructor/parser.py

@@ -11,7 +11,7 @@ try:
     from lark import Lark, Transformer, v_args
 except ImportError:
 
-    def v_args(*args: Any, **kwargs: Any) -> Any:  # type: ignore[misc]
+    def v_args(*_: Any, **__: Any) -> Any:  # type: ignore[misc]
         """Dummy decorator for when lark is not installed."""
         return lambda _: None
 

libs/langchain/langchain/chains/retrieval_qa/base.py

@@ -18,6 +18,7 @@ from langchain_core.prompts import PromptTemplate
 from langchain_core.retrievers import BaseRetriever
 from langchain_core.vectorstores import VectorStore
 from pydantic import ConfigDict, Field, model_validator
+from typing_extensions import override
 
 from langchain.chains.base import Chain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
@@ -330,6 +331,7 @@ class VectorDBQA(BaseRetrievalQA):
                 raise ValueError(msg)
         return values
 
+    @override
     def _get_docs(
         self,
         question: str,

libs/langchain/langchain/chains/router/embedding_router.py

@@ -11,6 +11,7 @@ from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.vectorstores import VectorStore
 from pydantic import ConfigDict
+from typing_extensions import override
 
 from langchain.chains.router.base import RouterChain
 
@@ -34,6 +35,7 @@ class EmbeddingRouterChain(RouterChain):
         """
         return self.routing_keys
 
+    @override
     def _call(
         self,
         inputs: dict[str, Any],
@@ -43,6 +45,7 @@ class EmbeddingRouterChain(RouterChain):
         results = self.vectorstore.similarity_search(_input, k=1)
         return {"next_inputs": inputs, "destination": results[0].metadata["name"]}
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, Any],

libs/langchain/langchain/chains/transform.py

@@ -10,6 +10,7 @@ from langchain_core.callbacks import (
     CallbackManagerForChainRun,
 )
 from pydantic import Field
+from typing_extensions import override
 
 from langchain.chains.base import Chain
 
@@ -63,6 +64,7 @@ class TransformChain(Chain):
         """
         return self.output_variables
 
+    @override
     def _call(
         self,
         inputs: dict[str, str],
@@ -70,6 +72,7 @@ class TransformChain(Chain):
     ) -> dict[str, str]:
         return self.transform_cb(inputs)
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, Any],

libs/langchain/langchain/evaluation/embedding_distance/base.py

@@ -331,6 +331,7 @@ class EmbeddingDistanceEvalChain(_EmbeddingDistanceChainMixin, StringEvaluator):
         """
         return ["prediction", "reference"]
 
+    @override
     def _call(
         self,
         inputs: dict[str, Any],
@@ -355,6 +356,7 @@ class EmbeddingDistanceEvalChain(_EmbeddingDistanceChainMixin, StringEvaluator):
         score = self._compute_score(vectors)
         return {"score": score}
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, Any],
@@ -382,6 +384,7 @@ class EmbeddingDistanceEvalChain(_EmbeddingDistanceChainMixin, StringEvaluator):
         score = self._compute_score(vectors)
         return {"score": score}
 
+    @override
     def _evaluate_strings(
         self,
         *,
@@ -416,6 +419,7 @@ class EmbeddingDistanceEvalChain(_EmbeddingDistanceChainMixin, StringEvaluator):
         )
         return self._prepare_output(result)
 
+    @override
     async def _aevaluate_strings(
         self,
         *,
@@ -478,6 +482,7 @@ class PairwiseEmbeddingDistanceEvalChain(
         """Return the evaluation name."""
         return f"pairwise_embedding_{self.distance_metric.value}_distance"
 
+    @override
     def _call(
         self,
         inputs: dict[str, Any],
@@ -505,6 +510,7 @@ class PairwiseEmbeddingDistanceEvalChain(
         score = self._compute_score(vectors)
         return {"score": score}
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, Any],
@@ -532,6 +538,7 @@ class PairwiseEmbeddingDistanceEvalChain(
         score = self._compute_score(vectors)
         return {"score": score}
 
+    @override
     def _evaluate_string_pairs(
         self,
         *,
@@ -567,6 +574,7 @@ class PairwiseEmbeddingDistanceEvalChain(
         )
         return self._prepare_output(result)
 
+    @override
     async def _aevaluate_string_pairs(
         self,
         *,

libs/langchain/langchain/evaluation/exact_match/base.py

@@ -1,6 +1,8 @@
 import string
 from typing import Any
 
+from typing_extensions import override
+
 from langchain.evaluation.schema import StringEvaluator
 
 
@@ -78,6 +80,7 @@ class ExactMatchStringEvaluator(StringEvaluator):
         """
         return "exact_match"
 
+    @override
     def _evaluate_strings(  # type: ignore[override]
         self,
         *,

libs/langchain/langchain/evaluation/parsing/json_schema.py

@@ -33,12 +33,9 @@ class JsonSchemaEvaluator(StringEvaluator):
 
     """  # noqa: E501
 
-    def __init__(self, **kwargs: Any) -> None:
+    def __init__(self, **_: Any) -> None:
         """Initializes the JsonSchemaEvaluator.
 
-        Args:
-            kwargs: Additional keyword arguments.
-
         Raises:
             ImportError: If the jsonschema package is not installed.
         """

libs/langchain/langchain/evaluation/regex_match/base.py

@@ -1,6 +1,8 @@
 import re
 from typing import Any
 
+from typing_extensions import override
+
 from langchain.evaluation.schema import StringEvaluator
 
 
@@ -70,6 +72,7 @@ class RegexMatchStringEvaluator(StringEvaluator):
         """
         return "regex_match"
 
+    @override
     def _evaluate_strings(  # type: ignore[override]
         self,
         *,

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

@@ -224,6 +224,7 @@ class StringDistanceEvalChain(StringEvaluator, _RapidFuzzChainMixin):
         """
         return f"{self.distance.value}_distance"
 
+    @override
     def _call(
         self,
         inputs: dict[str, Any],
@@ -242,6 +243,7 @@ class StringDistanceEvalChain(StringEvaluator, _RapidFuzzChainMixin):
         """
         return {"score": self.compute_metric(inputs["reference"], inputs["prediction"])}
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, Any],
@@ -357,6 +359,7 @@ class PairwiseStringDistanceEvalChain(PairwiseStringEvaluator, _RapidFuzzChainMi
         """
         return f"pairwise_{self.distance.value}_distance"
 
+    @override
     def _call(
         self,
         inputs: dict[str, Any],
@@ -377,6 +380,7 @@ class PairwiseStringDistanceEvalChain(PairwiseStringEvaluator, _RapidFuzzChainMi
             "score": self.compute_metric(inputs["prediction"], inputs["prediction_b"]),
         }
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, Any],
@@ -397,6 +401,7 @@ class PairwiseStringDistanceEvalChain(PairwiseStringEvaluator, _RapidFuzzChainMi
             "score": self.compute_metric(inputs["prediction"], inputs["prediction_b"]),
         }
 
+    @override
     def _evaluate_string_pairs(
         self,
         *,
@@ -431,6 +436,7 @@ class PairwiseStringDistanceEvalChain(PairwiseStringEvaluator, _RapidFuzzChainMi
         )
         return self._prepare_output(result)
 
+    @override
     async def _aevaluate_string_pairs(
         self,
         *,

libs/langchain/langchain/memory/buffer.py

@@ -79,10 +79,12 @@ class ConversationBufferMemory(BaseChatMemory):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return history buffer."""
         return {self.memory_key: self.buffer}
 
+    @override
     async def aload_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return key-value pairs given the text input to the chain."""
         buffer = await self.abuffer()
@@ -133,6 +135,7 @@ class ConversationStringBufferMemory(BaseMemory):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, str]:
         """Return history buffer."""
         return {self.memory_key: self.buffer}

libs/langchain/langchain/memory/buffer_window.py

@@ -2,6 +2,7 @@ from typing import Any, Union
 
 from langchain_core._api import deprecated
 from langchain_core.messages import BaseMessage, get_buffer_string
+from typing_extensions import override
 
 from langchain.memory.chat_memory import BaseChatMemory
 
@@ -55,6 +56,7 @@ class ConversationBufferWindowMemory(BaseChatMemory):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return history buffer."""
         return {self.memory_key: self.buffer}

libs/langchain/langchain/memory/summary.py

@@ -9,6 +9,7 @@ from langchain_core.messages import BaseMessage, SystemMessage, get_buffer_strin
 from langchain_core.prompts import BasePromptTemplate
 from langchain_core.utils import pre_init
 from pydantic import BaseModel
+from typing_extensions import override
 
 from langchain.chains.llm import LLMChain
 from langchain.memory.chat_memory import BaseChatMemory
@@ -133,6 +134,7 @@ class ConversationSummaryMemory(BaseChatMemory, SummarizerMixin):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return history buffer."""
         if self.return_messages:

libs/langchain/langchain/memory/summary_buffer.py

@@ -3,6 +3,7 @@ from typing import Any, Union
 from langchain_core._api import deprecated
 from langchain_core.messages import BaseMessage, get_buffer_string
 from langchain_core.utils import pre_init
+from typing_extensions import override
 
 from langchain.memory.chat_memory import BaseChatMemory
 from langchain.memory.summary import SummarizerMixin
@@ -46,6 +47,7 @@ class ConversationSummaryBufferMemory(BaseChatMemory, SummarizerMixin):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return history buffer."""
         buffer = self.chat_memory.messages
@@ -64,6 +66,7 @@ class ConversationSummaryBufferMemory(BaseChatMemory, SummarizerMixin):
             )
         return {self.memory_key: final_buffer}
 
+    @override
     async def aload_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Asynchronously return key-value pairs given the text input to the chain."""
         buffer = await self.chat_memory.aget_messages()

libs/langchain/langchain/memory/token_buffer.py

@@ -3,6 +3,7 @@ from typing import Any
 from langchain_core._api import deprecated
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.messages import BaseMessage, get_buffer_string
+from typing_extensions import override
 
 from langchain.memory.chat_memory import BaseChatMemory
 
@@ -55,6 +56,7 @@ class ConversationTokenBufferMemory(BaseChatMemory):
         """
         return [self.memory_key]
 
+    @override
     def load_memory_variables(self, inputs: dict[str, Any]) -> dict[str, Any]:
         """Return history buffer."""
         return {self.memory_key: self.buffer}

libs/langchain/langchain/retrievers/document_compressors/chain_extract.py

@@ -110,7 +110,7 @@ class LLMChainExtractor(BaseDocumentCompressor):
         llm: BaseLanguageModel,
         prompt: Optional[PromptTemplate] = None,
         get_input: Optional[Callable[[str, Document], str]] = None,
-        llm_chain_kwargs: Optional[dict] = None,
+        llm_chain_kwargs: Optional[dict] = None,  # noqa: ARG003
     ) -> LLMChainExtractor:
         """Initialize from LLM."""
         _prompt = prompt if prompt is not None else _get_default_chain_prompt()

libs/langchain/langchain/retrievers/document_compressors/cohere_rerank.py

@@ -9,6 +9,7 @@ from langchain_core.callbacks import Callbacks
 from langchain_core.documents import BaseDocumentCompressor, Document
 from langchain_core.utils import get_from_dict_or_env
 from pydantic import ConfigDict, model_validator
+from typing_extensions import override
 
 
 @deprecated(
@@ -98,6 +99,7 @@ class CohereRerank(BaseDocumentCompressor):
             for res in results
         ]
 
+    @override
     def compress_documents(
         self,
         documents: Sequence[Document],

libs/langchain/langchain/retrievers/document_compressors/cross_encoder_rerank.py

@@ -7,6 +7,7 @@ from typing import Optional
 from langchain_core.callbacks import Callbacks
 from langchain_core.documents import BaseDocumentCompressor, Document
 from pydantic import ConfigDict
+from typing_extensions import override
 
 from langchain.retrievers.document_compressors.cross_encoder import BaseCrossEncoder
 
@@ -25,6 +26,7 @@ class CrossEncoderReranker(BaseDocumentCompressor):
         extra="forbid",
     )
 
+    @override
     def compress_documents(
         self,
         documents: Sequence[Document],

libs/langchain/langchain/retrievers/document_compressors/embeddings_filter.py

@@ -6,6 +6,7 @@ from langchain_core.documents import BaseDocumentCompressor, Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.utils import pre_init
 from pydantic import ConfigDict, Field
+from typing_extensions import override
 
 
 def _get_similarity_function() -> Callable:
@@ -50,6 +51,7 @@ class EmbeddingsFilter(BaseDocumentCompressor):
             raise ValueError(msg)
         return values
 
+    @override
     def compress_documents(
         self,
         documents: Sequence[Document],
@@ -93,6 +95,7 @@ class EmbeddingsFilter(BaseDocumentCompressor):
             stateful_documents[i].state["query_similarity_score"] = similarity[i]
         return [stateful_documents[i] for i in included_idxs]
 
+    @override
     async def acompress_documents(
         self,
         documents: Sequence[Document],

libs/langchain/langchain/retrievers/multi_query.py

@@ -67,7 +67,7 @@ class MultiQueryRetriever(BaseRetriever):
         retriever: BaseRetriever,
         llm: BaseLanguageModel,
         prompt: BasePromptTemplate = DEFAULT_QUERY_PROMPT,
-        parser_key: Optional[str] = None,
+        parser_key: Optional[str] = None,  # noqa: ARG003
         include_original: bool = False,  # noqa: FBT001,FBT002
     ) -> "MultiQueryRetriever":
         """Initialize from llm using default template.

libs/langchain/langchain/retrievers/multi_vector.py

@@ -10,6 +10,7 @@ from langchain_core.retrievers import BaseRetriever
 from langchain_core.stores import BaseStore, ByteStore
 from langchain_core.vectorstores import VectorStore
 from pydantic import Field, model_validator
+from typing_extensions import override
 
 from langchain.storage._lc_store import create_kv_docstore
 
@@ -54,6 +55,7 @@ class MultiVectorRetriever(BaseRetriever):
         values["docstore"] = docstore
         return values
 
+    @override
     def _get_relevant_documents(
         self,
         query: str,
@@ -91,6 +93,7 @@ class MultiVectorRetriever(BaseRetriever):
         docs = self.docstore.mget(ids)
         return [d for d in docs if d is not None]
 
+    @override
     async def _aget_relevant_documents(
         self,
         query: str,

libs/langchain/langchain/retrievers/time_weighted_retriever.py

@@ -10,6 +10,7 @@ from langchain_core.documents import Document
 from langchain_core.retrievers import BaseRetriever
 from langchain_core.vectorstores import VectorStore
 from pydantic import ConfigDict, Field
+from typing_extensions import override
 
 
 def _get_hours_passed(time: datetime.datetime, ref_time: datetime.datetime) -> float:
@@ -128,6 +129,7 @@ class TimeWeightedVectorStoreRetriever(BaseRetriever):
             result.append(buffered_doc)
         return result
 
+    @override
     def _get_relevant_documents(
         self,
         query: str,
@@ -142,6 +144,7 @@ class TimeWeightedVectorStoreRetriever(BaseRetriever):
         docs_and_scores.update(self.get_salient_docs(query))
         return self._get_rescored_docs(docs_and_scores)
 
+    @override
     async def _aget_relevant_documents(
         self,
         query: str,

libs/langchain/langchain/smith/evaluation/progress.py

@@ -19,7 +19,6 @@ class ProgressBarCallback(base_callbacks.BaseCallbackHandler):
         total: int,
         ncols: int = 50,
         end_with: str = "\n",
-        **kwargs: Any,
     ):
         """Initialize the progress bar.
 

libs/langchain/langchain/smith/evaluation/string_run_evaluator.py

@@ -355,6 +355,7 @@ class StringRunEvaluatorChain(Chain, RunEvaluator):
             feedback.evaluator_info[RUN_KEY] = output[RUN_KEY]
         return feedback
 
+    @override
     def evaluate_run(
         self,
         run: Run,
@@ -372,6 +373,7 @@ class StringRunEvaluatorChain(Chain, RunEvaluator):
                 # TODO: Add run ID once we can declare it via callbacks
             )
 
+    @override
     async def aevaluate_run(
         self,
         run: Run,

libs/langchain/langchain/tools/python/__init__.py

@@ -1,7 +1,7 @@
 from typing import Any
 
 
-def __getattr__(name: str = "") -> Any:
+def __getattr__(_: str = "") -> Any:
     msg = (
         "This tool has been moved to langchain experiment. "
         "This tool has access to a python REPL. "

libs/langchain/pyproject.toml

@@ -145,6 +145,7 @@ ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy
 [tool.ruff.lint]
 select = [
     "A",      # flake8-builtins
+    "ARG",    # flake8-unused-arguments
     "ASYNC",  # flake8-async
     "B",      # flake8-bugbear
     "C4",     # flake8-comprehensions

libs/langchain/tests/integration_tests/cache/fake_embeddings.py

@@ -3,6 +3,7 @@
 import math
 
 from langchain_core.embeddings import Embeddings
+from typing_extensions import override
 
 fake_texts = ["foo", "bar", "baz"]
 
@@ -18,6 +19,7 @@ class FakeEmbeddings(Embeddings):
     async def aembed_documents(self, texts: list[str]) -> list[list[float]]:
         return self.embed_documents(texts)
 
+    @override
     def embed_query(self, text: str) -> list[float]:
         """Return constant query embeddings.
         Embeddings are identical to embed_documents(texts)[0].

libs/langchain/tests/unit_tests/agents/test_agent.py

@@ -25,6 +25,7 @@ from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.runnables.utils import add
 from langchain_core.tools import Tool, tool
 from langchain_core.tracers import RunLog, RunLogPatch
+from typing_extensions import override
 
 from langchain.agents import (
     AgentExecutor,
@@ -48,6 +49,7 @@ class FakeListLLM(LLM):
     responses: list[str]
     i: int = -1
 
+    @override
     def _call(
         self,
         prompt: str,
@@ -462,7 +464,7 @@ async def test_runnable_agent() -> None:
         ],
     )
 
-    def fake_parse(inputs: dict) -> Union[AgentFinish, AgentAction]:
+    def fake_parse(_: dict) -> Union[AgentFinish, AgentAction]:
         """A parser."""
         return AgentFinish(return_values={"foo": "meow"}, log="hard-coded-message")
 
@@ -569,7 +571,7 @@ async def test_runnable_agent_with_function_calls() -> None:
         ],
     )
 
-    def fake_parse(inputs: dict) -> Union[AgentFinish, AgentAction]:
+    def fake_parse(_: dict) -> Union[AgentFinish, AgentAction]:
         """A parser."""
         return cast("Union[AgentFinish, AgentAction]", next(parser_responses))
 
@@ -681,7 +683,7 @@ async def test_runnable_with_multi_action_per_step() -> None:
         ],
     )
 
-    def fake_parse(inputs: dict) -> Union[AgentFinish, AgentAction]:
+    def fake_parse(_: dict) -> Union[AgentFinish, AgentAction]:
         """A parser."""
         return cast("Union[AgentFinish, AgentAction]", next(parser_responses))
 
@@ -1032,7 +1034,7 @@ async def test_openai_agent_tools_agent() -> None:
         ],
     )
 
-    GenericFakeChatModel.bind_tools = lambda self, x: self  # type: ignore[assignment,misc]
+    GenericFakeChatModel.bind_tools = lambda self, _: self  # type: ignore[assignment,misc]
     model = GenericFakeChatModel(messages=infinite_cycle)
 
     @tool

libs/langchain/tests/unit_tests/agents/test_agent_async.py

@@ -8,6 +8,7 @@ from langchain_core.language_models.llms import LLM
 from langchain_core.messages import AIMessage, HumanMessage
 from langchain_core.runnables.utils import add
 from langchain_core.tools import Tool
+from typing_extensions import override
 
 from langchain.agents import AgentExecutor, AgentType, initialize_agent
 from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
@@ -19,6 +20,7 @@ class FakeListLLM(LLM):
     responses: list[str]
     i: int = -1
 
+    @override
     def _call(
         self,
         prompt: str,

libs/langchain/tests/unit_tests/agents/test_agent_iterator.py

@@ -364,7 +364,7 @@ def test_agent_iterator_failing_tool() -> None:
     tools = [
         Tool(
             name="FailingTool",
-            func=lambda x: 1 / 0,  # This tool will raise a ZeroDivisionError
+            func=lambda _: 1 / 0,  # This tool will raise a ZeroDivisionError
             description="A tool that fails",
         ),
     ]

libs/langchain/tests/unit_tests/agents/test_initialize.py

@@ -8,7 +8,7 @@ from tests.unit_tests.llms.fake_llm import FakeLLM
 
 
 @tool
-def my_tool(query: str) -> str:
+def my_tool(query: str) -> str:  # noqa: ARG001
     """A fake tool."""
     return "fake tool"
 

libs/langchain/tests/unit_tests/agents/test_mrkl.py

@@ -141,11 +141,11 @@ def test_valid_action_and_answer_raises_exception() -> None:
 def test_from_chains() -> None:
     """Test initializing from chains."""
     chain_configs = [
-        Tool(name="foo", func=lambda x: "foo", description="foobar1"),
+        Tool(name="foo", func=lambda _x: "foo", description="foobar1"),
-        Tool(name="bar", func=lambda x: "bar", description="foobar2"),
+        Tool(name="bar", func=lambda _x: "bar", description="foobar2"),
     ]
     agent = ZeroShotAgent.from_llm_and_tools(FakeLLM(), chain_configs)
-    expected_tools_prompt = "foo(x) - foobar1\nbar(x) - foobar2"
+    expected_tools_prompt = "foo(_x) - foobar1\nbar(_x) - foobar2"
     expected_tool_names = "foo, bar"
     expected_template = "\n\n".join(
         [

libs/langchain/tests/unit_tests/agents/test_openai_assistant.py

@@ -7,7 +7,7 @@ import pytest
 from langchain.agents.openai_assistant import OpenAIAssistantRunnable
 
 
-def _create_mock_client(*args: Any, use_async: bool = False, **kwargs: Any) -> Any:
+def _create_mock_client(*_: Any, use_async: bool = False, **__: Any) -> Any:
     client = AsyncMock() if use_async else MagicMock()
     mock_assistant = MagicMock()
     mock_assistant.id = "abc123"

libs/langchain/tests/unit_tests/callbacks/fake_callback_handler.py

@@ -7,6 +7,7 @@ from uuid import UUID
 from langchain_core.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler
 from langchain_core.messages import BaseMessage
 from pydantic import BaseModel
+from typing_extensions import override
 
 
 class BaseFakeCallbackHandler(BaseModel):
@@ -135,6 +136,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
         """Whether to ignore retriever callbacks."""
         return self.ignore_retriever_
 
+    @override
     def on_llm_start(
         self,
         *args: Any,
@@ -142,6 +144,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_llm_start_common()
 
+    @override
     def on_llm_new_token(
         self,
         *args: Any,
@@ -149,6 +152,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_llm_new_token_common()
 
+    @override
     def on_llm_end(
         self,
         *args: Any,
@@ -156,6 +160,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_llm_end_common()
 
+    @override
     def on_llm_error(
         self,
         *args: Any,
@@ -163,6 +168,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_llm_error_common()
 
+    @override
     def on_retry(
         self,
         *args: Any,
@@ -170,6 +176,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_retry_common()
 
+    @override
     def on_chain_start(
         self,
         *args: Any,
@@ -177,6 +184,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_chain_start_common()
 
+    @override
     def on_chain_end(
         self,
         *args: Any,
@@ -184,6 +192,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_chain_end_common()
 
+    @override
     def on_chain_error(
         self,
         *args: Any,
@@ -191,6 +200,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_chain_error_common()
 
+    @override
     def on_tool_start(
         self,
         *args: Any,
@@ -198,6 +208,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_tool_start_common()
 
+    @override
     def on_tool_end(
         self,
         *args: Any,
@@ -205,6 +216,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_tool_end_common()
 
+    @override
     def on_tool_error(
         self,
         *args: Any,
@@ -212,6 +224,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_tool_error_common()
 
+    @override
     def on_agent_action(
         self,
         *args: Any,
@@ -219,6 +232,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_agent_action_common()
 
+    @override
     def on_agent_finish(
         self,
         *args: Any,
@@ -226,6 +240,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_agent_finish_common()
 
+    @override
     def on_text(
         self,
         *args: Any,
@@ -233,6 +248,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_text_common()
 
+    @override
     def on_retriever_start(
         self,
         *args: Any,
@@ -240,6 +256,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_retriever_start_common()
 
+    @override
     def on_retriever_end(
         self,
         *args: Any,
@@ -247,6 +264,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
     ) -> Any:
         self.on_retriever_end_common()
 
+    @override
     def on_retriever_error(
         self,
         *args: Any,
@@ -259,6 +277,7 @@ class FakeCallbackHandler(BaseCallbackHandler, BaseFakeCallbackHandlerMixin):
 
 
 class FakeCallbackHandlerWithChatStart(FakeCallbackHandler):
+    @override
     def on_chat_model_start(
         self,
         serialized: dict[str, Any],
@@ -290,6 +309,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
         """Whether to ignore agent callbacks."""
         return self.ignore_agent_
 
+    @override
     async def on_retry(
         self,
         *args: Any,
@@ -297,6 +317,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> Any:
         self.on_retry_common()
 
+    @override
     async def on_llm_start(
         self,
         *args: Any,
@@ -304,6 +325,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_llm_start_common()
 
+    @override
     async def on_llm_new_token(
         self,
         *args: Any,
@@ -311,6 +333,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_llm_new_token_common()
 
+    @override
     async def on_llm_end(
         self,
         *args: Any,
@@ -318,6 +341,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_llm_end_common()
 
+    @override
     async def on_llm_error(
         self,
         *args: Any,
@@ -325,6 +349,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_llm_error_common()
 
+    @override
     async def on_chain_start(
         self,
         *args: Any,
@@ -332,6 +357,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_chain_start_common()
 
+    @override
     async def on_chain_end(
         self,
         *args: Any,
@@ -339,6 +365,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_chain_end_common()
 
+    @override
     async def on_chain_error(
         self,
         *args: Any,
@@ -346,6 +373,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_chain_error_common()
 
+    @override
     async def on_tool_start(
         self,
         *args: Any,
@@ -353,6 +381,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_tool_start_common()
 
+    @override
     async def on_tool_end(
         self,
         *args: Any,
@@ -360,6 +389,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_tool_end_common()
 
+    @override
     async def on_tool_error(
         self,
         *args: Any,
@@ -367,6 +397,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_tool_error_common()
 
+    @override
     async def on_agent_action(
         self,
         *args: Any,
@@ -374,6 +405,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_agent_action_common()
 
+    @override
     async def on_agent_finish(
         self,
         *args: Any,
@@ -381,6 +413,7 @@ class FakeAsyncCallbackHandler(AsyncCallbackHandler, BaseFakeCallbackHandlerMixi
     ) -> None:
         self.on_agent_finish_common()
 
+    @override
     async def on_text(
         self,
         *args: Any,

libs/langchain/tests/unit_tests/callbacks/test_file.py

@@ -3,6 +3,7 @@ import re
 from typing import Optional
 
 from langchain_core.callbacks import CallbackManagerForChainRun
+from typing_extensions import override
 
 from langchain.callbacks import FileCallbackHandler
 from langchain.chains.base import Chain
@@ -25,6 +26,7 @@ class FakeChain(Chain):
         """Output key of bar."""
         return self.the_output_keys
 
+    @override
     def _call(
         self,
         inputs: dict[str, str],

libs/langchain/tests/unit_tests/callbacks/test_stdout.py

@@ -2,6 +2,7 @@ from typing import Any, Optional
 
 import pytest
 from langchain_core.callbacks import CallbackManagerForChainRun
+from typing_extensions import override
 
 from langchain.callbacks import StdOutCallbackHandler
 from langchain.chains.base import Chain
@@ -24,6 +25,7 @@ class FakeChain(Chain):
         """Output key of bar."""
         return self.the_output_keys
 
+    @override
     def _call(
         self,
         inputs: dict[str, str],

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

@@ -7,6 +7,7 @@ import pytest
 from langchain_core.callbacks.manager import CallbackManagerForChainRun
 from langchain_core.memory import BaseMemory
 from langchain_core.tracers.context import collect_runs
+from typing_extensions import override
 
 from langchain.chains.base import Chain
 from langchain.schema import RUN_KEY
@@ -21,6 +22,7 @@ class FakeMemory(BaseMemory):
         """Return baz variable."""
         return ["baz"]
 
+    @override
     def load_memory_variables(
         self,
         inputs: Optional[dict[str, Any]] = None,
@@ -52,6 +54,7 @@ class FakeChain(Chain):
         """Output key of bar."""
         return self.the_output_keys
 
+    @override
     def _call(
         self,
         inputs: dict[str, str],

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

@@ -19,7 +19,7 @@ def _fake_docs_len_func(docs: list[Document]) -> int:
     return len(_fake_combine_docs_func(docs))
 
 
-def _fake_combine_docs_func(docs: list[Document], **kwargs: Any) -> str:
+def _fake_combine_docs_func(docs: list[Document], **_: Any) -> str:
     return "".join([d.page_content for d in docs])
 
 

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

@@ -8,6 +8,7 @@ from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import LLM
 from langchain_core.memory import BaseMemory
 from langchain_core.prompts.prompt import PromptTemplate
+from typing_extensions import override
 
 from langchain.chains.conversation.base import ConversationChain
 from langchain.memory.buffer import ConversationBufferMemory
@@ -26,6 +27,7 @@ class DummyLLM(LLM):
     def _llm_type(self) -> str:
         return "dummy"
 
+    @override
     def _call(
         self,
         prompt: str,

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

@@ -10,6 +10,7 @@ from langchain_core.callbacks.manager import (
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, LLMResult
+from typing_extensions import override
 
 from langchain.chains.hyde.base import HypotheticalDocumentEmbedder
 from langchain.chains.hyde.prompts import PROMPT_MAP
@@ -18,10 +19,12 @@ from langchain.chains.hyde.prompts import PROMPT_MAP
 class FakeEmbeddings(Embeddings):
     """Fake embedding class for tests."""
 
+    @override
     def embed_documents(self, texts: list[str]) -> list[list[float]]:
         """Return random floats."""
         return [list(np.random.uniform(0, 1, 10)) for _ in range(10)]
 
+    @override
     def embed_query(self, text: str) -> list[float]:
         """Return random floats."""
         return list(np.random.uniform(0, 1, 10))
@@ -32,6 +35,7 @@ class FakeLLM(BaseLLM):
 
     n: int = 1
 
+    @override
     def _generate(
         self,
         prompts: list[str],
@@ -41,6 +45,7 @@ class FakeLLM(BaseLLM):
     ) -> LLMResult:
         return LLMResult(generations=[[Generation(text="foo") for _ in range(self.n)]])
 
+    @override
     async def _agenerate(
         self,
         prompts: list[str],

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

@@ -8,6 +8,7 @@ from langchain_core.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
 )
+from typing_extensions import override
 
 from langchain.chains.base import Chain
 from langchain.chains.sequential import SequentialChain, SimpleSequentialChain
@@ -32,6 +33,7 @@ class FakeChain(Chain):
         """Input keys this chain returns."""
         return self.output_variables
 
+    @override
     def _call(
         self,
         inputs: dict[str, str],
@@ -43,6 +45,7 @@ class FakeChain(Chain):
             outputs[var] = f"{' '.join(variables)}foo"
         return outputs
 
+    @override
     async def _acall(
         self,
         inputs: dict[str, str],

libs/langchain/tests/unit_tests/document_loaders/test_base.py

@@ -4,6 +4,7 @@ from collections.abc import Iterator
 
 from langchain_core.document_loaders import BaseBlobParser, Blob
 from langchain_core.documents import Document
+from typing_extensions import override
 
 
 def test_base_blob_parser() -> None:
@@ -12,6 +13,7 @@ def test_base_blob_parser() -> None:
     class MyParser(BaseBlobParser):
         """A simple parser that returns a single document."""
 
+        @override
         def lazy_parse(self, blob: Blob) -> Iterator[Document]:
             """Lazy parsing interface."""
             yield Document(

libs/langchain/tests/unit_tests/embeddings/test_caching.py

@@ -7,12 +7,14 @@ import warnings
 
 import pytest
 from langchain_core.embeddings import Embeddings
+from typing_extensions import override
 
 from langchain.embeddings import CacheBackedEmbeddings
 from langchain.storage.in_memory import InMemoryStore
 
 
 class MockEmbeddings(Embeddings):
+    @override
     def embed_documents(self, texts: list[str]) -> list[list[float]]:
         # Simulate embedding documents
         embeddings: list[list[float]] = []
@@ -23,6 +25,7 @@ class MockEmbeddings(Embeddings):
             embeddings.append([len(text), len(text) + 1])
         return embeddings
 
+    @override
     def embed_query(self, text: str) -> list[float]:
         # Simulate embedding a query
         return [5.0, 6.0]

libs/langchain/tests/unit_tests/evaluation/agents/test_eval_chain.py

@@ -9,6 +9,7 @@ from langchain_core.exceptions import OutputParserException
 from langchain_core.messages import BaseMessage
 from langchain_core.tools import tool
 from pydantic import Field
+from typing_extensions import override
 
 from langchain.evaluation.agents.trajectory_eval_chain import (
     TrajectoryEval,
@@ -43,6 +44,7 @@ class _FakeTrajectoryChatModel(FakeChatModel):
     sequential_responses: Optional[bool] = False
     response_index: int = 0
 
+    @override
     def _call(
         self,
         messages: list[BaseMessage],

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

@@ -13,6 +13,7 @@ from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.indexing.api import _abatch, _get_document_with_hash
 from langchain_core.vectorstores import VST, VectorStore
+from typing_extensions import override
 
 from langchain.indexes import aindex, index
 from langchain.indexes._sql_record_manager import SQLRecordManager
@@ -45,18 +46,21 @@ class InMemoryVectorStore(VectorStore):
         self.store: dict[str, Document] = {}
         self.permit_upserts = permit_upserts
 
+    @override
     def delete(self, ids: Optional[Sequence[str]] = None, **kwargs: Any) -> None:
         """Delete the given documents from the store using their IDs."""
         if ids:
             for _id in ids:
                 self.store.pop(_id, None)
 
+    @override
     async def adelete(self, ids: Optional[Sequence[str]] = None, **kwargs: Any) -> None:
         """Delete the given documents from the store using their IDs."""
         if ids:
             for _id in ids:
                 self.store.pop(_id, None)
 
+    @override
     def add_documents(
         self,
         documents: Sequence[Document],
@@ -81,6 +85,7 @@ class InMemoryVectorStore(VectorStore):
 
         return list(ids)
 
+    @override
     async def aadd_documents(
         self,
         documents: Sequence[Document],

libs/langchain/tests/unit_tests/llms/fake_chat_model.py

@@ -16,11 +16,13 @@ from langchain_core.messages import (
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.runnables import run_in_executor
+from typing_extensions import override
 
 
 class FakeChatModel(SimpleChatModel):
     """Fake Chat Model wrapper for testing purposes."""
 
+    @override
     def _call(
         self,
         messages: list[BaseMessage],
@@ -30,6 +32,7 @@ class FakeChatModel(SimpleChatModel):
     ) -> str:
         return "fake response"
 
+    @override
     async def _agenerate(
         self,
         messages: list[BaseMessage],
@@ -74,6 +77,7 @@ class GenericFakeChatModel(BaseChatModel):
     into message chunks.
     """
 
+    @override
     def _generate(
         self,
         messages: list[BaseMessage],

libs/langchain/tests/unit_tests/llms/fake_llm.py

@@ -6,6 +6,7 @@ from typing import Any, Optional, cast
 from langchain_core.callbacks.manager import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from pydantic import model_validator
+from typing_extensions import override
 
 
 class FakeLLM(LLM):
@@ -32,6 +33,7 @@ class FakeLLM(LLM):
         """Return type of llm."""
         return "fake"
 
+    @override
     def _call(
         self,
         prompt: str,

libs/langchain/tests/unit_tests/llms/test_fake_chat_model.py

@@ -7,6 +7,7 @@ from uuid import UUID
 from langchain_core.callbacks.base import AsyncCallbackHandler
 from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
 from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
+from typing_extensions import override
 
 from tests.unit_tests.llms.fake_chat_model import GenericFakeChatModel
 from tests.unit_tests.stubs import _AnyIdAIMessage, _AnyIdAIMessageChunk
@@ -166,6 +167,7 @@ async def test_callback_handlers() -> None:
             # Required to implement since this is an abstract method
             pass
 
+        @override
         async def on_llm_new_token(
             self,
             token: str,

libs/langchain/tests/unit_tests/output_parsers/test_fix.py

@@ -8,6 +8,7 @@ from langchain_core.messages import AIMessage
 from langchain_core.output_parsers import BaseOutputParser
 from langchain_core.prompts.prompt import PromptTemplate
 from langchain_core.runnables import Runnable, RunnableLambda, RunnablePassthrough
+from typing_extensions import override
 
 from langchain.output_parsers.boolean import BooleanOutputParser
 from langchain.output_parsers.datetime import DatetimeOutputParser
@@ -21,6 +22,7 @@ class SuccessfulParseAfterRetries(BaseOutputParser[str]):
     parse_count: int = 0  # Number of times parse has been called
     attemp_count_before_success: int  # Number of times to fail before succeeding
 
+    @override
     def parse(self, *args: Any, **kwargs: Any) -> str:
         self.parse_count += 1
         if self.parse_count <= self.attemp_count_before_success:
@@ -62,7 +64,7 @@ def test_output_fixing_parser_parse(
 
 
 def test_output_fixing_parser_from_llm() -> None:
-    def fake_llm(prompt: str) -> AIMessage:
+    def fake_llm(_: str) -> AIMessage:
         return AIMessage("2024-07-08T00:00:00.000000Z")
 
     llm = RunnableLambda(fake_llm)

libs/langchain/tests/unit_tests/output_parsers/test_retry.py

@@ -7,6 +7,7 @@ from langchain_core.exceptions import OutputParserException
 from langchain_core.output_parsers import BaseOutputParser
 from langchain_core.prompt_values import PromptValue, StringPromptValue
 from langchain_core.runnables import Runnable, RunnableLambda, RunnablePassthrough
+from typing_extensions import override
 
 from langchain.output_parsers.boolean import BooleanOutputParser
 from langchain.output_parsers.datetime import DatetimeOutputParser
@@ -25,6 +26,7 @@ class SuccessfulParseAfterRetries(BaseOutputParser[str]):
     attemp_count_before_success: int  # Number of times to fail before succeeding
     error_msg: str = "error"
 
+    @override
     def parse(self, *args: Any, **kwargs: Any) -> str:
         self.parse_count += 1
         if self.parse_count <= self.attemp_count_before_success:

libs/langchain/tests/unit_tests/retrievers/self_query/test_base.py

@@ -14,6 +14,7 @@ from langchain_core.structured_query import (
     StructuredQuery,
     Visitor,
 )
+from typing_extensions import override
 
 from langchain.chains.query_constructor.schema import AttributeInfo
 from langchain.retrievers import SelfQueryRetriever
@@ -61,6 +62,7 @@ class FakeTranslator(Visitor):
 
 
 class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
+    @override
     def similarity_search(
         self,
         query: str,

libs/langchain/tests/unit_tests/retrievers/sequential_retriever.py

@@ -1,5 +1,8 @@
+from typing import Any
+
 from langchain_core.documents import Document
 from langchain_core.retrievers import BaseRetriever
+from typing_extensions import override
 
 
 class SequentialRetriever(BaseRetriever):
@@ -8,17 +11,21 @@ class SequentialRetriever(BaseRetriever):
     sequential_responses: list[list[Document]]
     response_index: int = 0
 
-    def _get_relevant_documents(  # type: ignore[override]
+    @override
+    def _get_relevant_documents(
         self,
         query: str,
+        **kwargs: Any,
     ) -> list[Document]:
         if self.response_index >= len(self.sequential_responses):
             return []
         self.response_index += 1
         return self.sequential_responses[self.response_index - 1]
 
-    async def _aget_relevant_documents(  # type: ignore[override]
+    @override
+    async def _aget_relevant_documents(
         self,
         query: str,
+        **kwargs: Any,
     ) -> list[Document]:
         return self._get_relevant_documents(query)

libs/langchain/tests/unit_tests/retrievers/test_ensemble.py

@@ -3,6 +3,7 @@ from typing import Optional
 from langchain_core.callbacks.manager import CallbackManagerForRetrieverRun
 from langchain_core.documents import Document
 from langchain_core.retrievers import BaseRetriever
+from typing_extensions import override
 
 from langchain.retrievers.ensemble import EnsembleRetriever
 
@@ -10,6 +11,7 @@ from langchain.retrievers.ensemble import EnsembleRetriever
 class MockRetriever(BaseRetriever):
     docs: list[Document]
 
+    @override
     def _get_relevant_documents(
         self,
         query: str,

libs/langchain/tests/unit_tests/retrievers/test_multi_vector.py

@@ -1,6 +1,7 @@
 from typing import Any, Callable
 
 from langchain_core.documents import Document
+from typing_extensions import override
 
 from langchain.retrievers.multi_vector import MultiVectorRetriever, SearchType
 from langchain.storage import InMemoryStore
@@ -15,6 +16,7 @@ class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
     def _select_relevance_score_fn(self) -> Callable[[float], float]:
         return self._identity_fn
 
+    @override
     def similarity_search(
         self,
         query: str,
@@ -26,6 +28,7 @@ class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
             return []
         return [res]
 
+    @override
     def similarity_search_with_score(
         self,
         query: str,

libs/langchain/tests/unit_tests/retrievers/test_parent_document.py

@@ -3,6 +3,7 @@ from typing import Any
 
 from langchain_core.documents import Document
 from langchain_text_splitters.character import CharacterTextSplitter
+from typing_extensions import override
 
 from langchain.retrievers import ParentDocumentRetriever
 from langchain.storage import InMemoryStore
@@ -10,6 +11,7 @@ from tests.unit_tests.indexes.test_indexing import InMemoryVectorStore
 
 
 class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
+    @override
     def similarity_search(
         self,
         query: str,
@@ -21,6 +23,7 @@ class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
             return []
         return [res]
 
+    @override
     def add_documents(self, documents: Sequence[Document], **kwargs: Any) -> list[str]:
         print(documents)  # noqa: T201
         return super().add_documents(

libs/langchain/tests/unit_tests/retrievers/test_time_weighted_retriever.py

@@ -8,6 +8,7 @@ import pytest
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.vectorstores import VectorStore
+from typing_extensions import override
 
 from langchain.retrievers.time_weighted_retriever import (
     TimeWeightedVectorStoreRetriever,
@@ -31,6 +32,7 @@ def _get_example_memories(k: int = 4) -> list[Document]:
 class MockVectorStore(VectorStore):
     """Mock invalid vector store."""
 
+    @override
     def add_texts(
         self,
         texts: Iterable[str],
@@ -39,6 +41,7 @@ class MockVectorStore(VectorStore):
     ) -> list[str]:
         return list(texts)
 
+    @override
     def similarity_search(
         self,
         query: str,
@@ -48,6 +51,7 @@ class MockVectorStore(VectorStore):
         return []
 
     @classmethod
+    @override
     def from_texts(
         cls: type["MockVectorStore"],
         texts: list[str],
@@ -57,6 +61,7 @@ class MockVectorStore(VectorStore):
     ) -> "MockVectorStore":
         return cls()
 
+    @override
     def _similarity_search_with_relevance_scores(
         self,
         query: str,

libs/langchain/tests/unit_tests/runnables/test_hub.py

@@ -38,7 +38,7 @@ repo_dict = {
 }
 
 
-def repo_lookup(owner_repo_commit: str, **kwargs: Any) -> ChatPromptTemplate:
+def repo_lookup(owner_repo_commit: str, **_: Any) -> ChatPromptTemplate:
     return repo_dict[owner_repo_commit]
 
 

libs/langchain/tests/unit_tests/runnables/test_openai_functions.py

@@ -6,6 +6,7 @@ from langchain_core.messages import AIMessage, BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatResult
 from pytest_mock import MockerFixture
 from syrupy.assertion import SnapshotAssertion
+from typing_extensions import override
 
 from langchain.runnables.openai_functions import OpenAIFunctionsRouter
 
@@ -15,6 +16,7 @@ class FakeChatOpenAI(BaseChatModel):
     def _llm_type(self) -> str:
         return "fake-openai-chat-model"
 
+    @override
     def _generate(
         self,
         messages: list[BaseMessage],

libs/langchain/tests/unit_tests/smith/evaluation/test_runner_utils.py

@@ -3,16 +3,14 @@
 import uuid
 from collections.abc import Iterator
 from datetime import datetime, timezone
-from typing import Any, Optional, Union
+from typing import Any
 from unittest import mock
 
 import pytest
 from freezegun import freeze_time
-from langchain_core.language_models import BaseLanguageModel
 from langsmith.client import Client
 from langsmith.schemas import Dataset, Example
 
-from langchain.chains.base import Chain
 from langchain.chains.transform import TransformChain
 from langchain.smith.evaluation.runner_utils import (
     InputFormatError,
@@ -243,7 +241,7 @@ def test_run_chat_model_all_formats(inputs: dict[str, Any]) -> None:
 
 
 @freeze_time("2023-01-01")
-async def test_arun_on_dataset(monkeypatch: pytest.MonkeyPatch) -> None:
+async def test_arun_on_dataset() -> None:
     dataset = Dataset(
         id=uuid.uuid4(),
         name="test",
@@ -298,22 +296,20 @@ async def test_arun_on_dataset(monkeypatch: pytest.MonkeyPatch) -> None:
         ),
     ]
 
-    def mock_read_dataset(*args: Any, **kwargs: Any) -> Dataset:
+    def mock_read_dataset(*_: Any, **__: Any) -> Dataset:
         return dataset
 
-    def mock_list_examples(*args: Any, **kwargs: Any) -> Iterator[Example]:
+    def mock_list_examples(*_: Any, **__: Any) -> Iterator[Example]:
         return iter(examples)
 
     async def mock_arun_chain(
         example: Example,
-        llm_or_chain: Union[BaseLanguageModel, Chain],
+        *_: Any,
-        tags: Optional[list[str]] = None,
+        **__: Any,
-        callbacks: Optional[Any] = None,
-        **kwargs: Any,
     ) -> dict[str, Any]:
         return {"result": f"Result for example {example.id}"}
 
-    def mock_create_project(*args: Any, **kwargs: Any) -> Any:
+    def mock_create_project(*_: Any, **__: Any) -> Any:
         proj = mock.MagicMock()
         proj.id = "123"
         return proj

libs/langchain/tests/unit_tests/tools/test_render.py

@@ -8,13 +8,13 @@ from langchain.tools.render import (
 
 
 @tool
-def search(query: str) -> str:
+def search(query: str) -> str:  # noqa: ARG001
     """Lookup things online."""
     return "foo"
 
 
 @tool
-def calculator(expression: str) -> str:
+def calculator(expression: str) -> str:  # noqa: ARG001
     """Do math."""
     return "bar"