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

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

Co-authored-by: Mason Daugherty <[email protected]>

Author: cbornet

libs/langchain/langchain/agents/agent.py

@@ -116,16 +116,15 @@ def input_keys(self) -> list[str]:
     def return_stopped_response(
         self,
         early_stopping_method: str,
-        intermediate_steps: list[tuple[AgentAction, str]],
-        **kwargs: Any,
+        intermediate_steps: list[tuple[AgentAction, str]],  # noqa: ARG002
+        **_: Any,
     ) -> AgentFinish:
         """Return response when agent has been stopped due to max iterations.
 
         Args:
             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 @@ def _agent_type(self) -> str:
         """Return Identifier of an agent type."""
         raise NotImplementedError
 
+    @override
     def dict(self, **kwargs: Any) -> builtins.dict:
         """Return dictionary representation of agent.
 
@@ -289,16 +289,15 @@ def input_keys(self) -> list[str]:
     def return_stopped_response(
         self,
         early_stopping_method: str,
-        intermediate_steps: list[tuple[AgentAction, str]],
-        **kwargs: Any,
+        intermediate_steps: list[tuple[AgentAction, str]],  # noqa: ARG002
+        **_: Any,
     ) -> AgentFinish:
         """Return response when agent has been stopped due to max iterations.
 
         Args:
             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 @@ def _agent_type(self) -> str:
         """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 @@ def input_keys(self) -> list[str]:
         """
         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 @@ def return_values(self) -> list[str]:
         """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 [
@@ -1021,13 +1011,15 @@ class ExceptionTool(BaseTool):
     description: str = "Exception tool"
     """Description of the tool."""
 
+    @override
     def _run(
         self,
         query: str,
         run_manager: Optional[CallbackManagerForToolRun] = None,
     ) -> str:
         return query
 
+    @override
     async def _arun(
         self,
         query: str,
@@ -1188,6 +1180,7 @@ def _action_agent(self) -> Union[BaseSingleActionAgent, BaseMultiActionAgent]:
             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 @@ def iter(
         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.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 @@ def _construct_scratchpad(
         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.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.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.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 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 @@ def memory_variables(self) -> list[str]:
         """
         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.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 @@ def _agent_type(self) -> str:
         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.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 @@ def _agent_type(self) -> str:
         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 @@ def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
         pass
 
     @classmethod
+    @override
     def _get_default_output_parser(
         cls,
         llm: Optional[BaseLanguageModel] = None,

libs/langchain/langchain/agents/tools.py

@@ -7,6 +7,7 @@
     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 @@ def _run(
             f"try one of [{available_tool_names_str}]."
         )
 
+    @override
     async def _arun(
         self,
         requested_tool_name: str,