chore(langchain): cleanup langchain_v1 ruff config

Author: cbornet

libs/langchain_v1/langchain/__init__.py

@@ -5,7 +5,7 @@
 __version__ = "1.0.0a6"
 
 
-def __getattr__(name: str) -> Any:  # noqa: ANN401
+def __getattr__(name: str) -> Any:
     """Get an attribute from the package.
 
     TODO: will be removed in a future alpha version.

libs/langchain_v1/langchain/_internal/_prompts.py

@@ -24,7 +24,7 @@
 
 
 def resolve_prompt(
-    prompt: str | None | Callable[[StateT, Runtime[ContextT]], list[MessageLikeRepresentation]],
+    prompt: str | Callable[[StateT, Runtime[ContextT]], list[MessageLikeRepresentation]] | None,
     state: StateT,
     runtime: Runtime[ContextT],
     default_user_content: str,
@@ -86,9 +86,9 @@ def custom_prompt(state, runtime):
 
 async def aresolve_prompt(
     prompt: str
-    | None
     | Callable[[StateT, Runtime[ContextT]], list[MessageLikeRepresentation]]
-    | Callable[[StateT, Runtime[ContextT]], Awaitable[list[MessageLikeRepresentation]]],
+    | Callable[[StateT, Runtime[ContextT]], Awaitable[list[MessageLikeRepresentation]]]
+    | None,
     state: StateT,
     runtime: Runtime[ContextT],
     default_user_content: str,

libs/langchain_v1/langchain/agents/middleware/prompt_caching.py

@@ -16,19 +16,19 @@ class AnthropicPromptCachingMiddleware(AgentMiddleware):
 
     def __init__(
         self,
-        type: Literal["ephemeral"] = "ephemeral",
+        cache_type: Literal["ephemeral"] = "ephemeral",
         ttl: Literal["5m", "1h"] = "5m",
         min_messages_to_cache: int = 0,
     ) -> None:
         """Initialize the middleware with cache control settings.
 
         Args:
-            type: The type of cache to use, only "ephemeral" is supported.
+            cache_type: The type of cache to use, only "ephemeral" is supported.
             ttl: The time to live for the cache, only "5m" and "1h" are supported.
             min_messages_to_cache: The minimum number of messages until the cache is used,
                 default is 0.
         """
-        self.type = type
+        self.cache_type = cache_type
         self.ttl = ttl
         self.min_messages_to_cache = min_messages_to_cache
 
@@ -39,27 +39,27 @@ def modify_model_request(  # type: ignore[override]
         """Modify the model request to add cache control blocks."""
         try:
             from langchain_anthropic import ChatAnthropic
-        except ImportError:
+        except ImportError as e:
             msg = (
                 "AnthropicPromptCachingMiddleware caching middleware only supports "
                 "Anthropic models."
                 "Please install langchain-anthropic."
             )
-            raise ValueError(msg)
+            raise ValueError(msg) from e
 
         if not isinstance(request.model, ChatAnthropic):
             msg = (
                 "AnthropicPromptCachingMiddleware caching middleware only supports "
                 f"Anthropic models, not instances of {type(request.model)}"
             )
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         messages_count = (
             len(request.messages) + 1 if request.system_prompt else len(request.messages)
         )
         if messages_count < self.min_messages_to_cache:
             return request
 
-        request.model_settings["cache_control"] = {"type": self.type, "ttl": self.ttl}
+        request.model_settings["cache_control"] = {"type": self.cache_type, "ttl": self.ttl}
 
         return request

libs/langchain_v1/langchain/agents/middleware/summarization.py

@@ -48,7 +48,7 @@
 <messages>
 Messages to summarize:
 {messages}
-</messages>"""  # noqa: E501
+</messages>"""
 
 SUMMARY_PREFIX = "## Previous conversation summary:"
 
@@ -229,7 +229,7 @@ def _create_summary(self, messages_to_summarize: list[AnyMessage]) -> str:
         try:
             response = self.model.invoke(self.summary_prompt.format(messages=trimmed_messages))
             return cast("str", response.content).strip()
-        except Exception as e:  # noqa: BLE001
+        except Exception as e:
             return f"Error generating summary: {e!s}"
 
     def _trim_messages_for_summary(self, messages: list[AnyMessage]) -> list[AnyMessage]:
@@ -244,5 +244,5 @@ def _trim_messages_for_summary(self, messages: list[AnyMessage]) -> list[AnyMess
                 allow_partial=True,
                 include_system=True,
             )
-        except Exception:  # noqa: BLE001
+        except Exception:
             return messages[-_DEFAULT_FALLBACK_MESSAGE_COUNT:]

libs/langchain_v1/langchain/agents/middleware_agent.py

@@ -72,7 +72,7 @@ def _resolve_schema(schemas: set[type], schema_name: str, omit_flag: str | None
 def _extract_metadata(type_: type) -> list:
     """Extract metadata from a field type, handling Required/NotRequired and Annotated wrappers."""
     # Handle Required[Annotated[...]] or NotRequired[Annotated[...]]
-    if get_origin(type_) in (Required, NotRequired):
+    if get_origin(type_) in {Required, NotRequired}:
         inner_type = get_args(type_)[0]
         if get_origin(inner_type) is Annotated:
             return list(get_args(inner_type)[1:])
@@ -133,7 +133,7 @@ def _handle_structured_output_error(
 ResponseT = TypeVar("ResponseT")
 
 
-def create_agent(  # noqa: PLR0915
+def create_agent(
     *,
     model: str | BaseChatModel,
     tools: Sequence[BaseTool | Callable | dict[str, Any]] | ToolNode | None = None,
@@ -290,8 +290,7 @@ def _handle_model_output(output: AIMessage) -> dict[str, Any]:
 
                     tool_message_content = (
                         response_format.tool_message_content
-                        if response_format.tool_message_content
-                        else f"Returning structured response: {structured_response}"
+                        or f"Returning structured response: {structured_response}"
                     )
 
                     return {
@@ -305,13 +304,13 @@ def _handle_model_output(output: AIMessage) -> dict[str, Any]:
                         ],
                         "response": structured_response,
                     }
-                except Exception as exc:  # noqa: BLE001
+                except Exception as exc:
                     exception = StructuredOutputValidationError(tool_call["name"], exc)
                     should_retry, error_message = _handle_structured_output_error(
                         exception, response_format
                     )
                     if not should_retry:
-                        raise exception
+                        raise exception from exc
 
                     return {
                         "messages": [

libs/langchain_v1/langchain/agents/react_agent.py

@@ -122,9 +122,9 @@ def _get_prompt_runnable(prompt: Prompt | None) -> Runnable:
             lambda state: _get_state_value(state, "messages"), name=PROMPT_RUNNABLE_NAME
         )
     elif isinstance(prompt, str):
-        _system_message: BaseMessage = SystemMessage(content=prompt)
+        system_message: BaseMessage = SystemMessage(content=prompt)
         prompt_runnable = RunnableCallable(
-            lambda state: [_system_message, *_get_state_value(state, "messages")],
+            lambda state: [system_message, *_get_state_value(state, "messages")],
             name=PROMPT_RUNNABLE_NAME,
         )
     elif isinstance(prompt, SystemMessage):
@@ -220,7 +220,7 @@ def __init__(
                 "The `model` parameter should not have pre-bound tools, "
                 "simply pass the model and tools separately."
             )
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         self._setup_tools()
         self._setup_state_schema()
@@ -397,13 +397,13 @@ def _handle_single_structured_output(
                     "structured_response": structured_response,
                 }
             )
-        except Exception as exc:  # noqa: BLE001
+        except Exception as exc:
             exception = StructuredOutputValidationError(tool_call["name"], exc)
 
             should_retry, error_message = self._handle_structured_output_error(exception)
 
             if not should_retry:
-                raise exception
+                raise exception from exc
 
             return Command(
                 update={
@@ -583,7 +583,7 @@ def _are_more_steps_needed(state: StateT, response: BaseMessage) -> bool:
                 remaining_steps is not None  # type: ignore[return-value]
                 and (
                     (remaining_steps < 1 and all_tools_return_direct)
-                    or (remaining_steps < 2 and has_tool_calls)
+                    or (remaining_steps < 2 and has_tool_calls)  # noqa: PLR2004
                 )
             )
 
@@ -1188,7 +1188,7 @@ def check_weather(location: str) -> str:
             response_format = ToolStrategy(
                 schema=response_format,
             )
-    elif isinstance(response_format, tuple) and len(response_format) == 2:
+    elif isinstance(response_format, tuple) and len(response_format) == 2:  # noqa: PLR2004
         msg = "Passing a 2-tuple as response_format is no longer supported. "
         raise ValueError(msg)
 

libs/langchain_v1/langchain/agents/structured_output.py

@@ -217,7 +217,7 @@ def __init__(
 
         def _iter_variants(schema: Any) -> Iterable[Any]:
             """Yield leaf variants from Union and JSON Schema oneOf."""
-            if get_origin(schema) in (UnionType, Union):
+            if get_origin(schema) in {UnionType, Union}:
                 for arg in get_args(schema):
                     yield from _iter_variants(arg)
                 return