docs: relocate init args to __init__

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -1,3 +1,3 @@
 """Tool execution node for LangGraph workflows.
 
 This module provides prebuilt functionality for executing tools in LangGraph.
@@ -249,29 +249,6 @@
 
     Tool calls can also be passed directly as a list of `ToolCall` dicts.
 
-    Args:
-        tools: A sequence of tools that can be invoked by this node. Tools can be
-            BaseTool instances or plain functions that will be converted to tools.
-        name: The name identifier for this node in the graph. Used for debugging
-            and visualization. Defaults to "tools".
-        tags: Optional metadata tags to associate with the node for filtering
-            and organization. Defaults to None.
-        handle_tool_errors: Configuration for error handling during tool execution.
-            Defaults to True. Supports multiple strategies:
-
-            - True: Catch all errors and return a ToolMessage with the default
-              error template containing the exception details.
-            - str: Catch all errors and return a ToolMessage with this custom
-              error message string.
-            - tuple[type[Exception], ...]: Only catch exceptions of the specified
-              types and return default error messages for them.
-            - Callable[..., str]: Catch exceptions matching the callable's signature
-              and return the string result of calling it with the exception.
-            - False: Disable error handling entirely, allowing exceptions to propagate.
-
-        messages_key: The key in the state dictionary that contains the message list.
-            This same key will be used for the output ToolMessages. Defaults to "messages".
-
     Example:
         Basic usage with simple tools:
 
@@ -334,11 +311,26 @@
         """Initialize the ToolNode with the provided tools and configuration.
 
         Args:
-            tools: Sequence of tools to make available for execution.
-            name: Node name for graph identification.
-            tags: Optional metadata tags.
-            handle_tool_errors: Error handling configuration.
-            messages_key: State key containing messages.
+            tools: A sequence of tools that can be invoked by this node. Tools can be
+                BaseTool instances or plain functions that will be converted to tools.
+            name: The name identifier for this node in the graph. Used for debugging
+                and visualization. Defaults to "tools".
+            tags: Optional metadata tags to associate with the node for filtering
+                and organization. Defaults to None.
+            handle_tool_errors: Configuration for error handling during tool execution.
+                Defaults to True. Supports multiple strategies:
+
+                - True: Catch all errors and return a ToolMessage with the default
+                    error template containing the exception details.
+                - str: Catch all errors and return a ToolMessage with this custom
+                    error message string.
+                - tuple[type[Exception], ...]: Only catch exceptions of the specified
+                    types and return default error messages for them.
+                - Callable[..., str]: Catch exceptions matching the callable's signature
+                    and return the string result of calling it with the exception.
+                - False: Disable error handling entirely, allowing exceptions to propagate.
+            messages_key: The key in the state dictionary that contains the message list.
+                This same key will be used for the output ToolMessages. Defaults to "messages".
         """
         super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
         self.tools_by_name: dict[str, BaseTool] = {}
@@ -867,12 +859,6 @@
     receive state data automatically during execution while remaining invisible
     to the model's tool-calling interface.
 
-    Args:
-        field: Optional key to extract from the state dictionary. If None, the entire
-            state is injected. If specified, only that field's value is injected.
-            This allows tools to request specific state components rather than
-            processing the full state structure.
-
     Example:
         ```python
         from typing import List
@@ -930,6 +916,14 @@
     """  # noqa: E501
 
     def __init__(self, field: Optional[str] = None) -> None:
+        """Initialize InjectedState annotation.
+
+        Args:
+            field: Optional key to extract from the state dictionary. If None, the entire
+                state is injected. If specified, only that field's value is injected.
+                This allows tools to request specific state components rather than
+                processing the full state structure.
+        """
         self.field = field
 
 

libs/prebuilt/langgraph/prebuilt/tool_validator.py

@@ -62,18 +62,6 @@ class ValidationNode(RunnableCallable):
         structured output that conforms to a complex schema without losing the original
         messages and tool IDs (for use in multi-turn conversations).
 
-    Args:
-        schemas: A list of schemas to validate the tool calls with. These can be
-            any of the following:
-            - A pydantic BaseModel class
-            - A BaseTool instance (the args_schema will be used)
-            - A function (a schema will be created from the function signature)
-        format_error: A function that takes an exception, a ToolCall, and a schema
-            and returns a formatted error string. By default, it returns the
-            exception repr and a message to respond after fixing validation errors.
-        name: The name of the node.
-        tags: A list of tags to add to the node.
-
     Returns:
         (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of ToolMessages with the validated content or error messages.
 
@@ -140,6 +128,20 @@ def __init__(
         name: str = "validation",
         tags: Optional[list[str]] = None,
     ) -> None:
+        """Initialize the ValidationNode.
+
+        Args:
+            schemas: A list of schemas to validate the tool calls with. These can be
+                any of the following:
+                - A pydantic BaseModel class
+                - A BaseTool instance (the args_schema will be used)
+                - A function (a schema will be created from the function signature)
+            format_error: A function that takes an exception, a ToolCall, and a schema
+                and returns a formatted error string. By default, it returns the
+                exception repr and a message to respond after fixing validation errors.
+            name: The name of the node.
+            tags: A list of tags to add to the node.
+        """
         super().__init__(self._func, None, name=name, tags=tags, trace=False)
         self._format_error = format_error or _default_format_error
         self.schemas_by_name: Dict[str, Type[BaseModel]] = {}