diff --git a/.github/workflows/_test.yml b/.github/workflows/_test.yml
index 6fb763003..2dd21aa97 100644
--- a/.github/workflows/_test.yml
+++ b/.github/workflows/_test.yml
@@ -17,7 +17,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.9"
           - "3.10"
           - "3.11"
           - "3.12"
diff --git a/.github/workflows/_test_langgraph.yml b/.github/workflows/_test_langgraph.yml
index df09511e7..f4f66e532 100644
--- a/.github/workflows/_test_langgraph.yml
+++ b/.github/workflows/_test_langgraph.yml
@@ -12,7 +12,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.9"
           - "3.10"
           - "3.11"
           - "3.12"
diff --git a/.github/workflows/uv_lock_ugprade.yml b/.github/workflows/uv_lock_ugprade.yml
index 75d74890c..5d57a1f4d 100644
--- a/.github/workflows/uv_lock_ugprade.yml
+++ b/.github/workflows/uv_lock_ugprade.yml
@@ -22,7 +22,7 @@ jobs:
         uses: astral-sh/setup-uv@v6
         with:
           # use minimum supported Python version
-          python-version: "3.9"
+          python-version: "3.10"
           enable-cache: true
           cache-suffix: "uv-lock-upgrade"
           
diff --git a/libs/prebuilt/langgraph/prebuilt/_internal/_typing.py b/libs/prebuilt/langgraph/prebuilt/_internal/_typing.py
index bf2121d7a..eb3d99e74 100644
--- a/libs/prebuilt/langgraph/prebuilt/_internal/_typing.py
+++ b/libs/prebuilt/langgraph/prebuilt/_internal/_typing.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import Awaitable, Callable, TypeVar, Union
+from collections.abc import Awaitable
+from typing import Callable, TypeVar, Union
 
 from typing_extensions import ParamSpec
 
diff --git a/libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py b/libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py
index 575c0c6a0..cfe7e87dd 100644
--- a/libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py
+++ b/libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py
@@ -1,14 +1,13 @@
 from __future__ import annotations
 
 import inspect
+from collections.abc import Awaitable, Sequence
 from dataclasses import asdict, is_dataclass
 from typing import (
+    Annotated,
     Any,
-    Awaitable,
     Callable,
     Generic,
-    Optional,
-    Sequence,
     Union,
     cast,
     get_type_hints,
@@ -31,7 +30,7 @@ from langchain_core.runnables import (
 )
 from langchain_core.tools import BaseTool
 from pydantic import BaseModel
-from typing_extensions import Annotated, NotRequired, TypedDict, TypeVar
+from typing_extensions import NotRequired, TypedDict, TypeVar
 
 from langgraph._internal._runnable import RunnableCallable, RunnableLike
 from langgraph.errors import ErrorCode, create_error_message
@@ -89,7 +88,7 @@ def _get_state_value(state: StateT, key: str, default: Any = None) -> Any:
     )
 
 
-def _get_prompt_runnable(prompt: Optional[Prompt]) -> Runnable:
+def _get_prompt_runnable(prompt: Prompt | None) -> Runnable:
     prompt_runnable: Runnable
     if prompt is None:
         prompt_runnable = RunnableCallable(
@@ -163,21 +162,19 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
 
     def __init__(
         self,
-        model: Union[
-            str,
-            BaseChatModel,
-            SyncOrAsync[[StateT, Runtime[ContextT]], BaseChatModel],
-        ],
-        tools: Union[Sequence[Union[BaseTool, Callable, dict[str, Any]]], ToolNode],
+        model: str
+        | BaseChatModel
+        | SyncOrAsync[[StateT, Runtime[ContextT]], BaseChatModel],
+        tools: Sequence[BaseTool | Callable | dict[str, Any]] | ToolNode,
         *,
-        prompt: Optional[Prompt] = None,
-        response_format: Optional[ResponseFormat[StructuredResponseT]] = None,
-        pre_model_hook: Optional[RunnableLike] = None,
-        post_model_hook: Optional[RunnableLike] = None,
-        state_schema: Optional[type[StateT]] = None,
-        context_schema: Optional[type[ContextT]] = None,
-        name: Optional[str] = None,
-        store: Optional[BaseStore] = None,
+        prompt: Prompt | None = None,
+        response_format: ResponseFormat[StructuredResponseT] | None = None,
+        pre_model_hook: RunnableLike | None = None,
+        post_model_hook: RunnableLike | None = None,
+        state_schema: type[StateT] | None = None,
+        context_schema: type[ContextT] | None = None,
+        name: str | None = None,
+        store: BaseStore | None = None,
     ):
         self.model = model
         self.tools = tools
@@ -282,7 +279,7 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
 
     def _handle_structured_response_tool_calls(
         self, response: AIMessage
-    ) -> Optional[Command]:
+    ) -> Command | None:
         """Handle tool calls that match structured output tools using the tools strategy.
 
         Args:
@@ -354,9 +351,7 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
         model_with_native_output = model.bind(**kwargs)
         return model_with_native_output
 
-    def _handle_structured_response_native(
-        self, response: AIMessage
-    ) -> Optional[Command]:
+    def _handle_structured_response_native(self, response: AIMessage) -> Command | None:
         """If native output is configured and there are no tool calls, parse using NativeOutputBinding."""
         if self.native_output_binding is None:
             return None
@@ -425,7 +420,7 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
             model = self._apply_native_output_binding(model)  # type: ignore[arg-type]
 
             # Extract just the model part for direct invocation
-            self._static_model: Optional[Runnable] = model
+            self._static_model: Runnable | None = model
         else:
             self._static_model = None
 
@@ -583,10 +578,10 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
 
         return RunnableCallable(call_model, acall_model)
 
-    def create_model_router(self) -> Callable[[StateT], Union[str, list[Send]]]:
+    def create_model_router(self) -> Callable[[StateT], str | list[Send]]:
         """Create routing function for model node conditional edges."""
 
-        def should_continue(state: StateT) -> Union[str, list[Send]]:
+        def should_continue(state: StateT) -> str | list[Send]:
             messages = _get_state_value(state, "messages")
             last_message = messages[-1]
 
@@ -621,10 +616,10 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
 
     def create_post_model_hook_router(
         self,
-    ) -> Callable[[StateT], Union[str, list[Send]]]:
+    ) -> Callable[[StateT], str | list[Send]]:
         """Create a routing function for post_model_hook node conditional edges."""
 
-        def post_model_hook_router(state: StateT) -> Union[str, list[Send]]:
+        def post_model_hook_router(state: StateT) -> str | list[Send]:
             messages = _get_state_value(state, "messages")
 
             # Check if the last message is a ToolMessage from a structured tool.
@@ -661,7 +656,7 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
 
         return post_model_hook_router
 
-    def create_tools_router(self) -> Optional[Callable[[StateT], str]]:
+    def create_tools_router(self) -> Callable[[StateT], str] | None:
         """Create a routing function for tools node conditional edges."""
         if not self._should_return_direct:
             return None
@@ -776,9 +771,9 @@ class _AgentBuilder(Generic[StateT, ContextT, StructuredResponseT]):
 
 
 def _supports_native_structured_output(
-    model: Union[
-        str, BaseChatModel, SyncOrAsync[[StateT, Runtime[ContextT]], BaseChatModel]
-    ],
+    model: str
+    | BaseChatModel
+    | SyncOrAsync[[StateT, Runtime[ContextT]], BaseChatModel],
 ) -> bool:
     """Check if a model supports native structured output.
 
@@ -802,31 +797,26 @@ def _supports_native_structured_output(
 
 
 def create_agent(
-    model: Union[
-        str,
-        BaseChatModel,
-        SyncOrAsync[[StateT, Runtime[ContextT]], BaseChatModel],
-    ],
-    tools: Union[Sequence[Union[BaseTool, Callable, dict[str, Any]]], ToolNode],
+    model: str
+    | BaseChatModel
+    | SyncOrAsync[[StateT, Runtime[ContextT]], BaseChatModel],
+    tools: Sequence[BaseTool | Callable | dict[str, Any]] | ToolNode,
     *,
-    prompt: Optional[Prompt] = None,
-    response_format: Optional[
-        Union[
-            ToolOutput[StructuredResponseT],
-            NativeOutput[StructuredResponseT],
-            type[StructuredResponseT],
-        ]
-    ] = None,
-    pre_model_hook: Optional[RunnableLike] = None,
-    post_model_hook: Optional[RunnableLike] = None,
-    state_schema: Optional[type[StateT]] = None,
-    context_schema: Optional[type[ContextT]] = None,
-    checkpointer: Optional[Checkpointer] = None,
-    store: Optional[BaseStore] = None,
-    interrupt_before: Optional[list[str]] = None,
-    interrupt_after: Optional[list[str]] = None,
+    prompt: Prompt | None = None,
+    response_format: ToolOutput[StructuredResponseT]
+    | NativeOutput[StructuredResponseT]
+    | type[StructuredResponseT]
+    | None = None,
+    pre_model_hook: RunnableLike | None = None,
+    post_model_hook: RunnableLike | None = None,
+    state_schema: type[StateT] | None = None,
+    context_schema: type[ContextT] | None = None,
+    checkpointer: Checkpointer | None = None,
+    store: BaseStore | None = None,
+    interrupt_before: list[str] | None = None,
+    interrupt_after: list[str] | None = None,
     debug: bool = False,
-    name: Optional[str] = None,
+    name: str | None = None,
 ) -> CompiledStateGraph:
     """Creates an agent graph that calls tools in a loop until a stopping condition is met.
 
diff --git a/libs/prebuilt/langgraph/prebuilt/responses.py b/libs/prebuilt/langgraph/prebuilt/responses.py
index cd45cc53d..e2cce4ad7 100644
--- a/libs/prebuilt/langgraph/prebuilt/responses.py
+++ b/libs/prebuilt/langgraph/prebuilt/responses.py
@@ -24,7 +24,7 @@ SchemaKind = Literal["pydantic", "dataclass", "typeddict", "json_schema"]
 
 
 def _parse_with_schema(
-    schema: Union[type[SchemaT], dict], schema_kind: SchemaKind, data: dict[str, Any]
+    schema: type[SchemaT] | dict, schema_kind: SchemaKind, data: dict[str, Any]
 ) -> Any:
     """Parse data using for any supported schema type.
 
@@ -53,7 +53,7 @@ def _parse_with_schema(
 class _SchemaSpec(Generic[SchemaT]):
     """Describes a structured output schema."""
 
-    schema: Union[type[SchemaT], dict[str, Any]]
+    schema: type[SchemaT] | dict[str, Any]
     """The schema for the response, can be a Pydantic model, dataclass, TypedDict, or JSON schema dict."""
 
     name: str
@@ -79,7 +79,7 @@ class _SchemaSpec(Generic[SchemaT]):
 
     def __init__(
         self,
-        schema: Union[type[SchemaT], dict[str, Any]],
+        schema: type[SchemaT] | dict[str, Any],
         *,
         name: str | None = None,
         description: str | None = None,
@@ -125,7 +125,7 @@ class _SchemaSpec(Generic[SchemaT]):
 class ToolOutput(Generic[SchemaT]):
     """Use a tool calling strategy for model responses."""
 
-    schema: Union[type[SchemaT], dict[str, Any]]
+    schema: type[SchemaT] | dict[str, Any]
     """Schema for the tool calls."""
 
     schema_specs: list[_SchemaSpec[SchemaT]]
@@ -136,7 +136,7 @@ class ToolOutput(Generic[SchemaT]):
 
     def __init__(
         self,
-        schema: Union[type[SchemaT], dict[str, Any]],
+        schema: type[SchemaT] | dict[str, Any],
         tool_message_content: str | None = None,
     ) -> None:
         """Initialize ToolOutput with schemas and tool message content."""
@@ -153,7 +153,7 @@ class ToolOutput(Generic[SchemaT]):
 class NativeOutput(Generic[SchemaT]):
     """Use the model provider's native structured output method."""
 
-    schema: Union[type[SchemaT], dict[str, Any]]
+    schema: type[SchemaT] | dict[str, Any]
     """Schema for native mode."""
 
     schema_spec: _SchemaSpec[SchemaT]
@@ -161,7 +161,7 @@ class NativeOutput(Generic[SchemaT]):
 
     def __init__(
         self,
-        schema: Union[type[SchemaT], dict[str, Any]],
+        schema: type[SchemaT] | dict[str, Any],
     ) -> None:
         self.schema = schema
         self.schema_spec = _SchemaSpec(schema)
@@ -188,7 +188,7 @@ class OutputToolBinding(Generic[SchemaT]):
     and the corresponding tool implementation used by the tools strategy.
     """
 
-    schema: Union[type[SchemaT], dict[str, Any]]
+    schema: type[SchemaT] | dict[str, Any]
     """The original schema provided for structured output (Pydantic model, dataclass, TypedDict, or JSON schema dict)."""
 
     schema_kind: SchemaKind
@@ -241,7 +241,7 @@ class NativeOutputBinding(Generic[SchemaT]):
     its type classification, and parsing logic for provider-enforced JSON.
     """
 
-    schema: Union[type[SchemaT], dict[str, Any]]
+    schema: type[SchemaT] | dict[str, Any]
     """The original schema provided for structured output (Pydantic model, dataclass, TypedDict, or JSON schema dict)."""
 
     schema_kind: SchemaKind
diff --git a/libs/prebuilt/langgraph/prebuilt/tool_node.py b/libs/prebuilt/langgraph/prebuilt/tool_node.py
index 34e3e5356..39c1fdce3 100644
--- a/libs/prebuilt/langgraph/prebuilt/tool_node.py
+++ b/libs/prebuilt/langgraph/prebuilt/tool_node.py
@@ -36,16 +36,14 @@ from __future__ import annotations
 import asyncio
 import inspect
 import json
+from collections.abc import Sequence
 from copy import copy, deepcopy
 from dataclasses import replace
 from typing import (
+    Annotated,
     Any,
     Callable,
     Literal,
-    Optional,
-    Sequence,
-    Tuple,
-    Type,
     Union,
     cast,
     get_type_hints,
@@ -71,7 +69,7 @@ from langchain_core.tools.base import (
     get_all_basemodel_annotations,
 )
 from pydantic import BaseModel
-from typing_extensions import Annotated, get_args, get_origin
+from typing_extensions import get_args, get_origin
 
 from langgraph._internal._runnable import RunnableCallable
 from langgraph.errors import GraphBubbleUp
@@ -85,7 +83,7 @@ INVALID_TOOL_NAME_ERROR_TEMPLATE = (
 TOOL_CALL_ERROR_TEMPLATE = "Error: {error}\n Please fix your mistakes."
 
 
-def msg_content_output(output: Any) -> Union[str, list[dict]]:
+def msg_content_output(output: Any) -> str | list[dict]:
     """Convert tool output to valid message content format.
 
     LangChain ToolMessages accept either string content or a list of content blocks.
@@ -127,12 +125,7 @@ def msg_content_output(output: Any) -> Union[str, list[dict]]:
 def _handle_tool_error(
     e: Exception,
     *,
-    flag: Union[
-        bool,
-        str,
-        Callable[..., str],
-        tuple[type[Exception], ...],
-    ],
+    flag: bool | str | Callable[..., str] | tuple[type[Exception], ...],
 ) -> str:
     """Generate error message content based on exception handling configuration.
 
@@ -338,13 +331,14 @@ class ToolNode(RunnableCallable):
 
     def __init__(
         self,
-        tools: Sequence[Union[BaseTool, Callable]],
+        tools: Sequence[BaseTool | Callable],
         *,
         name: str = "tools",
-        tags: Optional[list[str]] = None,
-        handle_tool_errors: Union[
-            bool, str, Callable[..., str], tuple[type[Exception], ...]
-        ] = True,
+        tags: list[str] | None = None,
+        handle_tool_errors: bool
+        | str
+        | Callable[..., str]
+        | tuple[type[Exception], ...] = True,
         messages_key: str = "messages",
     ) -> None:
         """Initialize the ToolNode with the provided tools and configuration.
@@ -358,13 +352,13 @@ class ToolNode(RunnableCallable):
         """
         super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
         self._tools_by_name: dict[str, BaseTool] = {}
-        self._tool_to_state_args: dict[str, dict[str, Optional[str]]] = {}
-        self._tool_to_store_arg: dict[str, Optional[str]] = {}
+        self._tool_to_state_args: dict[str, dict[str, str | None]] = {}
+        self._tool_to_store_arg: dict[str, str | None] = {}
         self._handle_tool_errors = handle_tool_errors
         self._messages_key = messages_key
         for tool in tools:
             if not isinstance(tool, BaseTool):
-                tool_ = create_tool(cast(Type[BaseTool], tool))
+                tool_ = create_tool(cast(type[BaseTool], tool))
             else:
                 tool_ = tool
             self._tools_by_name[tool_.name] = tool_
@@ -378,14 +372,10 @@ class ToolNode(RunnableCallable):
 
     def _func(
         self,
-        input: Union[
-            list[AnyMessage],
-            dict[str, Any],
-            BaseModel,
-        ],
+        input: list[AnyMessage] | dict[str, Any] | BaseModel,
         config: RunnableConfig,
         *,
-        store: Optional[BaseStore],
+        store: BaseStore | None,
     ) -> Any:
         tool_calls, input_type = self._parse_input(input, store)
         config_list = get_config_list(config, len(tool_calls))
@@ -399,14 +389,10 @@ class ToolNode(RunnableCallable):
 
     async def _afunc(
         self,
-        input: Union[
-            list[AnyMessage],
-            dict[str, Any],
-            BaseModel,
-        ],
+        input: list[AnyMessage] | dict[str, Any] | BaseModel,
         config: RunnableConfig,
         *,
-        store: Optional[BaseStore],
+        store: BaseStore | None,
     ) -> Any:
         tool_calls, input_type = self._parse_input(input, store)
         outputs = await asyncio.gather(
@@ -417,9 +403,9 @@ class ToolNode(RunnableCallable):
 
     def _combine_tool_outputs(
         self,
-        outputs: list[Union[ToolMessage, Command]],
+        outputs: list[ToolMessage | Command],
         input_type: Literal["list", "dict", "tool_calls"],
-    ) -> list[Union[Command, list[ToolMessage], dict[str, list[ToolMessage]]]]:
+    ) -> list[Command | list[ToolMessage] | dict[str, list[ToolMessage]]]:
         # preserve existing behavior for non-command tool outputs for backwards
         # compatibility
         if not any(isinstance(output, Command) for output in outputs):
@@ -433,7 +419,7 @@ class ToolNode(RunnableCallable):
         ] = []
 
         # combine all parent commands with goto into a single parent command
-        parent_command: Optional[Command] = None
+        parent_command: Command | None = None
         for output in outputs:
             if isinstance(output, Command):
                 if (
@@ -464,7 +450,7 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> Union[ToolMessage, Command]:
+    ) -> ToolMessage | Command:
         """Run a single tool call synchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
@@ -522,7 +508,7 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> Union[ToolMessage, Command]:
+    ) -> ToolMessage | Command:
         """Run a single tool call asynchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
@@ -577,13 +563,9 @@ class ToolNode(RunnableCallable):
 
     def _parse_input(
         self,
-        input: Union[
-            list[AnyMessage],
-            dict[str, Any],
-            BaseModel,
-        ],
-        store: Optional[BaseStore],
-    ) -> Tuple[list[ToolCall], Literal["list", "dict", "tool_calls"]]:
+        input: list[AnyMessage] | dict[str, Any] | BaseModel,
+        store: BaseStore | None,
+    ) -> tuple[list[ToolCall], Literal["list", "dict", "tool_calls"]]:
         input_type: Literal["list", "dict", "tool_calls"]
         if isinstance(input, list):
             if isinstance(input[-1], dict) and input[-1].get("type") == "tool_call":
@@ -616,7 +598,7 @@ class ToolNode(RunnableCallable):
         ]
         return tool_calls, input_type
 
-    def _validate_tool_call(self, call: ToolCall) -> Optional[ToolMessage]:
+    def _validate_tool_call(self, call: ToolCall) -> ToolMessage | None:
         requested_tool = call["name"]
         if requested_tool not in self.tools_by_name:
             all_tool_names = list(self.tools_by_name.keys())
@@ -633,11 +615,7 @@ class ToolNode(RunnableCallable):
     def _inject_state(
         self,
         tool_call: ToolCall,
-        input: Union[
-            list[AnyMessage],
-            dict[str, Any],
-            BaseModel,
-        ],
+        input: list[AnyMessage] | dict[str, Any] | BaseModel,
     ) -> ToolCall:
         state_args = self._tool_to_state_args[tool_call["name"]]
         if state_args and isinstance(input, list):
@@ -675,9 +653,7 @@ class ToolNode(RunnableCallable):
         }
         return tool_call
 
-    def _inject_store(
-        self, tool_call: ToolCall, store: Optional[BaseStore]
-    ) -> ToolCall:
+    def _inject_store(self, tool_call: ToolCall, store: BaseStore | None) -> ToolCall:
         store_arg = self._tool_to_store_arg[tool_call["name"]]
         if not store_arg:
             return tool_call
@@ -697,12 +673,8 @@ class ToolNode(RunnableCallable):
     def inject_tool_args(
         self,
         tool_call: ToolCall,
-        input: Union[
-            list[AnyMessage],
-            dict[str, Any],
-            BaseModel,
-        ],
-        store: Optional[BaseStore],
+        input: list[AnyMessage] | dict[str, Any] | BaseModel,
+        store: BaseStore | None,
     ) -> ToolCall:
         """Inject graph state and store into tool call arguments.
 
@@ -808,7 +780,7 @@ class ToolNode(RunnableCallable):
 
 
 def tools_condition(
-    state: Union[list[AnyMessage], dict[str, Any], BaseModel],
+    state: list[AnyMessage] | dict[str, Any] | BaseModel,
     messages_key: str = "messages",
 ) -> Literal["tools", "__end__"]:
     """Conditional routing function for tool-calling workflows.
@@ -954,7 +926,7 @@ class InjectedState(InjectedToolArg):
           tool execution
     """  # noqa: E501
 
-    def __init__(self, field: Optional[str] = None) -> None:
+    def __init__(self, field: str | None = None) -> None:
         self.field = field
 
 
@@ -1035,7 +1007,7 @@ class InjectedStore(InjectedToolArg):
 
 
 def _is_injection(
-    type_arg: Any, injection_type: Union[Type[InjectedState], Type[InjectedStore]]
+    type_arg: Any, injection_type: type[InjectedState] | type[InjectedStore]
 ) -> bool:
     """Check if a type argument represents an injection annotation.
 
@@ -1060,7 +1032,7 @@ def _is_injection(
     return False
 
 
-def _get_state_args(tool: BaseTool) -> dict[str, Optional[str]]:
+def _get_state_args(tool: BaseTool) -> dict[str, str | None]:
     """Extract state injection mappings from tool annotations.
 
     This function analyzes a tool's input schema to identify arguments that should
@@ -1099,7 +1071,7 @@ def _get_state_args(tool: BaseTool) -> dict[str, Optional[str]]:
     return tool_args_to_state_fields
 
 
-def _get_store_arg(tool: BaseTool) -> Optional[str]:
+def _get_store_arg(tool: BaseTool) -> str | None:
     """Extract store injection argument from tool annotations.
 
     This function analyzes a tool's input schema to identify the argument that
diff --git a/libs/prebuilt/langgraph/prebuilt/tool_validator.py b/libs/prebuilt/langgraph/prebuilt/tool_validator.py
index 19df4233f..409b65db8 100644
--- a/libs/prebuilt/langgraph/prebuilt/tool_validator.py
+++ b/libs/prebuilt/langgraph/prebuilt/tool_validator.py
@@ -5,14 +5,11 @@ returns a ToolMessage with the error message. The ValidationNode can be used in
 StateGraph with a "messages" key. If multiple tool calls are requested, they will be run in parallel.
 """
 
+from collections.abc import Sequence
 from typing import (
     Any,
     Callable,
-    Dict,
     Optional,
-    Sequence,
-    Tuple,
-    Type,
     Union,
     cast,
 )
@@ -39,7 +36,7 @@ from langgraph._internal._runnable import RunnableCallable
 def _default_format_error(
     error: BaseException,
     call: ToolCall,
-    schema: Union[Type[BaseModel], Type[BaseModelV1]],
+    schema: Union[type[BaseModel], type[BaseModelV1]],
 ) -> str:
     """Default error formatting function."""
     return f"{repr(error)}\n\nRespond after fixing all validation errors."
@@ -127,17 +124,17 @@ class ValidationNode(RunnableCallable):
 
     def __init__(
         self,
-        schemas: Sequence[Union[BaseTool, Type[BaseModel], Callable]],
+        schemas: Sequence[Union[BaseTool, type[BaseModel], Callable]],
         *,
         format_error: Optional[
-            Callable[[BaseException, ToolCall, Type[BaseModel]], str]
+            Callable[[BaseException, ToolCall, type[BaseModel]], str]
         ] = None,
         name: str = "validation",
         tags: Optional[list[str]] = None,
     ) -> None:
         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]] = {}
+        self.schemas_by_name: dict[str, type[BaseModel]] = {}
         for schema in schemas:
             if isinstance(schema, BaseTool):
                 if schema.args_schema is None:
@@ -155,7 +152,7 @@ class ValidationNode(RunnableCallable):
             elif isinstance(schema, type) and issubclass(
                 schema, (BaseModel, BaseModelV1)
             ):
-                self.schemas_by_name[schema.__name__] = cast(Type[BaseModel], schema)
+                self.schemas_by_name[schema.__name__] = cast(type[BaseModel], schema)
             elif callable(schema):
                 base_model = create_schema_from_function("Validation", schema)
                 self.schemas_by_name[schema.__name__] = base_model
@@ -166,7 +163,7 @@ class ValidationNode(RunnableCallable):
 
     def _get_message(
         self, input: Union[list[AnyMessage], dict[str, Any]]
-    ) -> Tuple[str, AIMessage]:
+    ) -> tuple[str, AIMessage]:
         """Extract the last AIMessage from the input."""
         if isinstance(input, list):
             output_type = "list"
diff --git a/libs/prebuilt/pyproject.toml b/libs/prebuilt/pyproject.toml
index 09bcb227b..0741d6cbb 100644
--- a/libs/prebuilt/pyproject.toml
+++ b/libs/prebuilt/pyproject.toml
@@ -7,7 +7,7 @@ name = "langgraph-prebuilt"
 version = "0.6.4"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
@@ -52,7 +52,7 @@ addopts = "--strict-markers --strict-config --durations=5 -vv"
 asyncio_mode = "auto"
 
 [tool.ruff]
-lint.select = [ "E", "F", "I", "TID251" ]
+lint.select = [ "E", "F", "I", "TID251", "UP" ]
 lint.ignore = [ "E501" ]
 
 [tool.pytest-watcher]
diff --git a/libs/prebuilt/tests/model.py b/libs/prebuilt/tests/model.py
index aab7885b9..285f5270b 100644
--- a/libs/prebuilt/tests/model.py
+++ b/libs/prebuilt/tests/model.py
@@ -1,15 +1,12 @@
 import json
+from collections.abc import Sequence
 from dataclasses import asdict, is_dataclass
 from typing import (
     Any,
     Callable,
-    Dict,
     Generic,
-    List,
     Literal,
     Optional,
-    Sequence,
-    Type,
     Union,
 )
 
@@ -36,8 +33,8 @@ class FakeToolCallingModel(BaseChatModel, Generic[StructuredResponseT]):
 
     def _generate(
         self,
-        messages: List[BaseMessage],
-        stop: Optional[List[str]] = None,
+        messages: list[BaseMessage],
+        stop: Optional[list[str]] = None,
         run_manager: Optional[CallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> ChatResult:
@@ -83,7 +80,7 @@ class FakeToolCallingModel(BaseChatModel, Generic[StructuredResponseT]):
 
     def bind_tools(
         self,
-        tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
+        tools: Sequence[Union[dict[str, Any], type[BaseModel], Callable, BaseTool]],
         **kwargs: Any,
     ) -> Runnable[LanguageModelInput, BaseMessage]:
         if len(tools) == 0:
diff --git a/libs/prebuilt/tests/test_responses_int.py b/libs/prebuilt/tests/test_responses_int.py
index c4e3363fe..fd04d1b78 100644
--- a/libs/prebuilt/tests/test_responses_int.py
+++ b/libs/prebuilt/tests/test_responses_int.py
@@ -1,8 +1,9 @@
 from __future__ import annotations
 
 import json
+from collections.abc import Sequence
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Sequence, Type, Union
+from typing import Any, Optional, Union
 from unittest.mock import MagicMock
 
 import pytest
@@ -21,7 +22,7 @@ else:
     skip_openai_integration_tests = False
 
 
-def _load_spec() -> List[Dict[str, Any]]:
+def _load_spec() -> list[dict[str, Any]]:
     with (Path(__file__).parent / "specifications" / "responses.json").open(
         "r", encoding="utf-8"
     ) as f:
@@ -51,10 +52,10 @@ def _make_tool(fn, *, name: str, description: str):
 
 
 def _build_tool_output_response_format(
-    response_format_spec: Sequence[Dict[str, Any]],
+    response_format_spec: Sequence[dict[str, Any]],
 ) -> ToolOutput:
-    models: List[Type[BaseModel]] = []
-    keyset_to_tool_name: Dict[frozenset[str], str] = {}
+    models: list[type[BaseModel]] = []
+    keyset_to_tool_name: dict[frozenset[str], str] = {}
     type_map = {
         "string": str,
         "number": float,
@@ -87,14 +88,14 @@ def _build_tool_output_response_format(
     reason="currently failing due to undefined behavior for multiple structured responses."
 )
 @pytest.mark.parametrize("case", TEST_CASES, ids=[c["name"] for c in TEST_CASES])
-def test_responses_integration_matrix(case: Dict[str, Any]) -> None:
-    def get_employee_role(*, name: str) -> Optional[str]:
+def test_responses_integration_matrix(case: dict[str, Any]) -> None:
+    def get_employee_role(*, name: str) -> str | None:
         for e in EMPLOYEES:
             if e["name"] == name:
                 return e["role"]
         return None
 
-    def get_employee_department(*, name: str) -> Optional[str]:
+    def get_employee_department(*, name: str) -> str | None:
         for e in EMPLOYEES:
             if e["name"] == name:
                 return e["department"]
@@ -118,7 +119,7 @@ def test_responses_integration_matrix(case: Dict[str, Any]) -> None:
 
     for assertion in case["assertionsByInvocation"]:
         prompt: str = assertion["prompt"]
-        expected_calls: Dict[str, int] = assertion["toolsWithExpectedCalls"]
+        expected_calls: dict[str, int] = assertion["toolsWithExpectedCalls"]
         expected_structured = assertion.get("expectedStructuredResponse")
         expected_last_message = assertion.get("expectedLastMessage")
 
diff --git a/libs/prebuilt/tests/test_tool_node.py b/libs/prebuilt/tests/test_tool_node.py
index b67b684d9..20d9e744c 100644
--- a/libs/prebuilt/tests/test_tool_node.py
+++ b/libs/prebuilt/tests/test_tool_node.py
@@ -4,8 +4,6 @@ from functools import partial
 from typing import (
     Annotated,
     Any,
-    List,
-    Type,
     TypeVar,
     Union,
 )
@@ -1216,7 +1214,7 @@ T = TypeVar("T")
         _InjectedStateDataclassSchema,
     ],
 )
-def test_tool_node_inject_state(schema_: Type[T]) -> None:
+def test_tool_node_inject_state(schema_: type[T]) -> None:
     def tool1(some_val: int, state: Annotated[T, InjectedState]) -> str:
         """Tool 1 docstring."""
         if isinstance(state, dict):
@@ -1234,13 +1232,13 @@ def test_tool_node_inject_state(schema_: Type[T]) -> None:
     def tool3(
         some_val: int,
         foo: Annotated[str, InjectedState("foo")],
-        msgs: Annotated[List[AnyMessage], InjectedState("messages")],
+        msgs: Annotated[list[AnyMessage], InjectedState("messages")],
     ) -> str:
         """Tool 1 docstring."""
         return foo
 
     def tool4(
-        some_val: int, msgs: Annotated[List[AnyMessage], InjectedState("messages")]
+        some_val: int, msgs: Annotated[list[AnyMessage], InjectedState("messages")]
     ) -> str:
         """Tool 1 docstring."""
         return msgs[0].content
diff --git a/libs/prebuilt/uv.lock b/libs/prebuilt/uv.lock
index 3bd2217bf..cdb769228 100644
--- a/libs/prebuilt/uv.lock
+++ b/libs/prebuilt/uv.lock
@@ -1,6 +1,6 @@
 version = 1
 revision = 2
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 
 [[package]]
 name = "aiosqlite"
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 ]
 
 [[package]]
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