Update libs/langgraph/langgraph/graph/state.py

docs/Makefile

@@ -18,9 +18,6 @@ build-prebuilt:
 build-docs: build-prebuilt
 	TARGET_LANGUAGE=python uv run python -m mkdocs build --clean -f mkdocs.yml --strict
 
-build-docs-js: build-prebuilt
-	TARGET_LANGUAGE=js uv run python -m mkdocs build --clean -f mkdocs.yml --strict
-
 llms-text:
 	uv run python -m _scripts.generate_llms_text docs/llms-full.txt
 

docs/_scripts/notebook_hooks.py

@@ -188,13 +188,13 @@ REDIRECT_MAP = {
     "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langgraph-platform/custom-docker",
     "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langgraph-platform/graph-rebuild",
     "concepts/langgraph_cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
-    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/hybrid",
-    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted",
-    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#data-plane-only",
+    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted-data-plane",
+    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted-control-plane",
+    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/standalone-container",
     "cloud/deployment/cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
-    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-hybrid",
-    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-full-platform",
-    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-data-plane-only",
+    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-data-plane",
+    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-control-plane",
+    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-standalone-container",
     "concepts/server-mcp.md": "https://docs.langchain.com/langgraph-platform/server-mcp",
     "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langgraph-platform/human-in-the-loop-time-travel",
     "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langgraph-platform/add-human-in-the-loop",

docs/docs/agents/agents.md

@@ -29,7 +29,7 @@ pip install -U langgraph "langchain[anthropic]"
 
 !!! info
 
-    `langchain[anthropic]` is installed so the agent can call the [model](https://python.langchain.com/docs/integrations/chat/).
+    LangChain is installed so the agent can call the [model](https://python.langchain.com/docs/integrations/chat/).
 
 :::
 
@@ -41,7 +41,7 @@ npm install @langchain/langgraph @langchain/core @langchain/anthropic
 
 !!! info
 
-    `@langchain/core` `@langchain/anthropic` are installed so the agent can call the [model](https://js.langchain.com/docs/integrations/chat/).
+    LangChain is installed so the agent can call the [model](https://js.langchain.com/docs/integrations/chat/).
 
 :::
 

docs/docs/concepts/auth.md

@@ -35,8 +35,7 @@ LangGraph Platform provides different security defaults:
 - Can be customized with your auth handler
 
 !!! note "Custom auth"
-
-   Custom auth **is supported** for all plans in LangGraph Platform.
+Custom auth **is supported** for all plans in LangGraph Platform.
 
 ### Self-Hosted
 

docs/docs/concepts/durable_execution.md

@@ -51,51 +51,6 @@ For some examples of pitfalls to avoid, see the [Common Pitfalls](./functional_a
 how to structure your code using **tasks** to avoid these issues. The same principles apply to the @[StateGraph (Graph API)][StateGraph].
 :::
 
-## Durability modes
-
-LangGraph supports three durability modes that allow you to balance performance and data consistency based on your application's requirements. The durability modes, from least to most durable, are as follows:
-
-- [`"exit"`](#exit)
-- [`"async"`](#async)
-- [`"sync"`](#sync)
-
-A higher durability mode add more overhead to the workflow execution.
-
-!!! version-added "Added in v0.6.0"
-
-    Use the `durability` parameter instead of `checkpoint_during` (deprecated in v0.6.0) for persistence policy management:
-    
-    * `durability="async"` replaces `checkpoint_during=True`
-    * `durability="exit"` replaces `checkpoint_during=False`
-    
-    for persistence policy management, with the following mapping:
-
-    * `checkpoint_during=True` -> `durability="async"`
-    * `checkpoint_during=False` -> `durability="exit"`
-
-
-### `"exit"`
-Changes are persisted only when graph execution completes (either successfully or with an error). This provides the best performance for long-running graphs but means intermediate state is not saved, so you cannot recover from mid-execution failures or interrupt the graph execution.
-
-### `"async"`
-Changes are persisted asynchronously while the next step executes. This provides good performance and durability, but there's a small risk that checkpoints might not be written if the process crashes during execution.
-
-### `"sync"`
-Changes are persisted synchronously before the next step starts. This ensures that every checkpoint is written before continuing execution, providing high durability at the cost of some performance overhead.
-
-You can specify the durability mode when calling any graph execution method:
-
-:::python
-
-```python
-graph.stream(
-    {"input": "test"}, 
-    durability="sync"
-)
-```
-
-:::
-
 ## Using tasks in nodes
 
 If a [node](./low_level.md#nodes) contains multiple operations, you may find it easier to convert each operation into a **task** rather than refactor the operations into individual nodes.

docs/docs/concepts/low_level.md

@@ -88,6 +88,8 @@ Typically, all graph nodes communicate with a single schema. This means that the
 
 It is possible to have nodes write to private state channels inside the graph for internal node communication. We can simply define a private schema, `PrivateState`.
 
+See [this guide](../how-tos/graph-api.ipynb#pass-private-state-between-nodes) for more detail.
+
 It is also possible to define explicit input and output schemas for a graph. In these cases, we define an "internal" schema that contains _all_ keys relevant to graph operations. But, we also define `input` and `output` schemas that are sub-sets of the "internal" schema to constrain the input and output of the graph. See [this guide](../how-tos/graph-api.md#define-input-and-output-schemas) for more detail.
 
 Let's look at an example:
@@ -471,7 +473,7 @@ const builder = new StateGraph(State);
 
 :::
 
-Behind the scenes, functions are converted to [RunnableLambda](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.RunnableLambda.html)s, which add batch and async support to your function, along with native tracing and debugging.
+Behind the scenes, functions are converted to [RunnableLambda](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.RunnableLambda.html#langchain_core.runnables.base.RunnableLambda)s, which add batch and async support to your function, along with native tracing and debugging.
 
 If you add a node to a graph without specifying a name, it will be given a default name equivalent to the function name.
 
@@ -699,8 +701,7 @@ graph.addConditionalEdges("nodeA", routingFunction, {
 :::
 
 !!! tip
-
-    Use [`Command`](#command) instead of conditional edges if you want to combine state updates and routing in a single function.
+Use [`Command`](#command) instead of conditional edges if you want to combine state updates and routing in a single function.
 
 ### Entry Point
 
@@ -819,6 +820,7 @@ def my_node(state: State) -> Command[Literal["my_other_node"]]:
         return Command(update={"foo": "baz"}, goto="my_other_node")
 ```
 
+Check out this [how-to guide](../how-tos/graph-api.ipynb#combine-control-flow-and-state-updates-with-command) for an end-to-end example of how to use `Command`.
 :::
 
 :::js
@@ -858,6 +860,7 @@ builder.addNode("myNode", myNode, {
 });
 ```
 
+Check out this [how-to guide](../how-tos/graph-api.ipynb#combine-control-flow-and-state-updates-with-command) for an end-to-end example of how to use `Command`.
 :::
 
 !!! important

docs/docs/how-tos/auth/custom_auth.md

@@ -145,7 +145,7 @@ def my_node(state, config):
 By default, if you add custom authorization on your resources, this will also apply to interactions made from the Studio. If you want, you can handle logged-in Studio users differently by checking [is_studio_user()](../../reference/functions/sdk_auth.isStudioUser.html).
 
 !!! note
-    `is_studio_user` was added in version 0.1.73 of the langgraph-sdk. If you're on an older version, you can still check whether `isinstance(ctx.user, StudioUser)`.
+`is_studio_user` was added in version 0.1.73 of the langgraph-sdk. If you're on an older version, you can still check whether `isinstance(ctx.user, StudioUser)`.
 
 ```python
 from langgraph_sdk.auth import is_studio_user, Auth

docs/docs/how-tos/multi_agent.md

@@ -57,7 +57,7 @@ def create_handoff_tool(*, agent_name: str, description: str | None = None):
     return handoff_tool
 ```
 
-1. Access the [state](../concepts/low_level.md#state) of the agent that is calling the handoff tool using the @[InjectedState] annotation. 
+1. Access the [state](../concepts/low_level.md#state) of the agent that is calling the handoff tool using the @[InjectedState][InjectedState] annotation. 
 2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs.
 3. Name of the agent or node to hand off to.
 4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.

docs/docs/tutorials/get-started/3-add-memory.md

@@ -17,7 +17,7 @@ Create a `MemorySaver` checkpointer:
 :::python
 
 ```python
-from langgraph.checkpoint.memory import InMemorySaver
+from langgraph.checkpoint.memory import MemorySaver
 
 memory = InMemorySaver()
 ```
@@ -447,4 +447,3 @@ const graph = new StateGraph(State)
 ## Next steps
 
 In the next tutorial, you will [add human-in-the-loop to the chatbot](./4-human-in-the-loop.md) to handle situations where it may need guidance or verification before proceeding.
-

docs/uv.lock

@@ -2337,7 +2337,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.2"
+version = "0.6.1"
 source = { editable = "../libs/langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -2524,7 +2524,6 @@ docs = [
     { name = "markdown-include" },
     { name = "mkdocs" },
     { name = "mkdocs-exclude" },
-    { name = "mkdocs-exclude-search" },
     { name = "mkdocs-git-committers-plugin-2" },
     { name = "mkdocs-include-markdown-plugin" },
     { name = "mkdocs-material", extra = ["imaging"] },
@@ -2596,7 +2595,6 @@ docs = [
     { name = "markdown-include" },
     { name = "mkdocs" },
     { name = "mkdocs-exclude" },
-    { name = "mkdocs-exclude-search" },
     { name = "mkdocs-git-committers-plugin-2" },
     { name = "mkdocs-include-markdown-plugin", specifier = ">=7.1.6" },
     { name = "mkdocs-material", extras = ["imaging"] },
@@ -2643,7 +2641,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.2"
+version = "0.6.1"
 source = { editable = "../libs/prebuilt" }
 dependencies = [
     { name = "langchain-core" },
@@ -3032,18 +3030,6 @@ dependencies = [
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/54/b5/3a8e289282c9e8d7003f8a2f53d673d4fdaa81d493dc6966092d9985b6fc/mkdocs-exclude-1.0.2.tar.gz", hash = "sha256:ba6fab3c80ddbe3fd31d3e579861fd3124513708271180a5f81846da8c7e2a51", size = 6751, upload-time = "2019-02-20T23:34:12.81Z" }
 
-[[package]]
-name = "mkdocs-exclude-search"
-version = "0.6.6"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "mkdocs" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/1d/52/8243589d294cf6091c1145896915fe50feea0e91d64d843942d0175770c2/mkdocs-exclude-search-0.6.6.tar.gz", hash = "sha256:3cdff1b9afdc1b227019cd1e124f401453235b92153d60c0e5e651a76be4f044", size = 9501, upload-time = "2023-12-03T22:58:21.259Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/3b/ef/9af45ffb1bdba684a0694922abae0bb771e9777aba005933f838b7f1bcea/mkdocs_exclude_search-0.6.6-py3-none-any.whl", hash = "sha256:2b4b941d1689808db533fe4a6afba75ce76c9bab8b21d4e31efc05fd8c4e0a4f", size = 7821, upload-time = "2023-12-03T22:58:19.355Z" },
-]
-
 [[package]]
 name = "mkdocs-get-deps"
 version = "0.2.0"

libs/langgraph/langgraph/_internal/_runnable.py

@@ -4,7 +4,6 @@ import asyncio
 import enum
 import inspect
 import sys
-import warnings
 from collections.abc import (
     AsyncIterator,
     Awaitable,
@@ -304,16 +303,6 @@ class RunnableCallable(Runnable):
             if typ != (ANY_TYPE,) and p.annotation not in typ:
                 # A specific type is required, but the function annotation does
                 # not match the expected type.
-
-                # If this is a config parameter with incorrect typing, emit a warning
-                # because we used to support any type but are moving towards more correct typing
-                if kw == "config" and p.annotation != inspect.Parameter.empty:
-                    warnings.warn(
-                        f"The 'config' parameter should be typed as 'RunnableConfig' or "
-                        f"'RunnableConfig | None', not '{p.annotation}'. ",
-                        UserWarning,
-                        stacklevel=4,
-                    )
                 continue
 
             # If the kwarg is accepted by the function, store the key / runtime attribute to inject

libs/langgraph/langgraph/errors.py

@@ -91,7 +91,7 @@ class GraphInterrupt(GraphBubbleUp):
 
 @deprecated(
     "NodeInterrupt is deprecated. Please use `langgraph.types.interrupt` instead.",
-    category=None,
+    stacklevel=2,
 )
 class NodeInterrupt(GraphInterrupt):
     """Raised by a node to interrupt execution.

libs/langgraph/langgraph/graph/state.py

@@ -128,6 +128,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             Use this to expose immutable context data to your nodes, like user_id, db_conn, etc.
         input_schema: The schema class that defines the input to the graph.
         output_schema: The schema class that defines the output from the graph.
+        name: The default name to use when compiling the graph.
 
     !!! warning "`config_schema` Deprecated"
         The `config_schema` parameter is deprecated in v0.6.0 and support will be removed in v2.0.0.
@@ -177,7 +178,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
     managed: dict[str, ManagedValueSpec]
     schemas: dict[type[Any], dict[str, BaseChannel | ManagedValueSpec]]
     waiting_edges: set[tuple[tuple[str, ...], str]]
-
+    name: str = "LangGraph"
     compiled: bool
     state_schema: type[StateT]
     context_schema: type[ContextT] | None
@@ -874,7 +875,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             debug=debug,
             store=store,
             cache=cache,
-            name=name or "LangGraph",
+            name=name or self.name,
         )
 
         compiled.attach_node(START, None)
@@ -1390,14 +1391,6 @@ def _is_field_managed_value(name: str, typ: type[Any]) -> ManagedValueSpec | Non
             if is_managed_value(decoration):
                 return decoration
 
-    # Handle Required, NotRequired, etc wrapped types by extracting the inner type
-    if (
-        get_origin(typ) is not None
-        and (args := get_args(typ))
-        and (inner_type := args[0])
-    ):
-        return _is_field_managed_value(name, inner_type)
-
     return None
 
 

libs/langgraph/langgraph/managed/base.py

@@ -8,7 +8,7 @@ from typing import (
 
 from typing_extensions import TypeGuard
 
-from langgraph._internal._scratchpad import PregelScratchpad
+from langgraph.pregel._scratchpad import PregelScratchpad
 
 V = TypeVar("V")
 U = TypeVar("U")

libs/langgraph/langgraph/managed/is_last_step.py

@@ -1,7 +1,7 @@
 from typing import Annotated
 
-from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph.managed.base import ManagedValue
+from langgraph.pregel._scratchpad import PregelScratchpad
 
 __all__ = ("IsLastStep", "RemainingStepsManager")
 

libs/langgraph/langgraph/pregel/_algo.py

@@ -53,7 +53,6 @@ from langgraph._internal._constants import (
     RETURN,
     TASKS,
 )
-from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.topic import Topic
@@ -70,6 +69,7 @@ from langgraph.pregel._call import get_runnable_for_task, identifier
 from langgraph.pregel._io import read_channels
 from langgraph.pregel._log import logger
 from langgraph.pregel._read import INPUT_CACHE_KEY_TYPE, PregelNode
+from langgraph.pregel._scratchpad import PregelScratchpad
 from langgraph.runtime import DEFAULT_RUNTIME, Runtime
 from langgraph.store.base import BaseStore
 from langgraph.types import (

libs/langgraph/langgraph/pregel/_loop.py

@@ -48,7 +48,6 @@ from langgraph._internal._constants import (
     PUSH,
     RESUME,
 )
-from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
 from langgraph.cache.base import BaseCache
 from langgraph.channels.base import BaseChannel
@@ -101,6 +100,7 @@ from langgraph.pregel._io import (
     read_channels,
 )
 from langgraph.pregel._read import PregelNode
+from langgraph.pregel._scratchpad import PregelScratchpad
 from langgraph.pregel._utils import get_new_channel_versions, is_xxh3_128_hexdigest
 from langgraph.pregel.debug import (
     map_debug_checkpoint,

libs/langgraph/langgraph/pregel/_runner.py

@@ -30,13 +30,13 @@ from langgraph._internal._constants import (
     RETURN,
 )
 from langgraph._internal._future import chain_future, run_coroutine_threadsafe
-from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import MISSING
 from langgraph.constants import TAG_HIDDEN
 from langgraph.errors import GraphBubbleUp, GraphInterrupt
 from langgraph.pregel._algo import Call
 from langgraph.pregel._executor import Submit
 from langgraph.pregel._retry import arun_with_retry, run_with_retry
+from langgraph.pregel._scratchpad import PregelScratchpad
 from langgraph.types import (
     CachePolicy,
     PregelExecutableTask,

libs/langgraph/langgraph/pregel/main.py

@@ -11,7 +11,7 @@ from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
 from dataclasses import is_dataclass
 from functools import partial
 from inspect import isclass
-from typing import Any, Callable, Generic, Union, cast, get_type_hints
+from typing import Any, Callable, Generic, Optional, Union, cast, get_type_hints
 from uuid import UUID, uuid5
 
 from langchain_core.globals import get_debug
@@ -637,7 +637,8 @@ class Pregel(
         **deprecated_kwargs: Unpack[DeprecatedKwargs],
     ) -> None:
         if (
-            config_type := deprecated_kwargs.get("config_type", MISSING)
+            config_type := deprecated_kwargs.get("config_type"),
+            MISSING,
         ) is not MISSING:
             warnings.warn(
                 "`config_type` is deprecated and will be removed. Please use `context_schema` instead.",
@@ -784,8 +785,7 @@ class Pregel(
         return self
 
     @deprecated(
-        "`config_schema` is deprecated. Use `get_context_jsonschema` for the relevant schema instead.",
-        category=None,
+        "`config_schema` is deprecated. Use `get_context_jsonschema` for the relevant schema instead."
     )
     def config_schema(self, *, include: Sequence[str] | None = None) -> type[BaseModel]:
         warnings.warn(
@@ -810,8 +810,7 @@ class Pregel(
         return create_model(self.get_name("Config"), field_definitions=fields)
 
     @deprecated(
-        "`get_config_jsonschema` is deprecated. Use `get_context_jsonschema` instead.",
-        category=None,
+        "`get_config_jsonschema` is deprecated. Use `get_context_jsonschema` instead."
     )
     def get_config_jsonschema(
         self, *, include: Sequence[str] | None = None
@@ -2352,6 +2351,7 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None,
         interrupt_after: All | Sequence[str] | None,
         durability: Durability | None = None,
+        checkpoint_during: bool | None = None,
     ) -> tuple[
         set[StreamMode],
         str | Sequence[str],
@@ -2399,6 +2399,15 @@ class Pregel(
             cache: BaseCache | None = config[CONF][CONFIG_KEY_CACHE]
         else:
             cache = self.cache
+        if checkpoint_during is not None:
+            if durability is not None:
+                raise ValueError(
+                    "Cannot use both `checkpoint_during` and `durability` parameters."
+                )
+            elif checkpoint_during:
+                durability = "async"
+            else:
+                durability = "exit"
         if durability is None:
             durability = config.get(CONF, {}).get(CONFIG_KEY_DURABILITY, "async")
         return (
@@ -2471,17 +2480,6 @@ class Pregel(
         Yields:
             The output of each step in the graph. The output shape depends on the stream_mode.
         """
-        if (checkpoint_during := kwargs.get("checkpoint_during")) is not None:
-            warnings.warn(
-                "`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
-                category=LangGraphDeprecatedSinceV10,
-                stacklevel=2,
-            )
-            if durability is not None:
-                raise ValueError(
-                    "Cannot use both `checkpoint_during` and `durability` parameters. Please use `durability` instead."
-                )
-            durability = "async" if checkpoint_during else "exit"
 
         if stream_mode is None:
             # if being called as a node in another graph, default to values mode
@@ -2505,6 +2503,14 @@ class Pregel(
             run_id=config.get("run_id"),
         )
         try:
+            deprecated_checkpoint_during = cast(
+                Optional[bool], kwargs.get("checkpoint_during")
+            )
+            if deprecated_checkpoint_during is not None:
+                warnings.warn(
+                    "`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
+                    category=LangGraphDeprecatedSinceV10,
+                )
             # assign defaults
             (
                 stream_modes,
@@ -2523,8 +2529,11 @@ class Pregel(
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
                 durability=durability,
+                checkpoint_during=deprecated_checkpoint_during,
             )
-            if checkpointer is None and durability is not None:
+            if checkpointer is None and (
+                durability is not None or deprecated_checkpoint_during is not None
+            ):
                 warnings.warn(
                     "`durability` has no effect when no checkpointer is present.",
                 )
@@ -2561,7 +2570,7 @@ class Pregel(
                     pass
 
             # set durability mode for subgraphs
-            if durability is not None:
+            if durability is not None or deprecated_checkpoint_during is not None:
                 config[CONF][CONFIG_KEY_DURABILITY] = durability_
 
             runtime = Runtime(
@@ -2732,17 +2741,6 @@ class Pregel(
         Yields:
             The output of each step in the graph. The output shape depends on the stream_mode.
         """
-        if (checkpoint_during := kwargs.get("checkpoint_during")) is not None:
-            warnings.warn(
-                "`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
-                category=LangGraphDeprecatedSinceV10,
-                stacklevel=2,
-            )
-            if durability is not None:
-                raise ValueError(
-                    "Cannot use both `checkpoint_during` and `durability` parameters. Please use `durability` instead."
-                )
-            durability = "async" if checkpoint_during else "exit"
 
         if stream_mode is None:
             # if being called as a node in another graph, default to values mode
@@ -2785,6 +2783,14 @@ class Pregel(
             else False
         )
         try:
+            deprecated_checkpoint_during = cast(
+                Optional[bool], kwargs.get("checkpoint_during")
+            )
+            if deprecated_checkpoint_during is not None:
+                warnings.warn(
+                    "`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
+                    category=LangGraphDeprecatedSinceV10,
+                )
             # assign defaults
             (
                 stream_modes,
@@ -2803,8 +2809,11 @@ class Pregel(
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
                 durability=durability,
+                checkpoint_during=deprecated_checkpoint_during,
             )
-            if checkpointer is None and durability is not None:
+            if checkpointer is None and (
+                durability is not None or deprecated_checkpoint_during is not None
+            ):
                 warnings.warn(
                     "`durability` has no effect when no checkpointer is present.",
                 )
@@ -2856,7 +2865,7 @@ class Pregel(
                     pass
 
             # set durability mode for subgraphs
-            if durability is not None:
+            if durability is not None or deprecated_checkpoint_during is not None:
                 config[CONF][CONFIG_KEY_DURABILITY] = durability_
 
             runtime = Runtime(
@@ -2981,7 +2990,6 @@ class Pregel(
         output_keys: str | Sequence[str] | None = None,
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
-        durability: Durability | None = None,
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
         """Run the graph with a single input and config.
@@ -2996,10 +3004,6 @@ class Pregel(
             output_keys: Optional. The output keys to retrieve from the graph run.
             interrupt_before: Optional. The nodes to interrupt the graph run before.
             interrupt_after: Optional. The nodes to interrupt the graph run after.
-            durability: The durability mode for the graph execution, defaults to "async". Options are:
-                - `"sync"`: Changes are persisted synchronously before the next step starts.
-                - `"async"`: Changes are persisted asynchronously while the next step executes.
-                - `"exit"`: Changes are persisted only when the graph exits.
             **kwargs: Additional keyword arguments to pass to the graph run.
 
         Returns:
@@ -3023,7 +3027,6 @@ class Pregel(
             output_keys=output_keys,
             interrupt_before=interrupt_before,
             interrupt_after=interrupt_after,
-            durability=durability,
             **kwargs,
         ):
             if stream_mode == "values":
@@ -3066,7 +3069,6 @@ class Pregel(
         output_keys: str | Sequence[str] | None = None,
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
-        durability: Durability | None = None,
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
         """Asynchronously invoke the graph on a single input.
@@ -3081,10 +3083,6 @@ class Pregel(
             output_keys: Optional. The output keys to include in the result. Default is None.
             interrupt_before: Optional. The nodes to interrupt before. Default is None.
             interrupt_after: Optional. The nodes to interrupt after. Default is None.
-            durability: The durability mode for the graph execution, defaults to "async". Options are:
-                - `"sync"`: Changes are persisted synchronously before the next step starts.
-                - `"async"`: Changes are persisted asynchronously while the next step executes.
-                - `"exit"`: Changes are persisted only when the graph exits.
             **kwargs: Additional keyword arguments.
 
         Returns:
@@ -3109,7 +3107,6 @@ class Pregel(
             output_keys=output_keys,
             interrupt_before=interrupt_before,
             interrupt_after=interrupt_after,
-            durability=durability,
             **kwargs,
         ):
             if stream_mode == "values":

libs/langgraph/langgraph/types.py

@@ -191,7 +191,10 @@ class Interrupt:
         return cls(value=value, id=xxh3_128_hexdigest(ns.encode()))
 
     @property
-    @deprecated("`interrupt_id` is deprecated. Use `id` instead.", category=None)
+    @deprecated(
+        "`interrupt_id` is deprecated. Use `id` instead.",
+        stacklevel=2,
+    )
     def interrupt_id(self) -> str:
         warn(
             "`interrupt_id` is deprecated. Use `id` instead.",

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "0.6.3"
+version = "0.6.2"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.9"

libs/langgraph/tests/__snapshots__/test_large_cases.ambr

@@ -175,10 +175,10 @@
   '''
 # ---
 # name: test_prebuilt_tool_chat
-  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of ChatModels.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
+  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of ChatModels.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "is_last_step": {"title": "Is Last Step", "type": "boolean"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages", "is_last_step", "remaining_steps"], "title": "AgentState", "type": "object"}'
 # ---
 # name: test_prebuilt_tool_chat.1
-  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of ChatModels.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
+  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of ChatModels.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "is_last_step": {"title": "Is Last Step", "type": "boolean"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages", "is_last_step", "remaining_steps"], "title": "AgentState", "type": "object"}'
 # ---
 # name: test_prebuilt_tool_chat.2
   '''

libs/langgraph/tests/test_deprecation.py

@@ -1,12 +1,6 @@
-from __future__ import annotations
-
-import warnings
-from typing import Any, Optional
-
 import pytest
-from langchain_core.runnables import RunnableConfig
 from pytest_mock import MockerFixture
-from typing_extensions import NotRequired, TypedDict
+from typing_extensions import TypedDict
 
 from langgraph.channels.last_value import LastValue
 from langgraph.errors import NodeInterrupt
@@ -100,6 +94,8 @@ def test_pregel_types_deprecation() -> None:
         from langgraph.pregel.types import StateSnapshot  # noqa: F401
 
 
+@pytest.mark.filterwarnings("ignore:`config_schema` is deprecated")
+@pytest.mark.filterwarnings("ignore:`get_config_jsonschema` is deprecated")
 def test_config_schema_deprecation() -> None:
     with pytest.warns(
         LangGraphDeprecatedSinceV10,
@@ -125,6 +121,7 @@ def test_config_schema_deprecation() -> None:
         graph.get_config_jsonschema()
 
 
+@pytest.mark.filterwarnings("ignore:`config_schema` is deprecated")
 def test_config_schema_deprecation_on_entrypoint() -> None:
     with pytest.warns(
         LangGraphDeprecatedSinceV10,
@@ -135,15 +132,10 @@ def test_config_schema_deprecation_on_entrypoint() -> None:
         def my_entrypoint(state: PlainState) -> PlainState:
             return state
 
-    with pytest.warns(
-        LangGraphDeprecatedSinceV10,
-        match="`config_schema` is deprecated. Use `get_context_jsonschema` for the relevant schema instead.",
-    ):
         assert my_entrypoint.context_schema == PlainState
         assert my_entrypoint.config_schema() is not None
 
 
-@pytest.mark.filterwarnings("ignore:`config_type` is deprecated")
 def test_config_type_deprecation_pregel(mocker: MockerFixture) -> None:
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
@@ -167,6 +159,7 @@ def test_config_type_deprecation_pregel(mocker: MockerFixture) -> None:
         assert instance.context_schema == PlainState
 
 
+@pytest.mark.filterwarnings("ignore:`interrupt_id` is deprecated. Use `id` instead.")
 def test_interrupt_attributes_deprecation() -> None:
     interrupt = Interrupt(value="question", id="abc")
 
@@ -177,6 +170,7 @@ def test_interrupt_attributes_deprecation() -> None:
         interrupt.interrupt_id
 
 
+@pytest.mark.filterwarnings("ignore:NodeInterrupt is deprecated.")
 def test_node_interrupt_deprecation() -> None:
     with pytest.warns(
         LangGraphDeprecatedSinceV10,
@@ -191,144 +185,3 @@ def test_deprecated_import() -> None:
         match="Importing PREVIOUS from langgraph.constants is deprecated. This constant is now private and should not be used directly.",
     ):
         from langgraph.constants import PREVIOUS  # noqa: F401
-
-
-@pytest.mark.filterwarnings(
-    "ignore:`durability` has no effect when no checkpointer is present"
-)
-def test_checkpoint_during_deprecation_state_graph() -> None:
-    class CheckDurability(TypedDict):
-        durability: NotRequired[str]
-
-    def plain_node(state: CheckDurability, config: RunnableConfig) -> CheckDurability:
-        return {"durability": config["configurable"]["__pregel_durability"]}
-
-    builder = StateGraph(CheckDurability)
-    builder.add_node("plain_node", plain_node)
-    builder.set_entry_point("plain_node")
-    graph = builder.compile()
-
-    with pytest.warns(
-        LangGraphDeprecatedSinceV10,
-        match="`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
-    ):
-        result = graph.invoke({}, checkpoint_during=True)
-        assert result["durability"] == "async"
-
-    with pytest.warns(
-        LangGraphDeprecatedSinceV10,
-        match="`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
-    ):
-        result = graph.invoke({}, checkpoint_during=False)
-        assert result["durability"] == "exit"
-
-    with pytest.warns(
-        LangGraphDeprecatedSinceV10,
-        match="`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
-    ):
-        for chunk in graph.stream({}, checkpoint_during=True):  # type: ignore[arg-type]
-            assert chunk["plain_node"]["durability"] == "async"
-
-    with pytest.warns(
-        LangGraphDeprecatedSinceV10,
-        match="`checkpoint_during` is deprecated and will be removed. Please use `durability` instead.",
-    ):
-        for chunk in graph.stream({}, checkpoint_during=False):  # type: ignore[arg-type]
-            assert chunk["plain_node"]["durability"] == "exit"
-
-
-def test_config_parameter_incorrect_typing() -> None:
-    """Test that a warning is raised when config parameter is typed incorrectly."""
-    builder = StateGraph(PlainState)
-
-    # Test sync function with config: dict
-    with pytest.warns(
-        UserWarning,
-        match="The 'config' parameter should be typed as 'RunnableConfig' or 'RunnableConfig | None', not '.*dict.*'. ",
-    ):
-
-        def sync_node_with_dict_config(state: PlainState, config: dict) -> PlainState:
-            return state
-
-        builder.add_node(sync_node_with_dict_config)
-
-    # Test async function with config: dict
-    with pytest.warns(
-        UserWarning,
-        match="The 'config' parameter should be typed as 'RunnableConfig' or 'RunnableConfig | None', not '.*dict.*'. ",
-    ):
-
-        async def async_node_with_dict_config(
-            state: PlainState, config: dict
-        ) -> PlainState:
-            return state
-
-        builder.add_node(async_node_with_dict_config)
-
-    # Test with other incorrect types
-    with pytest.warns(
-        UserWarning,
-        match="The 'config' parameter should be typed as 'RunnableConfig' or 'RunnableConfig | None', not '.*Any.*'. ",
-    ):
-
-        def sync_node_with_any_config(state: PlainState, config: Any) -> PlainState:
-            return state
-
-        builder.add_node(sync_node_with_any_config)
-
-    with pytest.warns(
-        UserWarning,
-        match="The 'config' parameter should be typed as 'RunnableConfig' or 'RunnableConfig | None', not '.*Any.*'. ",
-    ):
-
-        async def async_node_with_any_config(
-            state: PlainState, config: Any
-        ) -> PlainState:
-            return state
-
-        builder.add_node(async_node_with_any_config)
-
-    with warnings.catch_warnings(record=True) as w:
-
-        def node_with_correct_config(
-            state: PlainState, config: RunnableConfig
-        ) -> PlainState:
-            return state
-
-        builder.add_node(node_with_correct_config)
-
-        def node_with_optional_config(
-            state: PlainState,
-            config: Optional[RunnableConfig],  # noqa: UP045
-        ) -> PlainState:
-            return state
-
-        builder.add_node(node_with_optional_config)
-
-        def node_with_untyped_config(state: PlainState, config) -> PlainState:
-            return state
-
-        builder.add_node(node_with_untyped_config)
-
-        async def async_node_with_correct_config(
-            state: PlainState, config: RunnableConfig
-        ) -> PlainState:
-            return state
-
-        builder.add_node(async_node_with_correct_config)
-
-        async def async_node_with_optional_config(
-            state: PlainState,
-            config: Optional[RunnableConfig],  # noqa: UP045
-        ) -> PlainState:
-            return state
-
-        builder.add_node(async_node_with_optional_config)
-
-        async def async_node_with_untyped_config(
-            state: PlainState, config
-        ) -> PlainState:
-            return state
-
-        builder.add_node(async_node_with_untyped_config)
-        assert len(w) == 0

libs/langgraph/tests/test_interruption.py

@@ -1,12 +1,9 @@
-import operator
-from typing import Annotated
-
 import pytest
 from typing_extensions import TypedDict
 
 from langgraph.checkpoint.base import BaseCheckpointSaver
 from langgraph.graph import END, START, StateGraph
-from langgraph.types import Command, Durability, Send, interrupt
+from langgraph.types import Durability
 
 pytestmark = pytest.mark.anyio
 
@@ -93,162 +90,3 @@ async def test_interruption_without_state_updates_async(
     assert (await graph.aget_state(thread)).next == ()
     n_checkpoints = len([c async for c in graph.aget_state_history(thread)])
     assert n_checkpoints == (5 if durability != "exit" else 3)
-
-
-def test_interrupt_with_send_payloads(sync_checkpointer: BaseCheckpointSaver) -> None:
-    """Test interruption in map node with Send payloads and human-in-the-loop resume."""
-
-    # Global counter to track node executions
-    node_counter = {"entry": 0, "map_node": 0}
-
-    class State(TypedDict):
-        items: list[str]
-        processed: Annotated[list[str], operator.add]
-
-    def entry_node(state: State):
-        node_counter["entry"] += 1
-        return {}  # No state updates in entry node
-
-    def send_to_map(state: State):
-        return [Send("map_node", {"item": item}) for item in state["items"]]
-
-    def map_node(state: State):
-        node_counter["map_node"] += 1
-        if "dangerous" in state["item"]:
-            value = interrupt({"processing": state["item"]})
-            return {"processed": [f"processed_{value}"]}
-        else:
-            return {"processed": [f"processed_{state['item']}_auto"]}
-
-    builder = StateGraph(State)
-    builder.add_node("entry", entry_node)
-    builder.add_node("map_node", map_node)
-    builder.add_edge(START, "entry")
-    builder.add_conditional_edges("entry", send_to_map, ["map_node"])
-    builder.add_edge("map_node", END)
-
-    graph = builder.compile(checkpointer=sync_checkpointer)
-
-    config = {"configurable": {"thread_id": "test_interrupt_send"}}
-
-    # Run until interrupts
-    result = graph.invoke(
-        {"items": ["item1", "dangerous_item1", "dangerous_item2"]}, config=config
-    )
-
-    # Verify we have interrupts (only one for dangerous_item)
-    interrupts = result.get("__interrupt__", [])
-    assert len(interrupts) == 2
-    assert "dangerous_item" in interrupts[0].value["processing"]
-
-    # Resume with mapping of interrupt IDs to values
-    resume_map = {
-        i.interrupt_id: f"human_input_{i.value['processing']}" for i in interrupts
-    }
-
-    final_result = graph.invoke(Command(resume=resume_map), config=config)
-
-    # Verify final result contains processed items
-    assert "processed" in final_result
-    processed_items = final_result["processed"]
-    assert len(processed_items) == 3
-    assert "processed_item1_auto" in processed_items  # item1 processed automatically
-    assert any(
-        "processed_human_input_dangerous_item1" in item for item in processed_items
-    )  # dangerous_item1 processed after interrupt
-    assert any(
-        "processed_human_input_dangerous_item2" in item for item in processed_items
-    )  # dangerous_item2 processed after interrupt
-
-    # Verify node execution counts
-    assert node_counter["entry"] == 1  # Entry node runs once
-    # Map node runs 3 times initially (item1 completes, 2 dangerous_items interrupt),
-    # then 2 times on resume
-    assert node_counter["map_node"] == 5
-
-
-def test_interrupt_with_send_payloads_sequential_resume(
-    sync_checkpointer: BaseCheckpointSaver,
-) -> None:
-    """Test interruption in map node with Send payloads and sequential resume."""
-
-    # Global counter to track node executions
-    node_counter = {"entry": 0, "map_node": 0}
-
-    class State(TypedDict):
-        items: list[str]
-        processed: Annotated[list[str], operator.add]
-
-    def entry_node(state: State):
-        node_counter["entry"] += 1
-        return {}  # No state updates in entry node
-
-    def send_to_map(state: State):
-        return [Send("map_node", {"item": item}) for item in state["items"]]
-
-    def map_node(state: State):
-        node_counter["map_node"] += 1
-        if "dangerous" in state["item"]:
-            value = interrupt({"processing": state["item"]})
-            return {"processed": [f"processed_{value}"]}
-        else:
-            return {"processed": [f"processed_{state['item']}_auto"]}
-
-    builder = StateGraph(State)
-    builder.add_node("entry", entry_node)
-    builder.add_node("map_node", map_node)
-    builder.add_edge(START, "entry")
-    builder.add_conditional_edges("entry", send_to_map, ["map_node"])
-    builder.add_edge("map_node", END)
-
-    graph = builder.compile(checkpointer=sync_checkpointer)
-
-    config = {"configurable": {"thread_id": "test_interrupt_send_sequential"}}
-
-    # Run until interrupts
-    result = graph.invoke(
-        {"items": ["item1", "dangerous_item1", "dangerous_item2"]}, config=config
-    )
-
-    # Verify we have interrupts
-    interrupts = result.get("__interrupt__", [])
-    assert len(interrupts) == 2
-    assert "dangerous_item" in interrupts[0].value["processing"]
-
-    # Resume first interrupt only
-    first_interrupt = interrupts[0]
-    first_resume_map = {
-        first_interrupt.interrupt_id: f"human_input_{first_interrupt.value['processing']}"
-    }
-
-    partial_result = graph.invoke(Command(resume=first_resume_map), config=config)
-
-    # Verify we still have one pending interrupt
-    remaining_interrupts = partial_result.get("__interrupt__", [])
-    assert len(remaining_interrupts) == 1
-
-    # Resume second interrupt
-    second_interrupt = remaining_interrupts[0]
-    second_resume_map = {
-        second_interrupt.interrupt_id: f"human_input_{second_interrupt.value['processing']}"
-    }
-
-    final_result = graph.invoke(Command(resume=second_resume_map), config=config)
-
-    # Verify final result contains processed items
-    assert "processed" in final_result
-    processed_items = final_result["processed"]
-    assert len(processed_items) == 3
-    assert "processed_item1_auto" in processed_items  # item1 processed automatically
-    assert any(
-        "processed_human_input_dangerous_item1" in item for item in processed_items
-    )  # dangerous_item1 processed after interrupt
-    assert any(
-        "processed_human_input_dangerous_item2" in item for item in processed_items
-    )  # dangerous_item2 processed after interrupt
-
-    # Verify node execution counts
-    assert node_counter["entry"] == 1  # Entry node runs once
-    # Map node runs 3 times initially (item1 completes, 2 dangerous_items interrupt),
-    # then 1 time on first resume, then 1 time on second resume
-    assert node_counter["map_node"] == 5

libs/langgraph/tests/test_managed_values.py

@@ -1,27 +0,0 @@
-from typing_extensions import NotRequired, Required, TypedDict
-
-from langgraph.graph import StateGraph
-from langgraph.managed import RemainingSteps
-
-
-class StatePlain(TypedDict):
-    remaining_steps: RemainingSteps
-
-
-class StateNotRequired(TypedDict):
-    remaining_steps: NotRequired[RemainingSteps]
-
-
-class StateRequired(TypedDict):
-    remaining_steps: Required[RemainingSteps]
-
-
-def test_managed_values_recognized() -> None:
-    graph = StateGraph(StatePlain)
-    assert "remaining_steps" in graph.managed
-
-    graph = StateGraph(StateNotRequired)
-    assert "remaining_steps" in graph.managed
-
-    graph = StateGraph(StateRequired)
-    assert "remaining_steps" in graph.managed

libs/langgraph/uv.lock

@@ -1192,7 +1192,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.3"
+version = "0.6.2"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1433,7 +1433,7 @@ dev = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.3"
+version = "0.6.2"
 source = { editable = "../prebuilt" }
 dependencies = [
     { name = "langchain-core" },

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -34,7 +34,7 @@ from langchain_core.runnables import (
 )
 from langchain_core.tools import BaseTool
 from pydantic import BaseModel
-from typing_extensions import Annotated, NotRequired, TypedDict
+from typing_extensions import Annotated, TypedDict
 
 from langgraph._internal._runnable import RunnableCallable, RunnableLike
 from langgraph._internal._typing import MISSING
@@ -42,7 +42,7 @@ from langgraph.errors import ErrorCode, create_error_message
 from langgraph.graph import END, StateGraph
 from langgraph.graph.message import add_messages
 from langgraph.graph.state import CompiledStateGraph
-from langgraph.managed import RemainingSteps
+from langgraph.managed import IsLastStep, RemainingSteps
 from langgraph.prebuilt._internal import ToolCallWithContext
 from langgraph.prebuilt.tool_node import ToolNode
 from langgraph.runtime import Runtime
@@ -65,7 +65,9 @@ class AgentState(TypedDict):
 
     messages: Annotated[Sequence[BaseMessage], add_messages]
 
-    remaining_steps: NotRequired[RemainingSteps]
+    is_last_step: IsLastStep
+
+    remaining_steps: RemainingSteps
 
 
 class AgentStatePydantic(BaseModel):
@@ -569,13 +571,16 @@ def create_react_agent(
             else False
         )
         remaining_steps = _get_state_value(state, "remaining_steps", None)
-        if remaining_steps is not None:
-            if remaining_steps < 1 and all_tools_return_direct:
-                return True
-            elif remaining_steps < 2 and has_tool_calls:
-                return True
-
-        return False
+        is_last_step = _get_state_value(state, "is_last_step", False)
+        return (
+            (remaining_steps is None and is_last_step and has_tool_calls)
+            or (
+                remaining_steps is not None
+                and remaining_steps < 1
+                and all_tools_return_direct
+            )
+            or (remaining_steps is not None and remaining_steps < 2 and has_tool_calls)
+        )
 
     def _get_model_input_state(state: StateSchema) -> StateSchema:
         if pre_model_hook is not None:

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "0.6.3"
+version = "0.6.2"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.9"

libs/prebuilt/uv.lock

@@ -316,7 +316,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.3"
+version = "0.6.2"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -460,7 +460,7 @@ dev = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.3"
+version = "0.6.2"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },