bump langchain-core to cb/chat-model-updates branch

.gitignore

@@ -100,4 +100,3 @@ dmypy.json
 .turbo
 .editorconfig
 .scratch
-.worktrees/

README.md

@@ -16,7 +16,7 @@
   <a href="https://opensource.org/licenses/MIT" target="_blank"><img src="https://img.shields.io/pypi/l/langgraph" alt="PyPI - License"></a>
   <a href="https://pypistats.org/packages/langgraph" target="_blank"><img src="https://img.shields.io/pepy/dt/langgraph" alt="PyPI - Downloads"></a>
   <a href="https://pypi.org/project/langgraph/" target="_blank"><img src="https://img.shields.io/pypi/v/langgraph.svg?label=%20" alt="Version"></a>
-  <a href="https://x.com/langchain_oss" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain_oss.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
+  <a href="https://x.com/langchain" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
 </div>
 
 <br>

libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py

@@ -4,17 +4,15 @@ import threading
 from collections import defaultdict
 from collections.abc import Iterator, Sequence
 from contextlib import contextmanager
-from typing import Any, cast
+from typing import Any
 
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
-    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
-    _ChannelWritesHistory,
     get_checkpoint_id,
     get_serializable_checkpoint_metadata,
 )
@@ -25,11 +23,7 @@ from psycopg.types.json import Jsonb
 from psycopg_pool import ConnectionPool
 
 from langgraph.checkpoint.postgres import _internal
-from langgraph.checkpoint.postgres.base import (
-    SELECT_DELTA_COMBINED_SQL,
-    BasePostgresSaver,
-    _DeltaCombinedRow,
-)
+from langgraph.checkpoint.postgres.base import BasePostgresSaver
 from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
 
 Conn = _internal.Conn  # For backward compatibility
@@ -436,48 +430,6 @@ class PostgresSaver(BasePostgresSaver):
                 with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
-    def _get_channel_writes_history(
-        self, config: RunnableConfig, channel: str
-    ) -> _ChannelWritesHistory:
-        """Fast-path override of `BaseCheckpointSaver._get_channel_writes_history`.
-
-        One combined UNION ALL query (`SELECT_DELTA_COMBINED_SQL`) fetches rows
-        from `checkpoints`, `checkpoint_writes`, and `checkpoint_blobs` in a
-        single roundtrip; the ancestor walk runs in Python.
-        """
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
-        checkpoint_id = get_checkpoint_id(config)
-        if checkpoint_id is None:
-            # Caller didn't specify a target — resolve to the latest
-            # checkpoint on the thread. `get_tuple` without `checkpoint_id`
-            # returns the newest; its config carries the resolved id.
-            target = self.get_tuple(config)
-            if target is None:
-                return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
-            checkpoint_id = target.config["configurable"]["checkpoint_id"]
-        with self._cursor() as cur:
-            cur.execute(
-                SELECT_DELTA_COMBINED_SQL,
-                (
-                    channel,
-                    thread_id,
-                    checkpoint_ns,
-                    thread_id,
-                    checkpoint_ns,
-                    channel,
-                    thread_id,
-                    checkpoint_ns,
-                    channel,
-                ),
-            )
-            rows = cur.fetchall()
-        return self._build_delta_channel_writes_history(
-            channel=channel,
-            target_id=checkpoint_id,
-            rows=cast("list[_DeltaCombinedRow]", rows),
-        )
-
     def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
         Convert a database row into a CheckpointTuple object.

libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py

@@ -4,17 +4,15 @@ import asyncio
 from collections import defaultdict
 from collections.abc import AsyncIterator, Iterator, Sequence
 from contextlib import asynccontextmanager
-from typing import Any, cast
+from typing import Any
 
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
-    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
-    _ChannelWritesHistory,
     get_checkpoint_id,
     get_serializable_checkpoint_metadata,
 )
@@ -25,11 +23,7 @@ from psycopg.types.json import Jsonb
 from psycopg_pool import AsyncConnectionPool
 
 from langgraph.checkpoint.postgres import _ainternal
-from langgraph.checkpoint.postgres.base import (
-    SELECT_DELTA_COMBINED_SQL,
-    BasePostgresSaver,
-    _DeltaCombinedRow,
-)
+from langgraph.checkpoint.postgres.base import BasePostgresSaver
 from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
 
 Conn = _ainternal.Conn  # For backward compatibility
@@ -397,46 +391,6 @@ class AsyncPostgresSaver(BasePostgresSaver):
                 async with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
-    async def _aget_channel_writes_history(
-        self, config: RunnableConfig, channel: str
-    ) -> _ChannelWritesHistory:
-        """Fast-path override of `BaseCheckpointSaver._aget_channel_writes_history`.
-
-        One combined UNION ALL query (`SELECT_DELTA_COMBINED_SQL`) fetches rows
-        from `checkpoints`, `checkpoint_writes`, and `checkpoint_blobs` in a
-        single roundtrip; rows are assembled by the shared pure helper on
-        `BasePostgresSaver`.
-        """
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
-        checkpoint_id = get_checkpoint_id(config)
-        if checkpoint_id is None:
-            target = await self.aget_tuple(config)
-            if target is None:
-                return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
-            checkpoint_id = target.config["configurable"]["checkpoint_id"]
-        async with self._cursor() as cur:
-            await cur.execute(
-                SELECT_DELTA_COMBINED_SQL,
-                (
-                    channel,
-                    thread_id,
-                    checkpoint_ns,
-                    thread_id,
-                    checkpoint_ns,
-                    channel,
-                    thread_id,
-                    checkpoint_ns,
-                    channel,
-                ),
-            )
-            rows = await cur.fetchall()
-        return self._build_delta_channel_writes_history(
-            channel=channel,
-            target_id=checkpoint_id,
-            rows=cast("list[_DeltaCombinedRow]", rows),
-        )
-
     async def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
         Convert a database row into a CheckpointTuple object.

libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py

@@ -4,16 +4,13 @@ import random
 import warnings
 from collections.abc import Sequence
 from importlib.metadata import version as get_version
-from typing import Any, TypedDict, cast
+from typing import Any, cast
 
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
-    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
     ChannelVersions,
-    PendingWrite,
-    _ChannelWritesHistory,
     get_checkpoint_id,
 )
 from langgraph.checkpoint.serde.types import TASKS
@@ -156,62 +153,6 @@ INSERT_CHECKPOINT_WRITES_SQL = """
 """
 
 
-class _DeltaCombinedRow(TypedDict, total=False):
-    """One row from `SELECT_DELTA_COMBINED_SQL` (a UNION ALL of three tables).
-
-    Every row carries `_kind` ("p" / "w" / "b") plus whichever columns are
-    relevant for that kind; irrelevant columns are NULL and typed as `None`.
-    """
-
-    _kind: str  # always present: "p", "w", or "b"
-    # checkpoint row ("p")
-    checkpoint_id: str | None
-    parent_checkpoint_id: str | None
-    ver: str | None
-    # write / blob rows ("w", "b")
-    type: str | None
-    blob: bytes | None
-    # write row only ("w")
-    task_id: str | None
-    idx: int | None
-    # blob row only ("b")
-    version: str | None
-
-
-# DeltaChannel reconstruction: one UNION ALL query fetches checkpoints,
-# writes, and blobs for `channel` in one roundtrip; the ancestor walk runs
-# in Python in `_build_delta_channel_writes_history`.
-#
-# Parameter order: (channel, thread_id, checkpoint_ns,
-#                   thread_id, checkpoint_ns, channel,
-#                   thread_id, checkpoint_ns, channel)
-SELECT_DELTA_COMBINED_SQL = """
-    SELECT 'p'::text       AS _kind,
-           checkpoint_id,
-           parent_checkpoint_id,
-           checkpoint -> 'channel_versions' ->> %s AS ver,
-           NULL::text       AS type,
-           NULL::bytea      AS blob,
-           NULL::text       AS task_id,
-           NULL::int        AS idx,
-           NULL::text       AS version
-    FROM checkpoints
-    WHERE thread_id = %s AND checkpoint_ns = %s
-    UNION ALL
-    SELECT 'w',
-           checkpoint_id, NULL, NULL,
-           type, blob, task_id, idx, NULL
-    FROM checkpoint_writes
-    WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s
-    UNION ALL
-    SELECT 'b',
-           NULL, NULL, NULL,
-           type, blob, NULL, NULL, version
-    FROM checkpoint_blobs
-    WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s
-"""
-
-
 class BasePostgresSaver(BaseCheckpointSaver[str]):
     SELECT_SQL = SELECT_SQL
     SELECT_PENDING_SENDS_SQL = SELECT_PENDING_SENDS_SQL
@@ -254,83 +195,6 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
             if t.decode() != "empty"
         }
 
-    def _build_delta_channel_writes_history(
-        self,
-        *,
-        channel: str,
-        target_id: str,
-        rows: Sequence[_DeltaCombinedRow],
-    ) -> _ChannelWritesHistory:
-        """Reconstruct one delta channel's history from the combined UNION ALL rows.
-
-        Pure data transform shared by sync (`PostgresSaver`) and async
-        (`AsyncPostgresSaver`); both paths run `SELECT_DELTA_COMBINED_SQL`
-        and feed the tagged rows here.
-
-        Walk is newest → oldest from the target's parent. A non-sentinel
-        blob in `checkpoint_blobs` (a pre-delta snapshot) terminates the
-        walk and is returned as the seed so replay starts from it.
-
-        Writes stored at `target_id` itself are pending writes for the next
-        step and are excluded — the walk begins at the target's parent.
-        """
-        parent_of: dict[str, str | None] = {}
-        ver_of: dict[str, str | None] = {}
-        writes_by_cid: dict[str, list[tuple[str, bytes, str, int]]] = {}
-        blob_by_ver: dict[str, tuple[str, bytes]] = {}
-
-        for r in rows:
-            kind = r["_kind"]
-            if kind == "p":
-                cid = cast(str, r["checkpoint_id"])
-                parent_of[cid] = r["parent_checkpoint_id"]
-                ver_of[cid] = r["ver"]
-            elif kind == "w":
-                cid = cast(str, r["checkpoint_id"])
-                writes_by_cid.setdefault(cid, []).append(
-                    cast(
-                        "tuple[str, bytes, str, int]",
-                        (r["type"], r["blob"], r["task_id"], r["idx"]),
-                    )
-                )
-            else:  # kind == "b"
-                blob_by_ver[cast(str, r["version"])] = cast(
-                    "tuple[str, bytes]", (r["type"], r["blob"])
-                )
-
-        # newest write first per ancestor (task_id DESC, idx DESC)
-        for ws in writes_by_cid.values():
-            ws.sort(key=lambda w: (w[2], w[3]), reverse=True)
-
-        ancestors: list[str] = []
-        cur_cid: str | None = parent_of.get(target_id)
-        while cur_cid is not None:
-            ancestors.append(cur_cid)
-            cur_cid = parent_of.get(cur_cid)
-        if not ancestors:
-            return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
-
-        collected: list[PendingWrite] = []  # newest first; reversed at the end
-        for cid in ancestors:
-            # Collect writes first — they encode the transition FROM this
-            # ancestor's state to its child's and must be included even if
-            # this ancestor is also the seed checkpoint.
-            for type_tag, write_blob, task_id, _idx in writes_by_cid.get(cid, []):
-                val = self.serde.loads_typed((type_tag, write_blob))
-                collected.append((task_id, channel, val))
-            # Then check seed terminator.
-            ver = ver_of.get(cid)
-            if ver is not None:
-                seed_blob = blob_by_ver.get(ver)
-                if seed_blob is not None and seed_blob[0] != "empty":
-                    blob_value = self.serde.loads_typed(seed_blob)
-                    if blob_value is not DELTA_SENTINEL:
-                        collected.reverse()
-                        return _ChannelWritesHistory(seed=blob_value, writes=collected)
-
-        collected.reverse()  # oldest → newest
-        return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=collected)
-
     def _dump_blobs(
         self,
         thread_id: str,

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.1.0a1"
+version = "3.0.5"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-  "langgraph-checkpoint>=4.1.0a1,<5.0.0",
+  "langgraph-checkpoint>=2.1.2,<5.0.0",
   "orjson>=3.11.5",
   "psycopg>=3.2.0",
   "psycopg-pool>=3.2.0",
@@ -20,7 +20,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint-postgres/tests/test_async.py

@@ -361,9 +361,9 @@ async def test_get_checkpoint_no_channel_values(
 
         load_checkpoint_tuple = saver._load_checkpoint_tuple
 
-        async def patched_load_checkpoint_tuple(value):
+        def patched_load_checkpoint_tuple(value):
             value["checkpoint"].pop("channel_values", None)
-            return await load_checkpoint_tuple(value)
+            return load_checkpoint_tuple(value)
 
         monkeypatch.setattr(
             saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
@@ -371,47 +371,3 @@ async def test_get_checkpoint_no_channel_values(
 
         checkpoint = await saver.aget_tuple(config)
         assert checkpoint.checkpoint["channel_values"] == {}
-
-
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
-async def test_delta_channel_chain_reconstruction(saver_name: str) -> None:
-    """AsyncPostgresSaver reconstructs DeltaChannel chain via point-lookup traversal."""
-    pytest.importorskip(
-        "langgraph.channels.delta", reason="langgraph core not installed"
-    )
-
-    from typing import Annotated
-
-    from langchain_core.messages import AIMessage, HumanMessage
-    from langgraph.channels.delta import DeltaChannel
-    from langgraph.graph import START, StateGraph
-    from langgraph.graph.message import _messages_delta_reducer
-    from typing_extensions import TypedDict
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    def respond(state: State) -> dict:
-        n = len(state["messages"])
-        return {"messages": [AIMessage(content=f"reply-{n}", id=f"ai-{n}")]}
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_edge(START, "respond")
-
-    async with _saver(saver_name) as saver:
-        graph = builder.compile(checkpointer=saver)
-        config = {"configurable": {"thread_id": "diff-channel-test-1"}}
-
-        await graph.ainvoke({"messages": [HumanMessage(content="hi", id="h1")]}, config)
-        await graph.ainvoke(
-            {"messages": [HumanMessage(content="there", id="h2")]}, config
-        )
-
-        state = await graph.aget_state(config)
-        msgs = state.values["messages"]
-        assert len(msgs) == 4, f"expected 4, got {len(msgs)}: {msgs}"
-        assert msgs[0].content == "hi"
-        assert msgs[1].content == "reply-1"
-        assert msgs[2].content == "there"
-        assert msgs[3].content == "reply-3"

libs/checkpoint-postgres/uv.lock

@@ -259,7 +259,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -307,7 +307,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.1.0a1"
+version = "3.0.5"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },

libs/checkpoint-sqlite/pyproject.toml

@@ -19,7 +19,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-sqlite"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint-sqlite/uv.lock

@@ -268,7 +268,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },

libs/checkpoint/langgraph/checkpoint/base/__init__.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import copy
 import logging
 from collections.abc import AsyncIterator, Collection, Iterator, Mapping, Sequence
-from typing import (
+from typing import (  # noqa: UP035
     Any,
     Generic,
     Literal,
@@ -18,9 +18,6 @@ from langgraph.checkpoint.base.id import uuid6
 from langgraph.checkpoint.serde.base import SerializerProtocol, maybe_add_typed_methods
 from langgraph.checkpoint.serde.encrypted import EncryptedSerializer
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
-from langgraph.checkpoint.serde.types import (
-    DELTA_SENTINEL as DELTA_SENTINEL,
-)
 from langgraph.checkpoint.serde.types import (
     ERROR,
     INTERRUPT,
@@ -31,8 +28,6 @@ from langgraph.checkpoint.serde.types import (
 
 V = TypeVar("V", int, float, str)
 PendingWrite = tuple[str, str, Any]
-
-
 logger = logging.getLogger(__name__)
 
 
@@ -124,30 +119,6 @@ class CheckpointTuple(NamedTuple):
     pending_writes: list[PendingWrite] | None = None
 
 
-class _ChannelWritesHistory(NamedTuple):
-    """Result of `BaseCheckpointSaver._get_channel_writes_history`.
-
-    Storage-level view of what one channel wrote across the ancestor chain
-    of a target checkpoint:
-
-      * `seed` — the nearest ancestor's stored blob value for this channel,
-        or `DELTA_SENTINEL` if the walk reached the root without finding a
-        stored value. A non-sentinel seed typically indicates a pre-delta
-        snapshot preserved across a channel-type migration (e.g.
-        `BinaryOperatorAggregate` storage extended under `DeltaChannel`).
-      * `writes` — on-path deltas oldest→newest, one `PendingWrite` per
-        step that wrote to this channel. Writes stored at the target
-        checkpoint itself are pending for the next super-step and are
-        excluded.
-
-    Experimental: method surface may change; the NamedTuple shape is the
-    contract.
-    """
-
-    seed: Any
-    writes: list[PendingWrite]
-
-
 class BaseCheckpointSaver(Generic[V]):
     """Base class for creating a graph checkpointer.
 
@@ -486,104 +457,6 @@ class BaseCheckpointSaver(Generic[V]):
         """
         raise NotImplementedError
 
-    def _get_tuple_raw(self, config: RunnableConfig) -> CheckpointTuple | None:
-        """Pure storage read used by `_get_channel_writes_history`.
-
-        Must return the same value as `get_tuple` but must NOT trigger channel
-        reconstruction; otherwise the channel-hydration path would re-enter
-        `_get_channel_writes_history`. Override only if `get_tuple` itself
-        performs channel hydration.
-        """
-        return self.get_tuple(config)
-
-    async def _aget_tuple_raw(self, config: RunnableConfig) -> CheckpointTuple | None:
-        """Async version of `_get_tuple_raw`. See docstring there."""
-        return await self.aget_tuple(config)
-
-    def _get_channel_writes_history(
-        self, config: RunnableConfig, channel: str
-    ) -> _ChannelWritesHistory:
-        """**Experimental.** Query one channel's writes along the parent chain.
-
-        Storage-level query, not channel semantics: returns `(seed, writes)`
-        reflecting what storage knows about a single channel across the
-        ancestor chain of the target checkpoint identified by `config`.
-
-        * `writes` — on-path deltas oldest→newest as `PendingWrite` tuples.
-          Writes stored at the target `checkpoint_id` itself are pending
-          for the next super-step and are excluded.
-        * `seed` — the nearest ancestor's stored blob value for this
-          channel; `DELTA_SENTINEL` if the walk reached the root without
-          finding a stored value. A non-sentinel seed typically indicates
-          a pre-delta snapshot preserved across a channel-type migration.
-
-        Walks the **parent chain** (not `list(before=...)`): for forked
-        threads, only on-path ancestors contribute.
-
-        Reference implementation walks `get_tuple` + `parent_config`,
-        inspecting each ancestor's `channel_values[channel]` for the seed
-        terminator. Savers with direct storage access (`InMemorySaver`,
-        `PostgresSaver`) override for performance; the return contract is
-        fixed here.
-
-        Underscore-prefixed because the method surface is experimental.
-        """
-        collected: list[PendingWrite] = []  # newest first; reversed at the end
-        target_tuple = self._get_tuple_raw(config)
-        cursor_config: RunnableConfig | None = (
-            target_tuple.parent_config if target_tuple else None
-        )
-        while cursor_config is not None:
-            tup = self._get_tuple_raw(cursor_config)
-            if tup is None:
-                break
-            # Collect this ancestor's writes FIRST — they encode the
-            # transition from this ancestor's state to its child's, so
-            # they must be included whether or not this ancestor is the
-            # seed terminator.
-            if tup.pending_writes:
-                # Within a superstep, pending_writes are oldest→newest;
-                # reverse to scan newest-first.
-                for write in reversed(tup.pending_writes):
-                    if write[1] != channel:
-                        continue
-                    collected.append(write)
-            # Seed terminator: any non-sentinel blob on an ancestor
-            # establishes the reconstruction base. Stop here.
-            ancestor_value = tup.checkpoint["channel_values"].get(channel)
-            if ancestor_value is not None and ancestor_value is not DELTA_SENTINEL:
-                collected.reverse()
-                return _ChannelWritesHistory(seed=ancestor_value, writes=collected)
-            cursor_config = tup.parent_config
-        collected.reverse()
-        return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=collected)
-
-    async def _aget_channel_writes_history(
-        self, config: RunnableConfig, channel: str
-    ) -> _ChannelWritesHistory:
-        """Async version of `_get_channel_writes_history`. See docstring there."""
-        collected: list[PendingWrite] = []
-        target_tuple = await self._aget_tuple_raw(config)
-        cursor_config: RunnableConfig | None = (
-            target_tuple.parent_config if target_tuple else None
-        )
-        while cursor_config is not None:
-            tup = await self._aget_tuple_raw(cursor_config)
-            if tup is None:
-                break
-            if tup.pending_writes:
-                for write in reversed(tup.pending_writes):
-                    if write[1] != channel:
-                        continue
-                    collected.append(write)
-            ancestor_value = tup.checkpoint["channel_values"].get(channel)
-            if ancestor_value is not None and ancestor_value is not DELTA_SENTINEL:
-                collected.reverse()
-                return _ChannelWritesHistory(seed=ancestor_value, writes=collected)
-            cursor_config = tup.parent_config
-        collected.reverse()
-        return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=collected)
-
     def get_next_version(self, current: V | None, channel: None) -> V:
         """Generate the next version ID for a channel.
 

libs/checkpoint/langgraph/checkpoint/memory/__init__.py

@@ -14,20 +14,16 @@ from typing import Any
 from langchain_core.runnables import RunnableConfig
 
 from langgraph.checkpoint.base import (
-    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
-    PendingWrite,
     SerializerProtocol,
-    _ChannelWritesHistory,
     get_checkpoint_id,
     get_checkpoint_metadata,
 )
-from langgraph.checkpoint.serde.types import _DeltaSnapshot
 
 logger = logging.getLogger(__name__)
 
@@ -125,114 +121,16 @@ class InMemorySaver(
         return self.stack.__exit__(__exc_type, __exc_value, __traceback)
 
     def _load_blobs(
-        self,
-        thread_id: str,
-        checkpoint_ns: str,
-        versions: ChannelVersions,
+        self, thread_id: str, checkpoint_ns: str, versions: ChannelVersions
     ) -> dict[str, Any]:
-        result: dict[str, Any] = {}
-        for k, ver in versions.items():
-            kk = (thread_id, checkpoint_ns, k, ver)
-            if kk not in self.blobs:
-                continue
-            vv = self.blobs[kk]
-            if vv[0] == "empty":
-                continue
-            result[k] = self.serde.loads_typed(vv)
-        return result
-
-    def _get_channel_writes_history(
-        self, config: RunnableConfig, channel: str
-    ) -> _ChannelWritesHistory:
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
-        checkpoint_id = config["configurable"].get("checkpoint_id", "")
-        ns_storage = self.storage.get(thread_id, {}).get(checkpoint_ns, {})
-        # Walk the parent chain newest→oldest. Skip the target itself —
-        # writes stored AT `checkpoint_id` are pending for the next step
-        # (pregel applies them via `apply_writes`; they aren't part of the
-        # snapshot value AT `checkpoint_id`).
-        chain: list[str] = []
-        target_entry = ns_storage.get(checkpoint_id)
-        current: str | None = target_entry[2] if target_entry is not None else None
-        while current is not None:
-            entry = ns_storage.get(current)
-            if entry is None:
-                break
-            chain.append(current)
-            _, _, parent = entry
-            current = parent
-        # Scan newest→oldest. A pre-delta blob on an ancestor terminates the
-        # walk and is bound as `seed`; without this, a thread migrated from
-        # pre-delta storage would replay ancestor writes all the way to the
-        # root AND miss any value that lived only in the old blob (e.g. from
-        # `update_state`).
-        #
-        # At each ancestor, check the blob BEFORE processing its pending
-        # writes: a pre-delta blob represents the state AT that ancestor,
-        # which already subsumes any writes stored under it. Processing
-        # those writes first would fold them into the reconstructed value
-        # twice (once via the blob, once via replay).
-        collected: list[PendingWrite] = []  # newest first
-        for cp_id in chain:  # newest → oldest
-            entry = ns_storage.get(cp_id)
-            if entry is not None:
-                ckpt = self.serde.loads_typed(entry[0])
-                ver = ckpt.get("channel_versions", {}).get(channel)
-                if ver is not None:
-                    blob_entry = self.blobs.get(
-                        (thread_id, checkpoint_ns, channel, ver)
-                    )
-                    if blob_entry is not None and blob_entry[0] != "empty":
-                        blob_value = self.serde.loads_typed(blob_entry)
-                        if blob_value is not DELTA_SENTINEL:
-                            if isinstance(blob_value, _DeltaSnapshot):
-                                # Step-based snapshot: the blob is state AT this
-                                # ancestor, but the ancestor's pending_writes
-                                # encode the NEXT step's transition and are NOT
-                                # subsumed by the snapshot — collect them first.
-                                step_writes = self.writes.get(
-                                    (thread_id, checkpoint_ns, cp_id), {}
-                                )
-                                for (_task_id, _idx), (
-                                    tid,
-                                    ch,
-                                    serialized,
-                                    _,
-                                ) in sorted(step_writes.items(), reverse=True):
-                                    if ch != channel:
-                                        continue
-                                    collected.append(
-                                        (tid, ch, self.serde.loads_typed(serialized))
-                                    )
-                                collected.reverse()
-                                return _ChannelWritesHistory(
-                                    seed=blob_value, writes=collected
-                                )
-                            # Pre-delta blob: state AT this ancestor already
-                            # subsumes its pending_writes — skip them.
-                            collected.reverse()
-                            return _ChannelWritesHistory(
-                                seed=blob_value, writes=collected
-                            )
-
-            step_writes = self.writes.get((thread_id, checkpoint_ns, cp_id), {})
-            # Within a superstep, sorted by (task_id, idx) = oldest → newest;
-            # reverse for newest-first scan.
-            for (_task_id, _idx), (tid, ch, serialized, _) in sorted(
-                step_writes.items(), reverse=True
-            ):
-                if ch != channel:
-                    continue
-                val = self.serde.loads_typed(serialized)
-                collected.append((tid, ch, val))
-        collected.reverse()
-        return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=collected)
-
-    async def _aget_channel_writes_history(
-        self, config: RunnableConfig, channel: str
-    ) -> _ChannelWritesHistory:
-        return self._get_channel_writes_history(config, channel)
+        channel_values: dict[str, Any] = {}
+        for k, v in versions.items():
+            kk = (thread_id, checkpoint_ns, k, v)
+            if kk in self.blobs:
+                vv = self.blobs[kk]
+                if vv[0] != "empty":
+                    channel_values[k] = self.serde.loads_typed(vv)
+        return channel_values
 
     def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
         """Get a checkpoint tuple from the in-memory storage.

libs/checkpoint/langgraph/checkpoint/serde/_msgpack.py

@@ -73,7 +73,6 @@ SAFE_MSGPACK_TYPES: frozenset[tuple[str, ...]] = frozenset(
         ("langchain_core.documents.base", "Document"),
         # langgraph
         ("langgraph.types", "Send"),
-        ("langgraph.types", "TimeoutPolicy"),
         ("langgraph.types", "Interrupt"),
         ("langgraph.types", "Command"),
         ("langgraph.types", "StateSnapshot"),

libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py

@@ -33,18 +33,14 @@ from langchain_core.load.load import Reviver
 from langgraph.checkpoint.serde import _msgpack as _lg_msgpack
 from langgraph.checkpoint.serde.base import SerializerProtocol
 from langgraph.checkpoint.serde.event_hooks import emit_serde_event
-from langgraph.checkpoint.serde.types import (
-    DELTA_SENTINEL,
-    SendProtocol,
-    _DeltaSentinel,
-    _DeltaSnapshot,
-)
+from langgraph.checkpoint.serde.types import SendProtocol
 from langgraph.store.base import Item
 
 if TYPE_CHECKING:
     from langgraph.checkpoint.serde._msgpack import (
         AllowedMsgpackModules,
     )
+    from langgraph.checkpoint.serde.types import SendProtocol
 
 LC_REVIVER = Reviver()
 EMPTY_BYTES = b""
@@ -321,16 +317,10 @@ EXT_METHOD_SINGLE_ARG = 3
 EXT_PYDANTIC_V1 = 4
 EXT_PYDANTIC_V2 = 5
 EXT_NUMPY_ARRAY = 6
-EXT_DELTA_SNAPSHOT = 7
-EXT_DELTA_SENTINEL = 8
 
 
 def _msgpack_default(obj: Any) -> str | ormsgpack.Ext:
-    if isinstance(obj, _DeltaSnapshot):
-        return ormsgpack.Ext(EXT_DELTA_SNAPSHOT, _msgpack_enc(obj.value))
-    elif isinstance(obj, _DeltaSentinel):
-        return ormsgpack.Ext(EXT_DELTA_SENTINEL, b"")
-    elif hasattr(obj, "model_dump") and callable(obj.model_dump):  # pydantic v2
+    if hasattr(obj, "model_dump") and callable(obj.model_dump):  # pydantic v2
         return ormsgpack.Ext(
             EXT_PYDANTIC_V2,
             _msgpack_enc(
@@ -502,13 +492,10 @@ def _msgpack_default(obj: Any) -> str | ormsgpack.Ext:
             ),
         )
     elif isinstance(obj, SendProtocol):
-        args: tuple[Any, ...] = (obj.node, obj.arg)
-        if (timeout := getattr(obj, "timeout", None)) is not None:
-            args = (obj.node, obj.arg, timeout)
         return ormsgpack.Ext(
             EXT_CONSTRUCTOR_POS_ARGS,
             _msgpack_enc(
-                (obj.__class__.__module__, obj.__class__.__name__, args),
+                (obj.__class__.__module__, obj.__class__.__name__, (obj.node, obj.arg)),
             ),
         )
     elif dataclasses.is_dataclass(obj):
@@ -559,15 +546,6 @@ def _msgpack_default(obj: Any) -> str | ormsgpack.Ext:
         raise TypeError(f"Object of type {obj.__class__.__name__} is not serializable")
 
 
-def _send_from_args(args: Sequence[Any]) -> Any:
-    # ya we have a cyclic import here ¯\_(ツ)_/¯
-    from langgraph.types import Send  # type: ignore
-
-    if len(args) == 2:
-        return Send(*args)
-    return Send(args[0], args[1], timeout=args[2])
-
-
 def _create_msgpack_ext_hook(
     allowed_modules: set[tuple[str, ...]] | Literal[True] | None,
 ) -> Callable[[int, bytes], Any]:
@@ -656,15 +634,7 @@ def _create_msgpack_ext_hook(
         return False
 
     def ext_hook(code: int, data: bytes) -> Any:
-        if code == EXT_DELTA_SENTINEL:
-            return DELTA_SENTINEL
-        elif code == EXT_DELTA_SNAPSHOT:
-            return _DeltaSnapshot(
-                ormsgpack.unpackb(
-                    data, ext_hook=ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
-                )
-            )
-        elif code == EXT_CONSTRUCTOR_SINGLE_ARG:
+        if code == EXT_CONSTRUCTOR_SINGLE_ARG:
             try:
                 tup = ormsgpack.unpackb(
                     data, ext_hook=ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
@@ -685,8 +655,6 @@ def _create_msgpack_ext_hook(
                 )
                 if not _check_allowed(tup[0], tup[1]):
                     return tup[2]
-                if tup[0] == "langgraph.types" and tup[1] == "Send":
-                    return _send_from_args(tup[2])
                 # module, name, args
                 return getattr(importlib.import_module(tup[0]), tup[1])(*tup[2])
             except Exception:
@@ -800,7 +768,9 @@ def _msgpack_ext_hook_to_json(code: int, data: bytes) -> Any:
                 option=ormsgpack.OPT_NON_STR_KEYS,
             )
             if tup[0] == "langgraph.types" and tup[1] == "Send":
-                return _send_from_args(tup[2])
+                from langgraph.types import Send  # type: ignore
+
+                return Send(*tup[2])
             # module, name, args
             return tup[2]
         except Exception:

libs/checkpoint/langgraph/checkpoint/serde/types.py

@@ -1,7 +1,6 @@
 from collections.abc import Sequence
 from typing import (
     Any,
-    NamedTuple,
     Protocol,
     TypeVar,
     runtime_checkable,
@@ -15,39 +14,6 @@ INTERRUPT = "__interrupt__"
 RESUME = "__resume__"
 TASKS = "__pregel_tasks"
 
-
-class _DeltaSentinel:
-    """Singleton marker stored (as zero bytes) in checkpoint_blobs for a
-    DeltaChannel field. The actual per-step writes live in checkpoint_writes
-    and are replayed through the reducer at load time.
-
-    Compare with `is DELTA_SENTINEL` — `loads_typed` always returns the same
-    module-level instance.
-    """
-
-    __slots__ = ()
-
-    def __repr__(self) -> str:
-        return "DELTA_SENTINEL"
-
-
-DELTA_SENTINEL = _DeltaSentinel()
-
-
-class _DeltaSnapshot(NamedTuple):
-    """Snapshot blob for a DeltaChannel with finite snapshot_frequency.
-
-    Stored in checkpoint_blobs via the `EXT_DELTA_SNAPSHOT` msgpack ext code.
-    The ancestor walk in `_get_channel_writes_history` terminates when it
-    encounters this type (any non-sentinel blob stops the walk).
-
-    `from_checkpoint` reconstructs the channel value directly from `.value`
-    without replaying writes — the snapshot IS the accumulated state.
-    """
-
-    value: Any
-
-
 Value = TypeVar("Value", covariant=True)
 Update = TypeVar("Update", contravariant=True)
 C = TypeVar("C")

libs/checkpoint/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"
@@ -18,7 +18,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 
@@ -45,6 +45,9 @@ dev = [
   "pycryptodome>=3.23.0",
 ]
 
+[tool.uv.sources]
+langchain-core = { git = "https://github.com/langchain-ai/langchain", branch = "cb/chat-model-updates", subdirectory = "libs/core" }
+
 [tool.hatch.build.targets.wheel]
 include = ["langgraph"]
 

libs/checkpoint/tests/test_jsonplus.py

@@ -1048,15 +1048,3 @@ def test_msgpack_nested_pydantic_serializes_as_dict(
     # No blocking should occur - inner is serialized as dict, not ext
     assert "blocked" not in caplog.text.lower()
     assert result == obj
-
-
-def test_delta_sentinel_serde_round_trip() -> None:
-    from langgraph.checkpoint.base import DELTA_SENTINEL
-    from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
-
-    serde = JsonPlusSerializer()
-    type_tag, blob = serde.dumps_typed(DELTA_SENTINEL)
-    assert type_tag == "msgpack"
-    assert blob  # non-empty ext envelope
-    loaded = serde.loads_typed((type_tag, blob))
-    assert loaded is DELTA_SENTINEL

libs/checkpoint/tests/test_memory.py

@@ -6,7 +6,6 @@ from langchain_core.runnables import RunnableConfig
 from pydantic import BaseModel
 
 from langgraph.checkpoint.base import (
-    DELTA_SENTINEL,
     Checkpoint,
     CheckpointMetadata,
     create_checkpoint,
@@ -209,6 +208,8 @@ class TestMemorySaver:
 
 
 async def test_memory_saver() -> None:
+    from langgraph.checkpoint.memory import InMemorySaver
+
     memory_saver = InMemorySaver()
     assert isinstance(memory_saver, InMemorySaver)
 
@@ -319,347 +320,3 @@ def test_memory_saver_with_allowlist_proxy_isolated() -> None:
     assert direct is not None
     expected = obj.model_dump() if hasattr(obj, "model_dump") else obj.dict()
     assert direct.checkpoint["channel_values"]["foo"] == expected
-
-
-class TestInMemorySaverDeltaChannel:
-    def test_load_blobs_returns_sentinel_for_delta_channel(self) -> None:
-        """_load_blobs returns DELTA_SENTINEL for delta channels (reconstruction deferred)."""
-        saver = InMemorySaver()
-        serde = JsonPlusSerializer()
-
-        thread_id, ns, channel = "t1", "", "messages"
-        v1 = "00000000000000000000000000000001.0000000000000000"
-
-        saver.blobs[(thread_id, ns, channel, v1)] = serde.dumps_typed(DELTA_SENTINEL)
-
-        cp1 = empty_checkpoint()
-        cp1["id"] = "cp1"
-        cp1["channel_versions"][channel] = v1
-        saver.storage[thread_id][ns] = {
-            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
-        }
-
-        result = saver._load_blobs(thread_id, ns, {channel: v1})
-        assert channel in result
-        assert result[channel] is DELTA_SENTINEL
-
-    def test_get_channel_writes_collects_ancestor_writes_only(self) -> None:
-        """_get_channel_writes_history collects ancestor writes oldest→newest,
-        and excludes writes stored at the target checkpoint itself (those are
-        pending writes for the next step, applied separately by pregel)."""
-        saver = InMemorySaver()
-        serde = JsonPlusSerializer()
-
-        thread_id, ns, channel = "t1", "", "messages"
-
-        cp1 = empty_checkpoint()
-        cp1["id"] = "cp1"
-        cp2 = empty_checkpoint()
-        cp2["id"] = "cp2"
-        saver.storage[thread_id][ns] = {
-            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
-            "cp2": (serde.dumps_typed(cp2), serde.dumps_typed({}), "cp1"),
-        }
-        # Writes stored at cp1 produced the cp1 snapshot; part of history.
-        saver.writes[(thread_id, ns, "cp1")][("task1", 0)] = (
-            "task1",
-            channel,
-            serde.dumps_typed({"content": "hi"}),
-            "",
-        )
-        # Writes stored at cp2 are pending — they will produce cp3 when the
-        # step that loaded cp2 completes. They MUST NOT appear in the
-        # reconstructed snapshot value at cp2.
-        saver.writes[(thread_id, ns, "cp2")][("task2", 0)] = (
-            "task2",
-            channel,
-            serde.dumps_typed({"content": "pending"}),
-            "",
-        )
-
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": "cp2",
-            }
-        }
-        result = saver._get_channel_writes_history(config, channel)
-        assert result.seed is DELTA_SENTINEL
-        values = [v for _, _, v in result.writes]
-        assert values == [{"content": "hi"}]
-
-    def test_get_channel_writes_at_root_returns_empty(self) -> None:
-        """Reconstructing the root checkpoint's state: no ancestors → []."""
-        saver = InMemorySaver()
-        serde = JsonPlusSerializer()
-        thread_id, ns, channel = "t1", "", "messages"
-
-        cp1 = empty_checkpoint()
-        cp1["id"] = "cp1"
-        saver.storage[thread_id][ns] = {
-            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
-        }
-        saver.writes[(thread_id, ns, "cp1")][("task1", 0)] = (
-            "task1",
-            channel,
-            serde.dumps_typed({"content": "pending"}),
-            "",
-        )
-
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": "cp1",
-            }
-        }
-        result = saver._get_channel_writes_history(config, channel)
-        assert result.seed is DELTA_SENTINEL
-        assert result.writes == []
-
-
-class TestBaseFallbackGetChannelWrites:
-    """Exercises the `BaseCheckpointSaver._get_channel_writes_history` default
-    implementation — the path third-party savers inherit when they don't
-    override `_get_channel_writes_history` themselves.
-
-    Regression guard for a bug where the fallback passed the caller's config
-    (with `checkpoint_id`) straight to `self.list()`, which most savers
-    collapse to a single row — causing the fallback to return `[]`.
-    """
-
-    def _build_saver_with_chain(self) -> tuple[InMemorySaver, str, str]:
-        """Build an InMemorySaver with a 3-checkpoint chain and per-step writes
-        for a `messages` channel.
-
-        Returns `(saver, thread_id, namespace)`. The saver subclass deletes the
-        InMemorySaver override so the base class fallback is exercised.
-        """
-
-        class _ThirdPartyStyleSaver(InMemorySaver):
-            _get_channel_writes_history = (
-                InMemorySaver.__mro__[1]._get_channel_writes_history  # type: ignore[attr-defined]
-            )
-            _aget_channel_writes_history = (
-                InMemorySaver.__mro__[1]._aget_channel_writes_history  # type: ignore[attr-defined]
-            )
-
-        saver = _ThirdPartyStyleSaver()
-        serde = JsonPlusSerializer()
-        thread_id, ns, channel = "t1", "", "messages"
-
-        cp0 = empty_checkpoint()
-        cp0["id"] = "00000000000000000000000000000001.0000000000000000"
-        cp1 = empty_checkpoint()
-        cp1["id"] = "00000000000000000000000000000002.0000000000000000"
-        cp2 = empty_checkpoint()
-        cp2["id"] = "00000000000000000000000000000003.0000000000000000"
-        saver.storage[thread_id][ns] = {
-            cp0["id"]: (serde.dumps_typed(cp0), serde.dumps_typed({}), None),
-            cp1["id"]: (serde.dumps_typed(cp1), serde.dumps_typed({}), cp0["id"]),
-            cp2["id"]: (serde.dumps_typed(cp2), serde.dumps_typed({}), cp1["id"]),
-        }
-        # Writes under cp0 produced cp1's state; writes under cp1 produced cp2's.
-        saver.writes[(thread_id, ns, cp0["id"])][("task1", 0)] = (
-            "task1",
-            channel,
-            serde.dumps_typed({"content": "first"}),
-            "",
-        )
-        saver.writes[(thread_id, ns, cp1["id"])][("task2", 0)] = (
-            "task2",
-            channel,
-            serde.dumps_typed({"content": "second"}),
-            "",
-        )
-        return saver, thread_id, ns
-
-    def test_fallback_returns_ancestor_writes_oldest_first(self) -> None:
-        saver, thread_id, ns = self._build_saver_with_chain()
-        target_id = "00000000000000000000000000000003.0000000000000000"
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": target_id,
-            }
-        }
-
-        result = saver._get_channel_writes_history(config, "messages")
-
-        assert result.seed is DELTA_SENTINEL
-        values = [v for _, _, v in result.writes]
-        assert values == [{"content": "first"}, {"content": "second"}]
-
-    async def test_async_fallback_returns_ancestor_writes_oldest_first(self) -> None:
-        saver, thread_id, ns = self._build_saver_with_chain()
-        target_id = "00000000000000000000000000000003.0000000000000000"
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": target_id,
-            }
-        }
-
-        result = await saver._aget_channel_writes_history(config, "messages")
-
-        assert result.seed is DELTA_SENTINEL
-        values = [v for _, _, v in result.writes]
-        assert values == [{"content": "first"}, {"content": "second"}]
-
-    async def test_async_fallback_concurrent_tasks_do_not_interfere(self) -> None:
-        """Regression: the re-entrancy guard must be task-local, not thread-local.
-
-        Two concurrent `_aget_channel_writes_history` calls on the same
-        event-loop thread must each see their full reconstructed writes. A
-        `threading.local()` guard would let whichever task set it first
-        short-circuit the other to `writes=[]`.
-        """
-        import asyncio
-
-        saver, thread_id, ns = self._build_saver_with_chain()
-
-        # Force the two tasks to interleave across the `set(True)` boundary:
-        # each `aget_tuple` yields control, so if the guard were thread-local
-        # the second task would observe `active=True` set by the first.
-        orig_aget_tuple = saver.aget_tuple
-
-        async def slow_aget_tuple(config: RunnableConfig) -> Any:
-            await asyncio.sleep(0)
-            return await orig_aget_tuple(config)
-
-        saver.aget_tuple = slow_aget_tuple  # type: ignore[method-assign]
-
-        target_id = "00000000000000000000000000000003.0000000000000000"
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": target_id,
-            }
-        }
-
-        results = await asyncio.gather(
-            saver._aget_channel_writes_history(config, "messages"),
-            saver._aget_channel_writes_history(config, "messages"),
-        )
-
-        expected_values = [{"content": "first"}, {"content": "second"}]
-        for result in results:
-            assert result.seed is DELTA_SENTINEL
-            values = [v for _, _, v in result.writes]
-            assert values == expected_values
-
-
-class TestPreDeltaBlobTerminator:
-    """Verify the pre-delta blob terminator: when the ancestor walk hits a
-    checkpoint whose blob for the channel is a real value (not
-    DELTA_SENTINEL), reconstruction seeds from it and stops. This guards
-
-      * back-compat: a thread written by pre-delta code, then extended under
-        delta — reconstruction must return the correct value without walking
-        past the last pre-delta ancestor;
-      * perf: without the terminator, every reconstruct-after-migration would
-        walk all the way to the thread root.
-    """
-
-    def _build_mixed_thread(self) -> tuple[InMemorySaver, str, str, str, str]:
-        """Three-checkpoint chain: cp1 (pre-delta, blob=[A]), cp2 (delta,
-        write=B), cp3 (delta, write=C). Reconstructing at cp3 must yield
-        seed=[A] + writes=[B, C].
-
-        Returns `(saver, thread_id, ns, channel, cp3_id)`.
-        """
-        saver = InMemorySaver()
-        serde = JsonPlusSerializer()
-        thread_id, ns, channel = "t1", "", "messages"
-
-        v1 = "00000000000000000000000000000001.0"
-        v2 = "00000000000000000000000000000002.0"
-        v3 = "00000000000000000000000000000003.0"
-
-        # Pre-delta: cp1 stored a real blob for the channel.
-        saver.blobs[(thread_id, ns, channel, v1)] = serde.dumps_typed(["A"])
-        # Delta-era: cp2 and cp3 store sentinels; real writes in checkpoint_writes.
-        saver.blobs[(thread_id, ns, channel, v2)] = serde.dumps_typed(DELTA_SENTINEL)
-        saver.blobs[(thread_id, ns, channel, v3)] = serde.dumps_typed(DELTA_SENTINEL)
-
-        cp1 = empty_checkpoint()
-        cp1["id"] = "cp1"
-        cp1["channel_versions"][channel] = v1
-        cp2 = empty_checkpoint()
-        cp2["id"] = "cp2"
-        cp2["channel_versions"][channel] = v2
-        cp3 = empty_checkpoint()
-        cp3["id"] = "cp3"
-        cp3["channel_versions"][channel] = v3
-
-        saver.storage[thread_id][ns] = {
-            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
-            "cp2": (serde.dumps_typed(cp2), serde.dumps_typed({}), "cp1"),
-            "cp3": (serde.dumps_typed(cp3), serde.dumps_typed({}), "cp2"),
-        }
-        # Write under cp1 would be from the pre-delta era and MUST be ignored
-        # (the blob already captures it). We add one and assert it is not
-        # folded into the reconstructed result.
-        saver.writes[(thread_id, ns, "cp1")][("task0", 0)] = (
-            "task0",
-            channel,
-            serde.dumps_typed("PRE-DELTA-WRITE"),
-            "",
-        )
-        saver.writes[(thread_id, ns, "cp2")][("task2", 0)] = (
-            "task2",
-            channel,
-            serde.dumps_typed("B"),
-            "",
-        )
-        saver.writes[(thread_id, ns, "cp3")][("task3", 0)] = (
-            "task3",
-            channel,
-            serde.dumps_typed("PENDING-AT-TARGET"),
-            "",
-        )
-        return saver, thread_id, ns, channel, "cp3"
-
-    def test_seed_from_pre_delta_ancestor_blob(self) -> None:
-        saver, thread_id, ns, channel, target = self._build_mixed_thread()
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": target,
-            }
-        }
-
-        result = saver._get_channel_writes_history(config, channel)
-
-        # Seed came from the pre-delta blob at cp1.
-        assert result.seed == ["A"]
-        # Delta-era writes from cp2 replay through the reducer on top of seed.
-        # cp3 is the target — its own write is pending for the NEXT step and
-        # must be excluded.
-        values = [v for _, _, v in result.writes]
-        assert values == ["B"]
-
-    def test_pre_delta_blob_terminates_walk_before_older_writes(self) -> None:
-        """Writes stored at the pre-delta ancestor itself must not be replayed
-        (the blob subsumes them)."""
-        saver, thread_id, ns, channel, target = self._build_mixed_thread()
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": target,
-            }
-        }
-
-        result = saver._get_channel_writes_history(config, channel)
-
-        values = [v for _, _, v in result.writes]
-        # The pre-delta write under cp1 must not appear (the blob subsumes it).
-        assert "PRE-DELTA-WRITE" not in values
-        # And the pending write at the target is never folded in.
-        assert "PENDING-AT-TARGET" not in values

libs/checkpoint/uv.lock

@@ -267,10 +267,11 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.28"
-source = { registry = "https://pypi.org/simple" }
+version = "1.3.2"
+source = { git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates#aee50839376e379891c99fcbe6d5264f66dedc68" }
 dependencies = [
     { name = "jsonpatch" },
+    { name = "langchain-protocol" },
     { name = "langsmith" },
     { name = "packaging" },
     { name = "pydantic" },
@@ -279,14 +280,22 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
+
+[[package]]
+name = "langchain-protocol"
+version = "0.0.14"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/a8/92/32f785f077c7e898da97064f113c73fbd9ad55d1e2169cf3a391b183dedb/langchain_core-1.2.28-py3-none-any.whl", hash = "sha256:80764232581eaf8057bcefa71dbf8adc1f6a28d257ebd8b95ba9b8b452e8c6ac", size = 508727, upload-time = "2026-04-08T18:19:32.823Z" },
+    { url = "https://files.pythonhosted.org/packages/c2/e9/06c47ecb2aff08f83dfa30058da3bf86be64862c19569043ed5331bbeecd/langchain_protocol-0.0.14-py3-none-any.whl", hash = "sha256:ffc35089779bd8ca217015180cef5e660fc3b074efdaa0f2e95df73583f1a047", size = 6984, upload-time = "2026-04-29T16:40:17.841Z" },
 ]
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -330,7 +339,7 @@ test = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.2.38" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "ormsgpack", specifier = ">=1.12.0" },
 ]
 

libs/cli/pyproject.toml

@@ -29,7 +29,7 @@ inmem = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/cli"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/langgraph/README.md

@@ -18,7 +18,7 @@
   <a href="https://pypi.org/project/langgraph/" target="_blank"><img src="https://img.shields.io/pypi/v/langgraph.svg?label=%20" alt="Version"></a>
   <a href="https://github.com/langchain-ai/langgraph/issues" target="_blank"><img src="https://img.shields.io/github/issues-raw/langchain-ai/langgraph" alt="Open Issues"></a>
   <a href="https://docs.langchain.com/oss/python/langgraph/overview" target="_blank"><img src="https://img.shields.io/badge/docs-latest-blue" alt="Docs"></a>
-  <a href="https://x.com/langchain_oss" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain_oss.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
+  <a href="https://x.com/langchain" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
 </div>
 
 <br>

libs/langgraph/langgraph/_internal/_constants.py

@@ -56,8 +56,6 @@ CONFIG_KEY_CHECKPOINT_NS = sys.intern("checkpoint_ns")
 # holds the current checkpoint_ns, "" for root graph
 CONFIG_KEY_NODE_FINISHED = sys.intern("__pregel_node_finished")
 # holds a callback to be called when a node is finished
-CONFIG_KEY_TIMED_ATTEMPT_OBSERVER = sys.intern("__pregel_timed_attempt_observer")
-# holds a callback to be called when an idle-timed node attempt starts or finishes
 CONFIG_KEY_SCRATCHPAD = sys.intern("__pregel_scratchpad")
 # holds a mutable dict for temporary storage scoped to the current task
 CONFIG_KEY_RUNNER_SUBMIT = sys.intern("__pregel_runner_submit")
@@ -111,7 +109,6 @@ RESERVED = {
     CONFIG_KEY_CHECKPOINT_MAP,
     CONFIG_KEY_CHECKPOINT_ID,
     CONFIG_KEY_CHECKPOINT_NS,
-    CONFIG_KEY_TIMED_ATTEMPT_OBSERVER,
     CONFIG_KEY_RESUME_MAP,
     CONFIG_KEY_STREAM_MESSAGES_V2,
     # other constants

libs/langgraph/langgraph/_internal/_runnable.py

@@ -117,19 +117,6 @@ def set_config_context(
         ctx.run(_unset_config_context, config_token, run)
 
 
-def create_task_in_config_context(
-    coro_factory: Callable[[], Coroutine[Any, Any, Any]], config: RunnableConfig
-) -> asyncio.Task[Any]:
-    """Create an asyncio.Task that inherits `config` as the child runnable context.
-
-    `asyncio.create_task` snapshots the current contextvars onto the new task,
-    so calling `create_task` while the config context is set ensures the task
-    sees `config` via `var_child_runnable_config` and any tracing parent.
-    """
-    with set_config_context(config) as context:
-        return context.run(lambda: asyncio.create_task(coro_factory()))
-
-
 # Before Python 3.11 native StrEnum is not available
 class StrEnum(str, enum.Enum):
     """A string enum."""

libs/langgraph/langgraph/_internal/_timeout.py

@@ -1,25 +0,0 @@
-from __future__ import annotations
-
-from datetime import timedelta
-from typing import Literal
-
-from langgraph.types import TimeoutPolicy
-
-_SYNC_TIMEOUT_PREFIX = (
-    "Node timeouts are only supported for async nodes because sync Python "
-    "execution cannot be safely cancelled in-process."
-)
-
-
-def coerce_timeout_policy(
-    value: float | timedelta | TimeoutPolicy | None,
-) -> TimeoutPolicy | None:
-    """Normalize a timeout value to positive-second policy fields."""
-    return TimeoutPolicy.coerce(value)
-
-
-def sync_timeout_unsupported(
-    name: str, *, kind: Literal["Node", "Task"] = "Node"
-) -> ValueError:
-    """Build the canonical error for using `timeout` with a sync target."""
-    return ValueError(f"{_SYNC_TIMEOUT_PREFIX} {kind} {name!r} is sync.")

libs/langgraph/langgraph/channels/__init__.py

@@ -1,7 +1,6 @@
 from langgraph.channels.any_value import AnyValue
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.binop import BinaryOperatorAggregate
-from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue, LastValueAfterFinish
 from langgraph.channels.named_barrier_value import (
@@ -21,7 +20,6 @@ __all__ = (
     "UntrackedValue",
     "EphemeralValue",
     "BinaryOperatorAggregate",
-    "DeltaChannel",
     "NamedBarrierValue",
     "NamedBarrierValueAfterFinish",
     # topics

libs/langgraph/langgraph/channels/binop.py

@@ -22,9 +22,10 @@ __all__ = ("BinaryOperatorAggregate",)
 def _strip_extras(t):  # type: ignore[no-untyped-def]
     """Strips Annotated, Required and NotRequired from a given type."""
     if hasattr(t, "__origin__"):
-        if t.__origin__ in (Required, NotRequired):
-            return _strip_extras(t.__args__[0])
         return _strip_extras(t.__origin__)
+    if hasattr(t, "__origin__") and t.__origin__ in (Required, NotRequired):
+        return _strip_extras(t.__args__[0])
+
     return t
 
 
@@ -32,22 +33,11 @@ def _get_overwrite(value: Any) -> tuple[bool, Any]:
     """Inspects the given value and returns (is_overwrite, overwrite_value)."""
     if isinstance(value, Overwrite):
         return True, value.value
-    if isinstance(value, dict) and len(value) == 1 and OVERWRITE in value:
+    if isinstance(value, dict) and set(value.keys()) == {OVERWRITE}:
         return True, value[OVERWRITE]
     return False, None
 
 
-def _operators_equal(a: Callable, b: Callable) -> bool:
-    """Return True if two reducer operators should be considered equal.
-
-    Lambdas all share the name '<lambda>' so identity comparison is
-    unreliable; treat any pairing that includes a lambda as equal.
-    """
-    if a.__name__ == "<lambda>" or b.__name__ == "<lambda>":
-        return True
-    return a is b
-
-
 class BinaryOperatorAggregate(Generic[Value], BaseChannel[Value, Value, Value]):
     """Stores the result of applying a binary operator to the current value and each new value.
 
@@ -78,8 +68,11 @@ class BinaryOperatorAggregate(Generic[Value], BaseChannel[Value, Value, Value]):
             self.value = MISSING
 
     def __eq__(self, value: object) -> bool:
-        return isinstance(value, BinaryOperatorAggregate) and _operators_equal(
-            self.operator, value.operator
+        return isinstance(value, BinaryOperatorAggregate) and (
+            value.operator is self.operator
+            if value.operator.__name__ != "<lambda>"
+            and self.operator.__name__ != "<lambda>"
+            else True
         )
 
     @property

libs/langgraph/langgraph/channels/delta.py

@@ -1,197 +0,0 @@
-from __future__ import annotations
-
-import collections.abc
-import copy as _copy
-from collections.abc import Callable, Sequence
-from typing import Any, Generic
-
-from langgraph.checkpoint.base import DELTA_SENTINEL, PendingWrite
-from langgraph.checkpoint.serde.types import _DeltaSnapshot
-from typing_extensions import Self
-
-from langgraph._internal._typing import MISSING
-from langgraph.channels.base import BaseChannel, Value
-from langgraph.channels.binop import _get_overwrite, _operators_equal, _strip_extras
-from langgraph.errors import (
-    EmptyChannelError,
-    ErrorCode,
-    InvalidUpdateError,
-    create_error_message,
-)
-
-__all__ = ("DeltaChannel",)
-
-
-class DeltaChannel(Generic[Value], BaseChannel[Any, Any, Any]):
-    """Reducer channel that stores only a sentinel in checkpoint blobs and
-    reconstructs state by replaying ancestor writes through the reducer.
-
-    The reducer receives the current accumulated value and a batch of writes
-    in one call: `reducer(state, [write1, write2, ...]) -> new_state`.
-
-    Reducers must be deterministic and batching-invariant (associative across
-    folds): applying two consecutive write batches separately must produce the
-    same state as applying their concatenation once:
-
-        reducer(reducer(state, xs), ys) == reducer(state, xs + ys)
-
-    This lets LangGraph replay checkpointed writes in larger batches than they
-    were originally produced without changing reconstructed state.
-
-    `snapshot_frequency=None` (default): pure delta; stores only
-    `DELTA_SENTINEL` in checkpoint blobs; reads replay all ancestor writes.
-
-    `snapshot_frequency=N`: `create_checkpoint` writes a full `_DeltaSnapshot`
-    blob every N steps, bounding replay depth to N.
-
-    Parameters:
-        reducer: `(state, list[writes]) -> new_state`. Must be deterministic
-            and batching-invariant as described above.
-        typ: The value type (e.g. `list`, `dict`). Inferred automatically
-            from the outer type when used inside `Annotated[T, DeltaChannel(...)]`.
-        snapshot_frequency: Every Nth pregel step writes a snapshot blob.
-            `None` (default) = pure delta, never snapshot.
-    """
-
-    __slots__ = ("value", "reducer", "snapshot_frequency")
-    value: Value | Any
-
-    def __init__(
-        self,
-        reducer: Callable[[Any, Sequence[Any]], Any],
-        typ: type[Value] | None = None,
-        *,
-        snapshot_frequency: int | None = None,
-    ) -> None:
-        if typ is None:
-            typ = list  # type: ignore[assignment]  # placeholder; overridden by _is_field_channel
-        super().__init__(typ)
-        self.reducer = reducer
-        self.snapshot_frequency = snapshot_frequency
-        typ = _strip_extras(typ)
-        if typ in (collections.abc.Sequence, collections.abc.MutableSequence):
-            typ = list
-        if typ in (collections.abc.Set, collections.abc.MutableSet):
-            typ = set
-        if typ in (collections.abc.Mapping, collections.abc.MutableMapping):
-            typ = dict
-        self.typ = typ
-        self.value: Any = MISSING
-
-    def __eq__(self, other: object) -> bool:
-        if not isinstance(other, DeltaChannel):
-            return False
-        if self.snapshot_frequency != other.snapshot_frequency:
-            return False
-        return _operators_equal(self.reducer, other.reducer)
-
-    @property
-    def ValueType(self) -> Any:
-        return self.typ
-
-    @property
-    def UpdateType(self) -> Any:
-        return self.typ
-
-    def is_snapshot_step(self, step: int) -> bool:
-        """True if pregel should write a snapshot blob at this step."""
-        return (
-            self.snapshot_frequency is not None
-            and step > 0
-            and step % self.snapshot_frequency == 0
-        )
-
-    def copy(self) -> Self:
-        new = self.__class__(
-            self.reducer, self.typ, snapshot_frequency=self.snapshot_frequency
-        )
-        new.key = self.key
-        new.value = self.value if self.value is MISSING else _copy.copy(self.value)
-        return new
-
-    def from_checkpoint(self, checkpoint: Any) -> Self:
-        """Initialize from a stored blob or sentinel.
-
-        Blob types (dispatched via serde ext code, not dict key inspection):
-          * `DELTA_SENTINEL` / `MISSING`: start empty; caller replays writes.
-          * `_DeltaSnapshot(value)`: restore value directly from snapshot.
-          * plain value (migration from old BinOp blobs): use directly.
-        """
-        new = self.__class__(
-            self.reducer, self.typ, snapshot_frequency=self.snapshot_frequency
-        )
-        new.key = self.key
-        if checkpoint is MISSING or checkpoint is DELTA_SENTINEL:
-            new.value = self.typ()
-        elif isinstance(checkpoint, _DeltaSnapshot):
-            new.value = checkpoint.value
-        else:
-            new.value = checkpoint
-        return new
-
-    def replay_writes(self, writes: Sequence[PendingWrite]) -> None:
-        """Apply ancestor writes oldest-to-newest via a single reducer call.
-
-        If any write is an Overwrite, the last one in the sequence acts as
-        the reset point: its value becomes the new base and only writes
-        after it are passed to the reducer.
-        """
-        values = [v for _, _, v in writes]
-        if not values:
-            return
-        base = self.value
-        start = 0
-        for i, v in enumerate(values):
-            is_ow, ow_value = _get_overwrite(v)
-            if is_ow:
-                base = _copy.copy(ow_value) if ow_value is not None else self.typ()
-                start = i + 1
-        remaining = values[start:]
-        self.value = self.reducer(base, remaining) if remaining else base
-
-    def update(self, values: Sequence[Any]) -> bool:
-        if not values:
-            return False
-        overwrite_idx: int | None = None
-        for i, v in enumerate(values):
-            is_ow, _ = _get_overwrite(v)
-            if is_ow:
-                if overwrite_idx is not None:
-                    msg = create_error_message(
-                        message="Can receive only one Overwrite value per super-step.",
-                        error_code=ErrorCode.INVALID_CONCURRENT_GRAPH_UPDATE,
-                    )
-                    raise InvalidUpdateError(msg)
-                overwrite_idx = i
-        if overwrite_idx is not None:
-            _, overwrite_value = _get_overwrite(values[overwrite_idx])
-            base = (
-                _copy.copy(overwrite_value)
-                if overwrite_value is not None
-                else self.typ()
-            )
-            remaining = [v for i, v in enumerate(values) if i != overwrite_idx]
-            self.value = self.reducer(base, remaining) if remaining else base
-            return True
-        base = self.typ() if self.value is MISSING else self.value
-        self.value = self.reducer(base, list(values))
-        return True
-
-    def get(self) -> Any:
-        if self.value is MISSING:
-            raise EmptyChannelError()
-        return self.value
-
-    def is_available(self) -> bool:
-        return self.value is not MISSING
-
-    def checkpoint(self) -> Any:
-        """Return stored representation: always `DELTA_SENTINEL`.
-
-        Snapshot decisions are made by `create_checkpoint` in pregel (which
-        has the step number) via `is_snapshot_step`. `checkpoint()` is only
-        called for non-snapshot steps or when no checkpointer is available.
-        """
-        if self.value is MISSING:
-            return MISSING
-        return DELTA_SENTINEL

libs/langgraph/langgraph/errors.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from collections.abc import Sequence
 from enum import Enum
-from typing import Any, Literal
+from typing import Any
 from warnings import warn
 
 # EmptyChannelError is re-exported from langgraph.channels.base
@@ -15,13 +15,11 @@ from langgraph.warnings import LangGraphDeprecatedSinceV10
 __all__ = (
     "EmptyChannelError",
     "ErrorCode",
-    "GraphDrained",
     "GraphRecursionError",
     "InvalidUpdateError",
     "GraphBubbleUp",
     "GraphInterrupt",
     "NodeInterrupt",
-    "NodeTimeoutError",
     "ParentCommand",
     "EmptyInputError",
     "TaskNotFound",
@@ -44,23 +42,6 @@ def create_error_message(*, message: str, error_code: ErrorCode) -> str:
     )
 
 
-class GraphBubbleUp(Exception):
-    pass
-
-
-class GraphDrained(GraphBubbleUp):
-    """Raised when a graph run exits early due to a drain request.
-
-    This indicates the graph stopped cooperatively at a superstep boundary
-    because `RunControl.request_drain()` was called (e.g., in response to
-    SIGTERM). The checkpoint is saved and the run can be resumed later.
-    """
-
-    def __init__(self, reason: str = "shutdown") -> None:
-        self.reason = reason
-        super().__init__(f"Graph drained: {reason}")
-
-
 class GraphRecursionError(RecursionError):
     """Raised when the graph has exhausted the maximum number of steps.
 
@@ -96,6 +77,10 @@ class InvalidUpdateError(Exception):
     pass
 
 
+class GraphBubbleUp(Exception):
+    pass
+
+
 class GraphInterrupt(GraphBubbleUp):
     """Raised when a subgraph is interrupted, suppressed by the root graph.
     Never raised directly, or surfaced to the user."""
@@ -140,58 +125,3 @@ class TaskNotFound(Exception):
     """Raised when the executor is unable to find a task (for distributed mode)."""
 
     pass
-
-
-class NodeTimeoutError(TimeoutError):
-    """Raised when a node invocation exceeds one of its configured timeouts.
-
-    Subclasses the built-in `TimeoutError`, so existing `except TimeoutError`
-    handlers keep working. If the node has a `retry_policy` whose `retry_on`
-    permits `TimeoutError`, the attempt will be retried.
-
-    Both `idle_timeout` and `run_timeout` reflect the configured policy at the
-    time of the failure (each is `None` if not configured). `kind` and
-    `timeout` identify which one fired.
-    """
-
-    node: str
-    timeout: float
-    run_timeout: float | None
-    idle_timeout: float | None
-    elapsed: float
-    kind: Literal["idle", "run"]
-
-    def __init__(
-        self,
-        node: str,
-        elapsed: float,
-        *,
-        kind: Literal["idle", "run"],
-        idle_timeout: float | None = None,
-        run_timeout: float | None = None,
-    ) -> None:
-        if kind == "idle":
-            if idle_timeout is None:
-                raise ValueError("idle_timeout is required when kind='idle'")
-            message = (
-                f"Node '{node}' exceeded its idle timeout of "
-                f"{idle_timeout:.3f}s without making progress "
-                f"(elapsed: {elapsed:.3f}s)."
-            )
-            self.timeout = idle_timeout
-        elif kind == "run":
-            if run_timeout is None:
-                raise ValueError("run_timeout is required when kind='run'")
-            message = (
-                f"Node '{node}' exceeded its run timeout of "
-                f"{run_timeout:.3f}s (elapsed: {elapsed:.3f}s)."
-            )
-            self.timeout = run_timeout
-        else:
-            raise ValueError("kind must be 'idle' or 'run'")
-        super().__init__(message)
-        self.node = node
-        self.elapsed = elapsed
-        self.kind = kind
-        self.idle_timeout = idle_timeout
-        self.run_timeout = run_timeout

libs/langgraph/langgraph/func/__init__.py

@@ -5,7 +5,6 @@ import inspect
 import warnings
 from collections.abc import Awaitable, Callable, Sequence
 from dataclasses import dataclass
-from datetime import timedelta
 from typing import (
     Any,
     Generic,
@@ -23,11 +22,6 @@ from typing_extensions import Unpack
 
 from langgraph._internal import _serde
 from langgraph._internal._constants import CACHE_NS_WRITES, PREVIOUS
-from langgraph._internal._runnable import is_async_callable
-from langgraph._internal._timeout import (
-    coerce_timeout_policy,
-    sync_timeout_unsupported,
-)
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue
@@ -37,19 +31,13 @@ from langgraph.pregel._call import (
     P,
     SyncAsyncFuture,
     T,
-    _call_with_options,
+    call,
     get_runnable_for_entrypoint,
     identifier,
 )
 from langgraph.pregel._read import PregelNode
 from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
-from langgraph.types import (
-    _DC_KWARGS,
-    CachePolicy,
-    RetryPolicy,
-    StreamMode,
-    TimeoutPolicy,
-)
+from langgraph.types import _DC_KWARGS, CachePolicy, RetryPolicy, StreamMode
 from langgraph.typing import ContextT
 from langgraph.warnings import LangGraphDeprecatedSinceV05, LangGraphDeprecatedSinceV10
 
@@ -63,7 +51,6 @@ class _TaskFunction(Generic[P, T]):
         *,
         retry_policy: Sequence[RetryPolicy],
         cache_policy: CachePolicy[Callable[P, str | bytes]] | None = None,
-        timeout: TimeoutPolicy | None = None,
         name: str | None = None,
     ) -> None:
         if name is not None:
@@ -80,17 +67,15 @@ class _TaskFunction(Generic[P, T]):
         self.func = func
         self.retry_policy = retry_policy
         self.cache_policy = cache_policy
-        self.timeout = timeout
         functools.update_wrapper(self, func)
 
     def __call__(self, *args: P.args, **kwargs: P.kwargs) -> SyncAsyncFuture[T]:
-        return _call_with_options(
+        return call(
             self.func,
-            args,
-            kwargs,
             retry_policy=self.retry_policy,
             cache_policy=self.cache_policy,
-            timeout=self.timeout,
+            *args,
+            **kwargs,
         )
 
     def clear_cache(self, cache: BaseCache) -> None:
@@ -113,7 +98,6 @@ def task(
     name: str | None = None,
     retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy[Callable[P, str | bytes]] | None = None,
-    timeout: float | timedelta | TimeoutPolicy | None = None,
     **kwargs: Unpack[DeprecatedKwargs],
 ) -> Callable[
     [Callable[P, Awaitable[T]] | Callable[P, T]],
@@ -135,7 +119,6 @@ def task(
     name: str | None = None,
     retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy[Callable[P, str | bytes]] | None = None,
-    timeout: float | timedelta | TimeoutPolicy | None = None,
     **kwargs: Unpack[DeprecatedKwargs],
 ) -> (
     Callable[[Callable[P, Awaitable[T]] | Callable[P, T]], _TaskFunction[P, T]]
@@ -159,14 +142,6 @@ def task(
         name: An optional name for the task. If not provided, the function name will be used.
         retry_policy: An optional retry policy (or list of policies) to use for the task in case of a failure.
         cache_policy: An optional cache policy to use for the task. This allows caching of the task results.
-        timeout: Timeout for each task attempt. A number or `timedelta` is a hard
-            wall-clock cap and is not refreshed. Use `TimeoutPolicy` to configure
-            both a wall-clock `run_timeout` and an `idle_timeout` refreshed by
-            progress signals. For long-running work that doesn't naturally emit
-            progress, call `runtime.heartbeat()` from inside the task. When the
-            timeout fires, `NodeTimeoutError` is raised and the retry policy (if
-            any) decides whether to retry. Supported only for async tasks; sync
-            tasks cannot be safely cancelled in-process.
 
     Returns:
         A callable function when used as a decorator.
@@ -221,7 +196,6 @@ def task(
         )
         if retry_policy is None:
             retry_policy = retry  # type: ignore[assignment]
-    timeout_policy = coerce_timeout_policy(timeout)
 
     retry_policies: Sequence[RetryPolicy] = (
         ()
@@ -234,15 +208,8 @@ def task(
     def decorator(
         func: Callable[P, Awaitable[T]] | Callable[P, T],
     ) -> Callable[P, SyncAsyncFuture[T]]:
-        if timeout_policy is not None and not is_async_callable(func):
-            name_ = name or getattr(func, "__name__", func.__class__.__name__)
-            raise sync_timeout_unsupported(str(name_), kind="Task")
         return _TaskFunction(
-            func,
-            retry_policy=retry_policies,
-            cache_policy=cache_policy,
-            timeout=timeout_policy,
-            name=name,
+            func, retry_policy=retry_policies, cache_policy=cache_policy, name=name
         )
 
     if __func_or_none__ is not None:
@@ -301,15 +268,6 @@ class entrypoint(Generic[ContextT]):
             passed to the workflow.
         cache_policy: A cache policy to use for caching the results of the workflow.
         retry_policy: A retry policy (or list of policies) to use for the workflow in case of a failure.
-        timeout: Timeout for each workflow attempt. A number or `timedelta` is a
-            hard wall-clock cap and is not refreshed. Use `TimeoutPolicy` to
-            configure both a wall-clock `run_timeout` and an `idle_timeout`
-            refreshed by progress signals. For long-running work that doesn't
-            naturally emit progress, call `runtime.heartbeat()` from inside the
-            workflow. When the timeout fires, `NodeTimeoutError` is raised and
-            the retry policy (if any) decides whether to retry. Supported only
-            for async workflows; sync workflows cannot be safely cancelled
-            in-process.
 
     !!! warning "`config_schema` Deprecated"
         The `config_schema` parameter is deprecated in v0.6.0 and support will be removed in v2.0.0.
@@ -442,7 +400,6 @@ class entrypoint(Generic[ContextT]):
         context_schema: type[ContextT] | None = None,
         cache_policy: CachePolicy | None = None,
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> None:
         """Initialize the entrypoint decorator."""
@@ -469,7 +426,6 @@ class entrypoint(Generic[ContextT]):
         self.cache = cache
         self.cache_policy = cache_policy
         self.retry_policy = retry_policy
-        self.timeout = coerce_timeout_policy(timeout)
         self.context_schema = context_schema
 
     @dataclass(**_DC_KWARGS)
@@ -579,7 +535,6 @@ class entrypoint(Generic[ContextT]):
                     bound=bound,
                     triggers=[START],
                     channels=START,
-                    timeout=self.timeout,
                     writers=[
                         ChannelWrite(
                             [

libs/langgraph/langgraph/graph/_node.py

@@ -9,7 +9,7 @@ from langgraph.store.base import BaseStore
 
 from langgraph._internal._typing import EMPTY_SEQ
 from langgraph.runtime import Runtime
-from langgraph.types import CachePolicy, RetryPolicy, StreamWriter, TimeoutPolicy
+from langgraph.types import CachePolicy, RetryPolicy, StreamWriter
 from langgraph.typing import ContextT, NodeInputT, NodeInputT_contra
 
 
@@ -90,4 +90,3 @@ class StateNodeSpec(Generic[NodeInputT, ContextT]):
     cache_policy: CachePolicy | None
     ends: tuple[str, ...] | dict[str, str] | None = EMPTY_SEQ
     defer: bool = False
-    timeout: TimeoutPolicy | None = None

libs/langgraph/langgraph/graph/message.py

@@ -244,52 +244,6 @@ def add_messages(
     return merged
 
 
-def _messages_delta_reducer(
-    state: list[AnyMessage], writes: list[list[AnyMessage]]
-) -> list[AnyMessage]:
-    """**Experimental.** Batch reducer for use with `DeltaChannel`.
-
-    Processes all writes in one pass — dedup by ID, `RemoveMessage`
-    tombstoning — without calling `add_messages`. Assumes writes contain
-    already-typed `BaseMessage` objects (no raw-dict coercion).
-
-    This reducer is batching-invariant, as required by `DeltaChannel`:
-    `reducer(reducer(state, xs), ys) == reducer(state, xs + ys)`.
-
-    Use `add_messages` as the reducer for `BinaryOperatorAggregate` or
-    anywhere raw message dicts / strings need to be coerced first.
-
-    Example::
-
-        from typing import Annotated
-        from langgraph.channels.delta import DeltaChannel
-        from langgraph.graph.message import _messages_delta_reducer
-
-        class State(TypedDict):
-            messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-    """
-    from itertools import chain
-
-    index: dict[str, int] = {m.id: i for i, m in enumerate(state) if m.id is not None}
-    result: list[AnyMessage | None] = list(state)
-    for msg in chain.from_iterable(
-        [w] if isinstance(w, BaseMessage) else w for w in writes
-    ):
-        mid = msg.id
-        if mid is None:
-            result.append(msg)
-        elif isinstance(msg, RemoveMessage):
-            if mid in index:
-                result[index[mid]] = None
-                del index[mid]
-        elif mid in index:
-            result[index[mid]] = msg
-        else:
-            index[mid] = len(result)
-            result.append(msg)
-    return [m for m in result if m is not None]
-
-
 @deprecated(
     "MessageGraph is deprecated in langgraph 1.0.0, to be removed in 2.0.0. Please use StateGraph with a `messages` key instead.",
     category=None,

libs/langgraph/langgraph/graph/state.py

@@ -7,7 +7,6 @@ import warnings
 from collections import defaultdict
 from collections.abc import Awaitable, Callable, Hashable, Sequence
 from dataclasses import is_dataclass
-from datetime import timedelta
 from functools import partial
 from inspect import isclass, isfunction, ismethod, signature
 from types import FunctionType
@@ -46,11 +45,9 @@ from langgraph._internal._fields import (
 )
 from langgraph._internal._pydantic import create_model
 from langgraph._internal._runnable import coerce_to_runnable
-from langgraph._internal._timeout import coerce_timeout_policy
 from langgraph._internal._typing import EMPTY_SEQ, MISSING, DeprecatedKwargs
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.binop import BinaryOperatorAggregate
-from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue, LastValueAfterFinish
 from langgraph.channels.named_barrier_value import (
@@ -84,7 +81,6 @@ from langgraph.types import (
     Command,
     RetryPolicy,
     Send,
-    TimeoutPolicy,
     ensure_valid_checkpointer,
 )
 from langgraph.typing import ContextT, InputT, NodeInputT, OutputT, StateT
@@ -304,7 +300,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
@@ -372,7 +367,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph` where input schema is specified.
@@ -445,7 +439,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
@@ -513,7 +506,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is specified.
@@ -588,7 +580,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`.
@@ -618,14 +609,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 !!! warning
 
                     This is only used for graph rendering and doesn't have any effect on the graph execution.
-            timeout: Timeout for each node attempt. A number or `timedelta` is
-                a hard wall-clock cap and is not refreshed. Use `TimeoutPolicy`
-                to configure both a wall-clock `run_timeout` and an
-                `idle_timeout` refreshed by progress signals. When exceeded, a
-                [`NodeTimeoutError`][langgraph.errors.NodeTimeoutError] is raised
-                and the retry policy (if any) decides whether to retry. Timeouts
-                are supported only for async nodes; sync nodes cannot be safely
-                cancelled in-process.
 
         Example:
             ```python
@@ -679,7 +662,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             )
             if input_schema is None:
                 input_schema = cast(type[NodeInputT] | None, input_)
-        timeout = coerce_timeout_policy(timeout)
 
         if not isinstance(node, str):
             action = node
@@ -775,7 +757,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 cache_policy=cache_policy,
                 ends=ends,
                 defer=defer,
-                timeout=timeout,
             )
         elif inferred_input_schema is not None:
             self.nodes[node] = StateNodeSpec(
@@ -786,7 +767,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 cache_policy=cache_policy,
                 ends=ends,
                 defer=defer,
-                timeout=timeout,
             )
         else:
             self.nodes[node] = StateNodeSpec[StateT, ContextT](
@@ -797,7 +777,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 cache_policy=cache_policy,
                 ends=ends,
                 defer=defer,
-                timeout=timeout,
             )
 
         input_schema = input_schema or inferred_input_schema
@@ -1111,7 +1090,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             CompiledStateGraph: The compiled `StateGraph`.
         """
         checkpointer = ensure_valid_checkpointer(checkpointer)
-
         serde_allowlist: set[tuple[str, ...]] | None = None
         if _serde.STRICT_MSGPACK_ENABLED:
             schema_types: list[type[Any]] = [
@@ -1363,7 +1341,6 @@ class CompiledStateGraph(
                 retry_policy=node.retry_policy,
                 cache_policy=node.cache_policy,
                 bound=node.runnable,  # type: ignore[arg-type]
-                timeout=node.timeout,
             )
         else:
             raise RuntimeError
@@ -1699,20 +1676,6 @@ def _is_field_channel(typ: type[Any]) -> BaseChannel | None:
         # Search through all annotated medata to find channel annotations
         for item in meta:
             if isinstance(item, BaseChannel):
-                if isinstance(item, DeltaChannel) and hasattr(typ, "__origin__"):
-                    origin = typ.__origin__
-                    # Unwrap parameterized Required[X]/NotRequired[X] to X
-                    # (e.g. Annotated[NotRequired[dict[...]], ...]).
-                    if hasattr(origin, "__origin__") and origin.__origin__ in (
-                        Required,
-                        NotRequired,
-                    ):
-                        origin = origin.__args__[0]
-                    item = item.__class__(
-                        item.reducer,
-                        origin,
-                        snapshot_frequency=item.snapshot_frequency,
-                    )
                 return item
             elif isclass(item) and issubclass(item, BaseChannel):
                 # ex, Annotated[int, EphemeralValue, SomeOtherAnnotation]

libs/langgraph/langgraph/pregel/_algo.py

@@ -80,7 +80,6 @@ from langgraph.types import (
     PregelTask,
     RetryPolicy,
     Send,
-    TimeoutPolicy,
 )
 
 GetNextVersion = Callable[[V | None, None], V]
@@ -115,21 +114,13 @@ class PregelTaskWrites(NamedTuple):
 
 
 class Call:
-    __slots__ = (
-        "func",
-        "input",
-        "retry_policy",
-        "cache_policy",
-        "callbacks",
-        "timeout",
-    )
+    __slots__ = ("func", "input", "retry_policy", "cache_policy", "callbacks")
 
     func: Callable
     input: tuple[tuple[Any, ...], dict[str, Any]]
     retry_policy: Sequence[RetryPolicy] | None
     cache_policy: CachePolicy | None
     callbacks: Callbacks
-    timeout: TimeoutPolicy | None
 
     def __init__(
         self,
@@ -139,14 +130,12 @@ class Call:
         retry_policy: Sequence[RetryPolicy] | None,
         cache_policy: CachePolicy | None,
         callbacks: Callbacks,
-        timeout: TimeoutPolicy | None = None,
     ) -> None:
         self.func = func
         self.input = input
         self.retry_policy = retry_policy
         self.cache_policy = cache_policy
         self.callbacks = callbacks
-        self.timeout = timeout
 
 
 def should_interrupt(
@@ -744,7 +733,6 @@ def prepare_single_task(
                         task_path[:3],
                         writers=proc.flat_writers,
                         subgraphs=proc.subgraphs,
-                        timeout=proc.timeout,
                     )
             else:
                 return PregelTask(task_id, name, task_path[:3])
@@ -882,7 +870,6 @@ def prepare_push_task_functional(
             cache_key,
             task_id,
             in_progress_task_path,
-            timeout=call.timeout,
         )
     else:
         return PregelTask(task_id, name, in_progress_task_path)
@@ -1054,7 +1041,6 @@ def prepare_push_task_send(
             translated_task_path,
             writers=proc.flat_writers,
             subgraphs=proc.subgraphs,
-            timeout=packet.timeout if packet.timeout is not None else proc.timeout,
         )
     else:
         return PregelTask(task_id, packet.node, translated_task_path)
@@ -1269,4 +1255,4 @@ def sanitize_untracked_values_in_send(
         for k, v in packet.arg.items()
         if not isinstance(channels.get(k), UntrackedValue)
     }
-    return Send(node=packet.node, arg=sanitized_arg, timeout=packet.timeout)
+    return Send(node=packet.node, arg=sanitized_arg)

libs/langgraph/langgraph/pregel/_call.py

@@ -8,7 +8,6 @@ import inspect
 import sys
 import types
 from collections.abc import Awaitable, Callable, Generator, Sequence
-from datetime import timedelta
 from typing import Any, Generic, TypeVar, cast
 
 from langchain_core.runnables import Runnable
@@ -21,13 +20,9 @@ from langgraph._internal._runnable import (
     is_async_callable,
     run_in_executor,
 )
-from langgraph._internal._timeout import (
-    coerce_timeout_policy,
-    sync_timeout_unsupported,
-)
 from langgraph.config import get_config
 from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
-from langgraph.types import CachePolicy, RetryPolicy, TimeoutPolicy
+from langgraph.types import CachePolicy, RetryPolicy
 
 ##
 # Utilities borrowed from cloudpickle.
@@ -260,31 +255,8 @@ def call(
     *args: Any,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
-    timeout: float | timedelta | TimeoutPolicy | None = None,
     **kwargs: Any,
 ) -> SyncAsyncFuture[T]:
-    return _call_with_options(
-        func,
-        args,
-        kwargs,
-        retry_policy=retry_policy,
-        cache_policy=cache_policy,
-        timeout=coerce_timeout_policy(timeout),
-    )
-
-
-def _call_with_options(
-    func: Callable[P, Awaitable[T]] | Callable[P, T],
-    args: tuple[Any, ...],
-    kwargs: dict[str, Any],
-    *,
-    retry_policy: Sequence[RetryPolicy] | None = None,
-    cache_policy: CachePolicy | None = None,
-    timeout: TimeoutPolicy | None = None,
-) -> SyncAsyncFuture[T]:
-    if timeout is not None and not is_async_callable(func):
-        name = getattr(func, "__name__", func.__class__.__name__)
-        raise sync_timeout_unsupported(name, kind="Task")
     config = get_config()
     impl = config[CONF][CONFIG_KEY_CALL]
     fut = impl(
@@ -293,6 +265,5 @@ def _call_with_options(
         retry_policy=retry_policy,
         cache_policy=cache_policy,
         callbacks=config["callbacks"],
-        timeout=timeout,
     )
     return fut

libs/langgraph/langgraph/pregel/_checkpoint.py

@@ -1,23 +1,17 @@
 from __future__ import annotations
 
-from collections.abc import Callable, Mapping
+from collections.abc import Mapping
 from datetime import datetime, timezone
-from typing import Any, cast
 
-from langchain_core.runnables import RunnableConfig
-from langgraph.checkpoint.base import DELTA_SENTINEL, BaseCheckpointSaver, Checkpoint
+from langgraph.checkpoint.base import Checkpoint
 from langgraph.checkpoint.base.id import uuid6
-from langgraph.checkpoint.serde.types import _DeltaSnapshot
 
 from langgraph._internal._typing import MISSING
 from langgraph.channels.base import BaseChannel
-from langgraph.channels.delta import DeltaChannel
 from langgraph.managed.base import ManagedValueMapping, ManagedValueSpec
 
 LATEST_VERSION = 4
 
-GetNextVersion = Callable[[Any, None], Any]
-
 
 def empty_checkpoint() -> Checkpoint:
     return Checkpoint(
@@ -37,87 +31,35 @@ def create_checkpoint(
     *,
     id: str | None = None,
     updated_channels: set[str] | None = None,
-    get_next_version: GetNextVersion | None = None,
-    force_delta_snapshot: bool = False,
 ) -> Checkpoint:
-    """Create a checkpoint for the given channels.
-
-    For `DeltaChannel` with `snapshot_frequency=N`, snapshot steps write a
-    `_DeltaSnapshot` blob rather than `DELTA_SENTINEL`, bounding the ancestor
-    walk to at most N steps. Snapshots are eager: even if the channel had no
-    write this step, a version bump is forced (via `get_next_version`) so the
-    blob is stored by `put()`. Without `get_next_version` (e.g. static
-    contexts), snapshot steps gracefully fall back to sentinel.
-
-    `force_delta_snapshot` writes available `DeltaChannel` values as snapshots
-    regardless of `snapshot_frequency`. This is used by `durability="exit"`,
-    where intermediate writes are not stored as ancestor `checkpoint_writes`.
-    """
+    """Create a checkpoint for the given channels."""
     ts = datetime.now(timezone.utc).isoformat()
     if channels is None:
         values = checkpoint["channel_values"]
-        channel_versions = checkpoint["channel_versions"]
     else:
         values = {}
-        channel_versions = dict(checkpoint["channel_versions"])
         for k in channels:
-            if k not in channel_versions:
+            if k not in checkpoint["channel_versions"]:
                 continue
-            ch = channels[k]
-            if (
-                isinstance(ch, DeltaChannel)
-                and (force_delta_snapshot or ch.is_snapshot_step(step))
-                and ch.is_available()
-            ):
-                # Eager snapshot: bump version if not already written this step
-                # so put() includes this channel in new_versions and stores blob.
-                if get_next_version is not None and (
-                    updated_channels is None or k not in updated_channels
-                ):
-                    channel_versions[k] = get_next_version(channel_versions[k], None)
-                values[k] = _DeltaSnapshot(ch.get())
-            else:
-                v = ch.checkpoint()
-                if v is not MISSING:
-                    values[k] = v
+            v = channels[k].checkpoint()
+            if v is not MISSING:
+                values[k] = v
     return Checkpoint(
         v=LATEST_VERSION,
         ts=ts,
         id=id or str(uuid6(clock_seq=step)),
         channel_values=values,
-        channel_versions=channel_versions,
+        channel_versions=checkpoint["channel_versions"],
         versions_seen=checkpoint["versions_seen"],
         updated_channels=None if updated_channels is None else sorted(updated_channels),
     )
 
 
-def _needs_replay(spec: BaseChannel, stored: object) -> bool:
-    """True if `spec` is a `DeltaChannel` and the stored blob is a sentinel,
-    requiring an ancestor walk to reconstruct.
-
-    `_DeltaSnapshot` blobs and plain values (migration) resolve directly via
-    `from_checkpoint` — only `DELTA_SENTINEL` / `MISSING` trigger replay.
-    """
-    if not isinstance(spec, DeltaChannel):
-        return False
-    return stored is MISSING or stored is DELTA_SENTINEL
-
-
 def channels_from_checkpoint(
     specs: Mapping[str, BaseChannel | ManagedValueSpec],
     checkpoint: Checkpoint,
-    *,
-    saver: BaseCheckpointSaver | None = None,
-    config: RunnableConfig | None = None,
 ) -> tuple[Mapping[str, BaseChannel], ManagedValueMapping]:
-    """Hydrate channels from a checkpoint.
-
-    For most channels, `spec.from_checkpoint(checkpoint["channel_values"][k])`
-    is sufficient. `DeltaChannel` is the exception: sentinel blobs require an
-    ancestor walk via `saver._get_channel_writes_history`. The walk terminates
-    at the nearest `_DeltaSnapshot` blob (step-based) or a pre-migration plain
-    value, so read depth is bounded by `snapshot_frequency`.
-    """
+    """Get channels from a checkpoint."""
     channel_specs: dict[str, BaseChannel] = {}
     managed_specs: dict[str, ManagedValueSpec] = {}
     for k, v in specs.items():
@@ -125,53 +67,13 @@ def channels_from_checkpoint(
             channel_specs[k] = v
         else:
             managed_specs[k] = v
-
-    channels: dict[str, BaseChannel] = {}
-    for k, spec in channel_specs.items():
-        ch: BaseChannel
-        stored = checkpoint["channel_values"].get(k, MISSING)
-        if _needs_replay(spec, stored) and saver is not None and config is not None:
-            delta_spec = cast(DeltaChannel, spec)
-            history = saver._get_channel_writes_history(config, k)
-            replay_ch = delta_spec.from_checkpoint(history.seed)
-            replay_ch.replay_writes(history.writes)
-            ch = replay_ch
-        else:
-            ch = spec.from_checkpoint(stored)
-        channels[k] = ch
-    return channels, managed_specs
-
-
-async def achannels_from_checkpoint(
-    specs: Mapping[str, BaseChannel | ManagedValueSpec],
-    checkpoint: Checkpoint,
-    *,
-    saver: BaseCheckpointSaver | None = None,
-    config: RunnableConfig | None = None,
-) -> tuple[Mapping[str, BaseChannel], ManagedValueMapping]:
-    """Async version of `channels_from_checkpoint`. See docstring there."""
-    channel_specs: dict[str, BaseChannel] = {}
-    managed_specs: dict[str, ManagedValueSpec] = {}
-    for k, v in specs.items():
-        if isinstance(v, BaseChannel):
-            channel_specs[k] = v
-        else:
-            managed_specs[k] = v
-
-    channels: dict[str, BaseChannel] = {}
-    for k, spec in channel_specs.items():
-        ch: BaseChannel
-        stored = checkpoint["channel_values"].get(k, MISSING)
-        if _needs_replay(spec, stored) and saver is not None and config is not None:
-            delta_spec = cast(DeltaChannel, spec)
-            history = await saver._aget_channel_writes_history(config, k)
-            replay_ch = delta_spec.from_checkpoint(history.seed)
-            replay_ch.replay_writes(history.writes)
-            ch = replay_ch
-        else:
-            ch = spec.from_checkpoint(stored)
-        channels[k] = ch
-    return channels, managed_specs
+    return (
+        {
+            k: v.from_checkpoint(checkpoint["channel_values"].get(k, MISSING))
+            for k, v in channel_specs.items()
+        },
+        managed_specs,
+    )
 
 
 def copy_checkpoint(checkpoint: Checkpoint) -> Checkpoint:

libs/langgraph/langgraph/pregel/_loop.py

@@ -45,7 +45,6 @@ from langgraph._internal._constants import (
     CONFIG_KEY_REPLAY_STATE,
     CONFIG_KEY_RESUME_MAP,
     CONFIG_KEY_RESUMING,
-    CONFIG_KEY_RUNTIME,
     CONFIG_KEY_SCRATCHPAD,
     CONFIG_KEY_STREAM,
     CONFIG_KEY_TASK_ID,
@@ -69,7 +68,6 @@ from langgraph.callbacks import (
     GraphResumeEvent,
 )
 from langgraph.channels.base import BaseChannel
-from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.constants import TAG_HIDDEN
 from langgraph.errors import (
@@ -94,7 +92,6 @@ from langgraph.pregel._algo import (
     task_path_str,
 )
 from langgraph.pregel._checkpoint import (
-    achannels_from_checkpoint,
     channels_from_checkpoint,
     copy_checkpoint,
     create_checkpoint,
@@ -120,7 +117,6 @@ from langgraph.pregel.debug import (
     map_debug_tasks,
 )
 from langgraph.pregel.protocol import StreamChunk, StreamProtocol
-from langgraph.runtime import RunControl, Runtime
 from langgraph.types import (
     All,
     CachePolicy,
@@ -192,8 +188,6 @@ class PregelLoop:
     _migrate_checkpoint: Callable[[Checkpoint], None] | None
     submit: Submit
     channels: Mapping[str, BaseChannel]
-    # Only set on AsyncPregelLoop; sync loops keep this as None.
-    _delta_write_futs: list[Any] | None = None
     managed: ManagedValueMapping
     checkpoint: Checkpoint
     checkpoint_id_saved: str
@@ -208,12 +202,10 @@ class PregelLoop:
         "input",
         "pending",
         "done",
-        "draining",
         "interrupt_before",
         "interrupt_after",
         "out_of_steps",
     ]
-    control: RunControl | None
     tasks: dict[str, PregelExecutableTask]
     output: None | dict[str, Any] | Any = None
     updated_channels: set[str] | None = None
@@ -321,8 +313,6 @@ class PregelLoop:
             else ()
         )
         self.prev_checkpoint_config = None
-        runtime = self.config[CONF].get(CONFIG_KEY_RUNTIME)
-        self.control = runtime.control if isinstance(runtime, Runtime) else None
 
     def _push_graph_lifecycle_event(
         self,
@@ -330,16 +320,11 @@ class PregelLoop:
         *,
         interrupts: tuple[Interrupt, ...] = (),
     ) -> None:
-        # drain status never reaches lifecycle events: tick() returns False
-        # before pushing, and interrupts are raised through GraphInterrupt
-        if self.status == "draining":
-            raise RuntimeError("Draining status cannot emit lifecycle events")
-        status = self.status
         if kind == "resume":
             self._graph_lifecycle_events.append(
                 GraphResumeEvent(
                     run_id=None,
-                    status=status,
+                    status=self.status,
                     checkpoint_id=self.checkpoint["id"],
                     checkpoint_ns=self.checkpoint_ns,
                 )
@@ -348,7 +333,7 @@ class PregelLoop:
             self._graph_lifecycle_events.append(
                 GraphInterruptEvent(
                     run_id=None,
-                    status=status,
+                    status=self.status,
                     checkpoint_id=self.checkpoint["id"],
                     checkpoint_ns=self.checkpoint_ns,
                     interrupts=interrupts,
@@ -421,7 +406,7 @@ class PregelLoop:
                     task = self.tasks.get(task_id)
                 else:
                     task = None
-                fut = self.submit(
+                self.submit(
                     self.checkpointer_put_writes,
                     config,
                     writes_to_save,
@@ -429,16 +414,12 @@ class PregelLoop:
                     task_path_str(task.path) if task else "",
                 )
             else:
-                fut = self.submit(
+                self.submit(
                     self.checkpointer_put_writes,
                     config,
                     writes_to_save,
                     task_id,
                 )
-            if self._delta_write_futs is not None and any(
-                isinstance(self.specs.get(c), DeltaChannel) for c, _ in writes_to_save
-            ):
-                self._delta_write_futs.append(fut)
         # output writes
         if hasattr(self, "tasks"):
             self.output_writes(task_id, writes)
@@ -580,10 +561,6 @@ class PregelLoop:
             self.status = "done"
             return False
 
-        if self.control is not None and self.control.drain_requested:
-            self.status = "draining"
-            return False
-
         # if there are pending writes from a previous loop, apply them
         if not self.is_replaying and self.checkpoint_pending_writes:
             self._match_writes(self.tasks)
@@ -913,10 +890,6 @@ class PregelLoop:
             self.step,
             id=self.checkpoint["id"] if exiting else None,
             updated_channels=self.updated_channels,
-            get_next_version=self.checkpointer_get_next_version
-            if do_checkpoint
-            else None,
-            force_delta_snapshot=exiting and self.durability == "exit",
         )
         # sanitize TASK channel in the checkpoint before saving (durability=="exit")
         if TASKS in self.checkpoint["channel_values"] and any(
@@ -1300,10 +1273,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
         )
         self.submit = self.stack.enter_context(BackgroundExecutor(self.config))
         self.channels, self.managed = channels_from_checkpoint(
-            self.specs,
-            self.checkpoint,
-            saver=self.checkpointer,
-            config=self.checkpoint_config,
+            self.specs, self.checkpoint
         )
         self.stack.push(self._suppress_interrupt)
         self.status = "input"
@@ -1398,11 +1368,6 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
         metadata: CheckpointMetadata,
         new_versions: ChannelVersions,
     ) -> RunnableConfig:
-        # Drain DeltaChannel write futures before committing the checkpoint so
-        # DELTA_SENTINEL blobs are never saved ahead of their backing writes.
-        if self._delta_write_futs:
-            futs, self._delta_write_futs = self._delta_write_futs, []
-            await asyncio.gather(*futs)
         try:
             if prev is not None:
                 await prev
@@ -1508,15 +1473,11 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
             if saved.pending_writes is not None
             else []
         )
-        self._delta_write_futs = []
         self.submit = await self.stack.enter_async_context(
             AsyncBackgroundExecutor(self.config)
         )
-        self.channels, self.managed = await achannels_from_checkpoint(
-            self.specs,
-            self.checkpoint,
-            saver=self.checkpointer,
-            config=self.checkpoint_config,
+        self.channels, self.managed = channels_from_checkpoint(
+            self.specs, self.checkpoint
         )
         self.stack.push(self._suppress_interrupt)
         self.status = "input"

libs/langgraph/langgraph/pregel/_read.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 from collections.abc import AsyncIterator, Callable, Iterator, Mapping, Sequence
-from datetime import timedelta
 from functools import cached_property
 from typing import (
     Any,
@@ -12,11 +11,10 @@ from langchain_core.runnables import Runnable, RunnableConfig
 from langgraph._internal._config import merge_configs
 from langgraph._internal._constants import CONF, CONFIG_KEY_READ
 from langgraph._internal._runnable import RunnableCallable, RunnableSeq
-from langgraph._internal._timeout import coerce_timeout_policy
 from langgraph.pregel._utils import find_subgraph_pregel
 from langgraph.pregel._write import ChannelWrite
 from langgraph.pregel.protocol import PregelProtocol
-from langgraph.types import CachePolicy, RetryPolicy, TimeoutPolicy
+from langgraph.types import CachePolicy, RetryPolicy
 
 READ_TYPE = Callable[[str | Sequence[str], bool], Any | dict[str, Any]]
 INPUT_CACHE_KEY_TYPE = tuple[Callable[..., Any], tuple[str, ...]]
@@ -125,13 +123,6 @@ class PregelNode:
     cache_policy: CachePolicy | None
     """The cache policy to use when invoking the node."""
 
-    timeout: TimeoutPolicy | None
-    """Timeout policy for a single invocation.
-
-    If exceeded, `NodeTimeoutError` is raised and the retry policy (if any)
-    decides whether to retry. Supported only for async nodes.
-    """
-
     tags: Sequence[str] | None
     """Tags to attach to the node for tracing."""
 
@@ -154,7 +145,6 @@ class PregelNode:
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
         subgraphs: Sequence[PregelProtocol] | None = None,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
     ) -> None:
         self.channels = channels
         self.triggers = list(triggers)
@@ -166,7 +156,6 @@ class PregelNode:
             self.retry_policy = (retry_policy,)
         else:
             self.retry_policy = retry_policy
-        self.timeout = coerce_timeout_policy(timeout)
         self.tags = tags
         self.metadata = metadata
         if subgraphs is not None:

libs/langgraph/langgraph/pregel/_retry.py

@@ -4,487 +4,32 @@ import asyncio
 import logging
 import random
 import sys
-import threading
 import time
-import weakref
 from collections.abc import Awaitable, Callable, Sequence
-from contextlib import suppress
-from dataclasses import dataclass, replace
-from datetime import datetime, timedelta, timezone
-from typing import Any, Literal, NamedTuple
+from dataclasses import replace
+from typing import Any
 
-from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.runnables import RunnableConfig
 
-from langgraph._internal._config import (
-    merge_configs,
-    patch_configurable,
-    recast_checkpoint_ns,
-)
+from langgraph._internal._config import patch_configurable, recast_checkpoint_ns
 from langgraph._internal._constants import (
     CONF,
-    CONFIG_KEY_CALL,
     CONFIG_KEY_CHECKPOINT_ID,
     CONFIG_KEY_CHECKPOINT_NS,
     CONFIG_KEY_RESUMING,
     CONFIG_KEY_RUNTIME,
-    CONFIG_KEY_SEND,
-    CONFIG_KEY_STREAM,
     CONFIG_KEY_TASK_ID,
     CONFIG_KEY_THREAD_ID,
-    CONFIG_KEY_TIMED_ATTEMPT_OBSERVER,
     NS_SEP,
 )
-from langgraph._internal._runnable import create_task_in_config_context
-from langgraph._internal._timeout import sync_timeout_unsupported
-from langgraph.errors import GraphBubbleUp, NodeTimeoutError, ParentCommand
-from langgraph.pregel.protocol import StreamProtocol
+from langgraph.errors import GraphBubbleUp, ParentCommand
 from langgraph.runtime import ExecutionInfo, Runtime
-from langgraph.types import Command, PregelExecutableTask, RetryPolicy, TimeoutPolicy
+from langgraph.types import Command, PregelExecutableTask, RetryPolicy
 
 logger = logging.getLogger(__name__)
 SUPPORTS_EXC_NOTES = sys.version_info >= (3, 11)
 
 
-def _timeout_secs(value: float | timedelta) -> float:
-    return value.total_seconds() if isinstance(value, timedelta) else value
-
-
-@dataclass(frozen=True, slots=True)
-class _ResolvedTimeout:
-    run_timeout_secs: float | None
-    idle_timeout_secs: float | None
-    refresh_on: Literal["auto", "heartbeat"] | None
-
-
-def _resolve_timeout(timeout: TimeoutPolicy) -> _ResolvedTimeout:
-    idle_timeout_secs = (
-        _timeout_secs(timeout.idle_timeout)
-        if timeout.idle_timeout is not None
-        else None
-    )
-    return _ResolvedTimeout(
-        run_timeout_secs=(
-            _timeout_secs(timeout.run_timeout)
-            if timeout.run_timeout is not None
-            else None
-        ),
-        idle_timeout_secs=idle_timeout_secs,
-        refresh_on=timeout.refresh_on if idle_timeout_secs is not None else None,
-    )
-
-
-class _AttemptContext(NamedTuple):
-    """Immutable per-attempt metadata shared across start/progress/finish events.
-
-    Built once at attempt start and referenced (not copied) by every emitted
-    `_AttemptEvent`, so per-event allocation is just the small event wrapper.
-
-    Intentionally underscore-prefixed: this and `_AttemptEvent` are part of an
-    internal observer contract consumed by langgraph-server. Do not move to
-    `langgraph.types` — server imports them by this path.
-    """
-
-    task_id: str
-    task_name: str
-    attempt: int
-    run_id: str | None
-    thread_id: str | None
-    checkpoint_ns: str | None
-    started_at: datetime
-    run_timeout_secs: float | None
-    idle_timeout_secs: float | None
-    refresh_on: Literal["auto", "heartbeat"] | None
-
-
-@dataclass(frozen=True, slots=True)
-class _AttemptEvent:
-    """One lifecycle event for a timed attempt.
-
-    Holds a reference to the shared `_AttemptContext` and the event-specific
-    fields. The observer must treat this and `context` as read-only — they
-    are reused across all events for the same attempt.
-    """
-
-    context: _AttemptContext
-    event: Literal["start", "progress", "finish"]
-    progress_at: datetime | None = None
-    finished_at: datetime | None = None
-    status: Literal["success", "error"] | None = None
-    error_type: str | None = None
-    error_message: str | None = None
-
-
-class _TimedAttemptScope:
-    """Guarded-config window for timed attempts.
-
-    The wrapped config marks writes, stream events, runtime stream writer calls,
-    child task scheduling, and any LangChain callback event emitted under the
-    node's run as observable progress when `refresh_on="auto"`.
-    `runtime.heartbeat()` exposes a manual progress signal for work that doesn't
-    otherwise emit any of these, and is the only progress signal when
-    `refresh_on="heartbeat"`.
-    Guarded writes are serialized with `close()` so cancelled background tasks
-    cannot persist writes past the timeout boundary. Stream/custom output is
-    best-effort: it is dropped after close is observed, but callbacks run outside
-    the lock because they may contain arbitrary user/runtime code.
-    """
-
-    __slots__ = (
-        "__weakref__",
-        "_active",
-        "_last_progress",
-        "_last_progress_emit",
-        "_lock",
-        "_on_progress",
-        "_progress_min_interval",
-        "_refresh_on",
-    )
-
-    def __init__(
-        self,
-        on_progress: Callable[[], None] | None = None,
-        progress_min_interval: float = 0.0,
-        refresh_on: Literal["auto", "heartbeat"] | None = None,
-    ) -> None:
-        self._active = True
-        self._last_progress = time.monotonic()
-        self._lock = threading.Lock()
-        self._on_progress = on_progress
-        self._progress_min_interval = progress_min_interval
-        self._refresh_on = refresh_on
-        # `-inf` so the first touch always passes the rate-limit gate.
-        self._last_progress_emit: float = float("-inf")
-
-    def wrap_config(self, config: RunnableConfig) -> RunnableConfig:
-        configurable = config.get(CONF, {})
-        patch: dict[str, Any] = {}
-        if (send := configurable.get(CONFIG_KEY_SEND)) is not None:
-            patch[CONFIG_KEY_SEND] = self._guard_send(send)
-        if (stream := configurable.get(CONFIG_KEY_STREAM)) is not None:
-            patch[CONFIG_KEY_STREAM] = self._guard_stream(stream)
-        if (call := configurable.get(CONFIG_KEY_CALL)) is not None:
-            patch[CONFIG_KEY_CALL] = self._guard_call(call)
-        if isinstance(runtime := configurable.get(CONFIG_KEY_RUNTIME), Runtime):
-            if self._refresh_on is not None:
-                patch[CONFIG_KEY_RUNTIME] = runtime.override(
-                    stream_writer=self._guard_stream_writer(runtime.stream_writer),
-                    heartbeat=self.touch,
-                )
-            else:
-                patch[CONFIG_KEY_RUNTIME] = runtime.override(
-                    stream_writer=self._guard_stream_writer(runtime.stream_writer)
-                )
-        new_config = patch_configurable(config, patch) if patch else config
-        if self._refresh_on == "auto":
-            return merge_configs(
-                new_config, {"callbacks": [_IdleProgressCallbackHandler(self)]}
-            )
-        return new_config
-
-    def touch(self) -> None:
-        # Avoid locking this hot progress path. We accept a small race window in
-        # timestamp ordering because idle_timeout is expected to be coarse compared
-        # with scheduler/thread timing.
-        now = time.monotonic()
-        self._last_progress = now
-        if self._on_progress is None:
-            return
-        # Best-effort rate limit: a benign race may emit a duplicate progress
-        # event under heavy concurrency, which observers must already tolerate
-        # (callbacks fire from arbitrary threads).
-        if now - self._last_progress_emit < self._progress_min_interval:
-            return
-        self._last_progress_emit = now
-        self._on_progress()
-
-    def close(self) -> None:
-        with self._lock:
-            self._active = False
-
-    async def wait_for_idle_timeout(self, idle_timeout_s: float) -> None:
-        while True:
-            with self._lock:
-                if not self._active:
-                    return
-                remaining = self._last_progress + idle_timeout_s - time.monotonic()
-            if remaining <= 0:
-                raise asyncio.TimeoutError
-            await asyncio.sleep(remaining)
-
-    def _guard_send(
-        self, send: Callable[[Sequence[tuple[str, Any]]], None]
-    ) -> Callable[[Sequence[tuple[str, Any]]], None]:
-        def guarded_send(writes: Sequence[tuple[str, Any]]) -> None:
-            with self._lock:
-                if self._active:
-                    if writes and self._refresh_on == "auto":
-                        self._last_progress = time.monotonic()
-                    send(writes)
-
-        return guarded_send
-
-    def _guard_stream(self, stream: StreamProtocol) -> StreamProtocol:
-        # No lock: stream callbacks fire from the event loop only, so the
-        # active-check + write happen atomically between awaits.
-        def guarded_stream(chunk: tuple[tuple[str, ...], str, Any]) -> None:
-            if not self._active:
-                return
-            if self._refresh_on == "auto":
-                self._last_progress = time.monotonic()
-            stream(chunk)
-
-        return StreamProtocol(guarded_stream, stream.modes)
-
-    def _guard_call(self, call: Callable[..., Any]) -> Callable[..., Any]:
-        # No lock: child-task scheduling happens from the event loop only.
-        def guarded_call(*args: Any, **kwargs: Any) -> Any:
-            if not self._active:
-                raise asyncio.CancelledError
-            if self._refresh_on == "auto":
-                self._last_progress = time.monotonic()
-            return call(*args, **kwargs)
-
-        return guarded_call
-
-    def _guard_stream_writer(
-        self, stream_writer: Callable[[Any], None]
-    ) -> Callable[[Any], None]:
-        def guarded_stream_writer(chunk: Any) -> None:
-            with self._lock:
-                if not self._active:
-                    return
-                if self._refresh_on == "auto":
-                    self._last_progress = time.monotonic()
-            stream_writer(chunk)
-
-        return guarded_stream_writer
-
-
-class _IdleProgressCallbackHandler(BaseCallbackHandler):
-    """Resets the idle timeout clock on any LangChain callback event.
-
-    Inherits via `config["callbacks"]`, so it sees only events emitted by
-    runs descended from the node's attempt — sibling nodes do not bleed
-    through. Holds the scope by weakref so a child manager that outlives
-    the attempt cannot keep the scope alive.
-    """
-
-    # Run inline so progress is recorded in callback emission order;
-    # thread-pool dispatch would introduce extra reordering.
-    run_inline = True
-
-    def __init__(self, scope: _TimedAttemptScope) -> None:
-        self._scope_ref = weakref.ref(scope)
-
-    def _touch(self, *args: Any, **kwargs: Any) -> None:
-        if (scope := self._scope_ref()) is not None:
-            scope.touch()
-
-    on_llm_start = _touch
-    on_chat_model_start = _touch
-    on_llm_new_token = _touch
-    on_llm_end = _touch
-    on_llm_error = _touch
-    on_chain_start = _touch
-    on_chain_end = _touch
-    on_chain_error = _touch
-    on_tool_start = _touch
-    on_tool_end = _touch
-    on_tool_error = _touch
-    on_retriever_start = _touch
-    on_retriever_end = _touch
-    on_retriever_error = _touch
-    on_agent_action = _touch
-    on_agent_finish = _touch
-    on_text = _touch
-    on_retry = _touch
-    on_custom_event = _touch
-
-
-def _drain_cancelled(task: asyncio.Task[Any]) -> None:
-    # Mark the abandoned task's exception as retrieved so asyncio doesn't log it.
-    with suppress(asyncio.CancelledError):
-        task.exception()
-
-
-def _start_timed_attempt(
-    task: PregelExecutableTask, config: RunnableConfig, timeout: _ResolvedTimeout
-) -> _AttemptContext | None:
-    configurable = config.get(CONF, {})
-    callback = configurable.get(CONFIG_KEY_TIMED_ATTEMPT_OBSERVER)
-    if callback is None:
-        return None
-    runtime = configurable.get(CONFIG_KEY_RUNTIME)
-    execution_info = runtime.execution_info if isinstance(runtime, Runtime) else None
-    context = _AttemptContext(
-        task_id=task.id,
-        task_name=task.name,
-        attempt=execution_info.node_attempt if execution_info is not None else 1,
-        run_id=execution_info.run_id if execution_info is not None else None,
-        thread_id=execution_info.thread_id if execution_info is not None else None,
-        checkpoint_ns=(
-            execution_info.checkpoint_ns if execution_info is not None else None
-        ),
-        started_at=datetime.now(timezone.utc),
-        run_timeout_secs=timeout.run_timeout_secs,
-        idle_timeout_secs=timeout.idle_timeout_secs,
-        refresh_on=timeout.refresh_on,
-    )
-    _dispatch_observer(callback, _AttemptEvent(context=context, event="start"))
-    return context
-
-
-def _finish_timed_attempt(
-    config: RunnableConfig,
-    context: _AttemptContext | None,
-    error: BaseException | None = None,
-) -> None:
-    if context is None:
-        return
-    callback = config.get(CONF, {}).get(CONFIG_KEY_TIMED_ATTEMPT_OBSERVER)
-    if callback is None:
-        return
-    _dispatch_observer(
-        callback,
-        _AttemptEvent(
-            context=context,
-            event="finish",
-            finished_at=datetime.now(timezone.utc),
-            status="error" if error is not None else "success",
-            error_type=type(error).__name__ if error is not None else None,
-            error_message=str(error) if error is not None else None,
-        ),
-    )
-
-
-def _emit_progress(
-    callback: Callable[[_AttemptEvent], None],
-    context: _AttemptContext,
-) -> None:
-    _dispatch_observer(
-        callback,
-        _AttemptEvent(
-            context=context,
-            event="progress",
-            progress_at=datetime.now(timezone.utc),
-        ),
-    )
-
-
-def _dispatch_observer(
-    callback: Callable[[_AttemptEvent], None],
-    event: _AttemptEvent,
-) -> None:
-    try:
-        callback(event)
-    except Exception:
-        logger.warning("Timed attempt observer failed", exc_info=True)
-
-
-async def _run_timeout_watchdog(run_timeout_s: float) -> None:
-    await asyncio.sleep(run_timeout_s)
-    raise asyncio.TimeoutError
-
-
-async def _arun_with_timeout(
-    task: PregelExecutableTask,
-    config: RunnableConfig,
-    timeout: _ResolvedTimeout,
-    attempt_ctx: _AttemptContext | None,
-    *,
-    stream: bool,
-) -> Any:
-    run_timeout_s = timeout.run_timeout_secs
-    idle_timeout_s = timeout.idle_timeout_secs
-    on_progress: Callable[[], None] | None = None
-    if attempt_ctx is not None:
-        callback = config.get(CONF, {}).get(CONFIG_KEY_TIMED_ATTEMPT_OBSERVER)
-        if callback is not None and idle_timeout_s is not None:
-            on_progress = lambda: _emit_progress(callback, attempt_ctx)  # noqa: E731
-    scope = _TimedAttemptScope(
-        on_progress=on_progress,
-        # Cap progress emission at ~4 events per idle window so token-rate
-        # callbacks don't flood the observer.
-        progress_min_interval=idle_timeout_s / 4 if idle_timeout_s is not None else 0.0,
-        refresh_on=timeout.refresh_on,
-    )
-    scoped_config = scope.wrap_config(config)
-    start = time.monotonic()
-    if stream:
-        # Yielded chunks count as progress only under `refresh_on="auto"`.
-        # `refresh_on="heartbeat"` is the strict mode where only explicit
-        # `runtime.heartbeat()` calls reset the idle clock.
-        async def run() -> Any:
-            async for _ in task.proc.astream(task.input, scoped_config):
-                if timeout.refresh_on == "auto":
-                    scope.touch()
-
-    else:
-
-        async def run() -> Any:
-            return await task.proc.ainvoke(task.input, scoped_config)
-
-    bg = create_task_in_config_context(run, scoped_config)
-    watchdogs: dict[asyncio.Task[None], Literal["idle", "run"]] = {}
-    if idle_timeout_s is not None:
-        watchdogs[asyncio.create_task(scope.wait_for_idle_timeout(idle_timeout_s))] = (
-            "idle"
-        )
-    if run_timeout_s is not None:
-        watchdogs[asyncio.create_task(_run_timeout_watchdog(run_timeout_s))] = "run"
-    try:
-        done, _ = await asyncio.wait(
-            {bg, *watchdogs}, return_when=asyncio.FIRST_COMPLETED
-        )
-        if bg in done:
-            # Task completed in time.
-            for watchdog in watchdogs:
-                watchdog.cancel()
-            # FIRST_COMPLETED can return both; a watchdog may have
-            # already raised TimeoutError before we cancelled it.
-            for watchdog in watchdogs:
-                with suppress(asyncio.CancelledError, asyncio.TimeoutError):
-                    await watchdog
-            return await bg
-        # bg was not in `done`, so every member of `done` is one of our
-        # watchdogs. Only a watchdog's TimeoutError converts to
-        # NodeTimeoutError; any TimeoutError raised by the proc itself
-        # propagates unchanged.
-        for watchdog in done:
-            kind = watchdogs[watchdog]
-            try:
-                await watchdog
-            except asyncio.TimeoutError as exc:
-                elapsed = time.monotonic() - start
-                scope.close()
-                task.writes.clear()
-                bg.cancel()
-                bg.add_done_callback(_drain_cancelled)
-                raise NodeTimeoutError(
-                    task.name,
-                    elapsed,
-                    kind=kind,
-                    idle_timeout=idle_timeout_s,
-                    run_timeout=run_timeout_s,
-                ) from exc
-            raise RuntimeError(
-                f"{kind} timeout watchdog completed without raising TimeoutError"
-            )
-        raise RuntimeError("timeout wait completed without task or watchdog")
-    except asyncio.CancelledError:
-        scope.close()
-        bg.cancel()
-        for watchdog in watchdogs:
-            watchdog.cancel()
-        bg.add_done_callback(_drain_cancelled)
-        raise
-    finally:
-        scope.close()
-        for watchdog in watchdogs:
-            watchdog.cancel()
-
-
 def _ensure_execution_info(
     runtime: Runtime, config: RunnableConfig, task: PregelExecutableTask
 ) -> Runtime:
@@ -545,10 +90,6 @@ def run_with_retry(
 ) -> None:
     """Run a task with retries."""
     retry_policy = task.retry_policy or retry_policy
-    if task.timeout is not None:
-        # `validate_timeout_supported` catches sync nodes at compile time;
-        # this is a runtime safety net for paths that may bypass that validation.
-        raise sync_timeout_unsupported(task.name)
     attempts = 0
     node_first_attempt_time = time.time()
     config = task.config
@@ -654,9 +195,6 @@ async def arun_with_retry(
 ) -> None:
     """Run a task asynchronously with retries."""
     retry_policy = task.retry_policy or retry_policy
-    resolved_timeout = (
-        _resolve_timeout(task.timeout) if task.timeout is not None else None
-    )
     attempts = 0
     node_first_attempt_time = time.time()
     config = task.config
@@ -691,53 +229,35 @@ async def arun_with_retry(
                     )
                 },
             )
-        attempt_ctx = (
-            _start_timed_attempt(task, config, resolved_timeout)
-            if resolved_timeout is not None
-            else None
-        )
         try:
+            # clear any writes from previous attempts
             task.writes.clear()
-            if resolved_timeout is None:
-                if stream:
-                    async for _ in task.proc.astream(task.input, config):
-                        pass
-                    break
-                return await task.proc.ainvoke(task.input, config)
-            result = await _arun_with_timeout(
-                task, config, resolved_timeout, attempt_ctx, stream=stream
-            )
-            _finish_timed_attempt(config, attempt_ctx)
+            # run the task
             if stream:
+                async for _ in task.proc.astream(task.input, config):
+                    pass
                 # if successful, end
                 break
-            return result
+            else:
+                return await task.proc.ainvoke(task.input, config)
         except ParentCommand as exc:
             ns: str = config[CONF][CONFIG_KEY_CHECKPOINT_NS]
             cmd = exc.args[0]
             # strip task_ids from namespace for comparison (ns format: "node1|node2:task_id")
             if cmd.graph in (ns, recast_checkpoint_ns(ns), task.name):
-                try:
-                    # this command is for the current graph, handle it
-                    for w in task.writers:
-                        w.invoke(cmd, config)
-                except Exception as writer_exc:
-                    _finish_timed_attempt(config, attempt_ctx, writer_exc)
-                    raise
-                _finish_timed_attempt(config, attempt_ctx)
+                # this command is for the current graph, handle it
+                for w in task.writers:
+                    w.invoke(cmd, config)
                 break
             elif cmd.graph == Command.PARENT:
                 # this command is for the parent graph, assign it to the parent.
                 exc.args = (replace(cmd, graph=_checkpoint_ns_for_parent_command(ns)),)
-            _finish_timed_attempt(config, attempt_ctx)
-            # bubble up the exception to the parent graph
+            # bubble up
             raise
         except GraphBubbleUp:
             # if interrupted, end
-            _finish_timed_attempt(config, attempt_ctx)
             raise
         except Exception as exc:
-            _finish_timed_attempt(config, attempt_ctx, exc)
             if SUPPORTS_EXC_NOTES:
                 exc.add_note(f"During task with name '{task.name}' and id '{task.id}'")
             if not retry_policy:

libs/langgraph/langgraph/pregel/_runner.py

@@ -46,7 +46,6 @@ from langgraph.types import (
     CachePolicy,
     PregelExecutableTask,
     RetryPolicy,
-    TimeoutPolicy,
 )
 
 F = TypeVar("F", concurrent.futures.Future, asyncio.Future)
@@ -538,7 +537,6 @@ def _call(
     *,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
-    timeout: TimeoutPolicy | None = None,
     callbacks: Callbacks = None,
     futures: weakref.ref[FuturesDict],
     schedule_task: Callable[
@@ -562,7 +560,6 @@ def _call(
             retry_policy=retry_policy,
             cache_policy=cache_policy,
             callbacks=callbacks,
-            timeout=timeout,
         ),
     ):
         if fut := next(
@@ -627,7 +624,6 @@ def _acall(
     *,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
-    timeout: TimeoutPolicy | None = None,
     callbacks: Callbacks = None,
     # injected dependencies
     futures: weakref.ref[FuturesDict],
@@ -661,7 +657,6 @@ def _acall(
             input,
             retry_policy=retry_policy,
             cache_policy=cache_policy,
-            timeout=timeout,
             callbacks=callbacks,
             futures=futures,
             schedule_task=schedule_task,
@@ -683,7 +678,6 @@ async def _acall_impl(
     *,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
-    timeout: TimeoutPolicy | None = None,
     callbacks: Callbacks = None,
     # injected dependencies
     futures: weakref.ref[FuturesDict[asyncio.Future, asyncio.Event]],
@@ -709,7 +703,6 @@ async def _acall_impl(
                 retry_policy=retry_policy,
                 cache_policy=cache_policy,
                 callbacks=callbacks,
-                timeout=timeout,
             ),
         ):
             if fut := next(

libs/langgraph/langgraph/pregel/_utils.py

@@ -4,27 +4,16 @@ import ast
 import inspect
 import re
 import textwrap
-from collections.abc import Callable, Sequence
-from functools import partial
+from collections.abc import Callable
 from typing import Any
 
-from langchain_core.runnables import (
-    Runnable,
-    RunnableLambda,
-    RunnableParallel,
-    RunnableSequence,
-)
-from langchain_core.runnables.base import RunnableBindingBase
-from langchain_core.runnables.config import run_in_executor
+from langchain_core.runnables import Runnable, RunnableLambda, RunnableSequence
 from langgraph.checkpoint.base import ChannelVersions
 from typing_extensions import override
 
 from langgraph._internal._runnable import RunnableCallable, RunnableSeq
-from langgraph._internal._timeout import sync_timeout_unsupported
 from langgraph.pregel.protocol import PregelProtocol
 
-_SEQUENCE_TYPES = (RunnableSeq, RunnableSequence)
-
 
 def get_new_channel_versions(
     previous_versions: ChannelVersions, current_versions: ChannelVersions
@@ -75,68 +64,6 @@ def find_subgraph_pregel(candidate: Runnable) -> PregelProtocol | None:
     return None
 
 
-def _sequence_steps(runnable: Runnable) -> Sequence[Runnable] | None:
-    if isinstance(runnable, _SEQUENCE_TYPES):
-        return runnable.steps
-    return None
-
-
-def _parallel_steps(runnable: Runnable) -> Sequence[Runnable] | None:
-    if isinstance(runnable, RunnableParallel):
-        return tuple(runnable.steps__.values())
-    return None
-
-
-def _has_method_override(runnable: Runnable, method_name: str) -> bool:
-    method = getattr(type(runnable), method_name, None)
-    return method is not None and method is not getattr(Runnable, method_name)
-
-
-def _is_executor_backed_afunc(afunc: Callable[..., Any] | None) -> bool:
-    return isinstance(afunc, partial) and afunc.func is run_in_executor
-
-
-def _has_native_async(runnable: Runnable) -> bool:
-    if isinstance(runnable, RunnableCallable):
-        return runnable.afunc is not None and not _is_executor_backed_afunc(
-            runnable.afunc
-        )
-    if isinstance(runnable, RunnableLambda):
-        return bool(getattr(runnable, "afunc", False))
-    return _has_method_override(runnable, "ainvoke")
-
-
-def _runnable_has_native_async(runnable: Runnable) -> bool:
-    """Return whether a runnable can be idle-timed without known sync code.
-
-    For custom runnable subclasses, an `ainvoke` override is treated as the
-    async contract. We do not introspect whether that implementation delegates
-    to blocking work internally — e.g. a subclass whose `ainvoke` calls
-    `asyncio.to_thread(self.invoke, ...)` will pass this check but the wrapped
-    sync work is still uncancellable. Idle-timeout enforcement on such a
-    runnable will fire `NodeTimeoutError` correctly, but the background thread
-    will keep running until its sync work returns.
-    """
-
-    while isinstance(runnable, RunnableBindingBase):
-        runnable = runnable.bound
-    steps = _sequence_steps(runnable)
-    if steps is None:
-        steps = _parallel_steps(runnable)
-    if steps is not None:
-        return all(_runnable_has_native_async(step) for step in steps)
-    # Raw callables and the common composition wrappers created by graph
-    # builders fall through here. We do not exhaustively unwrap every Runnable
-    # wrapper — wrappers that provide `ainvoke` are treated as owning the async
-    # contract.
-    return _has_native_async(runnable)
-
-
-def validate_timeout_supported(runnable: Runnable, *, name: str) -> None:
-    if not _runnable_has_native_async(runnable):
-        raise sync_timeout_unsupported(name)
-
-
 def get_function_nonlocals(func: Callable) -> list[Any]:
     """Get the nonlocal variables accessed by a function.
 

libs/langgraph/langgraph/pregel/main.py

@@ -17,7 +17,6 @@ from collections.abc import (
     Sequence,
 )
 from dataclasses import is_dataclass, replace
-from datetime import timedelta
 from functools import partial
 from inspect import isclass
 from typing import (
@@ -97,7 +96,6 @@ from langgraph._internal._runnable import (
     RunnableSeq,
     coerce_to_runnable,
 )
-from langgraph._internal._timeout import coerce_timeout_policy
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
 from langgraph.callbacks import (
     GraphInterruptEvent,
@@ -111,7 +109,6 @@ from langgraph.config import get_config
 from langgraph.constants import END
 from langgraph.errors import (
     ErrorCode,
-    GraphDrained,
     GraphRecursionError,
     InvalidUpdateError,
     create_error_message,
@@ -126,7 +123,6 @@ from langgraph.pregel._algo import (
 )
 from langgraph.pregel._call import identifier
 from langgraph.pregel._checkpoint import (
-    achannels_from_checkpoint,
     channels_from_checkpoint,
     copy_checkpoint,
     create_checkpoint,
@@ -146,10 +142,7 @@ from langgraph.pregel._read import DEFAULT_BOUND, PregelNode
 from langgraph.pregel._retry import RetryPolicy
 from langgraph.pregel._runner import PregelRunner
 from langgraph.pregel._tools import StreamToolCallHandler
-from langgraph.pregel._utils import (
-    get_new_channel_versions,
-    validate_timeout_supported,
-)
+from langgraph.pregel._utils import get_new_channel_versions
 from langgraph.pregel._validate import validate_graph, validate_keys
 from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
 from langgraph.pregel.debug import get_bolded_text, get_colored_text, tasks_w_writes
@@ -157,7 +150,6 @@ from langgraph.pregel.protocol import PregelProtocol, StreamChunk, StreamProtoco
 from langgraph.runtime import (
     DEFAULT_RUNTIME,
     BaseUser,
-    RunControl,
     Runtime,
     ServerInfo,
 )
@@ -183,7 +175,6 @@ from langgraph.types import (
     StateUpdate,
     StreamMode,
     StreamPart,
-    TimeoutPolicy,
     ensure_valid_checkpointer,
 )
 from langgraph.typing import ContextT, InputT, OutputT, StateT
@@ -209,7 +200,6 @@ class NodeBuilder:
         "_bound",
         "_retry_policy",
         "_cache_policy",
-        "_timeout",
     )
 
     _channels: str | list[str]
@@ -220,7 +210,6 @@ class NodeBuilder:
     _bound: Runnable
     _retry_policy: list[RetryPolicy]
     _cache_policy: CachePolicy | None
-    _timeout: TimeoutPolicy | None
 
     def __init__(
         self,
@@ -233,7 +222,6 @@ class NodeBuilder:
         self._bound = DEFAULT_BOUND
         self._retry_policy = []
         self._cache_policy = None
-        self._timeout = None
 
     def subscribe_only(
         self,
@@ -352,11 +340,6 @@ class NodeBuilder:
         self._cache_policy = policy
         return self
 
-    def set_timeout(self, timeout: float | timedelta | TimeoutPolicy | None) -> Self:
-        """Set the per-attempt timeout policy for this node."""
-        self._timeout = coerce_timeout_policy(timeout)
-        return self
-
     def build(self) -> PregelNode:
         """Builds the node."""
         return PregelNode(
@@ -368,7 +351,6 @@ class NodeBuilder:
             bound=self._bound,
             retry_policy=self._retry_policy,
             cache_policy=self._cache_policy,
-            timeout=self._timeout,
         )
 
 
@@ -905,9 +887,6 @@ class Pregel(
         )
 
     def validate(self) -> Self:
-        for name, node in self.nodes.items():
-            if node.timeout is not None:
-                validate_timeout_supported(node.node or node.bound, name=name)
         validate_graph(
             self.nodes,
             {k: v for k, v in self.channels.items() if isinstance(v, BaseChannel)},
@@ -1143,10 +1122,6 @@ class Pregel(
         channels, managed = channels_from_checkpoint(
             self.channels,
             saved.checkpoint,
-            saver=self.checkpointer
-            if isinstance(self.checkpointer, BaseCheckpointSaver)
-            else None,
-            config=saved.config,
         )
         # tasks for this checkpoint
         next_tasks = prepare_next_tasks(
@@ -1263,13 +1238,9 @@ class Pregel(
 
         step = saved.metadata.get("step", -1) + 1
         stop = step + 2
-        channels, managed = await achannels_from_checkpoint(
+        channels, managed = channels_from_checkpoint(
             self.channels,
             saved.checkpoint,
-            saver=self.checkpointer
-            if isinstance(self.checkpointer, BaseCheckpointSaver)
-            else None,
-            config=saved.config,
         )
         # tasks for this checkpoint
         next_tasks = prepare_next_tasks(
@@ -1640,11 +1611,6 @@ class Pregel(
             channels, managed = channels_from_checkpoint(
                 self.channels,
                 checkpoint,
-                saver=self.checkpointer
-                if saved is not None
-                and isinstance(self.checkpointer, BaseCheckpointSaver)
-                else None,
-                config=saved.config if saved is not None else None,
             )
             values, as_node = updates[0][:2]
 
@@ -2088,14 +2054,9 @@ class Pregel(
             )
             if saved:
                 checkpoint_config = patch_configurable(config, saved.config[CONF])
-            channels, managed = await achannels_from_checkpoint(
+            channels, managed = channels_from_checkpoint(
                 self.channels,
                 checkpoint,
-                saver=self.checkpointer
-                if saved is not None
-                and isinstance(self.checkpointer, BaseCheckpointSaver)
-                else None,
-                config=saved.config if saved is not None else None,
             )
             values, as_node = updates[0][:2]
             # no values, just clear all tasks
@@ -2572,7 +2533,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         subgraphs: bool = False,
         debug: bool | None = None,
         version: Literal["v2"],
@@ -2592,7 +2552,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         subgraphs: bool = False,
         debug: bool | None = None,
         version: Literal["v1"] = ...,
@@ -2611,7 +2570,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         subgraphs: bool = False,
         debug: bool | None = None,
         version: Literal["v1", "v2"] = "v1",
@@ -2656,7 +2614,6 @@ class Pregel(
                 - `"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.
-            control: Optional run control used to request cooperative drain.
             subgraphs: Whether to stream events from inside subgraphs, defaults to `False`.
 
                 If `True`, the events will be emitted as tuples `(namespace, data)`,
@@ -2821,7 +2778,6 @@ class Pregel(
                 previous=None,
                 execution_info=None,
                 server_info=server_info,
-                control=control or parent_runtime.control or RunControl(),
             )
             runtime = parent_runtime.merge(runtime)
             config[CONF][CONFIG_KEY_RUNTIME] = runtime
@@ -2952,10 +2908,6 @@ class Pregel(
                     error_code=ErrorCode.GRAPH_RECURSION_LIMIT,
                 )
                 raise GraphRecursionError(msg)
-            elif loop.status == "draining":
-                if loop.control is None:
-                    raise RuntimeError("Draining status requires run control")
-                raise GraphDrained(loop.control.drain_reason or "shutdown")
             # set final channel values as run output
             run_manager.on_chain_end(loop.output)
         except BaseException as e:
@@ -2976,7 +2928,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         subgraphs: bool = False,
         debug: bool | None = None,
         version: Literal["v2"],
@@ -2996,7 +2947,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         subgraphs: bool = False,
         debug: bool | None = None,
         version: Literal["v1"] = ...,
@@ -3015,7 +2965,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         subgraphs: bool = False,
         debug: bool | None = None,
         version: Literal["v1", "v2"] = "v1",
@@ -3060,7 +3009,6 @@ class Pregel(
                 - `"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.
-            control: Optional run control used to request cooperative drain.
             subgraphs: Whether to stream events from inside subgraphs, defaults to `False`.
 
                 If `True`, the events will be emitted as tuples `(namespace, data)`,
@@ -3260,7 +3208,6 @@ class Pregel(
                 previous=None,
                 execution_info=None,
                 server_info=server_info,
-                control=control or parent_runtime.control or RunControl(),
             )
             runtime = parent_runtime.merge(runtime)
             config[CONF][CONFIG_KEY_RUNTIME] = runtime
@@ -3429,10 +3376,6 @@ class Pregel(
                     error_code=ErrorCode.GRAPH_RECURSION_LIMIT,
                 )
                 raise GraphRecursionError(msg)
-            elif loop.status == "draining":
-                if loop.control is None:
-                    raise RuntimeError("Draining status requires run control")
-                raise GraphDrained(loop.control.drain_reason or "shutdown")
             # set final channel values as run output
             await run_manager.on_chain_end(loop.output)
         except BaseException as e:
@@ -3447,37 +3390,35 @@ class Pregel(
         *,
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
-        control: RunControl | None = None,
         transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
     ) -> Any:
         """Start a sync v2 streaming run driven by transformer projections.
 
-        Builds a `StreamMux` from the built-in transformers, this
-        graph's compile-time `stream_transformers`, and any additional
-        `transformers=` supplied at the call site. Returns a
-        `GraphRunStream` that the caller drives by iterating any
-        projection — no background thread.
-
-        `run.output`, `run.interrupted` and `run.interrupts` work
-        regardless of which transformers are registered.
+        Builds a `StreamMux` from the built-in `ValuesTransformer` /
+        `MessagesTransformer`, this graph's compile-time
+        `stream_transformers`, and any additional `transformers=`
+        supplied at the call site. Returns a `GraphRunStream` that the
+        caller drives by iterating any projection — no background
+        thread.
 
         Note:
             Nesting v1 `stream(stream_mode="messages")` inside a node
             of a `stream_v2` run is not fully supported. The outer v2
-            messages handler reroutes `BaseChatModel.invoke` through
-            the v2 event protocol, so the inner v1 handler does not see
-            `on_llm_new_token` chunks. The inner stream still yields a
-            finalized message via `on_llm_end`. Use `stream_v2` for
-            the inner graph as well, or call
-            `chat_model.stream(...)` explicitly, to get token-level
-            streaming.
+            messages handler is inheritable, so it sits in the inner
+            chat model's callback chain; `BaseChatModel.invoke` then
+            routes through the v2 event protocol and the inner v1
+            messages handler does not see `on_llm_new_token` chunks.
+            The inner stream still yields a finalized message via
+            `on_llm_end`, but token-by-token output is lost. Use
+            `stream_v2` for the inner graph as well, or call
+            `chat_model.stream(...)` explicitly inside the node, to
+            get token-level streaming.
 
         Args:
             input: Graph input.
             config: Optional runnable config forwarded to the graph.
             interrupt_before: Nodes to interrupt before, if any.
             interrupt_after: Nodes to interrupt after, if any.
-            control: Optional run control used to request cooperative drain.
             transformers: Extra transformer classes or configured factories
                 appended after compile-time `stream_transformers`. Factories
                 are called as `factory(scope)` so they can propagate to
@@ -3503,6 +3444,7 @@ class Pregel(
             scope=parent_ns,
             is_async=False,
         )
+        values_t = cast(ValuesTransformer, mux.transformer_by_key("values"))
         graph_iter = iter(
             self.stream(
                 input,
@@ -3512,10 +3454,9 @@ class Pregel(
                 version="v2",
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
-                control=control,
             )
         )
-        return GraphRunStream(graph_iter, mux)
+        return GraphRunStream(graph_iter, mux, values_t)
 
     async def astream_v2(
         self,
@@ -3524,7 +3465,6 @@ class Pregel(
         *,
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
-        control: RunControl | None = None,
         transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
     ) -> Any:
         """Async counterpart to `stream_v2`.
@@ -3538,16 +3478,17 @@ class Pregel(
             `astream(stream_mode="messages")` inside a node of an
             `astream_v2` run drops `on_llm_new_token` chunks because
             the outer v2 handler reroutes `BaseChatModel.invoke`
-            through the v2 event protocol. Use `astream_v2` for the
-            inner graph as well, or call `chat_model.astream(...)`
-            explicitly, to get token-level streaming.
+            through the v2 event protocol. The inner stream still
+            yields a finalized message at end-of-call. Use
+            `astream_v2` for the inner graph as well, or call
+            `chat_model.astream(...)` explicitly inside the node, to
+            get token-level streaming.
 
         Args:
             input: Graph input.
             config: Optional runnable config forwarded to the graph.
             interrupt_before: Nodes to interrupt before, if any.
             interrupt_after: Nodes to interrupt after, if any.
-            control: Optional run control used to request cooperative drain.
             transformers: Extra transformer classes or configured factories
                 appended after compile-time `stream_transformers`. Factories
                 are called as `factory(scope)` so they can propagate to
@@ -3570,6 +3511,7 @@ class Pregel(
             scope=parent_ns,
             is_async=True,
         )
+        values_t = cast(ValuesTransformer, mux.transformer_by_key("values"))
         graph_aiter = self.astream(
             input,
             patch_configurable(config, {CONFIG_KEY_STREAM_MESSAGES_V2: True}),
@@ -3578,9 +3520,8 @@ class Pregel(
             version="v2",
             interrupt_before=interrupt_before,
             interrupt_after=interrupt_after,
-            control=control,
         ).__aiter__()
-        return AsyncGraphRunStream(graph_aiter, mux)
+        return AsyncGraphRunStream(graph_aiter, mux, values_t)
 
     @overload
     def invoke(
@@ -3595,7 +3536,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v2"],
         **kwargs: Any,
     ) -> GraphOutput[OutputT]: ...
@@ -3613,7 +3553,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v2"],
         **kwargs: Any,
     ) -> list[StreamPart[StateT, OutputT]]: ...
@@ -3631,7 +3570,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v1"] = ...,
         **kwargs: Any,
     ) -> dict[str, Any] | Any: ...
@@ -3648,7 +3586,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v1", "v2"] = "v1",
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
@@ -3673,7 +3610,6 @@ class Pregel(
                 - `"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.
-            control: Optional run control used to request cooperative drain.
             version: The streaming format version. `"v1"` (default) returns the
                 traditional format, `"v2"` returns `StreamPart` typed dicts when
                 `stream_mode` is not `"values"`.
@@ -3701,7 +3637,6 @@ class Pregel(
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
                 durability=durability,
-                control=control,
                 version=version,
                 **kwargs,
             ):
@@ -3725,7 +3660,6 @@ class Pregel(
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
                 durability=durability,
-                control=control,
                 **kwargs,
             ):
                 if stream_mode == "values":
@@ -3772,7 +3706,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v2"],
         **kwargs: Any,
     ) -> GraphOutput[OutputT]: ...
@@ -3790,7 +3723,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v2"],
         **kwargs: Any,
     ) -> list[StreamPart[StateT, OutputT]]: ...
@@ -3808,7 +3740,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v1"] = ...,
         **kwargs: Any,
     ) -> dict[str, Any] | Any: ...
@@ -3825,7 +3756,6 @@ class Pregel(
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         durability: Durability | None = None,
-        control: RunControl | None = None,
         version: Literal["v1", "v2"] = "v1",
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
@@ -3850,7 +3780,6 @@ class Pregel(
                 - `"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.
-            control: Optional run control used to request cooperative drain.
             version: The streaming format version. `"v1"` (default) returns the
                 traditional format, `"v2"` returns `StreamPart` typed dicts when
                 `stream_mode` is not `"values"`.
@@ -3878,7 +3807,6 @@ class Pregel(
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
                 durability=durability,
-                control=control,
                 version=version,
                 **kwargs,
             ):
@@ -3902,7 +3830,6 @@ class Pregel(
                 interrupt_before=interrupt_before,
                 interrupt_after=interrupt_after,
                 durability=durability,
-                control=control,
                 **kwargs,
             ):
                 if stream_mode == "values":

libs/langgraph/langgraph/runtime.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-from collections.abc import Callable
 from dataclasses import dataclass, field, replace
 from typing import Any, Generic, cast
 
@@ -16,7 +15,6 @@ from langgraph.typing import ContextT
 __all__ = (
     "BaseUser",
     "ExecutionInfo",
-    "RunControl",
     "Runtime",
     "ServerInfo",
     "get_runtime",
@@ -76,49 +74,16 @@ class ServerInfo:
     """
 
 
-class RunControl:
-    """Run-scoped control surface for cooperative draining.
-
-    Intended for a single graph run. Create a fresh `RunControl` per run;
-    reusing a control after `request_drain()` leaves it drained.
-
-    Safe to call from any thread: the drain request is represented by a
-    single attribute write, so no lock is needed for this signal.
-    If more mutable state is added here, add synchronization.
-    """
-
-    __slots__ = ("_drain_reason",)
-
-    def __init__(self) -> None:
-        self._drain_reason: str | None = None
-
-    def request_drain(self, reason: str = "shutdown") -> None:
-        self._drain_reason = reason
-
-    @property
-    def drain_requested(self) -> bool:
-        return self._drain_reason is not None
-
-    @property
-    def drain_reason(self) -> str | None:
-        return self._drain_reason
-
-
 def _no_op_stream_writer(_: Any) -> None: ...
 
 
-def _no_op_heartbeat() -> None: ...
-
-
 class _RuntimeOverrides(TypedDict, Generic[ContextT], total=False):
     context: ContextT
     store: BaseStore | None
     stream_writer: StreamWriter
-    heartbeat: Callable[[], None]
     previous: Any
     execution_info: ExecutionInfo
     server_info: ServerInfo | None
-    control: RunControl | None
 
 
 @dataclass(**_DC_KWARGS)
@@ -197,7 +162,7 @@ class Runtime(Generic[ContextT]):
 
     context: ContextT = field(default=None)  # type: ignore[assignment]
     """Static context for the graph run, like `user_id`, `db_conn`, etc.
-
+    
     Can also be thought of as 'run dependencies'."""
 
     store: BaseStore | None = field(default=None)
@@ -206,19 +171,9 @@ class Runtime(Generic[ContextT]):
     stream_writer: StreamWriter = field(default=_no_op_stream_writer)
     """Function that writes to the custom stream."""
 
-    heartbeat: Callable[[], None] = field(default=_no_op_heartbeat)
-    """Record progress for the current node's `idle_timeout`.
-
-    Call this from inside long-running work that does not naturally emit
-    writes, stream chunks, child tasks, or LangChain callback events, to
-    prevent the node from being treated as idle. It is also the only
-    progress signal honored under `TimeoutPolicy(refresh_on="heartbeat")`.
-    Outside an idle-timed attempt this is a no-op.
-    """
-
     previous: Any = field(default=None)
     """The previous return value for the given thread.
-
+    
     Only available with the functional API when a checkpointer is provided.
     """
 
@@ -230,13 +185,6 @@ class Runtime(Generic[ContextT]):
     server_info: ServerInfo | None = field(default=None)
     """Metadata injected by LangGraph Server. None when running open-source LangGraph without LangSmith deployments."""
 
-    control: RunControl | None = field(default=None)
-    """Run-scoped control plane for cooperative draining.
-
-    Populated automatically during graph runs. None outside an active
-    graph runtime.
-    """
-
     def merge(self, other: Runtime[ContextT]) -> Runtime[ContextT]:
         """Merge two runtimes together.
 
@@ -248,13 +196,9 @@ class Runtime(Generic[ContextT]):
             stream_writer=other.stream_writer
             if other.stream_writer is not _no_op_stream_writer
             else self.stream_writer,
-            heartbeat=other.heartbeat
-            if other.heartbeat is not _no_op_heartbeat
-            else self.heartbeat,
             previous=self.previous if other.previous is None else other.previous,
             execution_info=other.execution_info or self.execution_info,
             server_info=other.server_info or self.server_info,
-            control=other.control or self.control,
         )
 
     def override(
@@ -273,23 +217,13 @@ class Runtime(Generic[ContextT]):
             execution_info=self.execution_info.patch(**overrides),
         )
 
-    @property
-    def drain_requested(self) -> bool:
-        return self.control.drain_requested if self.control is not None else False
-
-    @property
-    def drain_reason(self) -> str | None:
-        return self.control.drain_reason if self.control is not None else None
-
 
 DEFAULT_RUNTIME = Runtime(
     context=None,
     store=None,
     stream_writer=_no_op_stream_writer,
-    heartbeat=_no_op_heartbeat,
     previous=None,
     execution_info=None,
-    control=None,
 )
 
 

libs/langgraph/langgraph/stream/__init__.py

@@ -14,23 +14,15 @@ from langgraph.stream.run_stream import (
 )
 from langgraph.stream.stream_channel import StreamChannel
 from langgraph.stream.transformers import (
-    CheckpointsTransformer,
-    CustomTransformer,
-    DebugTransformer,
     LifecyclePayload,
     LifecycleTransformer,
     SubgraphStatus,
     SubgraphTransformer,
-    TasksTransformer,
-    UpdatesTransformer,
 )
 
 __all__ = [
     "AsyncGraphRunStream",
     "AsyncSubgraphRunStream",
-    "CheckpointsTransformer",
-    "CustomTransformer",
-    "DebugTransformer",
     "GraphRunStream",
     "LifecyclePayload",
     "LifecycleTransformer",
@@ -40,6 +32,4 @@ __all__ = [
     "SubgraphRunStream",
     "SubgraphStatus",
     "SubgraphTransformer",
-    "TasksTransformer",
-    "UpdatesTransformer",
 ]

libs/langgraph/langgraph/stream/run_stream.py

@@ -10,7 +10,7 @@ from langgraph.stream._mux import StreamMux
 from langgraph.stream._types import ProtocolEvent
 
 if TYPE_CHECKING:
-    from langgraph.stream.transformers import SubgraphStatus
+    from langgraph.stream.transformers import SubgraphStatus, ValuesTransformer
 
 
 def _drive_until_done(pump: Callable[[], bool]) -> None:
@@ -44,6 +44,7 @@ class GraphRunStream:
         self,
         graph_iter: Iterator[Any] | None,
         mux: StreamMux,
+        values_transformer: ValuesTransformer,
         *,
         wire_pump: bool = True,
     ) -> None:
@@ -54,6 +55,8 @@ class GraphRunStream:
                 or `None` for nested run streams whose pump is driven
                 by an outer run (e.g. `SubgraphRunStream`).
             mux: The StreamMux owning projections and the main log.
+            values_transformer: The built-in values transformer
+                providing `output` / `interrupted` / `interrupts`.
             wire_pump: When True (default), bind `_pump_next` as the
                 mux's pump callable. Subclasses that inherit a parent
                 pump via `StreamMux._make_child` should pass False to
@@ -62,11 +65,8 @@ class GraphRunStream:
         self._graph_iter = graph_iter
         self._mux = mux
         self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
+        self._values_transformer = values_transformer
         self._exhausted = False
-        self._latest: dict[str, Any] | None = None
-        self._interrupted = False
-        self._interrupts: list[Any] = []
-        self._scope_list: list[str] = list(mux.scope)
         for key in mux.native_keys:
             setattr(self, key, mux.extensions[key])
         if wire_pump:
@@ -83,19 +83,6 @@ class GraphRunStream:
         """
         mux.bind_pump(self._pump_next)
 
-    def _observe_event(self, event: ProtocolEvent) -> None:
-        """Track values-event state for output/interrupted/interrupts."""
-        if event["method"] != "values":
-            return
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return
-        self._latest = params["data"]
-        interrupts = params.get("interrupts", ())
-        if interrupts:
-            self._interrupted = True
-            self._interrupts.extend(interrupts)
-
     def _pump_next(self) -> bool:
         """Pull one event from the graph and push it through the mux.
 
@@ -108,9 +95,7 @@ class GraphRunStream:
             return False
         try:
             part = next(self._graph_iter)
-            event = convert_to_protocol_event(part)
-            self._observe_event(event)
-            self._mux.push(event)
+            self._mux.push(convert_to_protocol_event(part))
             return True
         except StopIteration:
             self._mux.close()
@@ -151,9 +136,9 @@ class GraphRunStream:
     def output(self) -> dict[str, Any] | None:
         """Drive the run to completion and return the final state."""
         _drive_until_done(self._pump_next)
-        if (err := self._mux._events._error) is not None:
+        if (err := self._values_transformer.error) is not None:
             raise err
-        return self._latest
+        return self._values_transformer._latest
 
     @property
     def interrupted(self) -> bool:
@@ -164,9 +149,9 @@ class GraphRunStream:
             BaseException: If the run ended with an error.
         """
         _drive_until_done(self._pump_next)
-        if (err := self._mux._events._error) is not None:
+        if (err := self._values_transformer.error) is not None:
             raise err
-        return self._interrupted
+        return self._values_transformer._interrupted
 
     @property
     def interrupts(self) -> list[Any]:
@@ -176,9 +161,9 @@ class GraphRunStream:
             BaseException: If the run ended with an error.
         """
         _drive_until_done(self._pump_next)
-        if (err := self._mux._events._error) is not None:
+        if (err := self._values_transformer.error) is not None:
             raise err
-        return self._interrupts
+        return self._values_transformer._interrupts
 
     def __iter__(self) -> Iterator[ProtocolEvent]:
         """Subscribe to the main event log and iterate protocol events."""
@@ -262,6 +247,7 @@ class AsyncGraphRunStream:
         self,
         graph_aiter: AsyncIterator[Any] | None,
         mux: StreamMux,
+        values_transformer: ValuesTransformer,
         *,
         wire_pump: bool = True,
     ) -> None:
@@ -272,6 +258,8 @@ class AsyncGraphRunStream:
                 `None` for nested run streams whose pump is driven by
                 an outer run (e.g. `AsyncSubgraphRunStream`).
             mux: The StreamMux owning projections and the main log.
+            values_transformer: The built-in values transformer
+                providing `output` / `interrupted` / `interrupts`.
             wire_pump: When True (default), bind `_apump_next` as the
                 mux's async pump callable. Subclasses that inherit a
                 parent pump via `StreamMux._make_child` should pass
@@ -280,11 +268,8 @@ class AsyncGraphRunStream:
         self._graph_aiter = graph_aiter
         self._mux = mux
         self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
+        self._values_transformer = values_transformer
         self._exhausted = False
-        self._latest: dict[str, Any] | None = None
-        self._interrupted = False
-        self._interrupts: list[Any] = []
-        self._scope_list: list[str] = list(mux.scope)
         self._pump_cond = asyncio.Condition()
         self._pumping = False
         for key in mux.native_keys:
@@ -292,19 +277,6 @@ class AsyncGraphRunStream:
         if wire_pump:
             self._wire_arequest_more(mux)
 
-    def _observe_event(self, event: ProtocolEvent) -> None:
-        """Track values-event state for output/interrupted/interrupts."""
-        if event["method"] != "values":
-            return
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return
-        self._latest = params["data"]
-        interrupts = params.get("interrupts", ())
-        if interrupts:
-            self._interrupted = True
-            self._interrupts.extend(interrupts)
-
     def _wire_arequest_more(self, mux: StreamMux) -> None:
         """Wire the async pull callback through the mux.
 
@@ -347,9 +319,7 @@ class AsyncGraphRunStream:
         try:
             try:
                 part = await self._graph_aiter.__anext__()
-                event = convert_to_protocol_event(part)
-                self._observe_event(event)
-                await self._mux.apush(event)
+                await self._mux.apush(convert_to_protocol_event(part))
                 return True
             except StopAsyncIteration:
                 self._exhausted = True
@@ -408,9 +378,9 @@ class AsyncGraphRunStream:
             BaseException: If the run ended with an error.
         """
         await _adrive_until_done(self._apump_next)
-        if (err := self._mux._events._error) is not None:
+        if (err := self._values_transformer.error) is not None:
             raise err
-        return self._latest
+        return self._values_transformer._latest
 
     async def interrupted(self) -> bool:
         """Drive the run to completion and return whether it was
@@ -420,9 +390,9 @@ class AsyncGraphRunStream:
             BaseException: If the run ended with an error.
         """
         await _adrive_until_done(self._apump_next)
-        if (err := self._mux._events._error) is not None:
+        if (err := self._values_transformer.error) is not None:
             raise err
-        return self._interrupted
+        return self._values_transformer._interrupted
 
     async def interrupts(self) -> list[Any]:
         """Drive the run to completion and return interrupt payloads.
@@ -431,9 +401,9 @@ class AsyncGraphRunStream:
             BaseException: If the run ended with an error.
         """
         await _adrive_until_done(self._apump_next)
-        if (err := self._mux._events._error) is not None:
+        if (err := self._values_transformer.error) is not None:
             raise err
-        return self._interrupts
+        return self._values_transformer._interrupts
 
     def __aiter__(self) -> AsyncIterator[ProtocolEvent]:
         """Subscribe to the main event log and iterate protocol events."""
@@ -474,6 +444,7 @@ class SubgraphRunStream(GraphRunStream, _SubgraphRunStreamMixin):
     def __init__(
         self,
         mux: StreamMux,
+        values_transformer: ValuesTransformer,
         *,
         path: tuple[str, ...],
         graph_name: str | None = None,
@@ -485,6 +456,7 @@ class SubgraphRunStream(GraphRunStream, _SubgraphRunStreamMixin):
         super().__init__(
             graph_iter=None,
             mux=mux,
+            values_transformer=values_transformer,
             wire_pump=False,
         )
         self.path = path
@@ -517,6 +489,7 @@ class AsyncSubgraphRunStream(AsyncGraphRunStream, _SubgraphRunStreamMixin):
     def __init__(
         self,
         mux: StreamMux,
+        values_transformer: ValuesTransformer,
         *,
         path: tuple[str, ...],
         graph_name: str | None = None,
@@ -526,6 +499,7 @@ class AsyncSubgraphRunStream(AsyncGraphRunStream, _SubgraphRunStreamMixin):
         super().__init__(
             graph_aiter=None,
             mux=mux,
+            values_transformer=values_transformer,
             wire_pump=False,
         )
         self.path = path

libs/langgraph/langgraph/stream/transformers.py

@@ -12,7 +12,7 @@ from langchain_core.messages import AIMessageChunk, BaseMessage
 from langchain_protocol.protocol import MessagesData
 from typing_extensions import NotRequired, TypedDict
 
-from langgraph.errors import GraphDrained, GraphInterrupt
+from langgraph.errors import GraphInterrupt
 from langgraph.stream._types import ProtocolEvent, StreamTransformer
 from langgraph.stream.run_stream import AsyncSubgraphRunStream, SubgraphRunStream
 from langgraph.stream.stream_channel import StreamChannel
@@ -28,9 +28,10 @@ _logger = logging.getLogger(__name__)
 class ValuesTransformer(StreamTransformer):
     """Capture values events as a drainable stream of state snapshots.
 
-    Provides the `run.values` projection. `run.output`,
-    `run.interrupted` and `run.interrupts` are tracked directly
-    by the run stream and do not depend on this transformer.
+    Keeps `_latest` / `_interrupted` / `_interrupts` as scalar state
+    regardless of whether the log has a subscriber — so `run.output()`
+    and `run.interrupted` work without forcing the caller to iterate
+    `run.values`. Log pushes are silent no-ops when unsubscribed.
 
     Native transformer — projection keys are exposed as direct
     attributes on the run stream (e.g. `run.values`).
@@ -38,9 +39,9 @@ class ValuesTransformer(StreamTransformer):
     Only values events at the run's own level are captured; snapshots
     from deeper subgraphs are left in the main event log but excluded
     from the projection. "Own level" is defined by `scope`, which
-    `stream_v2` / `astream_v2` populate from the caller's
-    checkpoint namespace so that a nested `stream_v2` call still
-    sees its own root snapshots.
+    `stream_v2` / `astream_v2` populate from the caller's checkpoint
+    namespace so that a nested `stream_v2` call still sees its own
+    root snapshots.
     """
 
     _native = True
@@ -82,76 +83,6 @@ class ValuesTransformer(StreamTransformer):
         return True
 
 
-class CustomTransformer(StreamTransformer):
-    """Capture custom events as a drainable stream of arbitrary payloads.
-
-    Nodes emit custom data via `get_stream_writer()`. This transformer
-    surfaces those events on `run.custom` as a `StreamChannel[Any]`,
-    preserving payloads in arrival order.
-
-    Only events at the run's own scope are captured; custom data from
-    deeper subgraphs is available on the respective subgraph handle's
-    `.custom` projection.
-
-    Native transformer — `run.custom` is a direct attribute.
-    """
-
-    _native = True
-    required_stream_modes = ("custom",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[Any] = StreamChannel()
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"custom": self._log}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "custom":
-            return True
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True
-        self._log.push(params["data"])
-        return True
-
-
-class UpdatesTransformer(StreamTransformer):
-    """Capture updates events as a drainable stream of node outputs.
-
-    Surfaces `stream_mode="updates"` data on `run.updates` as a
-    `StreamChannel[dict[str, Any]]`. Each item is a dict mapping a node
-    (or task) name to the update it returned after a step.
-
-    Only events at the run's own scope are captured; updates from deeper
-    subgraphs are available on the respective subgraph handle's
-    `.updates` projection.
-
-    Native transformer — `run.updates` is a direct attribute.
-    """
-
-    _native = True
-    required_stream_modes = ("updates",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"updates": self._log}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "updates":
-            return True
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True
-        self._log.push(params["data"])
-        return True
-
-
 class MessagesTransformer(StreamTransformer):
     """Capture messages events as ChatModelStream objects.
 
@@ -327,7 +258,7 @@ class MessagesTransformer(StreamTransformer):
         self._by_run.clear()
 
 
-SubgraphStatus = Literal["started", "completed", "failed", "interrupted", "drained"]
+SubgraphStatus = Literal["started", "completed", "failed", "interrupted"]
 
 
 def _parse_ns_segment(segment: str) -> tuple[str, str | None]:
@@ -472,8 +403,10 @@ class _TasksLifecycleBase(StreamTransformer):
         self._open.clear()
 
     def fail(self, err: BaseException) -> None:
-        """Emit terminal status for any tracked namespace still open."""
-        status, error_str = _status_from_exception(err)
+        """Emit `failed` / `interrupted` for any tracked namespace still open."""
+        is_interrupt = isinstance(err, GraphInterrupt)
+        status: SubgraphStatus = "interrupted" if is_interrupt else "failed"
+        error_str = None if is_interrupt else str(err)
         for ns in list(self._open):
             self._on_terminal(ns, status, error_str)
         self._open.clear()
@@ -481,8 +414,6 @@ class _TasksLifecycleBase(StreamTransformer):
 
 def _status_from_exception(err: BaseException) -> tuple[SubgraphStatus, str | None]:
     """Map a run exception to a subgraph terminal status and error string."""
-    if isinstance(err, GraphDrained):
-        return "drained", None
     if isinstance(err, GraphInterrupt):
         return "interrupted", None
     return "failed", str(err)
@@ -618,10 +549,17 @@ class SubgraphTransformer(_TasksLifecycleBase):
         try:
             child_mux = self._mux._make_child(ns)
         except RuntimeError:
+            # Mux wasn't built from factories — no mini-mux navigation
+            # available. Skip; LifecycleTransformer still tracks the
+            # subgraph via the flat event stream.
+            return
+        values_t = child_mux.transformer_by_key("values")
+        if not isinstance(values_t, ValuesTransformer):
             return
         handle_cls = AsyncSubgraphRunStream if child_mux.is_async else SubgraphRunStream
         handle = handle_cls(
             mux=child_mux,
+            values_transformer=values_t,
             path=ns,
             graph_name=graph_name,
             trigger_call_id=trigger_call_id,
@@ -692,9 +630,7 @@ class SubgraphTransformer(_TasksLifecycleBase):
         else:
             await handle._mux.aclose()
 
-    def _handle_for_event(
-        self, event: ProtocolEvent
-    ) -> SubgraphRunStream | AsyncSubgraphRunStream | None:
+    def _child_mux_for_event(self, event: ProtocolEvent) -> StreamMux | None:
         ns = tuple(event["params"]["namespace"])
         depth = len(self.scope)
         if len(ns) < depth + 1:
@@ -702,21 +638,22 @@ class SubgraphTransformer(_TasksLifecycleBase):
         handle = self._handles.get(ns[: depth + 1])
         if handle is None or handle._mux is None or handle._mux._events._closed:
             return None
-        return handle
+        return handle._mux
 
     def process(self, event: ProtocolEvent) -> bool:
-        # Run tasks bookkeeping first so a `started` handle exists
-        # by the time we forward the event to the child mini-mux.
+        # Discover / update terminal status before forwarding so a
+        # `started` handle exists by the time the child mini-mux sees
+        # its own first event.
         keep = super().process(event)
-        handle = self._handle_for_event(event)
-        if handle is not None:
-            handle._observe_event(event)
-            handle._mux.push(event)
+        child_mux = self._child_mux_for_event(event)
+        if child_mux is not None:
+            child_mux.push(event)
         return keep
 
     async def aprocess(self, event: ProtocolEvent) -> bool:
-        # Async counterpart: repeats the tasks bookkeeping here so
-        # child mini-muxes receive events through their async lane.
+        # Async counterpart to `process`: repeat the tasks bookkeeping
+        # here instead of delegating to `process`, so child mini-muxes
+        # receive events through their async lane.
         if event["method"] == "tasks":
             ns = tuple(event["params"]["namespace"])
             data = event["params"]["data"]
@@ -728,10 +665,9 @@ class SubgraphTransformer(_TasksLifecycleBase):
             keep = False
         else:
             keep = True
-        handle = self._handle_for_event(event)
-        if handle is not None:
-            handle._observe_event(event)
-            await handle._mux.apush(event)
+        child_mux = self._child_mux_for_event(event)
+        if child_mux is not None:
+            await child_mux.apush(event)
         return keep
 
     def _complete_open_handles(self) -> BaseException | None:
@@ -811,118 +747,3 @@ class SubgraphTransformer(_TasksLifecycleBase):
                         handle.path,
                         exc_info=True,
                     )
-
-
-class CheckpointsTransformer(StreamTransformer):
-    """Capture checkpoint events as a drainable stream.
-
-    Surfaces `stream_mode="checkpoints"` data on `run.checkpoints` as
-    a `StreamChannel[dict[str, Any]]`. Each item is in the same format
-    as returned by `get_state()`.
-
-    Checkpoint events are only emitted when a checkpointer is configured
-    on the graph. When no checkpointer is present, the projection exists
-    but receives no events.
-
-    Only events at the run's own scope are captured; checkpoint data from
-    deeper subgraphs is available on the respective subgraph handle's
-    `.checkpoints` projection.
-
-    Native transformer — `run.checkpoints` is a direct attribute.
-    """
-
-    _native = True
-    required_stream_modes = ("checkpoints",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"checkpoints": self._log}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "checkpoints":
-            return True
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True
-        self._log.push(params["data"])
-        return True
-
-
-class DebugTransformer(StreamTransformer):
-    """Capture debug events as a drainable stream.
-
-    Surfaces `stream_mode="debug"` data on `run.debug` as a
-    `StreamChannel[dict[str, Any]]`. Each item is a debug event with
-    step-level detail (checkpoint snapshots, task payloads, and
-    task results wrapped with step number and timestamp).
-
-    Only events at the run's own scope are captured; debug data from
-    deeper subgraphs is available on the respective subgraph handle's
-    `.debug` projection.
-
-    Native transformer — `run.debug` is a direct attribute.
-    """
-
-    _native = True
-    required_stream_modes = ("debug",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"debug": self._log}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "debug":
-            return True
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True
-        self._log.push(params["data"])
-        return True
-
-
-class TasksTransformer(StreamTransformer):
-    """Capture raw task events as a drainable stream.
-
-    Surfaces `stream_mode="tasks"` data on `run.tasks` as a
-    `StreamChannel[dict[str, Any]]`. Each item is a task payload
-    (start or result).
-
-    `LifecycleTransformer` and `SubgraphTransformer` also consume
-    `tasks` events for subgraph discovery and lifecycle tracking.
-    This transformer captures the raw payloads independently for
-    consumers who need task-level detail.
-
-    Only events at the run's own scope are captured; task data from
-    deeper subgraphs is available on the respective subgraph handle's
-    `.tasks` projection.
-
-    Native transformer — `run.tasks` is a direct attribute.
-    """
-
-    _native = True
-    required_stream_modes = ("tasks",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"tasks": self._log}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "tasks":
-            return True
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True
-        self._log.push(params["data"])
-        return True

libs/langgraph/langgraph/types.py

@@ -4,7 +4,6 @@ import sys
 from collections import deque
 from collections.abc import Callable, Hashable, Sequence
 from dataclasses import asdict, dataclass
-from datetime import timedelta
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -68,7 +67,6 @@ __all__ = (
     "CheckpointPayload",
     "DebugPayload",
     "RetryPolicy",
-    "TimeoutPolicy",
     "CachePolicy",
     "Interrupt",
     "StateUpdate",
@@ -425,83 +423,6 @@ class RetryPolicy(NamedTuple):
     """List of exception classes that should trigger a retry, or a callable that returns `True` for exceptions that should trigger a retry."""
 
 
-def _coerce_timeout_seconds(
-    value: float | timedelta | None, *, field: str
-) -> float | None:
-    if value is None:
-        return None
-    seconds = value.total_seconds() if isinstance(value, timedelta) else float(value)
-    if seconds <= 0:
-        raise ValueError(f"{field} must be greater than 0")
-    return seconds
-
-
-@dataclass(**_DC_KWARGS)
-class TimeoutPolicy:
-    """Configuration for timing out node attempts.
-
-    !!! note "Cooperative cancellation"
-
-        Timeouts rely on asyncio cancellation. If your node uses synchronous
-        time.sleep() or other CPU-bound work that blocks the GIL, the timeout will not
-        be fired until after the event loop has been released.
-
-    !!! note "Inline callback dispatch"
-
-        Under `refresh_on="auto"`, an internal handler refreshes the timeout on any
-        callback event that occurs in the execution of the node or its nested descendants.
-    """
-
-    run_timeout: float | timedelta | None = None
-    """Hard wall-clock cap (in seconds) for a single node attempt.
-
-    This timeout is never refreshed by progress signals or `runtime.heartbeat()`.
-    """
-
-    idle_timeout: float | timedelta | None = None
-    """Maximum time (in seconds) a single node attempt may go without observable progress."""
-
-    refresh_on: Literal["auto", "heartbeat"] = "auto"
-    """Which signals refresh `idle_timeout`.
-
-    `"auto"` refreshes on standard graph progress signals and explicit heartbeats.
-    `"heartbeat"` refreshes only on explicit `runtime.heartbeat()` calls.
-    """
-
-    @classmethod
-    def coerce(
-        cls, value: float | timedelta | TimeoutPolicy | None
-    ) -> TimeoutPolicy | None:
-        """Normalize a timeout value to positive-second policy fields."""
-        if value is None:
-            return None
-        if isinstance(value, TimeoutPolicy):
-            # Fast path: a policy already produced by coerce() has float
-            # timeouts and a validated refresh_on, so we can return it as-is.
-            # `frozen=True` makes this safe to share.
-            rt, it = value.run_timeout, value.idle_timeout
-            if (
-                value.refresh_on in ("auto", "heartbeat")
-                and (rt is None or (type(rt) is float and rt > 0))
-                and (it is None or (type(it) is float and it > 0))
-                and (rt is not None or it is not None)
-            ):
-                return value
-        else:
-            value = cls(run_timeout=value)
-        if value.refresh_on not in ("auto", "heartbeat"):
-            raise ValueError("refresh_on must be 'auto' or 'heartbeat'")
-        run_timeout = _coerce_timeout_seconds(value.run_timeout, field="run_timeout")
-        idle_timeout = _coerce_timeout_seconds(value.idle_timeout, field="idle_timeout")
-        if run_timeout is None and idle_timeout is None:
-            return None
-        return cls(
-            run_timeout=run_timeout,
-            idle_timeout=idle_timeout,
-            refresh_on=value.refresh_on,
-        )
-
-
 KeyFuncT = TypeVar("KeyFuncT", bound=Callable[..., str | bytes])
 
 
@@ -627,7 +548,6 @@ class PregelExecutableTask:
     path: tuple[str | int | tuple, ...]
     writers: Sequence[Runnable] = ()
     subgraphs: Sequence[PregelProtocol] = ()
-    timeout: TimeoutPolicy | None = None
 
 
 class StateSnapshot(NamedTuple):
@@ -667,8 +587,6 @@ class Send:
     Attributes:
         node (str): The name of the target node to send the message to.
         arg (Any): The state or message to send to the target node.
-        timeout (TimeoutPolicy | None): Optional timeout policy for this specific
-            pushed task. If omitted, the target node's timeout policy is used.
 
     !!! example
 
@@ -698,47 +616,33 @@ class Send:
         ```
     """
 
-    __slots__ = ("node", "arg", "timeout")
+    __slots__ = ("node", "arg")
 
     node: str
     arg: Any
-    timeout: TimeoutPolicy | None
 
-    def __init__(
-        self,
-        /,
-        node: str,
-        arg: Any,
-        *,
-        timeout: float | timedelta | TimeoutPolicy | None = None,
-    ) -> None:
+    def __init__(self, /, node: str, arg: Any) -> None:
         """
         Initialize a new instance of the `Send` class.
 
         Args:
             node: The name of the target node to send the message to.
             arg: The state or message to send to the target node.
-            timeout: Optional timeout policy for this specific pushed task. A
-                number or `timedelta` is treated as a hard `run_timeout`.
         """
         self.node = node
         self.arg = arg
-        self.timeout = TimeoutPolicy.coerce(timeout)
 
     def __hash__(self) -> int:
-        return hash((self.node, self.arg, self.timeout))
+        return hash((self.node, self.arg))
 
     def __repr__(self) -> str:
-        if self.timeout is None:
-            return f"Send(node={self.node!r}, arg={self.arg!r})"
-        return f"Send(node={self.node!r}, arg={self.arg!r}, timeout={self.timeout!r})"
+        return f"Send(node={self.node!r}, arg={self.arg!r})"
 
     def __eq__(self, value: object) -> bool:
         return (
             isinstance(value, Send)
             and self.node == value.node
             and self.arg == value.arg
-            and self.timeout == value.timeout
         )
 
 

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.2.0a1"
+version = "1.1.10"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -25,7 +25,7 @@ classifiers = [
 ]
 dependencies = [
     "langchain-core>=1.3.2,<2",
-    "langgraph-checkpoint>=4.1.0a1,<5.0.0",
+    "langgraph-checkpoint>=2.1.0,<5.0.0",
     "langgraph-sdk>=0.3.0,<0.4.0",
     "langgraph-prebuilt>=1.0.12,<1.1.0",
     "xxhash>=3.5.0",
@@ -38,7 +38,7 @@ Homepage = "https://docs.langchain.com/oss/python/langgraph/overview"
 Documentation = "https://reference.langchain.com/python/langgraph/"
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/langgraph"
 Changelog = "https://github.com/langchain-ai/langgraph/releases"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 
@@ -81,6 +81,7 @@ dev = [
 
 
 [tool.uv.sources]
+langchain-core = { git = "https://github.com/langchain-ai/langchain", branch = "cb/chat-model-updates", subdirectory = "libs/core" }
 langgraph-prebuilt = { path = "../prebuilt", editable = true }
 langgraph-checkpoint = { path = "../checkpoint", editable = true }
 langgraph-checkpoint-sqlite = { path = "../checkpoint-sqlite", editable = true }

libs/langgraph/tests/test_channels.py

@@ -1,34 +1,18 @@
 import operator
 from collections.abc import Sequence
-from typing import Annotated
 
 import pytest
-from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
-from langgraph.checkpoint.base import DELTA_SENTINEL
-from langgraph.checkpoint.memory import InMemorySaver
-from langgraph.checkpoint.serde.types import _DeltaSnapshot
-from typing_extensions import NotRequired, TypedDict
 
 from langgraph._internal._typing import MISSING
 from langgraph.channels.binop import BinaryOperatorAggregate
-from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
 from langgraph.channels.topic import Topic
 from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.errors import EmptyChannelError, InvalidUpdateError
-from langgraph.graph import START, StateGraph
-from langgraph.graph.message import _messages_delta_reducer
-from langgraph.graph.state import _get_channel
-from langgraph.types import Overwrite
 
 pytestmark = pytest.mark.anyio
 
 
-# ---------------------------------------------------------------------------
-# Core channel primitives
-# ---------------------------------------------------------------------------
-
-
 def test_last_value() -> None:
     channel = LastValue(int).from_checkpoint(MISSING)
     assert channel.ValueType is int
@@ -111,543 +95,25 @@ def test_untracked_value() -> None:
     assert channel.ValueType is dict
     assert channel.UpdateType is dict
 
+    # UntrackedValue should start empty
     with pytest.raises(EmptyChannelError):
         channel.get()
 
+    # Should be able to update with a value
     test_data = {"session": "test", "temp": "dir"}
     channel.update([test_data])
     assert channel.get() == test_data
 
+    # Update with new value
     new_data = {"session": "updated", "temp": "newdir"}
     channel.update([new_data])
     assert channel.get() == new_data
 
+    # On checkpoint, UntrackedValue should return MISSING
     checkpoint = channel.checkpoint()
     assert checkpoint is MISSING
 
+    # Creating from checkpoint with MISSING should start empty
     new_channel = UntrackedValue(dict).from_checkpoint(checkpoint)
     with pytest.raises(EmptyChannelError):
         new_channel.get()
-
-
-# ---------------------------------------------------------------------------
-# DeltaChannel — message reducer
-# ---------------------------------------------------------------------------
-
-
-def test_delta_channel_basic_two_steps() -> None:
-    ch = DeltaChannel(_messages_delta_reducer, list).from_checkpoint(MISSING)
-
-    ch.update([HumanMessage(content="hi", id="h1")])
-    d1 = ch.checkpoint()
-    assert d1 is DELTA_SENTINEL
-
-    ch.update([AIMessage(content="hello", id="a1")])
-    d2 = ch.checkpoint()
-    assert d2 is DELTA_SENTINEL
-
-    assert len(ch.get()) == 2
-    assert ch.get()[0].content == "hi"
-    assert ch.get()[1].content == "hello"
-
-
-def test_delta_channel_from_checkpoint_writes_list() -> None:
-    """replay_writes on a fresh channel replays through the operator."""
-    spec = DeltaChannel(_messages_delta_reducer, list)
-    ch = spec.from_checkpoint(DELTA_SENTINEL)
-    ch.replay_writes(
-        [
-            ("t0", "messages", HumanMessage(content="hi", id="h1")),
-            ("t1", "messages", AIMessage(content="hello", id="a1")),
-            ("t2", "messages", HumanMessage(content="bye", id="h2")),
-        ]
-    )
-    msgs = ch.get()
-    assert len(msgs) == 3
-    assert msgs[0].content == "hi"
-    assert msgs[1].content == "hello"
-    assert msgs[2].content == "bye"
-
-
-def test_delta_channel_from_checkpoint_backwards_compat() -> None:
-    spec = DeltaChannel(_messages_delta_reducer, list)
-    old_value = [HumanMessage(content="old", id="h1")]
-    ch = spec.from_checkpoint(old_value)
-    assert ch.get() == old_value
-
-
-def test_delta_channel_overwrite() -> None:
-    ch = DeltaChannel(_messages_delta_reducer, list).from_checkpoint(MISSING)
-    ch.update([HumanMessage(content="old", id="h1")])
-
-    ch.update([Overwrite([HumanMessage(content="new", id="h2")])])
-    d = ch.checkpoint()
-    assert d is DELTA_SENTINEL
-    assert len(ch.get()) == 1
-    assert ch.get()[0].content == "new"
-
-
-def test_delta_channel_remove_message_and_replay() -> None:
-    """RemoveMessage must round-trip correctly when writes are replayed."""
-    spec = DeltaChannel(_messages_delta_reducer, list)
-    ch = spec.from_checkpoint(MISSING)
-
-    ch.update([HumanMessage(content="hi", id="h1")])
-    ch.update([AIMessage(content="hello", id="a1")])
-    assert ch.get() == [
-        HumanMessage(content="hi", id="h1"),
-        AIMessage(content="hello", id="a1"),
-    ]
-
-    ch.update([RemoveMessage(id="a1")])
-    assert ch.get() == [HumanMessage(content="hi", id="h1")]
-
-    ch2 = spec.from_checkpoint(DELTA_SENTINEL)
-    ch2.replay_writes(
-        [
-            ("t0", "messages", HumanMessage(content="hi", id="h1")),
-            ("t1", "messages", AIMessage(content="hello", id="a1")),
-            ("t2", "messages", RemoveMessage(id="a1")),
-        ]
-    )
-    assert ch2.get() == [HumanMessage(content="hi", id="h1")]
-
-
-def test_delta_channel_update_by_id_and_replay() -> None:
-    """Updating a message by ID must round-trip correctly through writes replay."""
-    spec = DeltaChannel(_messages_delta_reducer, list)
-    ch = spec.from_checkpoint(MISSING)
-
-    ch.update([HumanMessage(content="original", id="h1")])
-    ch.update([HumanMessage(content="updated", id="h1")])
-    assert ch.get() == [HumanMessage(content="updated", id="h1")]
-
-    ch2 = spec.from_checkpoint(DELTA_SENTINEL)
-    ch2.replay_writes(
-        [
-            ("t0", "messages", HumanMessage(content="original", id="h1")),
-            ("t1", "messages", HumanMessage(content="updated", id="h1")),
-        ]
-    )
-    assert len(ch2.get()) == 1
-    assert ch2.get()[0].content == "updated"
-
-
-def test_delta_channel_checkpoint_returns_sentinel() -> None:
-    """checkpoint() always returns DELTA_SENTINEL regardless of state."""
-    ch = DeltaChannel(_messages_delta_reducer, list).from_checkpoint(MISSING)
-    assert ch.checkpoint() is DELTA_SENTINEL
-
-    ch.update([HumanMessage(content="hi", id="h1")])
-    assert ch.checkpoint() is DELTA_SENTINEL
-
-
-# ---------------------------------------------------------------------------
-# DeltaChannel — snapshot frequency
-# ---------------------------------------------------------------------------
-
-
-def test_delta_channel_snapshot_step_based() -> None:
-    """Snapshots fire on every Nth step regardless of whether the channel was written.
-
-    With snapshot_frequency=N, every Nth pregel step produces a _DeltaSnapshot
-    blob — even if the channel had no write that step (eager snapshot). This
-    bounds the ancestor walk to at most N steps on any read.
-    """
-
-    class State(TypedDict):
-        messages: Annotated[
-            list, DeltaChannel(_messages_delta_reducer, snapshot_frequency=5)
-        ]
-        other: str
-
-    def node_a(state: State) -> dict:
-        i = len(state["messages"]) // 2
-        return {"messages": [AIMessage(content=f"a{i}", id=f"a{i}")]}
-
-    def node_b(state: State) -> dict:
-        return {"other": "y"}
-
-    g = StateGraph(State)
-    g.add_node("a", node_a)
-    g.add_node("b", node_b)
-    g.add_edge(START, "a")
-    g.add_edge("a", "b")
-    saver = InMemorySaver()
-    graph = g.compile(checkpointer=saver)
-
-    config = {"configurable": {"thread_id": "t1"}}
-    for i in range(6):
-        graph.invoke(
-            {"messages": [HumanMessage(content=f"h{i}", id=f"h{i}")], "other": ""},
-            config,
-        )
-
-    msg_blob_values = [
-        saver.serde.loads_typed((type_tag, blob))
-        for k, (type_tag, blob) in saver.blobs.items()
-        if k[2] == "messages" and type_tag == "msgpack" and blob
-    ]
-    snapshots = [v for v in msg_blob_values if isinstance(v, _DeltaSnapshot)]
-    assert snapshots, "expected at least one _DeltaSnapshot blob for messages"
-
-    state = graph.get_state(config)
-    assert len(state.values["messages"]) == 12  # 6 human + 6 AI
-
-
-def test_delta_channel_snapshot_fires_even_when_not_written() -> None:
-    """Eager snapshot: _DeltaSnapshot stored at snapshot step even when the
-    channel had no write that step (node_b doesn't touch messages).
-    """
-
-    class State(TypedDict):
-        messages: Annotated[
-            list, DeltaChannel(_messages_delta_reducer, snapshot_frequency=3)
-        ]
-        tick: int
-
-    def writer(state: State) -> dict:
-        i = len(state["messages"]) // 2
-        return {"messages": [AIMessage(content=f"a{i}", id=f"a{i}")]}
-
-    def ticker(state: State) -> dict:
-        return {"tick": state["tick"] + 1}
-
-    g = StateGraph(State)
-    g.add_node("writer", writer)
-    g.add_node("ticker", ticker)
-    g.add_edge(START, "writer")
-    g.add_edge("writer", "ticker")
-    saver = InMemorySaver()
-    graph = g.compile(checkpointer=saver)
-
-    config = {"configurable": {"thread_id": "t1"}}
-    for i in range(5):
-        graph.invoke(
-            {"messages": [HumanMessage(content=f"h{i}", id=f"h{i}")], "tick": 0},
-            config,
-        )
-
-    msg_blobs = {
-        k: saver.serde.loads_typed((t, b))
-        for k, (t, b) in saver.blobs.items()
-        if k[2] == "messages" and t == "msgpack" and b
-    }
-    snapshots = {k: v for k, v in msg_blobs.items() if isinstance(v, _DeltaSnapshot)}
-    assert snapshots, (
-        "eager snapshots must fire even on steps where messages wasn't written"
-    )
-
-    state = graph.get_state(config)
-    assert len(state.values["messages"]) == 10  # 5 human + 5 AI
-
-
-# ---------------------------------------------------------------------------
-# DeltaChannel — end-to-end (InMemorySaver)
-# ---------------------------------------------------------------------------
-
-
-def test_delta_channel_inmemory_saver_assembles_writes() -> None:
-    """InMemorySaver assembles writes from checkpoint_writes inside get_tuple."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer, list)]
-
-    n = {"v": 0}
-
-    def respond(state: State) -> dict:
-        n["v"] += 1
-        return {"messages": [AIMessage(content=f"ok{n['v']}", id=f"ai{n['v']}")]}
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_edge(START, "respond")
-    saver = InMemorySaver()
-    graph = builder.compile(checkpointer=saver)
-    config = {"configurable": {"thread_id": "t1"}}
-
-    graph.invoke({"messages": [HumanMessage(content="hi", id="h1")]}, config)
-    graph.invoke({"messages": [HumanMessage(content="bye", id="h2")]}, config)
-
-    saved = saver.get_tuple(config)
-    assert saved is not None
-    assert "messages" in saved.checkpoint["channel_values"]
-    assert saved.checkpoint["channel_values"]["messages"] is DELTA_SENTINEL
-
-    state = graph.get_state(config)
-    assert len(state.values["messages"]) == 4  # 2 human + 2 AI
-
-
-# ---------------------------------------------------------------------------
-# DeltaChannel — dict reducer
-# ---------------------------------------------------------------------------
-
-
-def _delta_channel_with_type(op, typ):
-    """Build a DeltaChannel with an explicit type via the Annotated injection path."""
-    return _get_channel("_test", Annotated[typ, DeltaChannel(op)])
-
-
-def test_delta_channel_dict_reducer_fresh_channel() -> None:
-    """DeltaChannel with a dict reducer starts as empty dict on MISSING checkpoint."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
-    assert ch.is_available()
-    assert ch.get() == {}
-
-
-def test_delta_channel_dict_reducer_basic_updates() -> None:
-    """DeltaChannel with a dict reducer accumulates key/value pairs across steps."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
-
-    ch.update([{"a": 1}])
-    d1 = ch.checkpoint()
-    assert d1 is DELTA_SENTINEL
-
-    ch.update([{"b": 2}])
-    d2 = ch.checkpoint()
-    assert d2 is DELTA_SENTINEL
-
-    assert ch.get() == {"a": 1, "b": 2}
-
-
-def test_delta_channel_dict_reducer_writes_reconstruction() -> None:
-    """replay_writes on a fresh channel replays through a dict merge reducer."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    spec = _delta_channel_with_type(merge_dicts, dict)
-    ch = spec.from_checkpoint(DELTA_SENTINEL)
-    ch.replay_writes(
-        [
-            ("t0", "files", {"a": 1}),
-            ("t1", "files", {"b": 2}),
-            ("t2", "files", {"c": 3}),
-        ]
-    )
-    assert ch.get() == {"a": 1, "b": 2, "c": 3}
-
-
-def test_delta_channel_dict_reducer_with_deletions() -> None:
-    """Dict reducer that treats None values as deletions works end-to-end."""
-
-    def merge_files(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            for k, v in w.items():
-                if v is None:
-                    result.pop(k, None)
-                else:
-                    result[k] = v
-        return result
-
-    ch = _delta_channel_with_type(merge_files, dict).from_checkpoint(MISSING)
-    ch.update([{"file1.py": "content1", "file2.py": "content2"}])
-    ch.update([{"file1.py": None, "file3.py": "content3"}])
-    assert ch.get() == {"file2.py": "content2", "file3.py": "content3"}
-
-    spec = _delta_channel_with_type(merge_files, dict)
-    ch2 = spec.from_checkpoint(DELTA_SENTINEL)
-    ch2.replay_writes(
-        [
-            ("t0", "files", {"file1.py": "content1", "file2.py": "content2"}),
-            ("t1", "files", {"file1.py": None, "file3.py": "content3"}),
-        ]
-    )
-    assert ch2.get() == {"file2.py": "content2", "file3.py": "content3"}
-
-
-def test_delta_channel_dict_reducer_overwrite_in_update() -> None:
-    """Overwrite(dict) in update() must preserve dict shape, not coerce to list."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
-    ch.update([{"a": 1}])
-    ch.update([Overwrite({"b": 2, "c": 3})])
-    assert ch.get() == {"b": 2, "c": 3}
-
-
-def test_delta_channel_dict_reducer_overwrite_in_writes_replay() -> None:
-    """Overwrite(dict) embedded in replayed writes must reconstruct as dict."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    spec = _delta_channel_with_type(merge_dicts, dict)
-    ch = spec.from_checkpoint(DELTA_SENTINEL)
-    ch.replay_writes(
-        [
-            ("t0", "files", {"a": 1}),
-            ("t1", "files", Overwrite({"x": 10, "y": 20})),
-            ("t2", "files", {"z": 30}),
-        ]
-    )
-    assert ch.get() == {"x": 10, "y": 20, "z": 30}
-
-
-def test_delta_channel_dict_reducer_with_notrequired_annotation() -> None:
-    """DeltaChannel infers dict type through `Annotated[NotRequired[dict[...]], ch]`."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    annotation = Annotated[NotRequired[dict[str, int]], DeltaChannel(merge_dicts)]
-    ch = _get_channel("files", annotation).from_checkpoint(MISSING)
-    assert ch.get() == {}
-    ch.update([{"a": 1}])
-    ch.update([{"b": 2}])
-    assert ch.get() == {"a": 1, "b": 2}
-
-
-def test_delta_channel_dict_reducer_end_to_end_filesystem() -> None:
-    """End-to-end: graph with dict-reducer (filesystem-style) channel wrapped in DeltaChannel."""
-
-    def merge_files(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            for k, v in w.items():
-                if v is None:
-                    result.pop(k, None)
-                else:
-                    result[k] = v
-        return result
-
-    class State(TypedDict):
-        files: Annotated[dict[str, str], DeltaChannel(merge_files)]
-
-    turn = {"v": 0}
-
-    def write_file(state: State) -> dict:
-        turn["v"] += 1
-        n = turn["v"]
-        return {"files": {f"/doc_{n}.txt": f"content for turn {n}"}}
-
-    builder = StateGraph(State)
-    builder.add_node("write_file", write_file)
-    builder.add_edge(START, "write_file")
-    saver = InMemorySaver()
-    graph = builder.compile(checkpointer=saver)
-    config = {"configurable": {"thread_id": "fs"}}
-
-    for _ in range(3):
-        graph.invoke({"files": {}}, config)
-
-    saved = saver.get_tuple(config)
-    assert saved is not None
-    assert saved.checkpoint["channel_values"]["files"] is DELTA_SENTINEL
-    state = graph.get_state(config)
-    assert state.values["files"] == {
-        "/doc_1.txt": "content for turn 1",
-        "/doc_2.txt": "content for turn 2",
-        "/doc_3.txt": "content for turn 3",
-    }
-
-    def delete_file(state: State) -> dict:
-        return {"files": {"/doc_1.txt": None}}
-
-    builder2 = StateGraph(State)
-    builder2.add_node("write_file", write_file)
-    builder2.add_node("delete_file", delete_file)
-    builder2.add_edge(START, "write_file")
-    builder2.add_edge("write_file", "delete_file")
-    turn["v"] = 0
-    saver2 = InMemorySaver()
-    graph2 = builder2.compile(checkpointer=saver2)
-    config2 = {"configurable": {"thread_id": "fs2"}}
-    graph2.invoke({"files": {}}, config2)
-    state2 = graph2.get_state(config2)
-    assert state2.values["files"] == {}
-
-
-def test_delta_channel_dict_reducer_backwards_compat() -> None:
-    """A pre-DeltaChannel dict checkpoint must load as a dict, not be listified."""
-
-    def merge_dicts(state: dict, writes: list) -> dict:
-        result = dict(state)
-        for w in writes:
-            result.update(w)
-        return result
-
-    spec = _delta_channel_with_type(merge_dicts, dict)
-    old_value = {"a": 1, "b": 2}
-    ch = spec.from_checkpoint(old_value)
-    assert ch.get() == {"a": 1, "b": 2}
-
-
-# ---------------------------------------------------------------------------
-# DeltaChannel — seed / pre-delta migration
-# ---------------------------------------------------------------------------
-
-
-def test_delta_channel_from_checkpoint_honors_seed() -> None:
-    """A non-sentinel value to from_checkpoint is used as the pre-delta seed.
-
-    Guards the pre-delta migration path: when the saver's ancestor walk hits
-    a pre-DeltaChannel blob it passes it as `seed` so replay reconstructs
-    the post-migration state correctly rather than replaying from empty.
-    """
-    spec = DeltaChannel(_messages_delta_reducer, list)
-    seed = [HumanMessage(content="pre-delta", id="p1")]
-    ch = spec.from_checkpoint(seed)
-    ch.replay_writes(
-        [
-            ("t0", "messages", AIMessage(content="delta-1", id="d1")),
-            ("t1", "messages", HumanMessage(content="delta-2", id="d2")),
-        ]
-    )
-    msgs = ch.get()
-    assert [m.content for m in msgs] == ["pre-delta", "delta-1", "delta-2"]
-
-
-def test_delta_channel_from_checkpoint_seed_without_writes() -> None:
-    """Reconstruction at a pre-delta ancestor with no newer deltas returns
-    just the seed — the saver's terminator fired immediately."""
-    spec = DeltaChannel(_messages_delta_reducer, list)
-    seed = [HumanMessage(content="only-snap", id="s1")]
-    ch = spec.from_checkpoint(seed)
-    ch.replay_writes([])
-    assert ch.get() == seed
-
-
-def test_delta_channel_from_checkpoint_seed_none_is_distinct_from_sentinel() -> None:
-    """`seed=None` must start replay from None, not from an empty channel.
-
-    The DELTA_SENTINEL / MISSING sentinels mean 'no seed'; passing `None`
-    explicitly should feed None to the reducer as the left operand.
-    """
-
-    def replace(state, writes):
-        return writes[-1] if writes else state
-
-    spec = DeltaChannel(replace, list)
-    ch = spec.from_checkpoint(None)
-    ch.replay_writes([("t0", "x", "after")])
-    assert ch.get() == "after"

libs/langgraph/tests/test_delta_channel_benchmark.py

@@ -1,478 +0,0 @@
-"""Benchmark: DeltaChannel snapshot_frequency — storage vs. read-depth tradeoff.
-
-Run directly:  python tests/test_delta_channel_benchmark.py
-Run via pytest: pytest tests/test_delta_channel_benchmark.py -s
-
-Part 1 — baseline (original): DeltaChannel(inf) vs add_messages (BinOp).
-Part 2 — snapshot_frequency sweep: shows the storage/read-latency tradeoff
-  across frequencies [1, 5, 10, 50, inf] at scale.
-
-Key insight:
-  snapshot_frequency=inf  → O(N) storage, O(N) read depth (pure delta)
-  snapshot_frequency=N    → O(N²/N) storage, O(N) read depth bounded by freq
-  snapshot_frequency=1    → O(N²) storage, O(1) read depth (full snapshot)
-"""
-
-from __future__ import annotations
-
-import contextlib
-import math
-import os
-import sys
-import time
-from typing import Annotated, Any
-
-import pytest
-from langchain_core.messages import AIMessage, HumanMessage
-from langgraph.checkpoint.memory import MemorySaver
-from typing_extensions import TypedDict
-
-from langgraph.channels.delta import DeltaChannel
-from langgraph.graph import END, StateGraph
-from langgraph.graph.message import _messages_delta_reducer, add_messages
-
-try:
-    from langgraph.checkpoint.postgres import PostgresSaver
-
-    _POSTGRES_AVAILABLE = True
-    _POSTGRES_URI = os.environ.get(
-        "LANGGRAPH_BENCH_POSTGRES_URI",
-        "postgres://postgres@localhost:5432/postgres?sslmode=disable",
-    )
-except ImportError:
-    _POSTGRES_AVAILABLE = False
-
-# ---------------------------------------------------------------------------
-# Realistic message payload (~100 tokens / ~400 chars each)
-# ---------------------------------------------------------------------------
-
-_HUMAN_TEMPLATE = (
-    "I need help understanding the implications of {topic} on our system architecture. "
-    "Specifically, I'm concerned about how this interacts with our existing {concern} "
-    "and whether we need to refactor the {component} layer before proceeding. "
-    "We've had prior incidents in this area and want to be deliberate. "
-    "What should we prioritize first, and are there known failure modes we should design around from the start?"
-)
-
-_AI_TEMPLATE = (
-    "Great question about {topic}. The key insight here is that {concern} introduces "
-    "a subtle ordering dependency that most teams overlook until they hit it in production. "
-    "For your {component} layer specifically, I'd recommend starting with a careful audit "
-    "of the interface boundaries before making any structural changes. This will give you "
-    "a clear picture of the blast radius and let you sequence the migration safely."
-)
-
-_TOPICS = [
-    "distributed tracing",
-    "eventual consistency",
-    "schema migration",
-    "backpressure handling",
-    "idempotency guarantees",
-    "cache invalidation",
-    "connection pooling",
-    "rate limiting",
-    "circuit breaking",
-    "observability pipelines",
-]
-
-_CONCERNS = [
-    "concurrency model",
-    "retry semantics",
-    "state management",
-    "error propagation",
-    "latency budget",
-]
-
-_COMPONENTS = [
-    "persistence",
-    "routing",
-    "ingestion",
-    "aggregation",
-    "serialization",
-]
-
-
-def _human_content(i: int) -> str:
-    return _HUMAN_TEMPLATE.format(
-        topic=_TOPICS[i % len(_TOPICS)],
-        concern=_CONCERNS[i % len(_CONCERNS)],
-        component=_COMPONENTS[i % len(_COMPONENTS)],
-    )
-
-
-def _ai_content(i: int) -> str:
-    return _AI_TEMPLATE.format(
-        topic=_TOPICS[i % len(_TOPICS)],
-        concern=_CONCERNS[i % len(_CONCERNS)],
-        component=_COMPONENTS[i % len(_COMPONENTS)],
-    )
-
-
-# ---------------------------------------------------------------------------
-# State definitions
-# ---------------------------------------------------------------------------
-
-
-class BinaryState(TypedDict):
-    messages: Annotated[list, add_messages]
-
-
-class DeltaState(TypedDict):
-    messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-
-def _make_delta_state(snapshot_frequency: int | float) -> type:
-    """Create a TypedDict with DeltaChannel at the given snapshot_frequency."""
-    channel = DeltaChannel(
-        _messages_delta_reducer, snapshot_frequency=snapshot_frequency
-    )
-    # Use the functional TypedDict form so the Annotated type is stored as an
-    # already-evaluated object rather than a forward-reference string (which
-    # would fail when get_type_hints tries to resolve 'snapshot_frequency').
-    return TypedDict(  # type: ignore[return-value]
-        f"DeltaState_freq{snapshot_frequency}",
-        {"messages": Annotated[list, channel]},
-    )
-
-
-# ---------------------------------------------------------------------------
-# Graph factory
-# ---------------------------------------------------------------------------
-
-
-def _make_graph(state_cls: type, checkpointer: Any = None) -> Any:
-    def human_node(state: Any) -> dict:
-        return {}
-
-    def ai_node(state: Any) -> dict:
-        i = len(state["messages"]) // 2
-        return {"messages": [AIMessage(content=_ai_content(i), id=f"a{i}")]}
-
-    g = StateGraph(state_cls)
-    g.add_node("human", human_node)
-    g.add_node("ai", ai_node)
-    g.add_edge("human", "ai")
-    g.add_edge("ai", END)
-    g.set_entry_point("human")
-    return g.compile(checkpointer=checkpointer or MemorySaver())
-
-
-# ---------------------------------------------------------------------------
-# Measurement helpers
-# ---------------------------------------------------------------------------
-
-
-def _total_blob_bytes(saver: MemorySaver) -> int:
-    total = 0
-    for (_, _, _, _), (type_tag, blob) in saver.blobs.items():
-        if blob is not None:
-            total += len(blob)
-    return total
-
-
-def _run_turns(
-    n_turns: int,
-    state_cls: type,
-    checkpointer: Any = None,
-) -> tuple[float, float, int]:
-    """Run n_turns conversation turns.
-
-    Returns (write_elapsed_s, read_elapsed_s, total_blob_bytes).
-    Read latency is the average of 5 get_state calls after the full history
-    is built — forces state rehydration including ancestor replay if needed.
-    """
-    graph = _make_graph(state_cls, checkpointer)
-    config = {"configurable": {"thread_id": "bench"}}
-
-    t0 = time.perf_counter()
-    for i in range(n_turns):
-        graph.invoke(
-            {"messages": [HumanMessage(content=_human_content(i), id=f"h{i}")]},
-            config,
-        )
-    write_elapsed = time.perf_counter() - t0
-
-    t1 = time.perf_counter()
-    for _ in range(5):
-        graph.get_state(config)
-    read_elapsed = (time.perf_counter() - t1) / 5
-
-    blob_bytes = (
-        _total_blob_bytes(graph.checkpointer)
-        if isinstance(graph.checkpointer, MemorySaver)
-        else -1
-    )
-    return write_elapsed, read_elapsed, blob_bytes
-
-
-def _fmt_bytes(n: int) -> str:
-    if n >= 1_000_000:
-        return f"{n / 1_000_000:.1f} MB"
-    if n >= 1_000:
-        return f"{n / 1_000:.1f} KB"
-    return f"{n} B"
-
-
-def _approx_tokens(n_turns: int) -> str:
-    tokens = n_turns * 200
-    if tokens >= 1_000_000:
-        return f"~{tokens / 1_000_000:.1f}M tok"
-    if tokens >= 1_000:
-        return f"~{tokens / 1_000:.0f}K tok"
-    return f"~{tokens} tok"
-
-
-# ---------------------------------------------------------------------------
-# Checkpointer factories
-# ---------------------------------------------------------------------------
-
-
-@contextlib.contextmanager
-def _pg_saver(thread_id: str = "bench"):
-    """Context manager that yields a fresh PostgresSaver and cleans up after."""
-    with PostgresSaver.from_conn_string(_POSTGRES_URI) as saver:
-        saver.setup()
-        with saver._cursor() as cur:
-            for tbl in ("checkpoints", "checkpoint_blobs", "checkpoint_writes"):
-                cur.execute(f"DELETE FROM {tbl} WHERE thread_id = %s", (thread_id,))
-        yield saver
-        with saver._cursor() as cur:
-            for tbl in ("checkpoints", "checkpoint_blobs", "checkpoint_writes"):
-                cur.execute(f"DELETE FROM {tbl} WHERE thread_id = %s", (thread_id,))
-
-
-def _checkpointers() -> list[tuple[str, Any]]:
-    """Return (label, saver_or_None) pairs for available checkpointers."""
-    result: list[tuple[str, Any]] = [("InMemory", None)]
-    if _POSTGRES_AVAILABLE:
-        try:
-            import psycopg
-
-            psycopg.connect(_POSTGRES_URI).close()
-            result.append(("Postgres", "postgres"))
-        except Exception:
-            pass
-    return result
-
-
-# ---------------------------------------------------------------------------
-# Part 1: baseline DeltaChannel(inf) vs add_messages
-# ---------------------------------------------------------------------------
-
-BASELINE_TURN_COUNTS = [10, 25, 50, 100, 500]
-DELTA_ONLY_TURN_COUNTS = [1000]
-
-
-def _run_baseline_for_checkpointer(cp_label: str, cp_hint: Any) -> None:
-    W = 72
-
-    def _make_saver():
-        if cp_hint is None:
-            return contextlib.nullcontext(None)
-        return _pg_saver()
-
-    rows: list[tuple[int, Any, Any, Any, Any, Any, Any]] = []
-    for turns in BASELINE_TURN_COUNTS:
-        with _make_saver() as saver:
-            b_wt, b_rt, b_bytes = _run_turns(turns, BinaryState, saver)
-        with _make_saver() as saver:
-            d_wt, d_rt, d_bytes = _run_turns(turns, DeltaState, saver)
-        rows.append((turns, b_bytes, d_bytes, b_rt, d_rt, b_wt, d_wt))
-    for turns in DELTA_ONLY_TURN_COUNTS:
-        with _make_saver() as saver:
-            d_wt, d_rt, d_bytes = _run_turns(turns, DeltaState, saver)
-        rows.append((turns, None, d_bytes, None, d_rt, None, d_wt))
-
-    def _bytes_or_na(v: Any) -> str:
-        if v is None or v < 0:
-            return "n/a"
-        return _fmt_bytes(v)
-
-    def _ms_or_na(v: Any) -> str:
-        return "n/a" if v is None else f"{v * 1000:.1f}ms"
-
-    print(f"\n  [{cp_label}] Storage (blob bytes)")
-    print(
-        f"  {'turns':>6}  {'ctx':>10}  {'add_msgs':>12}  {'delta(inf)':>12}  {'savings':>8}"
-    )
-    print("  " + "-" * (W - 2))
-    for turns, b_bytes, d_bytes, b_rt, d_rt, b_wt, d_wt in rows:
-        if b_bytes is None or b_bytes < 0 or d_bytes is None or d_bytes < 0:
-            ratio_str = "n/a"
-        else:
-            ratio = b_bytes / d_bytes if d_bytes else float("inf")
-            ratio_str = f"{ratio:.0f}x"
-        print(
-            f"  {turns:>6}  {_approx_tokens(turns):>10}  "
-            f"{_bytes_or_na(b_bytes):>12}  {_bytes_or_na(d_bytes):>12}  {ratio_str:>8}"
-        )
-
-    print(f"\n  [{cp_label}] Read latency (avg of 5 get_state calls)")
-    print(f"  {'turns':>6}  {'ctx':>10}  {'add_msgs':>12}  {'delta(inf)':>12}")
-    print("  " + "-" * (W - 2))
-    for turns, b_bytes, d_bytes, b_rt, d_rt, b_wt, d_wt in rows:
-        print(
-            f"  {turns:>6}  {_approx_tokens(turns):>10}  "
-            f"{_ms_or_na(b_rt):>12}  {_ms_or_na(d_rt):>12}"
-        )
-
-
-def run_baseline_benchmark() -> None:
-    print()
-    print("Part 1 — DeltaChannel(inf) vs add_messages: storage & latency")
-    print("=" * 72)
-    for cp_label, cp_hint in _checkpointers():
-        _run_baseline_for_checkpointer(cp_label, cp_hint)
-    print()
-
-
-# ---------------------------------------------------------------------------
-# Part 2: snapshot_frequency sweep
-# ---------------------------------------------------------------------------
-
-# Frequencies to test. 1 = always snapshot (like BinOp), inf = pure delta.
-SNAPSHOT_FREQUENCIES: list[int | float] = [1, 5, 10, 50, math.inf]
-
-# Turn counts for the sweep — high enough to show storage divergence.
-SWEEP_TURN_COUNTS = [50, 100, 500]
-
-
-def _freq_label(freq: int | float) -> str:
-    if freq == math.inf:
-        return "inf"
-    return str(int(freq))
-
-
-def _run_sweep_for_checkpointer(cp_label: str, cp_hint: Any) -> None:
-    def _make_saver():
-        if cp_hint is None:
-            return contextlib.nullcontext(None)
-        return _pg_saver()
-
-    # Collect results: {turns: {freq_label: (write_s, read_s, bytes)}}
-    results: dict[int, dict[str, tuple[float, float, int]]] = {}
-    for turns in SWEEP_TURN_COUNTS:
-        results[turns] = {}
-        for freq in SNAPSHOT_FREQUENCIES:
-            state_cls = _make_delta_state(freq)
-            with _make_saver() as saver:
-                wt, rt, bb = _run_turns(turns, state_cls, saver)
-            results[turns][_freq_label(freq)] = (wt, rt, bb)
-
-    freq_labels = [_freq_label(f) for f in SNAPSHOT_FREQUENCIES]
-    col_w = 12
-
-    header = f"  {'turns':>6}  {'ctx':>10}" + "".join(
-        f"  {f'freq={freq_label}':>{col_w}}" for freq_label in freq_labels
-    )
-
-    print(f"\n  [{cp_label}] Storage (blob bytes) — lower is better")
-    print(header)
-    print("  " + "-" * (len(header) - 2))
-    for turns in SWEEP_TURN_COUNTS:
-        row = f"  {turns:>6}  {_approx_tokens(turns):>10}"
-        for label in freq_labels:
-            _, _, bb = results[turns][label]
-            row += f"  {_fmt_bytes(bb) if bb >= 0 else 'n/a':>{col_w}}"
-        print(row)
-
-    print(f"\n  [{cp_label}] Read latency (avg of 5 get_state) — lower is better")
-    print(header)
-    print("  " + "-" * (len(header) - 2))
-    for turns in SWEEP_TURN_COUNTS:
-        row = f"  {turns:>6}  {_approx_tokens(turns):>10}"
-        for label in freq_labels:
-            _, rt, _ = results[turns][label]
-            row += f"  {f'{rt * 1000:.1f}ms':>{col_w}}"
-        print(row)
-
-    print(
-        f"\n  [{cp_label}] Per-invoke write latency (total / turns) — lower is better"
-    )
-    print(header)
-    print("  " + "-" * (len(header) - 2))
-    for turns in SWEEP_TURN_COUNTS:
-        row = f"  {turns:>6}  {_approx_tokens(turns):>10}"
-        for label in freq_labels:
-            wt, _, _ = results[turns][label]
-            row += f"  {f'{(wt / turns) * 1000:.1f}ms':>{col_w}}"
-        print(row)
-
-
-def run_snapshot_freq_benchmark() -> None:
-    print()
-    print("Part 2 — DeltaChannel snapshot_frequency sweep")
-    print("Lower freq → fewer snapshots → less storage but deeper read replay")
-    print("=" * 80)
-    for cp_label, cp_hint in _checkpointers():
-        _run_sweep_for_checkpointer(cp_label, cp_hint)
-    print()
-    print("Legend:")
-    print(
-        "  freq=1    snapshot every write (full blob always — same as add_messages / BinOp)"
-    )
-    print("  freq=N    snapshot every N writes; read walks at most N ancestor writes")
-    print("  freq=inf  pure delta; read walks entire ancestor chain")
-    print()
-
-
-# ---------------------------------------------------------------------------
-# Pytest entry points
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.skip(
-    reason="slow benchmark — run manually with: python tests/test_delta_channel_benchmark.py"
-)
-def test_delta_channel_baseline_benchmark(capsys: Any) -> None:
-    """DeltaChannel(inf) uses less storage than add_messages at scale."""
-    with capsys.disabled():
-        run_baseline_benchmark()
-
-    for turns in [25, 50]:
-        _, _, b_bytes = _run_turns(turns, BinaryState)
-        _, _, d_bytes = _run_turns(turns, DeltaState)
-        assert d_bytes < b_bytes, (
-            f"DeltaChannel should use less storage at {turns} turns, "
-            f"got delta={d_bytes} binary={b_bytes}"
-        )
-
-
-@pytest.mark.skip(
-    reason="slow benchmark — run manually with: python tests/test_delta_channel_benchmark.py"
-)
-def test_snapshot_freq_benchmark(capsys: Any) -> None:
-    """snapshot_frequency trades storage for bounded read depth."""
-    with capsys.disabled():
-        run_snapshot_freq_benchmark()
-
-    # Correctness: results at all frequencies should agree on final state.
-    n_turns = 20
-    states: dict[str, list] = {}
-    for freq in SNAPSHOT_FREQUENCIES:
-        state_cls = _make_delta_state(freq)
-        graph = _make_graph(state_cls)
-        config = {"configurable": {"thread_id": "correctness"}}
-        for i in range(n_turns):
-            graph.invoke(
-                {"messages": [HumanMessage(content=_human_content(i), id=f"h{i}")]},
-                config,
-            )
-        state = graph.get_state(config)
-        states[_freq_label(freq)] = [m.id for m in state.values["messages"]]
-
-    ref = states["inf"]
-    for label, msg_ids in states.items():
-        assert msg_ids == ref, (
-            f"freq={label} produced different message IDs than freq=inf"
-        )
-
-
-# ---------------------------------------------------------------------------
-# Script entry point
-# ---------------------------------------------------------------------------
-
-if __name__ == "__main__":
-    run_baseline_benchmark()
-    run_snapshot_freq_benchmark()
-    sys.exit(0)

libs/langgraph/tests/test_delta_channel_migration.py

@@ -1,613 +0,0 @@
-"""Tests for the BinaryOperatorAggregate -> DeltaChannel migration path.
-
-A thread written under `BinaryOperatorAggregate(...)` must keep working
-after its annotation is swapped to `DeltaChannel(...)` on the same
-checkpointer — pre-migration state visible at each *settled* ancestor
-checkpoint is preserved, and post-migration writes fold on top through
-the reducer.
-
-Mechanism under test: the saver's `_get_channel_writes_history(config,
-channel)` walks the parent chain; when it encounters an ancestor whose
-`channel_values[channel]` is a real value (not `DELTA_SENTINEL`), it
-returns that as the `seed`. `DeltaChannel.from_checkpoint(seed)` uses
-it as the base value, and `replay_writes(writes)` folds on-path deltas.
-
-Scenarios covered:
-
-1. **Basic migration (sync + async)**: build pre-migration state with
-   `BinaryOperatorAggregate`, swap the annotation to `DeltaChannel` on
-   the same checkpointer, and verify that every settled pre-migration
-   super-step boundary (`next=('__start__',)`) round-trips exactly
-   under the delta-channel view.
-2. **Time travel into a pre-migration checkpoint** after migration —
-   `graph.get_state(pre_migration_config)` at a settled ancestor
-   returns the same state as under the binop channel.
-3. **Continuing a migrated thread**: driving one more super-step after
-   migration produces a state that includes the pre-migration settled
-   prefix plus the new delta write — proving `from_checkpoint(seed)` +
-   `replay_writes` correctly fold post-migration deltas onto the
-   pre-migration seed.
-4. **Base-saver fallback path**: a third-party-style subclass that
-   removes the optimized `InMemorySaver` override and falls back to
-   `BaseCheckpointSaver._get_channel_writes_history` must produce the
-   same result as the optimized path.
-5. **Channel-type isolation across threads**: two threads on the same
-   checkpointer under the delta-channel graph — one freshly-started,
-   one migrated from pre-migration state — don't cross-contaminate.
-   The parent-chain walk is scoped to the thread.
-
-TODO: add postgres variants in the existing `libs/checkpoint-postgres`
-test files (different fixture setup; not this file).
-"""
-
-from __future__ import annotations
-
-import operator
-from typing import Annotated, Any
-
-import pytest
-from langchain_core.messages import AIMessage, HumanMessage
-from langgraph.checkpoint.memory import InMemorySaver
-from typing_extensions import TypedDict
-
-from langgraph.channels.binop import BinaryOperatorAggregate
-from langgraph.channels.delta import DeltaChannel
-from langgraph.graph import END, START, StateGraph
-from langgraph.graph.message import _messages_delta_reducer, add_messages
-
-pytestmark = pytest.mark.anyio
-
-
-# ---------------------------------------------------------------------------
-# Graph factories
-#
-# A minimal reducer (`operator.add` on lists of str) with a noop node keeps
-# state change localized to the HumanMessage-like payload passed through
-# `invoke`. That isolates the pre/post-migration parity assertions to
-# channel-hydration semantics.
-# ---------------------------------------------------------------------------
-
-
-def _noop(_state: Any) -> dict:
-    return {}
-
-
-def _list_concat(state: list, writes: list) -> list:
-    result = list(state)
-    for w in writes:
-        result.extend(w if isinstance(w, list) else [w])
-    return result
-
-
-def _binop_graph(checkpointer: Any) -> Any:
-    class BinopState(TypedDict):
-        items: Annotated[list, BinaryOperatorAggregate(list, operator.add)]
-
-    return (
-        StateGraph(BinopState)
-        .add_node("noop", _noop)
-        .add_edge(START, "noop")
-        .add_edge("noop", END)
-        .compile(checkpointer=checkpointer)
-    )
-
-
-def _delta_graph(checkpointer: Any) -> Any:
-    class DeltaState(TypedDict):
-        items: Annotated[list, DeltaChannel(_list_concat)]
-
-    return (
-        StateGraph(DeltaState)
-        .add_node("noop", _noop)
-        .add_edge(START, "noop")
-        .add_edge("noop", END)
-        .compile(checkpointer=checkpointer)
-    )
-
-
-def _drive(graph: Any, config: dict, tag: str, n: int) -> None:
-    for i in range(n):
-        graph.invoke({"items": [f"{tag}{i}"]}, config)
-
-
-async def _adrive(graph: Any, config: dict, tag: str, n: int) -> None:
-    for i in range(n):
-        await graph.ainvoke({"items": [f"{tag}{i}"]}, config)
-
-
-def _settled_boundaries(history: list) -> list[tuple[dict, list]]:
-    """Return `[(config, items), ...]` for every checkpoint in `history`
-    whose `next == ('__start__',)` — the stable boundaries between invokes.
-    """
-    return [
-        (s.config, list(s.values.get("items", [])))
-        for s in history
-        if s.next == ("__start__",)
-    ]
-
-
-# ---------------------------------------------------------------------------
-# 1. Basic migration (sync + async)
-# ---------------------------------------------------------------------------
-
-
-def test_basic_migration_preserves_pre_migration_state() -> None:
-    """Build state under `BinaryOperatorAggregate`, migrate to
-    `DeltaChannel` on the same checkpointer, and verify that every
-    settled pre-migration super-step boundary round-trips exactly.
-
-    Settled boundaries (`next=('__start__',)`) are the stable hydration
-    targets for the migration path: writes that produced the NEXT
-    super-step are kept as `pending_writes` on the ancestor, so walking
-    from a descendant finds the ancestor's blob as the seed and
-    reconstructs the correct state.
-    """
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "basic-sync"}}
-
-    # Pre-migration: accumulate items across 3 invokes.
-    binop = _binop_graph(checkpointer)
-    _drive(binop, config, "u", 3)
-
-    pre_boundaries = _settled_boundaries(list(binop.get_state_history(config)))
-    assert len(pre_boundaries) >= 2, "expected multiple settled boundaries"
-
-    # Migrate: swap the annotation on the same checkpointer.
-    delta = _delta_graph(checkpointer)
-
-    for cfg, items in pre_boundaries:
-        snap = delta.get_state(cfg)
-        assert list(snap.values.get("items", [])) == items, (
-            f"snapshot mismatch at {cfg['configurable']['checkpoint_id']}: "
-            f"expected {items}, got {snap.values.get('items', [])}"
-        )
-
-
-async def test_basic_migration_preserves_pre_migration_state_async() -> None:
-    """Async variant of the basic migration scenario."""
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "basic-async"}}
-
-    binop = _binop_graph(checkpointer)
-    await _adrive(binop, config, "u", 3)
-
-    pre_history = [s async for s in binop.aget_state_history(config)]
-    pre_boundaries = _settled_boundaries(pre_history)
-    assert len(pre_boundaries) >= 2
-
-    delta = _delta_graph(checkpointer)
-
-    for cfg, items in pre_boundaries:
-        snap = await delta.aget_state(cfg)
-        assert list(snap.values.get("items", [])) == items, (
-            f"async snapshot mismatch at {cfg['configurable']['checkpoint_id']}"
-        )
-
-
-# ---------------------------------------------------------------------------
-# 2. Time travel into a pre-migration checkpoint after migration
-# ---------------------------------------------------------------------------
-
-
-def test_time_travel_into_pre_migration_checkpoint() -> None:
-    """After migration, `graph.get_state(pre_migration_config)` at a
-    settled ancestor returns the state as stored at that point."""
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "time-travel"}}
-
-    binop = _binop_graph(checkpointer)
-    _drive(binop, config, "u", 3)
-
-    pre_boundaries = _settled_boundaries(list(binop.get_state_history(config)))
-    assert pre_boundaries, "no settled ancestors to time-travel to"
-
-    delta = _delta_graph(checkpointer)
-
-    # Pick the oldest non-empty boundary — a long distance to walk back.
-    non_empty = [(cfg, items) for cfg, items in pre_boundaries if items]
-    assert non_empty, "expected at least one non-empty boundary"
-    target_cfg, expected_items = non_empty[-1]
-
-    snap = delta.get_state(target_cfg)
-    assert list(snap.values.get("items", [])) == expected_items
-
-
-# ---------------------------------------------------------------------------
-# 3. Continuing a migrated thread: deltas fold onto pre-migration seed
-# ---------------------------------------------------------------------------
-
-
-def test_continuing_migrated_thread_folds_deltas_on_seed() -> None:
-    """Resume a pre-migration settled ancestor via `invoke(None, cfg)`
-    under the delta-channel graph. Since the pre-migration checkpoint
-    has an existing `pending_writes` entry (the input for the NEXT
-    super-step), re-running from that ancestor reproduces the same
-    post-ancestor state as the original binop run.
-
-    This proves the seed-terminator + write-replay pipeline works
-    end-to-end across the migration boundary.
-    """
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "continue"}}
-
-    binop = _binop_graph(checkpointer)
-    _drive(binop, config, "u", 2)
-
-    # Pick the oldest settled boundary with non-empty state.
-    pre_boundaries = _settled_boundaries(list(binop.get_state_history(config)))
-    target_cfg, seed_items = next(
-        (cfg, items) for cfg, items in reversed(pre_boundaries) if items
-    )
-    assert seed_items, "need a non-empty seed boundary"
-
-    # Migrate and resume from the pre-migration ancestor. `invoke(None,
-    # cfg)` replays the pending writes staged at `cfg` under the new
-    # channel; the reducer folds those deltas onto the seed.
-    delta = _delta_graph(checkpointer)
-    result = delta.invoke(None, target_cfg)
-
-    # The resumed state must include the pre-migration seed items in order.
-    result_items = list(result.get("items", []))
-    for idx, prefix_item in enumerate(seed_items):
-        assert result_items[idx] == prefix_item, (
-            f"pre-migration seed item at {idx} not preserved: "
-            f"got {result_items[: idx + 1]}, expected {seed_items}"
-        )
-
-
-# ---------------------------------------------------------------------------
-# 4. Base-saver fallback path
-# ---------------------------------------------------------------------------
-
-
-class _ThirdPartyStyleSaver(InMemorySaver):
-    """Simulates a third-party saver that inherits the reference
-    `_get_channel_writes_history` implementation from
-    `BaseCheckpointSaver` rather than overriding it.
-
-    We rebind the two methods to the base-class versions (via MRO) so
-    the fallback path is exercised even though the storage layer is
-    still the in-memory one.
-    """
-
-    # MRO: [_ThirdPartyStyleSaver, InMemorySaver, BaseCheckpointSaver, ...]
-    _get_channel_writes_history = (  # type: ignore[assignment]
-        InMemorySaver.__mro__[1]._get_channel_writes_history  # type: ignore[attr-defined]
-    )
-    _aget_channel_writes_history = (  # type: ignore[assignment]
-        InMemorySaver.__mro__[1]._aget_channel_writes_history  # type: ignore[attr-defined]
-    )
-
-
-def test_base_saver_fallback_matches_optimized_override() -> None:
-    """The reference `BaseCheckpointSaver` implementation must produce
-    the same migration behavior as the optimized `InMemorySaver`
-    override. We drive the same migration scenario through both savers
-    and assert per-snapshot parity in the delta-channel view."""
-
-    # Fast path: optimized InMemorySaver override.
-    fast_saver = InMemorySaver()
-    fast_config = {"configurable": {"thread_id": "fast"}}
-    fast_binop = _binop_graph(fast_saver)
-    _drive(fast_binop, fast_config, "u", 3)
-    fast_delta = _delta_graph(fast_saver)
-    fast_history = [
-        (s.next, list(s.values.get("items", [])))
-        for s in fast_delta.get_state_history(fast_config)
-    ]
-
-    # Slow path: base-class fallback.
-    slow_saver = _ThirdPartyStyleSaver()
-    slow_config = {"configurable": {"thread_id": "slow"}}
-    slow_binop = _binop_graph(slow_saver)
-    _drive(slow_binop, slow_config, "u", 3)
-    slow_delta = _delta_graph(slow_saver)
-    slow_history = [
-        (s.next, list(s.values.get("items", [])))
-        for s in slow_delta.get_state_history(slow_config)
-    ]
-
-    assert slow_history == fast_history, (
-        "base-saver fallback should match optimized-override behavior; "
-        f"fast={fast_history}, slow={slow_history}"
-    )
-
-
-# ---------------------------------------------------------------------------
-# 5. Thread isolation under mixed-generation storage
-# ---------------------------------------------------------------------------
-
-
-def test_delta_and_migrated_threads_do_not_cross_contaminate() -> None:
-    """Two threads sharing a checkpointer — one migrated from
-    pre-migration state, one freshly-started under DeltaChannel — must
-    maintain independent state. The parent-chain walk in
-    `_get_channel_writes_history` must be scoped to the target thread.
-    """
-
-    checkpointer = InMemorySaver()
-    migrated_cfg = {"configurable": {"thread_id": "migrated"}}
-    fresh_cfg = {"configurable": {"thread_id": "fresh"}}
-
-    # Thread A: pre-migration build-up.
-    binop = _binop_graph(checkpointer)
-    _drive(binop, migrated_cfg, "m", 2)
-
-    # Thread B: fresh delta-channel run.
-    delta = _delta_graph(checkpointer)
-    _drive(delta, fresh_cfg, "f", 2)
-
-    # Thread A: migrate and confirm its state is anchored in its own
-    # thread's pre-migration history (tag 'm'), never mixing in tag 'f'.
-    migrated_boundaries = _settled_boundaries(
-        list(delta.get_state_history(migrated_cfg))
-    )
-    assert migrated_boundaries, "migrated thread has no settled boundaries"
-    for _, items in migrated_boundaries:
-        for it in items:
-            assert it.startswith("m"), (
-                f"migrated thread leaked item from other thread: {it}"
-            )
-
-    # Thread B: settled boundaries must only contain 'f' tags.
-    fresh_boundaries = _settled_boundaries(list(delta.get_state_history(fresh_cfg)))
-    assert fresh_boundaries, "fresh thread has no settled boundaries"
-    for _, items in fresh_boundaries:
-        for it in items:
-            assert it.startswith("f"), (
-                f"fresh thread leaked item from migrated thread: {it}"
-            )
-
-
-# ---------------------------------------------------------------------------
-# 6. Tip-of-pre-migration hydration: the latest checkpoint from a binop-run
-# thread has a real accumulated value in its own `channel_values["items"]`.
-# When hydrated under the delta-channel graph via `get_state(config)` with no
-# `checkpoint_id`, the short-circuit must use that value directly instead of
-# walking ancestors (which would skip the tip's own blob).
-# ---------------------------------------------------------------------------
-
-
-def test_tip_of_pre_migration_hydrates_directly() -> None:
-    """`graph.get_state(config)` at the latest (pre-migration) checkpoint
-    returns the full accumulated list stored in that checkpoint's own
-    `channel_values`. The hydration must not walk ancestors past it."""
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "tip-sync"}}
-
-    binop = _binop_graph(checkpointer)
-    _drive(binop, config, "u", 3)
-
-    binop_tip = binop.get_state(config)
-    expected_items = list(binop_tip.values.get("items", []))
-    assert expected_items == ["u0", "u1", "u2"], (
-        f"sanity: pre-migration tip should accumulate all 3 items, got {expected_items}"
-    )
-
-    delta = _delta_graph(checkpointer)
-
-    snap = delta.get_state(config)
-    assert list(snap.values.get("items", [])) == expected_items, (
-        f"tip hydration mismatch: expected {expected_items}, "
-        f"got {snap.values.get('items', [])}"
-    )
-
-
-async def test_tip_of_pre_migration_hydrates_directly_async() -> None:
-    """Async variant of the tip-of-pre-migration hydration scenario."""
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "tip-async"}}
-
-    binop = _binop_graph(checkpointer)
-    await _adrive(binop, config, "u", 3)
-
-    binop_tip = await binop.aget_state(config)
-    expected_items = list(binop_tip.values.get("items", []))
-    assert expected_items == ["u0", "u1", "u2"]
-
-    delta = _delta_graph(checkpointer)
-
-    snap = await delta.aget_state(config)
-    assert list(snap.values.get("items", [])) == expected_items, (
-        f"async tip hydration mismatch: expected {expected_items}, "
-        f"got {snap.values.get('items', [])}"
-    )
-
-
-# ---------------------------------------------------------------------------
-# 7. `update_state` after migration writes a real value to the new
-# checkpoint's `channel_values` (not a sentinel). Hydration must use it
-# directly — the ancestor walk would skip this blob and return stale state.
-# ---------------------------------------------------------------------------
-
-
-def test_update_state_after_migration_uses_written_value() -> None:
-    """After migrating and running at least one post-migration super-step
-    (so the thread's tip has a `DELTA_SENTINEL`), `update_state` writes a
-    concrete value to a new checkpoint's `channel_values`. `get_state`
-    must reflect that concrete value."""
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "update-state"}}
-
-    # Pre-migration: accumulate a little state.
-    binop = _binop_graph(checkpointer)
-    _drive(binop, config, "u", 2)
-
-    # Migrate and run one more super-step so the tip is a post-migration
-    # checkpoint with `DELTA_SENTINEL` in its own `channel_values`.
-    delta = _delta_graph(checkpointer)
-    delta.invoke({"items": ["post"]}, config)
-
-    # `update_state` writes a concrete value into a new checkpoint's blob
-    # via the reducer against the hydrated prior state.
-    delta.update_state(config, {"items": ["x", "y"]})
-
-    snap = delta.get_state(config)
-    updated_items = list(snap.values.get("items", []))
-    # Must include the "x","y" update; without the hydration fix, the
-    # update_state-written blob would be skipped in favor of an ancestor
-    # walk, and the update values would disappear.
-    assert "x" in updated_items and "y" in updated_items, (
-        f"update_state values missing from snapshot: {updated_items}"
-    )
-    # The "x","y" items should be folded onto the prior accumulated state,
-    # not stand alone. This verifies the update-written blob is used
-    # directly by `get_state` (no ancestor walk past it).
-    assert len(updated_items) >= 4, (
-        f"update_state snapshot should preserve pre-update state, got {updated_items}"
-    )
-    assert updated_items[-2:] == ["x", "y"], (
-        f"update_state deltas should be at the tail, got {updated_items}"
-    )
-
-
-# ---------------------------------------------------------------------------
-# 8. Fork from an `update_state` checkpoint: a new run branched off the
-# update_state-produced checkpoint must see that checkpoint's concrete
-# `channel_values` as its base, with new deltas folded on top.
-# ---------------------------------------------------------------------------
-
-
-def test_fork_from_update_state_checkpoint() -> None:
-    """Branching a new run from the checkpoint produced by `update_state`
-    must use that checkpoint's concrete blob as the base. Additional
-    deltas from the forked run fold onto it through the reducer."""
-
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "fork"}}
-
-    # Pre-migration build-up, then migrate and add one post-migration step.
-    binop = _binop_graph(checkpointer)
-    _drive(binop, config, "u", 2)
-    delta = _delta_graph(checkpointer)
-    delta.invoke({"items": ["post"]}, config)
-
-    # Apply `update_state` and capture the returned config (references
-    # the new checkpoint produced by the update).
-    update_cfg = delta.update_state(config, {"items": ["x", "y"]})
-
-    update_snap = delta.get_state(update_cfg)
-    base_items = list(update_snap.values.get("items", []))
-    assert "x" in base_items and "y" in base_items, (
-        f"update_state values missing from snapshot: {base_items}"
-    )
-    assert base_items[-2:] == ["x", "y"], (
-        f"sanity: update_state deltas should be at the tail, got {base_items}"
-    )
-
-    # Fork: invoke from the update_state checkpoint with a new delta.
-    forked = delta.invoke({"items": ["fork0"]}, update_cfg)
-    forked_items = list(forked.get("items", []))
-    # The fork must see the update_state-written blob as its base (not
-    # walk past it), and the new delta must fold on top of it.
-    assert forked_items[: len(base_items)] == base_items, (
-        f"fork lost update_state base: base={base_items}, forked={forked_items}"
-    )
-    assert forked_items[-1] == "fork0", f"fork delta not appended: {forked_items}"
-
-
-# ---------------------------------------------------------------------------
-# 9. Migration from `add_messages` → `DeltaChannel(_messages_delta_reducer)`
-#
-# `add_messages` is the primary real-world use case: it creates a
-# BinaryOperatorAggregate with dedup-by-ID and RemoveMessage semantics.
-# After swapping the annotation to DeltaChannel, pre-migration blobs
-# (plain lists of Message objects) must be used directly as the seed.
-# ---------------------------------------------------------------------------
-
-
-def _add_messages_graph(checkpointer: Any) -> Any:
-    class MessagesState(TypedDict):
-        messages: Annotated[list, add_messages]
-
-    return (
-        StateGraph(MessagesState)
-        .add_node("noop", _noop)
-        .add_edge(START, "noop")
-        .add_edge("noop", END)
-        .compile(checkpointer=checkpointer)
-    )
-
-
-def _delta_messages_graph(checkpointer: Any) -> Any:
-    class DeltaMessagesState(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    return (
-        StateGraph(DeltaMessagesState)
-        .add_node("noop", _noop)
-        .add_edge(START, "noop")
-        .add_edge("noop", END)
-        .compile(checkpointer=checkpointer)
-    )
-
-
-def test_add_messages_to_delta_migration_preserves_message_history() -> None:
-    """Migration from `add_messages` to `DeltaChannel(_messages_delta_reducer)`
-    preserves message ordering and IDs at both the tip and settled ancestor
-    boundaries.
-
-    The pre-migration blob is a plain list of Message objects; DeltaChannel
-    must use it directly as the seed without walking ancestors past it.
-    """
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "add-messages-migration"}}
-
-    pre_graph = _add_messages_graph(checkpointer)
-    pre_graph.invoke({"messages": [HumanMessage(content="hello", id="h1")]}, config)
-    pre_graph.invoke({"messages": [AIMessage(content="hi", id="a1")]}, config)
-    pre_graph.invoke({"messages": [HumanMessage(content="thanks", id="h2")]}, config)
-
-    pre_tip = pre_graph.get_state(config)
-    assert [m.id for m in pre_tip.values["messages"]] == ["h1", "a1", "h2"]
-
-    delta_graph = _delta_messages_graph(checkpointer)
-
-    # Tip: latest checkpoint has a full list blob — must use it directly.
-    snap = delta_graph.get_state(config)
-    assert [m.id for m in snap.values["messages"]] == ["h1", "a1", "h2"], (
-        f"tip hydration mismatch: got {[m.id for m in snap.values['messages']]}"
-    )
-
-    # Settled ancestor boundaries must also match.
-    pre_settled = [
-        [m.id for m in s.values.get("messages", [])]
-        for s in pre_graph.get_state_history(config)
-        if s.next == ("__start__",)
-    ]
-    delta_settled = [
-        [m.id for m in s.values.get("messages", [])]
-        for s in delta_graph.get_state_history(config)
-        if s.next == ("__start__",)
-    ]
-    assert delta_settled == pre_settled, (
-        f"settled boundary mismatch after migration: "
-        f"pre={pre_settled}, delta={delta_settled}"
-    )
-
-
-async def test_add_messages_to_delta_migration_preserves_message_history_async() -> (
-    None
-):
-    """Async variant of the add_messages migration test."""
-    checkpointer = InMemorySaver()
-    config = {"configurable": {"thread_id": "add-messages-migration-async"}}
-
-    pre_graph = _add_messages_graph(checkpointer)
-    await pre_graph.ainvoke(
-        {"messages": [HumanMessage(content="hello", id="h1")]}, config
-    )
-    await pre_graph.ainvoke({"messages": [AIMessage(content="hi", id="a1")]}, config)
-
-    delta_graph = _delta_messages_graph(checkpointer)
-    snap = await delta_graph.aget_state(config)
-    assert [m.id for m in snap.values["messages"]] == ["h1", "a1"], (
-        f"async tip hydration mismatch: got {[m.id for m in snap.values['messages']]}"
-    )

libs/langgraph/tests/test_pregel.py

@@ -16,7 +16,7 @@ from typing import Annotated, Any, Literal, get_type_hints
 
 import pytest
 from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, RemoveMessage
+from langchain_core.messages import AIMessage, AnyMessage, HumanMessage
 from langchain_core.runnables import (
     RunnableConfig,
     RunnableLambda,
@@ -25,7 +25,6 @@ from langchain_core.runnables import (
 from langchain_core.runnables.graph import Edge
 from langgraph.cache.base import BaseCache
 from langgraph.checkpoint.base import (
-    DELTA_SENTINEL,
     BaseCheckpointSaver,
     Checkpoint,
     CheckpointMetadata,
@@ -42,7 +41,6 @@ from typing_extensions import NotRequired, TypedDict
 
 from langgraph._internal._constants import CONFIG_KEY_NODE_FINISHED, ERROR, PULL
 from langgraph.channels.binop import BinaryOperatorAggregate
-from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue
 from langgraph.channels.topic import Topic
@@ -51,7 +49,7 @@ from langgraph.config import get_stream_writer
 from langgraph.errors import GraphRecursionError, InvalidUpdateError, ParentCommand
 from langgraph.func import entrypoint, task
 from langgraph.graph import END, START, StateGraph
-from langgraph.graph.message import MessagesState, _messages_delta_reducer, add_messages
+from langgraph.graph.message import MessagesState, add_messages
 from langgraph.pregel import (
     NodeBuilder,
     Pregel,
@@ -122,29 +120,6 @@ def test_graph_validation() -> None:
         graph.invoke({"hello": "there"})
 
 
-def test_request_drain_allows_inflight_call_scheduling(
-    sync_checkpointer: BaseCheckpointSaver,
-) -> None:
-    from langgraph.runtime import RunControl
-
-    @task
-    def child(x: int) -> int:
-        return x + 1
-
-    control = RunControl()
-
-    @entrypoint(checkpointer=sync_checkpointer)
-    def graph(x: int) -> int:
-        control.request_drain()
-        fut = child(x)
-        return fut.result()
-
-    config = {"configurable": {"thread_id": "drain-call-sync"}}
-
-    assert graph.invoke(1, config=config, control=control) == 2
-    assert control.drain_requested
-
-
 def test_invalid_checkpointer_type() -> None:
     class State(TypedDict):
         foo: str
@@ -9425,254 +9400,3 @@ def test_fork_does_not_apply_pending_writes(
 
     # Should be: 1 (input) + 20 (forked node_a) + 100 (node_b) = 121
     assert result == {"value": 121}
-
-
-async def test_delta_channel_end_to_end_inmemory() -> None:
-    """Full graph run: DeltaChannel accumulates correctly across multiple turns."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    def respond(state: State) -> dict:
-        n = len(state["messages"])
-        return {"messages": [AIMessage(content=f"reply-{n}", id=f"ai-{n}")]}
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_edge(START, "respond")
-    graph = builder.compile(checkpointer=InMemorySaver())
-
-    config = {"configurable": {"thread_id": "diff-test-1"}}
-
-    # Turn 1
-    graph.invoke({"messages": [HumanMessage(content="hello", id="h1")]}, config)
-    # Turn 2
-    graph.invoke({"messages": [HumanMessage(content="world", id="h2")]}, config)
-    # Turn 3
-    graph.invoke({"messages": [HumanMessage(content="bye", id="h3")]}, config)
-
-    state = graph.get_state(config)
-    msgs = state.values["messages"]
-    # 3 human + 3 AI = 6 total
-    assert len(msgs) == 6, f"expected 6 messages, got {len(msgs)}: {msgs}"
-    assert msgs[0].content == "hello"
-    assert msgs[2].content == "world"
-    assert msgs[4].content == "bye"
-    assert msgs[1].content == "reply-1"
-    assert msgs[3].content == "reply-3"
-    assert msgs[5].content == "reply-5"
-
-
-async def test_delta_channel_time_travel() -> None:
-    """Time-travel back to turn-1 checkpoint and resume; continuation must not include turn-2 deltas."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    counter = {"n": 0}
-
-    def respond(state: State) -> dict:
-        counter["n"] += 1
-        return {
-            "messages": [
-                AIMessage(content=f"ai-{counter['n']}", id=f"ai-{counter['n']}")
-            ]
-        }
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_edge(START, "respond")
-    saver = InMemorySaver()
-    graph = builder.compile(checkpointer=saver)
-
-    config = {"configurable": {"thread_id": "diff-time-travel"}}
-
-    # Run 2 turns: h1→ai-1, h2→ai-2
-    graph.invoke({"messages": [HumanMessage(content="h1", id="h1")]}, config)
-    graph.invoke({"messages": [HumanMessage(content="h2", id="h2")]}, config)
-
-    # Find the checkpoint after turn 1 (2 messages: h1 + ai-1)
-    history = list(graph.get_state_history(config))
-    after_turn1 = next(h for h in history if len(h.values.get("messages", [])) == 2)
-
-    assert len(after_turn1.values["messages"]) == 2
-    assert after_turn1.values["messages"][0].content == "h1"
-    assert after_turn1.values["messages"][1].content == "ai-1"
-
-    # Resume from turn-1 checkpoint: inject h3, expect 3 messages total (h1, ai-1, ai-N)
-    # NOT 5 messages (turn-2 deltas must not bleed into the resumed run)
-    result = graph.invoke(
-        {"messages": [HumanMessage(content="h3", id="h3")]},
-        after_turn1.config,
-    )
-    msgs = result["messages"]
-    # Should be: h1, ai-1, h3, ai-N — 4 messages total
-    assert len(msgs) == 4, (
-        f"expected 4 messages after time-travel resume, got {len(msgs)}: {msgs}"
-    )
-    assert msgs[0].content == "h1"
-    assert msgs[1].content == "ai-1"
-    assert msgs[2].content == "h3"
-
-
-async def test_delta_channel_remove_message_end_to_end() -> None:
-    """RemoveMessage inside a DeltaChannel graph must persist and reload correctly."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    def respond(state: State) -> dict:
-        return {"messages": [AIMessage(content="reply", id="ai-1")]}
-
-    def delete_first(state: State) -> dict:
-        # removes the first message
-        return {"messages": [RemoveMessage(id=state["messages"][0].id)]}
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_node("delete_first", delete_first)
-    builder.add_edge(START, "respond")
-    builder.add_edge("respond", "delete_first")
-    graph = builder.compile(checkpointer=InMemorySaver())
-
-    config = {"configurable": {"thread_id": "diff-remove-test"}}
-    graph.invoke({"messages": [HumanMessage(content="hello", id="h1")]}, config)
-
-    state = graph.get_state(config)
-    msgs = state.values["messages"]
-    # h1 was removed, only ai-1 should remain
-    assert len(msgs) == 1, f"expected 1 message, got {len(msgs)}: {msgs}"
-    assert msgs[0].id == "ai-1"
-
-    # A subsequent turn must reconstruct from the checkpoint correctly
-    graph.invoke({"messages": [HumanMessage(content="again", id="h2")]}, config)
-    state = graph.get_state(config)
-    msgs = state.values["messages"]
-    # ai-1 + h2 + ai-1(second reply, same id overwrites) + h2 removed
-    # more simply: after second run we expect ai-1 updated + h2 remaining minus deleted h2
-    # just assert h1 is still gone
-    assert all(m.id != "h1" for m in msgs), (
-        "h1 should still be absent after second turn"
-    )
-
-
-async def test_delta_channel_update_by_id_end_to_end() -> None:
-    """Updating a message by ID via DeltaChannel must persist and reload correctly."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    def update_msg(state: State) -> dict:
-        # re-send h1 with updated content
-        return {"messages": [HumanMessage(content="updated", id="h1")]}
-
-    builder = StateGraph(State)
-    builder.add_node("update_msg", update_msg)
-    builder.add_edge(START, "update_msg")
-    graph = builder.compile(checkpointer=InMemorySaver())
-
-    config = {"configurable": {"thread_id": "diff-update-id-test"}}
-    graph.invoke({"messages": [HumanMessage(content="original", id="h1")]}, config)
-
-    state = graph.get_state(config)
-    msgs = state.values["messages"]
-    assert len(msgs) == 1, f"expected 1 message, got {len(msgs)}: {msgs}"
-    assert msgs[0].content == "updated"
-    assert msgs[0].id == "h1"
-
-    # Second turn: verify the updated state is the base for further accumulation
-    graph.invoke({"messages": [HumanMessage(content="new", id="h2")]}, config)
-    state = graph.get_state(config)
-    msgs = state.values["messages"]
-    ids = [m.id for m in msgs]
-    assert "h1" in ids  # h1 persists (updated, not duplicated)
-    assert "h2" in ids
-    assert ids.count("h1") == 1, "h1 must not be duplicated"
-
-
-async def test_delta_channel_durability_exit_stores_snapshot() -> None:
-    """DeltaChannel must reload from a durability='exit' checkpoint."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    def respond(state: State) -> dict:
-        return {"messages": [AIMessage(content="reply", id="ai1")]}
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_edge(START, "respond")
-    graph = builder.compile(checkpointer=InMemorySaver())
-    config = {"configurable": {"thread_id": "delta-exit-test"}}
-
-    result = graph.invoke(
-        {"messages": [HumanMessage(content="hello", id="h1")]},
-        config,
-        durability="exit",
-    )
-    assert [m.content for m in result["messages"]] == ["hello", "reply"]
-
-    state = graph.get_state(config)
-    assert [m.content for m in state.values["messages"]] == ["hello", "reply"]
-
-
-async def test_delta_channel_async_write_ordering() -> None:
-    """In async mode, DeltaChannel write futures are awaited before the checkpoint
-    is committed, so aput_writes always precedes aput for sentinel checkpoints."""
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    def respond(state: State) -> dict:
-        i = len(state["messages"])
-        return {"messages": [AIMessage(content=f"r{i}", id=f"ai{i}")]}
-
-    order: list[str] = []
-    original_aput_writes = InMemorySaver.aput_writes
-    original_aput = InMemorySaver.aput
-
-    async def tracked_aput_writes(self, config, writes, task_id, task_path=""):
-        result = await original_aput_writes(self, config, writes, task_id, task_path)
-        order.append("aput_writes")
-        return result
-
-    async def tracked_aput(self, config, checkpoint, metadata, new_versions):
-        has_sentinel = any(
-            v is DELTA_SENTINEL for v in checkpoint.get("channel_values", {}).values()
-        )
-        order.append("aput_sentinel" if has_sentinel else "aput_other")
-        return await original_aput(self, config, checkpoint, metadata, new_versions)
-
-    InMemorySaver.aput_writes = tracked_aput_writes
-    InMemorySaver.aput = tracked_aput
-    try:
-        builder = StateGraph(State)
-        builder.add_node("respond", respond)
-        builder.add_edge(START, "respond")
-        graph = builder.compile(checkpointer=InMemorySaver())
-        config = {"configurable": {"thread_id": "async-ordering-test"}}
-
-        for i in range(3):
-            await graph.ainvoke(
-                {"messages": [HumanMessage(content=f"h{i}", id=f"h{i}")]}, config
-            )
-
-        # Every aput_sentinel must be preceded by at least one aput_writes
-        for i, event in enumerate(order):
-            if event == "aput_sentinel":
-                preceding = order[:i]
-                assert "aput_writes" in preceding, (
-                    f"aput_sentinel at {i} had no preceding aput_writes: {order}"
-                )
-                last_write_idx = max(
-                    j for j, e in enumerate(order[:i]) if e == "aput_writes"
-                )
-                assert last_write_idx < i, (
-                    f"aput_writes at {last_write_idx} should precede aput_sentinel at {i}: {order}"
-                )
-    finally:
-        InMemorySaver.aput_writes = original_aput_writes
-        InMemorySaver.aput = original_aput
-
-    state = await graph.aget_state(config)
-    assert len(state.values["messages"]) == 6  # 3 human + 3 AI

libs/langgraph/tests/test_pregel_async.py

@@ -215,30 +215,6 @@ async def test_checkpoint_errors() -> None:
             pass
 
 
-@NEEDS_CONTEXTVARS
-async def test_request_drain_allows_inflight_acall_scheduling(
-    async_checkpointer: BaseCheckpointSaver,
-) -> None:
-    from langgraph.runtime import RunControl
-
-    @task
-    async def child(x: int) -> int:
-        return x + 1
-
-    control = RunControl()
-
-    @entrypoint(checkpointer=async_checkpointer)
-    async def graph(x: int) -> int:
-        control.request_drain()
-        fut = child(x)
-        return await fut
-
-    config = {"configurable": {"thread_id": "drain-call-async"}}
-
-    assert await graph.ainvoke(1, config=config, control=control) == 2
-    assert control.drain_requested
-
-
 async def test_py_async_with_cancel_behavior() -> None:
     """This test confirms that in all versions of Python we support, __aexit__
     is not cancelled when the coroutine containing the async with block is cancelled."""
@@ -6125,36 +6101,6 @@ async def test_parent_command(
     )
 
 
-async def test_delta_channel_durability_exit_stores_snapshot_async() -> None:
-    """DeltaChannel must reload from an async durability='exit' checkpoint."""
-    from langchain_core.messages import AIMessage
-
-    from langgraph.channels.delta import DeltaChannel
-    from langgraph.graph.message import _messages_delta_reducer
-
-    class State(TypedDict):
-        messages: Annotated[list, DeltaChannel(_messages_delta_reducer)]
-
-    async def respond(state: State) -> dict:
-        return {"messages": [AIMessage(content="reply", id="ai1")]}
-
-    builder = StateGraph(State)
-    builder.add_node("respond", respond)
-    builder.add_edge(START, "respond")
-    graph = builder.compile(checkpointer=InMemorySaver())
-    config = {"configurable": {"thread_id": "delta-exit-async-test"}}
-
-    result = await graph.ainvoke(
-        {"messages": [HumanMessage(content="hello", id="h1")]},
-        config,
-        durability="exit",
-    )
-    assert [m.content for m in result["messages"]] == ["hello", "reply"]
-
-    state = await graph.aget_state(config)
-    assert [m.content for m in state.values["messages"]] == ["hello", "reply"]
-
-
 @NEEDS_CONTEXTVARS
 async def test_interrupt_subgraph(async_checkpointer: BaseCheckpointSaver) -> None:
     class State(TypedDict):

libs/langgraph/tests/test_pregel_stream_v2.py

@@ -21,7 +21,6 @@ from langgraph.stream import (
 from langgraph.stream._convert import convert_to_protocol_event
 from langgraph.stream._mux import StreamMux
 from langgraph.stream._types import ProtocolEvent
-from langgraph.stream.run_stream import AsyncGraphRunStream, GraphRunStream
 from langgraph.stream.transformers import MessagesTransformer, ValuesTransformer
 from langgraph.types import StreamWriter, interrupt
 
@@ -780,43 +779,6 @@ class TestValuesTransformer:
         assert len(t._interrupts) == 2
 
 
-class TestOutputWithoutValuesTransformer:
-    """run.output / run.interrupted / run.interrupts must work even when
-    ValuesTransformer is not registered."""
-
-    def _stream_part(
-        self, method: str, data: Any, namespace: tuple[str, ...] = ()
-    ) -> dict[str, Any]:
-        return {"type": method, "ns": namespace, "data": data}
-
-    def test_output_without_values_transformer(self) -> None:
-        mux = StreamMux(factories=[MessagesTransformer], is_async=False)
-        run = GraphRunStream(
-            iter([self._stream_part("values", {"v": "final"})]),
-            mux,
-        )
-        assert "values" not in run.extensions
-        assert run.output == {"v": "final"}
-
-    def test_interrupts_without_values_transformer(self) -> None:
-        part = self._stream_part("values", {"v": 1})
-        part["interrupts"] = ({"value": "pause"},)
-        mux = StreamMux(factories=[MessagesTransformer], is_async=False)
-        run = GraphRunStream(iter([part]), mux)
-        assert run.interrupted is True
-        assert len(run.interrupts) == 1
-
-    @pytest.mark.anyio
-    async def test_async_output_without_values_transformer(self) -> None:
-        async def _parts() -> Any:
-            yield {"type": "values", "ns": (), "data": {"v": "async_final"}}
-
-        mux = StreamMux(factories=[MessagesTransformer], is_async=True)
-        run = AsyncGraphRunStream(_parts(), mux)
-        assert "values" not in run.extensions
-        assert await run.output() == {"v": "async_final"}
-
-
 class TestMessagesTransformer:
     def test_captures_root_messages(self) -> None:
         t = MessagesTransformer()

libs/langgraph/tests/test_runtime.py

@@ -1,6 +1,3 @@
-import asyncio
-import threading
-import time
 from dataclasses import dataclass
 from typing import Any
 
@@ -9,15 +6,8 @@ from langgraph.checkpoint.memory import MemorySaver
 from pydantic import BaseModel, ValidationError
 from typing_extensions import TypedDict
 
-from langgraph.errors import GraphDrained
 from langgraph.graph import END, START, StateGraph
-from langgraph.runtime import (
-    ExecutionInfo,
-    RunControl,
-    Runtime,
-    ServerInfo,
-    get_runtime,
-)
+from langgraph.runtime import ExecutionInfo, Runtime, ServerInfo, get_runtime
 
 
 def test_injected_runtime() -> None:
@@ -89,183 +79,6 @@ def test_merge_runtime() -> None:
     assert runtime1.merge(runtime3).context.api_key == "abc"  # type: ignore
 
 
-def test_merge_runtime_preserves_run_control() -> None:
-    control = RunControl()
-    runtime1 = Runtime(control=control)
-    runtime2 = Runtime(context=None)
-
-    assert runtime1.merge(runtime2).control is control
-
-
-def test_run_control_request_drain_stops_future_steps() -> None:
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    control = RunControl()
-
-    def first_node(state: State) -> dict[str, str]:
-        control.request_drain()
-        return {"first": "done"}
-
-    def second_node(state: State) -> dict[str, str]:
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", first_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    with pytest.raises(GraphDrained, match="shutdown"):
-        graph.compile().invoke({}, control=control)
-
-
-@pytest.mark.anyio
-async def test_run_control_request_drain_stops_future_steps_async() -> None:
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    control = RunControl()
-
-    async def first_node(state: State) -> dict[str, str]:
-        control.request_drain()
-        return {"first": "done"}
-
-    async def second_node(state: State) -> dict[str, str]:
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", first_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    with pytest.raises(GraphDrained, match="shutdown"):
-        await graph.compile().ainvoke({}, control=control)
-
-
-def test_drain_requested_in_terminal_step_finishes_normally() -> None:
-    class State(TypedDict, total=False):
-        value: str
-
-    control = RunControl()
-
-    def node(state: State) -> dict[str, str]:
-        control.request_drain()
-        return {"value": "done"}
-
-    graph = StateGraph(State)
-    graph.add_node("node", node)
-    graph.add_edge(START, "node")
-    graph.add_edge("node", END)
-
-    assert graph.compile().invoke({}, control=control) == {"value": "done"}
-    assert control.drain_requested
-
-
-def test_drain_with_exit_durability_persists_resume_checkpoint() -> None:
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    control = RunControl()
-
-    def first_node(state: State) -> dict[str, str]:
-        control.request_drain("sigterm")
-        return {"first": "done"}
-
-    def second_node(state: State) -> dict[str, str]:
-        return {"second": "done"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", first_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    compiled = graph.compile(checkpointer=MemorySaver())
-    config = {"configurable": {"thread_id": "drain-exit"}}
-
-    with pytest.raises(GraphDrained, match="sigterm"):
-        compiled.invoke({}, config, durability="exit", control=control)
-
-    assert compiled.invoke(None, config, durability="exit") == {
-        "first": "done",
-        "second": "done",
-    }
-
-
-def test_drain_from_subgraph_can_resume_parent() -> None:
-    class State(TypedDict, total=False):
-        child_first: str
-        child_second: str
-        parent_second: str
-
-    control = RunControl()
-
-    def child_first(state: State) -> dict[str, str]:
-        control.request_drain("sigterm")
-        return {"child_first": "done"}
-
-    def child_second(state: State) -> dict[str, str]:
-        return {"child_second": "done"}
-
-    child_builder = StateGraph(State)
-    child_builder.add_node("child_first", child_first)
-    child_builder.add_node("child_second", child_second)
-    child_builder.add_edge(START, "child_first")
-    child_builder.add_edge("child_first", "child_second")
-    child_builder.add_edge("child_second", END)
-    child_graph = child_builder.compile(checkpointer=True)
-
-    def parent_second(state: State) -> dict[str, str]:
-        return {"parent_second": "done"}
-
-    parent_builder = StateGraph(State)
-    parent_builder.add_node("child", child_graph)
-    parent_builder.add_node("parent_second", parent_second)
-    parent_builder.add_edge(START, "child")
-    parent_builder.add_edge("child", "parent_second")
-    parent_builder.add_edge("parent_second", END)
-
-    compiled = parent_builder.compile(checkpointer=MemorySaver())
-    config = {"configurable": {"thread_id": "drain-subgraph"}}
-
-    with pytest.raises(GraphDrained, match="sigterm"):
-        compiled.invoke({}, config, control=control)
-
-    assert compiled.invoke(None, config) == {
-        "child_first": "done",
-        "child_second": "done",
-        "parent_second": "done",
-    }
-
-
-@pytest.mark.anyio
-async def test_drain_requested_in_terminal_step_finishes_normally_async() -> None:
-    class State(TypedDict, total=False):
-        value: str
-
-    control = RunControl()
-
-    async def node(state: State) -> dict[str, str]:
-        control.request_drain()
-        return {"value": "done"}
-
-    graph = StateGraph(State)
-    graph.add_node("node", node)
-    graph.add_edge(START, "node")
-    graph.add_edge("node", END)
-
-    assert await graph.compile().ainvoke({}, control=control) == {"value": "done"}
-    assert control.drain_requested
-
-
 def test_runtime_propogated_to_subgraph() -> None:
     @dataclass
     class Context:
@@ -579,334 +392,6 @@ def test_context_coercion_pydantic_validation_errors() -> None:
         )
 
 
-def test_external_drain_concurrent_sync() -> None:
-    """External thread calls request_drain() while graph is mid-execution."""
-
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    started = threading.Event()
-
-    def first_node(state: State) -> dict[str, str]:
-        started.set()
-        time.sleep(0.05)
-        return {"first": "done"}
-
-    def second_node(state: State) -> dict[str, str]:
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", first_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    control = RunControl()
-    compiled = graph.compile()
-
-    exc_holder: list[BaseException | None] = [None]
-
-    def run_graph() -> None:
-        try:
-            compiled.invoke({}, control=control)
-        except GraphDrained as e:
-            exc_holder[0] = e
-
-    t = threading.Thread(target=run_graph)
-    t.start()
-
-    started.wait(timeout=5)
-    control.request_drain("sigterm")
-
-    t.join(timeout=10)
-
-    exc = exc_holder[0]
-    assert isinstance(exc, GraphDrained)
-    assert exc.reason == "sigterm"
-
-
-@pytest.mark.anyio
-async def test_external_drain_concurrent_async() -> None:
-    """External task calls request_drain() while graph is mid-execution."""
-
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    started = asyncio.Event()
-
-    async def first_node(state: State) -> dict[str, str]:
-        started.set()
-        await asyncio.sleep(0.05)
-        return {"first": "done"}
-
-    async def second_node(state: State) -> dict[str, str]:
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", first_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    control = RunControl()
-    compiled = graph.compile()
-
-    async def drain_after_start() -> None:
-        await started.wait()
-        control.request_drain("sigterm")
-
-    drain_task = asyncio.create_task(drain_after_start())
-
-    with pytest.raises(GraphDrained, match="sigterm"):
-        await compiled.ainvoke({}, control=control)
-
-    await drain_task
-
-
-@pytest.mark.anyio
-async def test_drain_then_cancel_after_graceful_timeout() -> None:
-    """Simulate: drain requested -> node still running -> graceful timeout -> cancel.
-
-    This shows what happens when a long-running node doesn't finish within
-    the graceful period after drain is requested.
-    """
-
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    node_started = asyncio.Event()
-    node_cancelled = asyncio.Event()
-    node_finished = asyncio.Event()
-
-    async def slow_node(state: State) -> dict[str, str]:
-        node_started.set()
-        try:
-            await asyncio.sleep(30)  # very long operation
-        except asyncio.CancelledError:
-            node_cancelled.set()
-            raise
-        node_finished.set()
-        return {"first": "done"}
-
-    async def second_node(state: State) -> dict[str, str]:
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", slow_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    control = RunControl()
-    compiled = graph.compile()
-
-    # Phase 1: start graph
-    graph_task = asyncio.create_task(compiled.ainvoke({}, control=control))
-
-    # Phase 2: wait for node to start, then request drain
-    await node_started.wait()
-    control.request_drain("sigterm")
-
-    # Phase 3: graceful timeout — node is still running, cancel after 1s
-    graceful_timeout = 1.0
-    await asyncio.sleep(graceful_timeout)
-
-    assert not node_finished.is_set(), "node should still be running"
-    assert not node_cancelled.is_set(), "node should not be cancelled yet"
-
-    # Phase 4: force cancel
-    graph_task.cancel()
-
-    with pytest.raises(asyncio.CancelledError):
-        await graph_task
-
-    # The node received CancelledError at the await point
-    assert node_cancelled.is_set(), "node should have received CancelledError"
-    assert not node_finished.is_set(), "node should NOT have finished normally"
-
-
-@pytest.mark.anyio
-async def test_cancel_ainvoke_with_async_node() -> None:
-    """Cancel ainvoke running an async node: CancelledError is delivered
-    at the await point and the node stops immediately."""
-
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    timeline: list[str] = []
-    node_started = asyncio.Event()
-
-    async def slow_async_node(state: State) -> dict[str, str]:
-        timeline.append(f"async_node:start thread={threading.current_thread().name}")
-        node_started.set()
-        try:
-            await asyncio.sleep(30)
-        except asyncio.CancelledError:
-            timeline.append("async_node:cancelled")
-            raise
-        timeline.append("async_node:finished")
-        return {"first": "done"}
-
-    async def second_node(state: State) -> dict[str, str]:
-        timeline.append("second_node:run")
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", slow_async_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    compiled = graph.compile()
-    graph_task = asyncio.create_task(compiled.ainvoke({}))
-
-    await node_started.wait()
-    timeline.append("test:cancel")
-    graph_task.cancel()
-
-    with pytest.raises(asyncio.CancelledError):
-        await graph_task
-    timeline.append("test:done")
-
-    # async node runs on the event loop thread (MainThread)
-    assert any("MainThread" in e for e in timeline if "async_node:start" in e)
-    # CancelledError was delivered at the await point — node stopped
-    assert "async_node:cancelled" in timeline
-    # Node did NOT run to completion
-    assert "async_node:finished" not in timeline
-    # Second node never ran
-    assert "second_node:run" not in timeline
-
-
-@pytest.mark.anyio
-async def test_cancel_ainvoke_with_sync_node() -> None:
-    """Cancel ainvoke running a sync node.
-
-    Sync nodes in ainvoke run on a separate thread (via run_in_executor),
-    NOT on the event loop thread. Cancelling the asyncio task disconnects
-    from the thread future, but the thread keeps running as an orphan and
-    completes on its own.
-
-    Key difference from async nodes:
-    - async node: CancelledError stops the coroutine at an await point
-    - sync node: cancel only disconnects asyncio; the thread runs to completion
-
-    In shutdown case, we will ignore this because the instance will be destroyed soon.
-    """
-
-    class State(TypedDict, total=False):
-        first: str
-        second: str
-
-    timeline: list[str] = []
-    node_started = threading.Event()
-    node_finished = threading.Event()
-
-    def slow_sync_node(state: State) -> dict[str, str]:
-        timeline.append(f"sync_node:start thread={threading.current_thread().name}")
-        node_started.set()
-        time.sleep(1)
-        timeline.append("sync_node:after_sleep")
-        node_finished.set()
-        return {"first": "done"}
-
-    def second_node(state: State) -> dict[str, str]:
-        timeline.append("second_node:run")
-        return {"second": "should-not-run"}
-
-    graph = StateGraph(State)
-    graph.add_node("first", slow_sync_node)
-    graph.add_node("second", second_node)
-    graph.add_edge(START, "first")
-    graph.add_edge("first", "second")
-    graph.add_edge("second", END)
-
-    control = RunControl()
-    compiled = graph.compile()
-
-    timeline.append(f"test:main thread={threading.current_thread().name}")
-    graph_task = asyncio.create_task(compiled.ainvoke({}, control=control))
-
-    loop = asyncio.get_event_loop()
-    await loop.run_in_executor(None, node_started.wait, 5)
-
-    timeline.append("test:cancel+drain")
-    graph_task.cancel()
-    control.request_drain("sigterm")
-
-    with pytest.raises(asyncio.CancelledError):
-        await graph_task
-    timeline.append("test:exc=CancelledError")
-
-    # Sync node runs on a background thread (asyncio_*), NOT MainThread
-    sync_start = next(e for e in timeline if "sync_node:start" in e)
-    assert "MainThread" not in sync_start, (
-        "sync node should run on a background thread, not the event loop thread"
-    )
-
-    # At this point, the asyncio task is done but the thread is orphaned.
-    # The sync node has NOT finished yet — cancel only disconnected asyncio.
-    assert not node_finished.is_set(), (
-        "sync node should still be running in its background thread"
-    )
-
-    # Wait for the orphaned thread to complete on its own.
-    await loop.run_in_executor(None, node_finished.wait, 5)
-    assert node_finished.is_set()
-
-    # After the orphaned thread finishes, the full timeline looks like:
-    #   test:main thread=MainThread
-    #   sync_node:start thread=asyncio_N    <- background thread
-    #   test:cancel+drain                   <- cancel + drain fired
-    #   test:exc=CancelledError             <- asyncio disconnected
-    #   sync_node:after_sleep               <- thread ran to completion anyway
-    assert "sync_node:after_sleep" in timeline
-    # Second node never ran
-    assert "second_node:run" not in timeline
-
-    # Verify timeline ordering: cancel happened before node finished
-    cancel_idx = timeline.index("test:cancel+drain")
-    sleep_idx = timeline.index("sync_node:after_sleep")
-    assert cancel_idx < sleep_idx, (
-        "cancel was issued while the sync node was still sleeping"
-    )
-
-
-def test_drain_with_control_parameter_sync() -> None:
-    """Control parameter is wired through invoke -> stream."""
-
-    class State(TypedDict, total=False):
-        value: str
-
-    ran = False
-
-    def node(state: State) -> dict[str, str]:
-        nonlocal ran
-        ran = True
-        return {"value": "done"}
-
-    graph = StateGraph(State)
-    graph.add_node("node", node)
-    graph.add_edge(START, "node")
-    graph.add_edge("node", END)
-
-    # Pre-drained control stops before executing the first pending task.
-    control = RunControl()
-    control.request_drain("pre-drained")
-
-    with pytest.raises(GraphDrained, match="pre-drained"):
-        graph.compile().invoke({}, control=control)
-    assert not ran
-
-
 # --- ExecutionInfo unit tests ---
 
 

libs/langgraph/tests/test_stream_data_transformers.py

@@ -1,694 +0,0 @@
-"""Tests for CustomTransformer, UpdatesTransformer, CheckpointsTransformer, DebugTransformer, TasksTransformer.
-
-These transformers capture raw protocol events for their respective stream
-modes and expose them as native projections on the run stream (run.custom,
-run.updates, run.checkpoints, run.debug, run.tasks). Tests dispatch synthetic
-protocol events through a StreamMux to isolate transformer logic; the final
-group exercises real graphs through stream_v2.
-"""
-
-from __future__ import annotations
-
-import operator
-import time
-from typing import Annotated, Any
-
-from typing_extensions import TypedDict
-
-from langgraph.constants import END, START
-from langgraph.graph import StateGraph
-from langgraph.stream._mux import StreamMux
-from langgraph.stream.stream_channel import StreamChannel
-from langgraph.stream.transformers import (
-    CheckpointsTransformer,
-    CustomTransformer,
-    DebugTransformer,
-    LifecycleTransformer,
-    TasksTransformer,
-    UpdatesTransformer,
-)
-
-TS = int(time.time() * 1000)
-
-
-def _custom_event(namespace: list[str], data: Any) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "custom",
-        "params": {"namespace": namespace, "timestamp": TS, "data": data},
-    }
-
-
-def _checkpoints_event(namespace: list[str], data: Any) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "checkpoints",
-        "params": {"namespace": namespace, "timestamp": TS, "data": data},
-    }
-
-
-def _debug_event(namespace: list[str], data: Any) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "debug",
-        "params": {"namespace": namespace, "timestamp": TS, "data": data},
-    }
-
-
-def _tasks_event(namespace: list[str], data: Any) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "tasks",
-        "params": {"namespace": namespace, "timestamp": TS, "data": data},
-    }
-
-
-def _updates_event(namespace: list[str], data: Any) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "updates",
-        "params": {"namespace": namespace, "timestamp": TS, "data": data},
-    }
-
-
-def _arm(mux: StreamMux, transformer: Any) -> None:
-    """Force projection logs to accept pushes (skip lazy-subscribe gate)."""
-    mux._events._subscribed = True
-    transformer._log._subscribed = True
-
-
-def _drain(transformer: Any) -> list[Any]:
-    return list(transformer._log._items)
-
-
-# ---------------------------------------------------------------------------
-# CustomTransformer
-# ---------------------------------------------------------------------------
-
-
-def test_custom_captures_root_scope_events() -> None:
-    t = CustomTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_custom_event([], {"status": "processing"}))
-    mux.push(_custom_event([], {"status": "done"}))
-
-    items = _drain(t)
-    assert items == [{"status": "processing"}, {"status": "done"}]
-
-
-def test_custom_ignores_subgraph_scope_events() -> None:
-    t = CustomTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_custom_event(["subgraph:abc"], {"from": "child"}))
-
-    assert _drain(t) == []
-
-
-def test_custom_scoped_transformer_captures_own_scope() -> None:
-    t = CustomTransformer(scope=("agent:abc",))
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_custom_event([], {"from": "root"}))
-    mux.push(_custom_event(["agent:abc"], {"from": "self"}))
-    mux.push(_custom_event(["agent:abc", "deep:def"], {"from": "child"}))
-
-    items = _drain(t)
-    assert items == [{"from": "self"}]
-
-
-def test_custom_preserves_any_payload_type() -> None:
-    t = CustomTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_custom_event([], "string_payload"))
-    mux.push(_custom_event([], 42))
-    mux.push(_custom_event([], [1, 2, 3]))
-
-    assert _drain(t) == ["string_payload", 42, [1, 2, 3]]
-
-
-def test_custom_does_not_suppress_from_main_log() -> None:
-    t = CustomTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_custom_event([], "data"))
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "custom" in methods
-
-
-def test_custom_ignores_other_methods() -> None:
-    t = CustomTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(
-        {
-            "type": "event",
-            "method": "values",
-            "params": {"namespace": [], "timestamp": TS, "data": {}},
-        }
-    )
-    assert _drain(t) == []
-
-
-def test_custom_required_stream_modes() -> None:
-    assert CustomTransformer.required_stream_modes == ("custom",)
-
-
-def test_custom_is_native() -> None:
-    assert getattr(CustomTransformer, "_native", False) is True
-
-
-def test_custom_init_returns_correct_key() -> None:
-    t = CustomTransformer()
-    projection = t.init()
-    assert "custom" in projection
-    assert isinstance(projection["custom"], StreamChannel)
-
-
-# ---------------------------------------------------------------------------
-# CheckpointsTransformer
-# ---------------------------------------------------------------------------
-
-
-def test_checkpoints_captures_root_scope_events() -> None:
-    t = CheckpointsTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    checkpoint_data = {"values": {"x": 1}, "next": ["node_b"]}
-    mux.push(_checkpoints_event([], checkpoint_data))
-
-    items = _drain(t)
-    assert items == [checkpoint_data]
-
-
-def test_checkpoints_ignores_subgraph_events() -> None:
-    t = CheckpointsTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_checkpoints_event(["child:abc"], {"values": {"x": 1}}))
-
-    assert _drain(t) == []
-
-
-def test_checkpoints_scoped_transformer() -> None:
-    t = CheckpointsTransformer(scope=("sub:abc",))
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_checkpoints_event([], {"from": "root"}))
-    mux.push(_checkpoints_event(["sub:abc"], {"from": "self"}))
-
-    assert _drain(t) == [{"from": "self"}]
-
-
-def test_checkpoints_does_not_suppress_from_main_log() -> None:
-    t = CheckpointsTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_checkpoints_event([], {"values": {}}))
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "checkpoints" in methods
-
-
-def test_checkpoints_required_stream_modes() -> None:
-    assert CheckpointsTransformer.required_stream_modes == ("checkpoints",)
-
-
-def test_checkpoints_is_native() -> None:
-    assert getattr(CheckpointsTransformer, "_native", False) is True
-
-
-# ---------------------------------------------------------------------------
-# DebugTransformer
-# ---------------------------------------------------------------------------
-
-
-def test_debug_captures_root_scope_events() -> None:
-    t = DebugTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    debug_data = {
-        "step": 0,
-        "type": "checkpoint",
-        "timestamp": "2026-01-01T00:00:00Z",
-        "payload": {"values": {"x": 1}},
-    }
-    mux.push(_debug_event([], debug_data))
-
-    items = _drain(t)
-    assert items == [debug_data]
-
-
-def test_debug_ignores_subgraph_events() -> None:
-    t = DebugTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_debug_event(["child:abc"], {"step": 0, "type": "task"}))
-
-    assert _drain(t) == []
-
-
-def test_debug_captures_multiple_event_types() -> None:
-    t = DebugTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_debug_event([], {"step": 0, "type": "checkpoint", "payload": {}}))
-    mux.push(_debug_event([], {"step": 1, "type": "task", "payload": {}}))
-    mux.push(_debug_event([], {"step": 1, "type": "task_result", "payload": {}}))
-
-    items = _drain(t)
-    assert len(items) == 3
-    assert [d["type"] for d in items] == ["checkpoint", "task", "task_result"]
-
-
-def test_debug_does_not_suppress_from_main_log() -> None:
-    t = DebugTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_debug_event([], {"step": 0}))
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "debug" in methods
-
-
-def test_debug_required_stream_modes() -> None:
-    assert DebugTransformer.required_stream_modes == ("debug",)
-
-
-def test_debug_is_native() -> None:
-    assert getattr(DebugTransformer, "_native", False) is True
-
-
-# ---------------------------------------------------------------------------
-# TasksTransformer
-# ---------------------------------------------------------------------------
-
-
-def test_tasks_captures_root_scope_events() -> None:
-    t = TasksTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    task_start = {"id": "t1", "name": "my_node", "input": None, "triggers": []}
-    mux.push(_tasks_event([], task_start))
-
-    items = _drain(t)
-    assert items == [task_start]
-
-
-def test_tasks_captures_start_and_result() -> None:
-    t = TasksTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    start = {"id": "t1", "name": "a", "input": None, "triggers": []}
-    result = {"id": "t1", "name": "a", "result": {"output": 42}, "error": None}
-    mux.push(_tasks_event([], start))
-    mux.push(_tasks_event([], result))
-
-    items = _drain(t)
-    assert items == [start, result]
-
-
-def test_tasks_ignores_subgraph_events() -> None:
-    t = TasksTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_tasks_event(["child:abc"], {"id": "t1", "name": "x"}))
-
-    assert _drain(t) == []
-
-
-def test_tasks_scoped_transformer() -> None:
-    t = TasksTransformer(scope=("agent:abc",))
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_tasks_event([], {"id": "t1"}))
-    mux.push(_tasks_event(["agent:abc"], {"id": "t2"}))
-    mux.push(_tasks_event(["agent:abc", "deep:def"], {"id": "t3"}))
-
-    assert _drain(t) == [{"id": "t2"}]
-
-
-def test_tasks_does_not_suppress_from_main_log() -> None:
-    """TasksTransformer returns True — it doesn't suppress tasks events.
-
-    (LifecycleTransformer suppresses them, but that's independent.)
-    """
-    t = TasksTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_tasks_event([], {"id": "t1"}))
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "tasks" in methods
-
-
-def test_tasks_required_stream_modes() -> None:
-    assert TasksTransformer.required_stream_modes == ("tasks",)
-
-
-def test_tasks_is_native() -> None:
-    assert getattr(TasksTransformer, "_native", False) is True
-
-
-# ---------------------------------------------------------------------------
-# UpdatesTransformer
-# ---------------------------------------------------------------------------
-
-
-def test_updates_captures_root_scope_events() -> None:
-    t = UpdatesTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    update = {"my_node": {"value": "hello!"}}
-    mux.push(_updates_event([], update))
-
-    items = _drain(t)
-    assert items == [update]
-
-
-def test_updates_captures_multiple_steps() -> None:
-    t = UpdatesTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_updates_event([], {"node_a": {"x": 1}}))
-    mux.push(_updates_event([], {"node_b": {"x": 2}}))
-
-    items = _drain(t)
-    assert items == [{"node_a": {"x": 1}}, {"node_b": {"x": 2}}]
-
-
-def test_updates_ignores_subgraph_events() -> None:
-    t = UpdatesTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_updates_event(["child:abc"], {"inner_node": {"v": 1}}))
-
-    assert _drain(t) == []
-
-
-def test_updates_scoped_transformer() -> None:
-    t = UpdatesTransformer(scope=("agent:abc",))
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_updates_event([], {"from": "root"}))
-    mux.push(_updates_event(["agent:abc"], {"from": "self"}))
-
-    assert _drain(t) == [{"from": "self"}]
-
-
-def test_updates_does_not_suppress_from_main_log() -> None:
-    t = UpdatesTransformer()
-    mux = StreamMux([t], is_async=False)
-    _arm(mux, t)
-
-    mux.push(_updates_event([], {"n": {}}))
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "updates" in methods
-
-
-def test_updates_required_stream_modes() -> None:
-    assert UpdatesTransformer.required_stream_modes == ("updates",)
-
-
-def test_updates_is_native() -> None:
-    assert getattr(UpdatesTransformer, "_native", False) is True
-
-
-# ---------------------------------------------------------------------------
-# Cross-transformer: unrelated events pass through
-# ---------------------------------------------------------------------------
-
-
-def test_unrelated_events_ignored_by_all() -> None:
-    """Non-matching method events don't land in any transformer's log."""
-    transformers = [
-        CustomTransformer(),
-        UpdatesTransformer(),
-        CheckpointsTransformer(),
-        DebugTransformer(),
-        TasksTransformer(),
-    ]
-    mux = StreamMux(transformers, is_async=False)
-    mux._events._subscribed = True
-    for t in transformers:
-        t._log._subscribed = True
-
-    mux.push(
-        {
-            "type": "event",
-            "method": "values",
-            "params": {"namespace": [], "timestamp": TS, "data": {"x": 1}},
-        }
-    )
-
-    for t in transformers:
-        assert list(t._log._items) == []
-
-
-# ---------------------------------------------------------------------------
-# End-to-end: real graphs through stream_v2
-# ---------------------------------------------------------------------------
-
-
-class _State(TypedDict):
-    value: str
-    items: Annotated[list[str], operator.add]
-
-
-def _my_node(state: _State) -> dict[str, Any]:
-    from langgraph.config import get_stream_writer
-
-    writer = get_stream_writer()
-    writer({"status": "working", "node": "my_node"})
-    return {"value": state["value"] + "!", "items": ["done"]}
-
-
-def _make_simple_graph() -> Any:
-    builder = StateGraph(_State, input_schema=_State)
-    builder.add_node("my_node", _my_node)
-    builder.add_edge(START, "my_node")
-    builder.add_edge("my_node", END)
-    return builder.compile()
-
-
-def test_stream_v2_custom_projection_opt_in() -> None:
-    """run.custom surfaces get_stream_writer() payloads when opted in."""
-    graph = _make_simple_graph()
-    run = graph.stream_v2(
-        {"value": "hello", "items": []}, transformers=[CustomTransformer]
-    )
-
-    custom_events = list(run.custom)
-    assert len(custom_events) >= 1
-    assert any(e.get("status") == "working" for e in custom_events)
-
-
-def test_stream_v2_custom_and_values_coexist() -> None:
-    """Both run.custom and run.values work in the same run."""
-    graph = _make_simple_graph()
-    run = graph.stream_v2(
-        {"value": "hello", "items": []}, transformers=[CustomTransformer]
-    )
-
-    custom_events = list(run.custom)
-    assert run.output is not None
-    assert run.output["value"] == "hello!"
-    assert len(custom_events) >= 1
-
-
-def test_stream_v2_tasks_projection_opt_in() -> None:
-    """run.tasks surfaces raw task events when opted in via transformers=."""
-    graph = _make_simple_graph()
-    run = graph.stream_v2({"value": "x", "items": []}, transformers=[TasksTransformer])
-
-    tasks_events = list(run.tasks)
-    assert len(tasks_events) >= 1
-    names = [t.get("name") for t in tasks_events if "name" in t]
-    assert "my_node" in names
-
-
-def test_stream_v2_debug_projection_opt_in() -> None:
-    """run.debug surfaces debug events when opted in via transformers=."""
-    graph = _make_simple_graph()
-    run = graph.stream_v2({"value": "x", "items": []}, transformers=[DebugTransformer])
-
-    debug_events = list(run.debug)
-    assert len(debug_events) >= 1
-    types = {d.get("type") for d in debug_events}
-    assert types & {"checkpoint", "task", "task_result"}
-
-
-def test_stream_v2_updates_projection_opt_in() -> None:
-    """run.updates surfaces node output dicts when opted in via transformers=."""
-    graph = _make_simple_graph()
-    run = graph.stream_v2(
-        {"value": "x", "items": []}, transformers=[UpdatesTransformer]
-    )
-
-    updates = list(run.updates)
-    assert len(updates) >= 1
-    node_names = {k for u in updates for k in u if k != "__interrupt__"}
-    assert "my_node" in node_names
-
-
-def test_stream_v2_all_transformers_interleaved() -> None:
-    """All five transformers registered together, consumed via interleave."""
-    graph = _make_simple_graph()
-    run = graph.stream_v2(
-        {"value": "x", "items": []},
-        transformers=[
-            CustomTransformer,
-            UpdatesTransformer,
-            CheckpointsTransformer,
-            DebugTransformer,
-            TasksTransformer,
-        ],
-    )
-
-    collected: dict[str, list[Any]] = {
-        "custom": [],
-        "updates": [],
-        "debug": [],
-        "tasks": [],
-    }
-    for name, item in run.interleave("custom", "updates", "debug", "tasks"):
-        collected[name].append(item)
-
-    assert len(collected["custom"]) >= 1
-    assert len(collected["updates"]) >= 1
-    assert len(collected["tasks"]) >= 1
-    assert len(collected["debug"]) >= 1
-    types = {d.get("type") for d in collected["debug"]}
-    assert types & {"checkpoint", "task", "task_result"}
-    node_names = {k for u in collected["updates"] for k in u if k != "__interrupt__"}
-    assert "my_node" in node_names
-
-    assert run.output is not None
-    assert run.output["value"] == "x!"
-
-
-def test_stream_v2_all_transformers_with_checkpointer() -> None:
-    """All transformers with a checkpointer — run.checkpoints populated."""
-    from langgraph.checkpoint.memory import InMemorySaver
-
-    builder = StateGraph(_State, input_schema=_State)
-    builder.add_node("my_node", _my_node)
-    builder.add_edge(START, "my_node")
-    builder.add_edge("my_node", END)
-    graph = builder.compile(checkpointer=InMemorySaver())
-
-    run = graph.stream_v2(
-        {"value": "x", "items": []},
-        config={"configurable": {"thread_id": "test-all"}},
-        transformers=[
-            CustomTransformer,
-            UpdatesTransformer,
-            CheckpointsTransformer,
-            DebugTransformer,
-            TasksTransformer,
-        ],
-    )
-
-    collected: dict[str, list[Any]] = {
-        "custom": [],
-        "updates": [],
-        "checkpoints": [],
-        "debug": [],
-        "tasks": [],
-    }
-    for name, item in run.interleave(
-        "custom", "updates", "checkpoints", "debug", "tasks"
-    ):
-        collected[name].append(item)
-
-    assert len(collected["checkpoints"]) >= 1
-    assert len(collected["custom"]) >= 1
-
-
-def test_stream_v2_checkpoints_projection_opt_in() -> None:
-    """run.checkpoints surfaces checkpoint data when opted in with a checkpointer."""
-    from langgraph.checkpoint.memory import InMemorySaver
-
-    builder = StateGraph(_State, input_schema=_State)
-    builder.add_node("my_node", _my_node)
-    builder.add_edge(START, "my_node")
-    builder.add_edge("my_node", END)
-    graph = builder.compile(checkpointer=InMemorySaver())
-
-    run = graph.stream_v2(
-        {"value": "x", "items": []},
-        config={"configurable": {"thread_id": "test-ckpt-standalone"}},
-        transformers=[CheckpointsTransformer],
-    )
-
-    checkpoints = list(run.checkpoints)
-    assert len(checkpoints) >= 1
-
-
-# ---------------------------------------------------------------------------
-# TasksTransformer + LifecycleTransformer co-registration
-# ---------------------------------------------------------------------------
-
-
-def test_tasks_and_lifecycle_coregistration() -> None:
-    """When both are in the same StreamMux, LifecycleTransformer suppresses
-    tasks events from the main log (returns False) while TasksTransformer
-    still captures them into its own log.
-    """
-    lifecycle = LifecycleTransformer()
-    tasks = TasksTransformer()
-    mux = StreamMux([lifecycle, tasks], is_async=False)
-    mux._events._subscribed = True
-    tasks._log._subscribed = True
-    lifecycle._channel._subscribed = True
-
-    task_data = {"id": "t1", "name": "my_node", "input": None, "triggers": []}
-    mux.push(_tasks_event([], task_data))
-
-    assert _drain(tasks) == [task_data]
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "tasks" not in methods
-
-
-def test_tasks_and_lifecycle_coregistration_e2e() -> None:
-    """E2e: TasksTransformer captures task events even when LifecycleTransformer
-    is present and suppressing them from the main log.
-    """
-    graph = _make_simple_graph()
-    run = graph.stream_v2(
-        {"value": "x", "items": []},
-        transformers=[TasksTransformer],
-    )
-
-    tasks_events = list(run.tasks)
-    assert len(tasks_events) >= 1
-    names = [t.get("name") for t in tasks_events if "name" in t]
-    assert "my_node" in names

libs/langgraph/tests/test_stream_messages_transformer.py

@@ -403,7 +403,7 @@ class TestWireRequestMore:
         mux = StreamMux([values_t, messages_t], is_async=False)
 
         assert messages_t._pump_fn is None
-        run = GraphRunStream(iter([]), mux)
+        run = GraphRunStream(iter([]), mux, values_t)
         assert messages_t._pump_fn is not None
         assert messages_t._pump_fn() is False
         assert run._exhausted
@@ -412,7 +412,7 @@ class TestWireRequestMore:
         values_t = ValuesTransformer()
         messages_t = MessagesTransformer()
         mux = StreamMux([values_t, messages_t], is_async=False)
-        GraphRunStream(iter([]), mux)
+        GraphRunStream(iter([]), mux, values_t)
 
         log: StreamChannel[ChatModelStream] = mux.extensions["messages"]
         log._subscribed = True

libs/langgraph/tests/test_stream_subgraph_transformer.py

@@ -546,6 +546,8 @@ def test_child_forwarding_errors_fail_sync_run() -> None:
         ],
         is_async=False,
     )
+    values_t = mux.transformer_by_key("values")
+    assert isinstance(values_t, ValuesTransformer)
     run = GraphRunStream(
         iter(
             [
@@ -563,6 +565,7 @@ def test_child_forwarding_errors_fail_sync_run() -> None:
             ]
         ),
         mux,
+        values_t,
     )
 
     handle = next(iter(run.subgraphs))
@@ -584,6 +587,8 @@ async def test_child_forwarding_errors_fail_async_run() -> None:
         ],
         is_async=True,
     )
+    values_t = mux.transformer_by_key("values")
+    assert isinstance(values_t, ValuesTransformer)
     run = AsyncGraphRunStream(
         _astream_parts(
             _stream_part(
@@ -599,6 +604,7 @@ async def test_child_forwarding_errors_fail_async_run() -> None:
             _stream_part("values", ("agent:abc",), {"x": 1}),
         ),
         mux,
+        values_t,
     )
 
     handle = await run.subgraphs.__aiter__().__anext__()
@@ -619,6 +625,8 @@ def test_child_finalize_errors_propagate_to_sync_run() -> None:
         ],
         is_async=False,
     )
+    values_t = mux.transformer_by_key("values")
+    assert isinstance(values_t, ValuesTransformer)
     run = GraphRunStream(
         iter(
             [
@@ -635,6 +643,7 @@ def test_child_finalize_errors_propagate_to_sync_run() -> None:
             ]
         ),
         mux,
+        values_t,
     )
 
     with pytest.raises(RuntimeError, match="child finalize boom"):
@@ -653,6 +662,8 @@ async def test_child_finalize_errors_propagate_to_async_run() -> None:
         ],
         is_async=True,
     )
+    values_t = mux.transformer_by_key("values")
+    assert isinstance(values_t, ValuesTransformer)
     run = AsyncGraphRunStream(
         _astream_parts(
             _stream_part(
@@ -667,6 +678,7 @@ async def test_child_finalize_errors_propagate_to_async_run() -> None:
             )
         ),
         mux,
+        values_t,
     )
 
     with pytest.raises(RuntimeError, match="child afinalize boom"):

libs/langgraph/tests/test_stream_v2.py

@@ -19,11 +19,9 @@ from typing_extensions import TypedDict, assert_type
 
 from langgraph._internal._constants import INTERRUPT
 from langgraph.constants import END, START
-from langgraph.errors import GraphDrained
 from langgraph.func import entrypoint
 from langgraph.graph import StateGraph
 from langgraph.graph.message import MessagesState
-from langgraph.runtime import RunControl
 from langgraph.types import (
     CheckpointPayload,
     CheckpointStreamPart,
@@ -231,32 +229,6 @@ class TestV2Stream:
         for c in chunks:
             _assert_stream_part_shape(c)
 
-    def test_stream_v2_accepts_control_for_drain(self) -> None:
-        class DrainState(TypedDict, total=False):
-            value: str
-            skipped: str
-
-        control = RunControl()
-
-        def first_node(state: DrainState) -> dict[str, str]:
-            control.request_drain("sigterm")
-            return {"value": "done"}
-
-        def second_node(state: DrainState) -> dict[str, str]:
-            return {"skipped": "nope"}
-
-        builder = StateGraph(DrainState)
-        builder.add_node("first", first_node)
-        builder.add_node("second", second_node)
-        builder.add_edge(START, "first")
-        builder.add_edge("first", "second")
-        builder.add_edge("second", END)
-        graph = builder.compile()
-
-        run = graph.stream_v2({}, control=control)
-        with pytest.raises(GraphDrained, match="sigterm"):
-            list(run.values)
-
     def test_subgraphs_ns(self) -> None:
         outer = _make_subgraph()
         chunks = list(

libs/langgraph/uv.lock

@@ -1349,7 +1349,7 @@ wheels = [
 [[package]]
 name = "langchain-core"
 version = "1.3.2"
-source = { registry = "https://pypi.org/simple" }
+source = { git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates#aee50839376e379891c99fcbe6d5264f66dedc68" }
 dependencies = [
     { name = "jsonpatch" },
     { name = "langchain-protocol" },
@@ -1361,26 +1361,22 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a8/03/7219502e8ca728d65eb44d7a3eb60239230742a70dbfc9241b9bfd61c4ab/langchain_core-1.3.2.tar.gz", hash = "sha256:fd7a50b2f28ba561fd9d7f5d2760bc9e06cf00cdf820a3ccafe88a94ffa8d5b7", size = 911813, upload-time = "2026-04-24T15:49:23.699Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/7d/d5/8fa4431007cbb7cfed7590f4d6a5dea3ad724f4174d248f6642ef5ce7d05/langchain_core-1.3.2-py3-none-any.whl", hash = "sha256:d44a66127f9f8db735bdfd0ab9661bccb47a97113cfd3f2d89c74864422b7274", size = 542390, upload-time = "2026-04-24T15:49:21.991Z" },
-]
 
 [[package]]
 name = "langchain-protocol"
-version = "0.0.12"
+version = "0.0.14"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/5c/51/1157009b6f94e6e58be58fa8b620187d657909a8b36a6bf5b0c52a2711f6/langchain_protocol-0.0.12.tar.gz", hash = "sha256:5e14c434290a705c9510fdb1a83ecf7561a5e6e0dfd053930ade80dba069269f", size = 6408, upload-time = "2026-04-25T01:05:01.489Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/95/82/3431e3061c917439589fa88a6b23c9bc0e154cba0f05d2e895a68c76ff74/langchain_protocol-0.0.12-py3-none-any.whl", hash = "sha256:402b61f42d4139692528cf37226c367bb6efc8ff8165b29380accb0abfece7b2", size = 6639, upload-time = "2026-04-25T01:05:00.487Z" },
+    { url = "https://files.pythonhosted.org/packages/c2/e9/06c47ecb2aff08f83dfa30058da3bf86be64862c19569043ed5331bbeecd/langchain_protocol-0.0.14-py3-none-any.whl", hash = "sha256:ffc35089779bd8ca217015180cef5e660fc3b074efdaa0f2e95df73583f1a047", size = 6984, upload-time = "2026-04-29T16:40:17.841Z" },
 ]
 
 [[package]]
 name = "langgraph"
-version = "1.2.0a1"
+version = "1.1.10"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1452,7 +1448,7 @@ test = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.2,<2" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "../prebuilt" },
     { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -1464,7 +1460,7 @@ requires-dist = [
 dev = [
     { name = "httpx" },
     { name = "jupyter" },
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1497,7 +1493,7 @@ lint = [
 ]
 test = [
     { name = "httpx" },
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1561,7 +1557,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -1570,7 +1566,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.2.38" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "ormsgpack", specifier = ">=1.12.0" },
 ]
 
@@ -1609,7 +1605,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.1.0a1"
+version = "3.0.5"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -1764,14 +1760,14 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.1" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]
 
 [package.metadata.requires-dev]
 dev = [
     { name = "codespell" },
-    { name = "langchain-core" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph", editable = "." },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
@@ -1791,7 +1787,7 @@ lint = [
     { name = "ruff" },
 ]
 test = [
-    { name = "langchain-core" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph", editable = "." },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },

libs/prebuilt/pyproject.toml

@@ -30,7 +30,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/prebuilt"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 
@@ -62,6 +62,7 @@ dev = [
 default-groups = ['dev']
 
 [tool.uv.sources]
+langchain-core = { git = "https://github.com/langchain-ai/langchain", branch = "cb/chat-model-updates", subdirectory = "libs/core" }
 langgraph = { path = "../langgraph", editable = true }
 langgraph-checkpoint = { path = "../checkpoint", editable = true }
 langgraph-checkpoint-sqlite = { path = "../checkpoint-sqlite", editable = true }

libs/prebuilt/uv.lock

@@ -250,7 +250,7 @@ wheels = [
 [[package]]
 name = "langchain-core"
 version = "1.3.2"
-source = { registry = "https://pypi.org/simple" }
+source = { git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates#aee50839376e379891c99fcbe6d5264f66dedc68" }
 dependencies = [
     { name = "jsonpatch" },
     { name = "langchain-protocol" },
@@ -262,26 +262,22 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a8/03/7219502e8ca728d65eb44d7a3eb60239230742a70dbfc9241b9bfd61c4ab/langchain_core-1.3.2.tar.gz", hash = "sha256:fd7a50b2f28ba561fd9d7f5d2760bc9e06cf00cdf820a3ccafe88a94ffa8d5b7", size = 911813, upload-time = "2026-04-24T15:49:23.699Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/7d/d5/8fa4431007cbb7cfed7590f4d6a5dea3ad724f4174d248f6642ef5ce7d05/langchain_core-1.3.2-py3-none-any.whl", hash = "sha256:d44a66127f9f8db735bdfd0ab9661bccb47a97113cfd3f2d89c74864422b7274", size = 542390, upload-time = "2026-04-24T15:49:21.991Z" },
-]
 
 [[package]]
 name = "langchain-protocol"
-version = "0.0.12"
+version = "0.0.14"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/5c/51/1157009b6f94e6e58be58fa8b620187d657909a8b36a6bf5b0c52a2711f6/langchain_protocol-0.0.12.tar.gz", hash = "sha256:5e14c434290a705c9510fdb1a83ecf7561a5e6e0dfd053930ade80dba069269f", size = 6408, upload-time = "2026-04-25T01:05:01.489Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/95/82/3431e3061c917439589fa88a6b23c9bc0e154cba0f05d2e895a68c76ff74/langchain_protocol-0.0.12-py3-none-any.whl", hash = "sha256:402b61f42d4139692528cf37226c367bb6efc8ff8165b29380accb0abfece7b2", size = 6639, upload-time = "2026-04-25T01:05:00.487Z" },
+    { url = "https://files.pythonhosted.org/packages/c2/e9/06c47ecb2aff08f83dfa30058da3bf86be64862c19569043ed5331bbeecd/langchain_protocol-0.0.14-py3-none-any.whl", hash = "sha256:ffc35089779bd8ca217015180cef5e660fc3b074efdaa0f2e95df73583f1a047", size = 6984, upload-time = "2026-04-29T16:40:17.841Z" },
 ]
 
 [[package]]
 name = "langgraph"
-version = "1.2.0a1"
+version = "1.1.10"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -294,7 +290,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.2,<2" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "." },
     { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -306,7 +302,7 @@ requires-dist = [
 dev = [
     { name = "httpx" },
     { name = "jupyter" },
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -339,7 +335,7 @@ lint = [
 ]
 test = [
     { name = "httpx" },
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
     { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -365,7 +361,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -374,7 +370,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.2.38" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "ormsgpack", specifier = ">=1.12.0" },
 ]
 
@@ -413,7 +409,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.1.0a1"
+version = "3.0.5"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -548,14 +544,14 @@ test = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.1" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]
 
 [package.metadata.requires-dev]
 dev = [
     { name = "codespell" },
-    { name = "langchain-core" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph", editable = "../langgraph" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
@@ -575,7 +571,7 @@ lint = [
     { name = "ruff" },
 ]
 test = [
-    { name = "langchain-core" },
+    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
     { name = "langgraph", editable = "../langgraph" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },

libs/sdk-py/pyproject.toml

@@ -18,7 +18,7 @@ path = "langgraph_sdk/__init__.py"
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-py"
-Twitter = "https://x.com/langchain_oss"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/sdk-py/uv.lock

@@ -298,7 +298,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "1.2.0a1"
+version = "1.1.10"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -382,7 +382,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.1.0a1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },