refactor(delta-channel): infer typ from Annotated outer type instead of constructor arg

Remove the positional `typ` parameter from `DeltaChannel.__init__`. The type is
now injected automatically from the `Annotated` outer type in `_is_field_channel`
(matching how `BinaryOperatorAggregate` receives its type). `copy()` and
`from_checkpoint()` propagate `self.typ` explicitly. Test helpers updated to
use `_get_channel` with the proper `Annotated` path.

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

@@ -4,7 +4,7 @@ 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 (
@@ -442,22 +442,14 @@ class PostgresSaver(BasePostgresSaver):
             including its configuration, metadata, parent checkpoint (if any),
             and pending writes.
         """
-        from langgraph.checkpoint.base import DeltaChannelSentinel
-
-        channel_values = self._load_blobs(value["channel_values"])
-        if any(isinstance(v, DeltaChannelSentinel) for v in channel_values.values()):
-            cp_config = cast(
-                RunnableConfig,
-                {
-                    "configurable": {
-                        "thread_id": value["thread_id"],
-                        "checkpoint_ns": value["checkpoint_ns"],
-                        "checkpoint_id": value["checkpoint_id"],
-                    }
-                },
+        with self._cursor() as cur:
+            channel_values = self._load_blobs(
+                value["channel_values"],
+                thread_id=value["thread_id"],
+                checkpoint_ns=value["checkpoint_ns"],
+                checkpoint_id=value["checkpoint_id"],
+                cur=cur,
             )
-            with self._cursor() as cur:
-                self._resolve_delta_channels(cp_config, channel_values, cur)
         return CheckpointTuple(
             {
                 "configurable": {

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

@@ -13,7 +13,8 @@ from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
-    DeltaChannelSentinel,
+    DeltaChainValue,
+    DeltaValue,
     get_checkpoint_id,
     get_serializable_checkpoint_metadata,
 )
@@ -392,57 +393,80 @@ class AsyncPostgresSaver(BasePostgresSaver):
                 async with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
-    async def _aget_channel_writes_cur(
+    async def _aload_delta_chain(
         self,
         thread_id: str,
         checkpoint_ns: str,
         checkpoint_id: str,
         channel: str,
         cur: Any,
-    ) -> list[Any]:
-        """Async version of _get_channel_writes_cur — see sync version for rationale."""
+    ) -> DeltaChainValue:
+        """Fetch the full delta chain for a channel in one recursive CTE query (async)."""
         await cur.execute(
-            "SELECT checkpoint_id, parent_checkpoint_id FROM checkpoints "
-            "WHERE thread_id = %s AND checkpoint_ns = %s",
-            (thread_id, checkpoint_ns),
-        )
-        parent_map: dict[str, str | None] = {
-            row["checkpoint_id"]: row["parent_checkpoint_id"]
-            for row in await cur.fetchall()
-        }
-        ancestor_ids: list[str] = []
-        cid: str | None = parent_map.get(checkpoint_id)
-        while cid is not None:
-            ancestor_ids.append(cid)
-            cid = parent_map.get(cid)
-        if not ancestor_ids:
-            return []
-        await cur.execute(
-            "SELECT checkpoint_id, type, blob FROM checkpoint_writes "
-            "WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s "
-            "  AND checkpoint_id = ANY(%s) "
-            "ORDER BY task_id, idx",
-            (thread_id, checkpoint_ns, channel, ancestor_ids),
-        )
-        writes_by_cp: dict[str, list[tuple[str, bytes]]] = defaultdict(list)
-        for row in await cur.fetchall():
-            writes_by_cp[row["checkpoint_id"]].append((row["type"], row["blob"]))
-        result = []
-        for cid in reversed(ancestor_ids):
-            for type_tag, blob in writes_by_cp.get(cid, []):
-                result.append(self.serde.loads_typed((type_tag, blob)))
-        return result
+            """
+            WITH RECURSIVE chain AS (
+                SELECT
+                    c.checkpoint_id,
+                    c.parent_checkpoint_id,
+                    cb.version,
+                    cb.type,
+                    cb.blob
+                FROM checkpoints c
+                JOIN checkpoint_blobs cb
+                    ON  cb.thread_id     = %s
+                    AND cb.checkpoint_ns = %s
+                    AND cb.channel       = %s
+                    AND cb.version       = (c.checkpoint->'channel_versions'->>%s)::text
+                WHERE c.thread_id     = %s
+                  AND c.checkpoint_ns = %s
+                  AND c.checkpoint_id = %s
 
-    async def aget_channel_writes(
-        self, config: RunnableConfig, channel: str
-    ) -> list[Any]:
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
-        checkpoint_id = config["configurable"]["checkpoint_id"]
-        async with self._cursor() as cur:
-            return await self._aget_channel_writes_cur(
-                thread_id, checkpoint_ns, checkpoint_id, channel, cur
+                UNION ALL
+
+                SELECT
+                    c.checkpoint_id,
+                    c.parent_checkpoint_id,
+                    cb.version,
+                    cb.type,
+                    cb.blob
+                FROM chain prev
+                JOIN checkpoints c ON c.checkpoint_id = prev.parent_checkpoint_id
+                JOIN checkpoint_blobs cb
+                    ON  cb.thread_id     = %s
+                    AND cb.checkpoint_ns = %s
+                    AND cb.channel       = %s
+                    AND cb.version       = (c.checkpoint->'channel_versions'->>%s)::text
+                WHERE prev.parent_checkpoint_id IS NOT NULL
+                  AND prev.type = 'delta'
             )
+            SELECT DISTINCT ON (version) type, blob
+            FROM chain
+            ORDER BY version ASC
+            """,
+            (
+                thread_id,
+                checkpoint_ns,
+                channel,
+                channel,
+                thread_id,
+                checkpoint_ns,
+                checkpoint_id,
+                thread_id,
+                checkpoint_ns,
+                channel,
+                channel,
+            ),
+        )
+        rows = await cur.fetchall()
+        base = None
+        deltas: list[list[Any]] = []
+        for row in rows:
+            blob = self.serde.loads_typed((row["type"], row["blob"]))
+            if isinstance(blob, DeltaValue):
+                deltas.append(blob.delta)
+            else:
+                base = blob
+        return DeltaChainValue(base=base, deltas=deltas)
 
     async def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
@@ -465,14 +489,12 @@ class AsyncPostgresSaver(BasePostgresSaver):
         if blob_values:
             channel_values = self._load_blobs(blob_values)
             delta_channels = [
-                ch
-                for ch, v in channel_values.items()
-                if isinstance(v, DeltaChannelSentinel)
+                k.decode() for k, t, _ in blob_values if t.decode() == "delta"
             ]
             if delta_channels:
                 async with self._cursor() as cur:
                     for channel in delta_channels:
-                        channel_values[channel] = await self._aget_channel_writes_cur(
+                        channel_values[channel] = await self._aload_delta_chain(
                             thread_id, checkpoint_ns, checkpoint_id, channel, cur
                         )
 

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

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 import random
 import warnings
-from collections import defaultdict
 from collections.abc import Sequence
 from importlib.metadata import version as get_version
 from typing import Any, cast
@@ -12,7 +11,8 @@ from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
     ChannelVersions,
-    DeltaChannelSentinel,
+    DeltaChainValue,
+    DeltaValue,
     get_checkpoint_id,
 )
 from langgraph.checkpoint.serde.types import TASKS
@@ -188,77 +188,105 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
 
     def _load_blobs(
         self,
-        blob_values: Any,
+        blob_values: list[tuple[bytes, bytes, bytes]],
+        *,
+        thread_id: str = "",
+        checkpoint_ns: str = "",
+        checkpoint_id: str = "",
+        cur: Any = None,
     ) -> dict[str, Any]:
         if not blob_values:
             return {}
         result: dict[str, Any] = {}
+        delta_channels: list[str] = []
         for k, t, v in blob_values:
+            channel = k.decode()
             type_tag = t.decode()
-            if type_tag != "empty":
-                result[k.decode()] = self.serde.loads_typed((type_tag, v))
+            if type_tag == "delta":
+                delta_channels.append(channel)
+            elif type_tag != "empty":
+                result[channel] = self.serde.loads_typed((type_tag, v))
+        if delta_channels and cur is not None and checkpoint_id:
+            for channel in delta_channels:
+                result[channel] = self._load_delta_chain(
+                    thread_id, checkpoint_ns, checkpoint_id, channel, cur
+                )
         return result
 
-    def _resolve_delta_channels(
-        self,
-        config: RunnableConfig,
-        channel_values: dict[str, Any],
-        cur: Any,
-    ) -> None:
-        for channel, value in list(channel_values.items()):
-            if isinstance(value, DeltaChannelSentinel):
-                channel_values[channel] = self._get_channel_writes_cur(
-                    config["configurable"]["thread_id"],
-                    config["configurable"].get("checkpoint_ns", ""),
-                    config["configurable"]["checkpoint_id"],
-                    channel,
-                    cur,
-                )
-
-    def _get_channel_writes_cur(
+    def _load_delta_chain(
         self,
         thread_id: str,
         checkpoint_ns: str,
         checkpoint_id: str,
         channel: str,
         cur: Any,
-    ) -> list[Any]:
-        """Fetch writes for `channel` across the checkpoint ancestor chain, oldest→newest.
+    ) -> DeltaChainValue:
+        """Fetch the full delta chain for a channel in one recursive CTE query."""
+        cur.execute(
+            """
+            WITH RECURSIVE chain AS (
+                SELECT
+                    c.checkpoint_id,
+                    c.parent_checkpoint_id,
+                    cb.version,
+                    cb.type,
+                    cb.blob
+                FROM checkpoints c
+                JOIN checkpoint_blobs cb
+                    ON  cb.thread_id     = %s
+                    AND cb.checkpoint_ns = %s
+                    AND cb.channel       = %s
+                    AND cb.version       = (c.checkpoint->'channel_versions'->>%s)::text
+                WHERE c.thread_id     = %s
+                  AND c.checkpoint_ns = %s
+                  AND c.checkpoint_id = %s
 
-        Two queries:
-        1. Fetch all (checkpoint_id, parent_checkpoint_id) for the thread — cheap, IDs only.
-        2. Walk the ancestor chain in Python, then fetch writes with a plain ANY() filter.
-        """
-        cur.execute(
-            "SELECT checkpoint_id, parent_checkpoint_id FROM checkpoints "
-            "WHERE thread_id = %s AND checkpoint_ns = %s",
-            (thread_id, checkpoint_ns),
+                UNION ALL
+
+                SELECT
+                    c.checkpoint_id,
+                    c.parent_checkpoint_id,
+                    cb.version,
+                    cb.type,
+                    cb.blob
+                FROM chain prev
+                JOIN checkpoints c ON c.checkpoint_id = prev.parent_checkpoint_id
+                JOIN checkpoint_blobs cb
+                    ON  cb.thread_id     = %s
+                    AND cb.checkpoint_ns = %s
+                    AND cb.channel       = %s
+                    AND cb.version       = (c.checkpoint->'channel_versions'->>%s)::text
+                WHERE prev.parent_checkpoint_id IS NOT NULL
+                  AND prev.type = 'delta'
+            )
+            SELECT DISTINCT ON (version) type, blob
+            FROM chain
+            ORDER BY version ASC
+            """,
+            (
+                thread_id,
+                checkpoint_ns,
+                channel,
+                channel,
+                thread_id,
+                checkpoint_ns,
+                checkpoint_id,
+                thread_id,
+                checkpoint_ns,
+                channel,
+                channel,
+            ),
         )
-        parent_map: dict[str, str | None] = {
-            row["checkpoint_id"]: row["parent_checkpoint_id"] for row in cur.fetchall()
-        }
-        ancestor_ids: list[str] = []
-        cid: str | None = parent_map.get(checkpoint_id)
-        while cid is not None:
-            ancestor_ids.append(cid)
-            cid = parent_map.get(cid)
-        if not ancestor_ids:
-            return []
-        cur.execute(
-            "SELECT checkpoint_id, type, blob FROM checkpoint_writes "
-            "WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s "
-            "  AND checkpoint_id = ANY(%s) "
-            "ORDER BY task_id, idx",
-            (thread_id, checkpoint_ns, channel, ancestor_ids),
-        )
-        writes_by_cp: dict[str, list[tuple[str, bytes]]] = defaultdict(list)
-        for row in cur.fetchall():
-            writes_by_cp[row["checkpoint_id"]].append((row["type"], row["blob"]))
-        result = []
-        for cid in reversed(ancestor_ids):
-            for type_tag, blob in writes_by_cp.get(cid, []):
-                result.append(self.serde.loads_typed((type_tag, blob)))
-        return result
+        rows = cur.fetchall()
+        base = None
+        deltas: list[list[Any]] = []
+        for row in rows:
+            blob = self.serde.loads_typed((row["type"], row["blob"]))
+            if isinstance(blob, DeltaValue):
+                deltas.append(blob.delta)
+            else:
+                base = blob
+        return DeltaChainValue(base=base, deltas=deltas)
 
     def _dump_blobs(
         self,

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

@@ -3,12 +3,10 @@ from __future__ import annotations
 import copy
 import dataclasses
 import logging
-import threading
 from collections.abc import AsyncIterator, Collection, Iterator, Mapping, Sequence
 from typing import (  # noqa: UP035
     Any,
     Generic,
-    List,
     Literal,
     NamedTuple,
     TypedDict,
@@ -34,17 +32,19 @@ PendingWrite = tuple[str, str, Any]
 
 
 @dataclasses.dataclass
-class DeltaChannelSentinel:
-    """Marker stored in checkpoint_blobs for a DeltaChannel field.
+class DeltaValue:
+    """Returned by DeltaChannel.checkpoint(). Represents one step's writes."""
 
-    No data is stored here — the actual per-step writes live in checkpoint_writes
-    and are replayed through the reducer at load time.
-    """
-
-    pass
+    delta: list[Any]
 
 
-_DELTA_RECONSTRUCTION: threading.local = threading.local()
+@dataclasses.dataclass
+class DeltaChainValue:
+    """Passed to DeltaChannel.from_checkpoint(). Assembled by the pregel layer."""
+
+    base: list[Any] | None  # starting accumulated value; None = start from empty
+    deltas: list[list[Any]]  # per-step write-sets, ordered oldest → newest
+
 
 logger = logging.getLogger(__name__)
 
@@ -475,56 +475,6 @@ class BaseCheckpointSaver(Generic[V]):
         """
         raise NotImplementedError
 
-    def get_channel_writes(self, config: RunnableConfig, channel: str) -> List[Any]:  # noqa: UP006
-        """Collect all writes for `channel` across this checkpoint's ancestry, oldest→newest.
-
-        Default implementation walks the full thread history via `list()`. Savers can
-        override with a more efficient query (InMemorySaver and PostgresSaver do this).
-        """
-        # Guard against re-entrant calls: when list() triggers reconstruction which
-        # calls list() again, the inner call returns tuples with DeltaChannelSentinel
-        # in channel_values (which get_channel_writes ignores — it only reads
-        # pending_writes). This breaks the recursion safely.
-        if getattr(_DELTA_RECONSTRUCTION, "active", False):
-            return []
-        _DELTA_RECONSTRUCTION.active = True
-        try:
-            result: list[Any] = []
-            target_id = config["configurable"].get("checkpoint_id")
-            for tup in self.list(config):
-                if tup.config["configurable"].get("checkpoint_id") == target_id:
-                    continue  # skip the checkpoint itself; we want its ancestors' writes
-                if tup.pending_writes:
-                    for _, ch, value in tup.pending_writes:
-                        if ch == channel:
-                            result.append(value)
-            result.reverse()  # list() yields newest→oldest; we want oldest→newest
-            return result
-        finally:
-            _DELTA_RECONSTRUCTION.active = False
-
-    async def aget_channel_writes(
-        self, config: RunnableConfig, channel: str
-    ) -> List[Any]:  # noqa: UP006
-        """Async version of get_channel_writes."""
-        if getattr(_DELTA_RECONSTRUCTION, "active", False):
-            return []
-        _DELTA_RECONSTRUCTION.active = True
-        try:
-            result: list[Any] = []
-            target_id = config["configurable"].get("checkpoint_id")
-            async for tup in self.alist(config):
-                if tup.config["configurable"].get("checkpoint_id") == target_id:
-                    continue
-                if tup.pending_writes:
-                    for _, ch, value in tup.pending_writes:
-                        if ch == channel:
-                            result.append(value)
-            result.reverse()
-            return result
-        finally:
-            _DELTA_RECONSTRUCTION.active = False
-
     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

@@ -9,7 +9,7 @@ from collections import defaultdict
 from collections.abc import AsyncIterator, Iterator, Sequence
 from contextlib import AbstractAsyncContextManager, AbstractContextManager, ExitStack
 from types import TracebackType
-from typing import Any, cast
+from typing import Any
 
 from langchain_core.runnables import RunnableConfig
 
@@ -20,7 +20,8 @@ from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
-    DeltaChannelSentinel,
+    DeltaChainValue,
+    DeltaValue,
     SerializerProtocol,
     get_checkpoint_id,
     get_checkpoint_metadata,
@@ -126,56 +127,68 @@ class InMemorySaver(
         thread_id: str,
         checkpoint_ns: str,
         versions: ChannelVersions,
+        checkpoint_id: str = "",
     ) -> dict[str, Any]:
-        result: dict[str, Any] = {}
-        for k, ver in versions.items():
-            kk = (thread_id, checkpoint_ns, k, ver)
+        channel_values: dict[str, Any] = {}
+        delta_channels: list[str] = []
+        for k, v in versions.items():
+            kk = (thread_id, checkpoint_ns, k, v)
             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
+            if vv[0] == "delta":
+                delta_channels.append(k)
+            elif vv[0] != "empty":
+                channel_values[k] = self.serde.loads_typed(vv)
+        for channel in delta_channels:
+            channel_values[channel] = self._assemble_delta_chain(
+                thread_id, checkpoint_ns, checkpoint_id, channel
+            )
+        return channel_values
 
-    def _resolve_delta_channels(
+    def _assemble_delta_chain(
         self,
-        config: RunnableConfig,
-        channel_values: dict[str, Any],
-    ) -> None:
-        """Replace DeltaChannelSentinel entries with reconstructed write lists."""
-        for channel, value in list(channel_values.items()):
-            if isinstance(value, DeltaChannelSentinel):
-                channel_values[channel] = self.get_channel_writes(config, channel)
-
-    def get_channel_writes(self, config: RunnableConfig, channel: str) -> list[Any]:
-        thread_id = config["configurable"]["thread_id"]
-        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
-        checkpoint_id = config["configurable"].get("checkpoint_id", "")
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> DeltaChainValue:
+        """Walk the checkpoint parent tree to collect all delta blobs for a channel."""
         ns_storage = self.storage.get(thread_id, {}).get(checkpoint_ns, {})
-        # Walk the parent chain newest→oldest collecting checkpoint IDs.
-        chain: list[str] = []
-        current: str | None = checkpoint_id
-        while current is not None:
-            entry = ns_storage.get(current)
+        blobs: list[Any] = []
+        current_id: str | None = checkpoint_id
+        seen_versions: set[str] = set()
+        while current_id is not None:
+            entry = ns_storage.get(current_id)
             if entry is None:
                 break
-            chain.append(current)
-            _, _, parent = entry
-            current = parent
-        # Collect writes oldest→newest.
-        result: list[Any] = []
-        for cp_id in reversed(chain):
-            step_writes = self.writes.get((thread_id, checkpoint_ns, cp_id), {})
-            for (_task_id, _idx), (_, ch, serialized, _) in sorted(step_writes.items()):
-                if ch == channel:
-                    result.append(self.serde.loads_typed(serialized))
-        return result
-
-    async def aget_channel_writes(
-        self, config: RunnableConfig, channel: str
-    ) -> list[Any]:
-        return self.get_channel_writes(config, channel)
+            checkpoint = self.serde.loads_typed(entry[0])
+            version = checkpoint["channel_versions"].get(channel)
+            if version is None:
+                break  # channel not yet in this checkpoint
+            _, _, current_id = entry  # advance to parent before the continue/break
+            if version in seen_versions:
+                continue  # same blob already collected; keep walking to older checkpoints
+            seen_versions.add(version)
+            kk = (thread_id, checkpoint_ns, channel, version)
+            if kk not in self.blobs:
+                break
+            vv = self.blobs[kk]
+            if vv[0] == "empty":
+                break
+            blob = self.serde.loads_typed(vv)
+            blobs.append(blob)
+            if not isinstance(blob, DeltaValue):
+                break  # hit a snapshot (plain list) — chain root found
+        blobs.reverse()
+        base = None
+        deltas: list[list[Any]] = []
+        for blob in blobs:
+            if isinstance(blob, DeltaValue):
+                deltas.append(blob.delta)
+            else:
+                base = blob
+        return DeltaChainValue(base=base, deltas=deltas)
 
     def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
         """Get a checkpoint tuple from the in-memory storage.
@@ -198,17 +211,16 @@ class InMemorySaver(
                 checkpoint, metadata, parent_checkpoint_id = saved
                 writes = self.writes[(thread_id, checkpoint_ns, checkpoint_id)].values()
                 checkpoint_: Checkpoint = self.serde.loads_typed(checkpoint)
-                channel_values = self._load_blobs(
-                    thread_id,
-                    checkpoint_ns,
-                    checkpoint_["channel_versions"],
-                )
-                self._resolve_delta_channels(config, channel_values)
                 return CheckpointTuple(
                     config=config,
                     checkpoint={
                         **checkpoint_,
-                        "channel_values": channel_values,
+                        "channel_values": self._load_blobs(
+                            thread_id,
+                            checkpoint_ns,
+                            checkpoint_["channel_versions"],
+                            checkpoint_id,
+                        ),
                     },
                     metadata=self.serde.loads_typed(metadata),
                     pending_writes=[
@@ -232,27 +244,22 @@ class InMemorySaver(
                 checkpoint, metadata, parent_checkpoint_id = checkpoints[checkpoint_id]
                 writes = self.writes[(thread_id, checkpoint_ns, checkpoint_id)].values()
                 checkpoint_ = self.serde.loads_typed(checkpoint)
-                resolved_config = cast(
-                    RunnableConfig,
-                    {
+                return CheckpointTuple(
+                    config={
                         "configurable": {
                             "thread_id": thread_id,
                             "checkpoint_ns": checkpoint_ns,
                             "checkpoint_id": checkpoint_id,
                         }
                     },
-                )
-                channel_values = self._load_blobs(
-                    thread_id,
-                    checkpoint_ns,
-                    checkpoint_["channel_versions"],
-                )
-                self._resolve_delta_channels(resolved_config, channel_values)
-                return CheckpointTuple(
-                    config=resolved_config,
                     checkpoint={
                         **checkpoint_,
-                        "channel_values": channel_values,
+                        "channel_values": self._load_blobs(
+                            thread_id,
+                            checkpoint_ns,
+                            checkpoint_["channel_versions"],
+                            checkpoint_id,
+                        ),
                     },
                     metadata=self.serde.loads_typed(metadata),
                     pending_writes=[
@@ -347,28 +354,22 @@ class InMemorySaver(
 
                     checkpoint_: Checkpoint = self.serde.loads_typed(checkpoint)
 
-                    list_config = cast(
-                        RunnableConfig,
-                        {
+                    yield CheckpointTuple(
+                        config={
                             "configurable": {
                                 "thread_id": thread_id,
                                 "checkpoint_ns": checkpoint_ns,
                                 "checkpoint_id": checkpoint_id,
                             }
                         },
-                    )
-                    channel_values = self._load_blobs(
-                        thread_id,
-                        checkpoint_ns,
-                        checkpoint_["channel_versions"],
-                    )
-                    self._resolve_delta_channels(list_config, channel_values)
-
-                    yield CheckpointTuple(
-                        config=list_config,
                         checkpoint={
                             **checkpoint_,
-                            "channel_values": channel_values,
+                            "channel_values": self._load_blobs(
+                                thread_id,
+                                checkpoint_ns,
+                                checkpoint_["channel_versions"],
+                                checkpoint_id,
+                            ),
                         },
                         metadata=metadata,
                         parent_config=(

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

@@ -80,6 +80,8 @@ SAFE_MSGPACK_TYPES: frozenset[tuple[str, ...]] = frozenset(
         ("langgraph.types", "Overwrite"),
         ("langgraph.store.base", "Item"),
         ("langgraph.store.base", "GetOp"),
+        # DeltaChannel checkpoint value type
+        ("langgraph.checkpoint.base", "DeltaValue"),
     }
 )
 

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

@@ -46,30 +46,11 @@ LC_REVIVER = Reviver()
 EMPTY_BYTES = b""
 logger = logging.getLogger(__name__)
 
-# Dedup log warnings across process lifetime; cap bounds state if types are
-# dynamically generated (also acts as a circuit breaker on warning volume).
-# Dedup is best-effort: racing threads may each emit once for the same key,
-# and warnings are silently dropped once _MAX_WARNED_TYPES is reached.
-_MAX_WARNED_TYPES = 1000
-_warned_unregistered_types: set[tuple[str, str]] = set()
-_warned_blocked_types: set[tuple[str, str]] = set()
 
+def _is_delta_value(obj: Any) -> bool:
+    from langgraph.checkpoint.base import DeltaValue  # lazy import avoids circular dep
 
-def _warn_once(
-    seen: set[tuple[str, str]], key: tuple[str, str], msg: str, *args: object
-) -> None:
-    if key in seen or len(seen) >= _MAX_WARNED_TYPES:
-        return
-    seen.add(key)
-    logger.warning(msg, *args)
-
-
-def _get_delta_sentinel_cls() -> type:
-    from langgraph.checkpoint.base import (
-        DeltaChannelSentinel,
-    )  # lazy import avoids circular dep
-
-    return DeltaChannelSentinel
+    return isinstance(obj, DeltaValue)
 
 
 class JsonPlusSerializer(SerializerProtocol):
@@ -264,8 +245,8 @@ class JsonPlusSerializer(SerializerProtocol):
             return "bytes", obj
         elif isinstance(obj, bytearray):
             return "bytearray", obj
-        elif isinstance(obj, _get_delta_sentinel_cls()):
-            return "delta", b""
+        elif _is_delta_value(obj):
+            return "delta", _msgpack_enc({"d": obj.delta})
         else:
             try:
                 return "msgpack", _msgpack_enc(obj)
@@ -289,9 +270,12 @@ class JsonPlusSerializer(SerializerProtocol):
                 data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
             )
         elif type_ == "delta":
-            from langgraph.checkpoint.base import DeltaChannelSentinel
+            from langgraph.checkpoint.base import DeltaValue  # lazy import
 
-            return DeltaChannelSentinel()
+            raw = ormsgpack.unpackb(
+                data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
+            )
+            return DeltaValue(delta=raw["d"])
         elif self.pickle_fallback and type_ == "pickle":
             return pickle.loads(data_)
         else:
@@ -565,9 +549,7 @@ def _create_msgpack_ext_hook(
                     "name": name,
                 }
             )
-            _warn_once(
-                _warned_unregistered_types,
-                key,
+            logger.warning(
                 "Deserializing unregistered type %s.%s from checkpoint. "
                 "This will be blocked in a future version. "
                 "Set LANGGRAPH_STRICT_MSGPACK=true to block now, or add "
@@ -589,9 +571,7 @@ def _create_msgpack_ext_hook(
                 "name": name,
             }
         )
-        _warn_once(
-            _warned_blocked_types,
-            key,
+        logger.warning(
             "Blocked deserialization of %s.%s - not in allowed_msgpack_modules. "
             "Add to allowed_msgpack_modules to allow: [(%r, %r)]",
             module,

libs/checkpoint/tests/test_encrypted.py

@@ -29,8 +29,6 @@ from langgraph.checkpoint.serde.jsonplus import (
     EXT_METHOD_SINGLE_ARG,
     JsonPlusSerializer,
     _msgpack_enc,
-    _warned_blocked_types,
-    _warned_unregistered_types,
 )
 
 
@@ -104,13 +102,6 @@ def test_msgpack_method_pathlib_blocked_encrypted_strict(
 class TestEncryptedSerializerMsgpackAllowlist:
     """Test msgpack allowlist behavior through EncryptedSerializer."""
 
-    @pytest.fixture(autouse=True)
-    def _reset_warned_types(self) -> None:
-        # Warning dedup state is process-global; reset per-test so each case
-        # sees a fresh slate and assertions about warning emission are stable.
-        _warned_unregistered_types.clear()
-        _warned_blocked_types.clear()
-
     def test_safe_types_no_warning(self, caplog: pytest.LogCaptureFixture) -> None:
         """Test safe types deserialize without warnings through encryption."""
         serde = _make_encrypted_serde()

libs/checkpoint/tests/test_jsonplus.py

@@ -35,8 +35,6 @@ from langgraph.checkpoint.serde.jsonplus import (
     JsonPlusSerializer,
     _msgpack_enc,
     _msgpack_ext_hook_to_json,
-    _warned_blocked_types,
-    _warned_unregistered_types,
 )
 from langgraph.store.base import Item
 
@@ -582,14 +580,6 @@ def test_msgpack_safe_types_no_warning(caplog: pytest.LogCaptureFixture) -> None
         assert result is not None
 
 
-@pytest.fixture(autouse=True)
-def _reset_warned_types() -> None:
-    # Warning dedup state is process-global; reset per-test so each case sees
-    # a fresh slate and assertions about warning emission are stable.
-    _warned_unregistered_types.clear()
-    _warned_blocked_types.clear()
-
-
 def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) -> None:
     """Pydantic models not in allowlist should log warning but still deserialize."""
     current = _lg_msgpack.STRICT_MSGPACK_ENABLED
@@ -605,12 +595,6 @@ def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) ->
     assert "unregistered type" in caplog.text.lower()
     assert "allowed_msgpack_modules" in caplog.text
     assert result == obj
-
-    # Second deserialization of the same type should NOT produce another warning
-    caplog.clear()
-    result2 = serde.loads_typed(dumped)
-    assert "unregistered type" not in caplog.text.lower()
-    assert result2 == obj
     _lg_msgpack.STRICT_MSGPACK_ENABLED = current
 
 
@@ -655,6 +639,7 @@ def test_msgpack_allowlist_silences_warning(caplog: pytest.LogCaptureFixture) ->
 
 def test_msgpack_none_blocks_unregistered(caplog: pytest.LogCaptureFixture) -> None:
     """allowed_msgpack_modules=None should block unregistered types."""
+
     serde = JsonPlusSerializer(allowed_msgpack_modules=None)
 
     obj = MyPydantic(foo="test", bar=42, inner=InnerPydantic(hello="world"))
@@ -672,6 +657,7 @@ def test_msgpack_allowlist_blocks_non_listed(
     caplog: pytest.LogCaptureFixture,
 ) -> None:
     """Allowlists should block unregistered types even if msgpack is enabled."""
+
     serde = JsonPlusSerializer(
         allowed_msgpack_modules=[("tests.test_jsonplus", "MyPydantic")]
     )
@@ -999,13 +985,14 @@ def test_msgpack_nested_pydantic_serializes_as_dict(
     assert result == obj
 
 
-def test_delta_channel_sentinel_serde_round_trip() -> None:
-    from langgraph.checkpoint.base import DeltaChannelSentinel
+def test_delta_value_serde_round_trip() -> None:
+    from langgraph.checkpoint.base import DeltaValue
     from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
 
     serde = JsonPlusSerializer()
-    original = DeltaChannelSentinel()
+    original = DeltaValue(delta=[{"type": "human", "content": "hi"}])
     type_tag, blob = serde.dumps_typed(original)
     assert type_tag == "delta"
     loaded = serde.loads_typed((type_tag, blob))
-    assert isinstance(loaded, DeltaChannelSentinel)
+    assert isinstance(loaded, DeltaValue)
+    assert loaded.delta == original.delta

libs/checkpoint/tests/test_memory.py

@@ -12,25 +12,13 @@ from langgraph.checkpoint.base import (
     empty_checkpoint,
 )
 from langgraph.checkpoint.memory import InMemorySaver
-from langgraph.checkpoint.serde.jsonplus import (
-    JsonPlusSerializer,
-    _warned_blocked_types,
-    _warned_unregistered_types,
-)
+from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
 
 
 class MemoryPydantic(BaseModel):
     foo: str
 
 
-@pytest.fixture(autouse=True)
-def _reset_warned_types() -> None:
-    # Warning dedup state is process-global; reset per-test so each case sees
-    # a fresh slate and assertions about warning emission are stable.
-    _warned_unregistered_types.clear()
-    _warned_blocked_types.clear()
-
-
 class TestMemorySaver:
     @pytest.fixture(autouse=True)
     def setup(self) -> None:
@@ -323,10 +311,11 @@ def test_memory_saver_with_allowlist_proxy_isolated() -> None:
 
 
 class TestInMemorySaverDeltaChannel:
-    def test_load_blobs_returns_sentinel_for_delta_channel(self) -> None:
-        """_load_blobs returns DeltaChannelSentinel for delta channels (reconstruction deferred)."""
+    def test_load_blobs_assembles_delta_chain(self) -> None:
+        """_load_blobs returns DeltaChainValue for delta channels, not raw DeltaValue."""
         from langgraph.checkpoint.base import (
-            DeltaChannelSentinel,
+            DeltaChainValue,
+            DeltaValue,
             empty_checkpoint,
         )
 
@@ -335,59 +324,55 @@ class TestInMemorySaverDeltaChannel:
 
         thread_id, ns, channel = "t1", "", "messages"
         v1 = "00000000000000000000000000000001.0000000000000000"
+        v2 = "00000000000000000000000000000002.0000000000000000"
 
-        sentinel = DeltaChannelSentinel()
-        saver.blobs[(thread_id, ns, channel, v1)] = serde.dumps_typed(sentinel)
+        delta1 = DeltaValue(delta=[{"content": "hi"}])
+        delta2 = DeltaValue(delta=[{"content": "bye"}])
+        saver.blobs[(thread_id, ns, channel, v1)] = serde.dumps_typed(delta1)
+        saver.blobs[(thread_id, ns, channel, v2)] = serde.dumps_typed(delta2)
 
         cp1 = empty_checkpoint()
         cp1["id"] = "cp1"
         cp1["channel_versions"][channel] = v1
+        cp2 = empty_checkpoint()
+        cp2["id"] = "cp2"
+        cp2["channel_versions"][channel] = v2
         saver.storage[thread_id][ns] = {
             "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
+            "cp2": (serde.dumps_typed(cp2), serde.dumps_typed({}), "cp1"),
         }
 
-        result = saver._load_blobs(thread_id, ns, {channel: v1})
+        result = saver._load_blobs(thread_id, ns, {channel: v2}, "cp2")
         assert channel in result
-        assert isinstance(result[channel], DeltaChannelSentinel)
+        chain = result[channel]
+        assert isinstance(chain, DeltaChainValue)
+        assert chain.deltas == [[{"content": "hi"}], [{"content": "bye"}]]
 
-    def test_get_channel_writes_collects_writes(self) -> None:
-        """get_channel_writes collects per-step writes oldest→newest."""
-        from langgraph.checkpoint.base import empty_checkpoint
+    def test_load_blobs_single_delta_no_parent(self) -> None:
+        """Single delta with no parent checkpoint produces a chain with one delta."""
+        from langgraph.checkpoint.base import (
+            DeltaChainValue,
+            DeltaValue,
+            empty_checkpoint,
+        )
 
         saver = InMemorySaver()
         serde = JsonPlusSerializer()
 
         thread_id, ns, channel = "t1", "", "messages"
+        v1 = "00000000000000000000000000000001.0000000000000000"
+        delta = DeltaValue(delta=[{"content": "only"}])
+        saver.blobs[(thread_id, ns, channel, v1)] = serde.dumps_typed(delta)
 
         cp1 = empty_checkpoint()
         cp1["id"] = "cp1"
-        cp2 = empty_checkpoint()
-        cp2["id"] = "cp2"
+        cp1["channel_versions"][channel] = v1
         saver.storage[thread_id][ns] = {
-            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
-            "cp2": (serde.dumps_typed(cp2), serde.dumps_typed({}), "cp1"),
+            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None)
         }
-        # cp1 has a write for channel
-        saver.writes[(thread_id, ns, "cp1")][("task1", 0)] = (
-            "task1",
-            channel,
-            serde.dumps_typed({"content": "hi"}),
-            "",
-        )
-        # cp2 has a write for channel
-        saver.writes[(thread_id, ns, "cp2")][("task2", 0)] = (
-            "task2",
-            channel,
-            serde.dumps_typed({"content": "bye"}),
-            "",
-        )
 
-        config: RunnableConfig = {
-            "configurable": {
-                "thread_id": thread_id,
-                "checkpoint_ns": ns,
-                "checkpoint_id": "cp2",
-            }
-        }
-        result = saver.get_channel_writes(config, channel)
-        assert result == [{"content": "hi"}, {"content": "bye"}]
+        result = saver._load_blobs(thread_id, ns, {channel: v1}, "cp1")
+        chain = result[channel]
+        assert isinstance(chain, DeltaChainValue)
+        assert chain.base is None
+        assert chain.deltas == [[{"content": "only"}]]

libs/cli/examples/graph_prerelease_reqs/deps/zuper_deps/pyproject.toml

@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.1.14"
+  "langchain-openai==1.0.1"
 ]

libs/cli/examples/graph_prerelease_reqs/pyproject.toml

@@ -5,7 +5,7 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.1.14",
+  "langchain-openai==1.0.0a2",
   "langchain-anthropic==1.0.0a5",
   "langgraph==1.1.5"
 ]

libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml

@@ -5,7 +5,7 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.1.14",
+  "langchain-openai==1.0.0a2",
   "langgraph==1.1.2",
   "langchain_community>=0.3.0",
 ]

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.23"
+__version__ = "0.4.22"

libs/cli/pyproject.toml

@@ -23,7 +23,7 @@ dependencies = [
 path = "langgraph_cli/__init__.py"
 [project.optional-dependencies]
 inmem = [
-    "langgraph-api>=0.5.35,<0.9.0 ; python_version >= '3.11'",
+    "langgraph-api>=0.5.35,<0.8.0 ; python_version >= '3.11'",
     "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
 ]
 

libs/langgraph/langgraph/callbacks.py

@@ -245,6 +245,15 @@ class _GraphCallbackManager(BaseCallbackManager):
             run_id=run_id,
         )
 
+    def add_handler(
+        self,
+        handler: BaseCallbackHandler,
+        inherit: bool = True,  # noqa: FBT001,FBT002
+    ) -> None:
+        if not isinstance(handler, GraphCallbackHandler):
+            raise TypeError("handlers must inherit GraphCallbackHandler")
+        super().add_handler(handler, inherit=inherit)
+
     def copy(
         self,
         *,
@@ -312,6 +321,15 @@ class _AsyncGraphCallbackManager(BaseCallbackManager):
             run_id=run_id,
         )
 
+    def add_handler(
+        self,
+        handler: BaseCallbackHandler,
+        inherit: bool = True,  # noqa: FBT001,FBT002
+    ) -> None:
+        if not isinstance(handler, GraphCallbackHandler):
+            raise TypeError("handlers must inherit GraphCallbackHandler")
+        super().add_handler(handler, inherit=inherit)
+
     def copy(
         self,
         *,

libs/langgraph/langgraph/channels/delta.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 from collections.abc import Callable, Sequence
 from typing import Any, Generic
 
-from langgraph.checkpoint.base import DeltaChannelSentinel
+from langgraph.checkpoint.base import DeltaChainValue, DeltaValue
 from typing_extensions import Self
 
 from langgraph._internal._typing import MISSING
@@ -14,41 +14,64 @@ from langgraph.errors import EmptyChannelError
 __all__ = ("DeltaChannel",)
 
 
-class DeltaChannel(
-    Generic[Value], BaseChannel[list[Value], Value, DeltaChannelSentinel]
-):
-    """A channel that stores only a sentinel in checkpoints; per-step writes are
-    stored in checkpoint_writes and replayed through the operator at load time.
+class DeltaChannel(Generic[Value], BaseChannel[list[Value], Value, DeltaValue]):
+    """A channel that stores only per-step write deltas in checkpoints.
 
-    Use with append-style reducers (e.g. `add_messages`) on long-running threads
-    to eliminate O(N²) blob growth — storage is O(N) using the writes table that
-    every checkpointer already maintains.
+    Reconstructs the full accumulated list at load time by replaying the
+    chain of deltas through the operator. Use with append-style reducers
+    (e.g. `add_messages`) on long-running threads to reduce checkpoint
+    storage from O(N²) to O(N).
 
-    Works with all checkpointers. Savers with dedicated implementations
-    (InMemorySaver, PostgresSaver) reconstruct in one pass; others fall back to
-    walking the checkpoint list.
+    Works with all checkpointers. Savers with a dedicated blob store
+    (InMemorySaver, PostgresSaver) use an O(1) fast-path per chain step;
+    all others (SQLite, MongoDB, etc.) fall back to get_tuple traversal.
+
+    Use `snapshot_every=N` to cap chain traversal depth at N steps. Every N
+    steps a full snapshot is written as the chain root; subsequent deltas
+    chain back to it, so `get_state` / reload never traverses more than N
+    checkpoints regardless of thread length. Recommended for savers without
+    a dedicated blob store.
 
     Usage::
 
         class State(TypedDict):
             messages: Annotated[list[AnyMessage], DeltaChannel(add_messages)]
+            # Cap reconstruction depth (recommended for SQLite / MongoDB savers):
+            messages: Annotated[list[AnyMessage], DeltaChannel(add_messages, snapshot_every=50)]
             # Dict-type reducer (type inferred from the Annotated outer type):
             files: Annotated[dict, DeltaChannel(merge_files)]
     """
 
-    __slots__ = ("value", "operator")
+    __slots__ = (
+        "value",
+        "operator",
+        "snapshot_every",
+        "_pending",
+        "_base_version",
+        "_overwritten",
+        "_steps_since_snapshot",
+    )
 
     def __init__(
         self,
         operator: Callable[[list[Value], Any], list[Value]],
+        *,
+        snapshot_every: int | None = None,
     ) -> None:
         super().__init__(list)
         self.operator = operator
+        self.snapshot_every = snapshot_every
         self.value: list[Value] = []
+        self._pending: list[Any] = []
+        self._base_version: str | None = None
+        self._overwritten: bool = False
+        self._steps_since_snapshot: int = 0
 
     def __eq__(self, other: object) -> bool:
         if not isinstance(other, DeltaChannel):
             return False
+        if self.snapshot_every != other.snapshot_every:
+            return False
         if (
             self.operator.__name__ != "<lambda>"
             and other.operator.__name__ != "<lambda>"
@@ -65,14 +88,18 @@ class DeltaChannel(
         return self.typ | list[self.typ]  # type: ignore[name-defined]
 
     def copy(self) -> Self:
-        new = DeltaChannel(self.operator)
+        new = DeltaChannel(self.operator, snapshot_every=self.snapshot_every)
         new.typ = self.typ
         new.key = self.key
         new.value = self.value if self.value is MISSING else self.value.copy()
+        new._pending = self._pending[:]
+        new._base_version = self._base_version
+        new._overwritten = self._overwritten
+        new._steps_since_snapshot = self._steps_since_snapshot
         return new
 
     def from_checkpoint(self, checkpoint: Any) -> Self:
-        new = DeltaChannel(self.operator)
+        new = DeltaChannel(self.operator, snapshot_every=self.snapshot_every)
         new.typ = self.typ
         new.key = self.key
         if checkpoint is MISSING:
@@ -80,21 +107,29 @@ class DeltaChannel(
                 new.value = new.typ()
             except Exception:
                 new.value = []
-        elif isinstance(checkpoint, list):
-            # Flat list of write values (oldest→newest) from get_channel_writes.
-            try:
-                value: Any = new.typ()
-            except Exception:
-                value = []
-            for write in checkpoint:
-                value = new.operator(value, write)
-            new.value = value
+        elif isinstance(checkpoint, DeltaChainValue):
+            accumulated: list[Value] = (
+                checkpoint.base if checkpoint.base is not None else new.typ()
+            )
+            for step_writes in checkpoint.deltas:
+                for write in step_writes:
+                    accumulated = new.operator(accumulated, write)
+            new.value = accumulated
+            # Seed the counter from actual chain depth so rehydration fires at
+            # the right time regardless of how many prior invocations there were.
+            new._steps_since_snapshot = len(checkpoint.deltas)
+        elif isinstance(checkpoint, DeltaValue):
+            raise ValueError(
+                f"Channel '{self.key}' uses DeltaChannel but the checkpointer "
+                "does not support incremental channel storage. "
+                "Use InMemorySaver or PostgresSaver, or remove DeltaChannel from your schema."
+            )
         else:
-            # Backward compat: plain accumulated value (e.g. from a migrated thread).
-            try:
-                new.value = list(checkpoint)
-            except Exception:
-                new.value = []
+            # Backwards compat: plain list from old BinaryOperatorAggregate checkpoint.
+            new.value = list(checkpoint)
+        new._pending = []
+        new._base_version = None  # set by the subsequent after_checkpoint() call
+        new._overwritten = False
         return new
 
     def update(self, values: Sequence[Any]) -> bool:
@@ -119,10 +154,13 @@ class DeltaChannel(
                 self.value = (
                     list(overwrite_value) if overwrite_value is not None else self.typ()
                 )
+                self._pending = list(self.value)
+                self._overwritten = True
                 seen_overwrite = True
             elif not seen_overwrite:
                 base = self.typ() if self.value is MISSING else self.value
                 self.value = self.operator(base, value)
+                self._pending.append(value)
         return True
 
     def get(self) -> list[Value]:
@@ -133,5 +171,26 @@ class DeltaChannel(
     def is_available(self) -> bool:
         return self.value is not MISSING
 
-    def checkpoint(self) -> DeltaChannelSentinel:
-        return DeltaChannelSentinel()
+    def checkpoint(self) -> Any:
+        if (
+            self.snapshot_every is not None
+            and self._steps_since_snapshot >= self.snapshot_every
+        ):
+            # Emit a full snapshot to cap chain depth at snapshot_every.
+            # The saver stores this as a plain (non-diff) blob, so future
+            # deltas will chain back to it and traversal depth resets to 1.
+            return list(self.value)
+        return DeltaValue(delta=self._pending[:])
+
+    def after_checkpoint(self, version: Any, checkpoint_id: str | None = None) -> None:
+        if version != self._base_version:
+            if self._base_version is None:
+                pass  # First call after from_checkpoint — anchor without counting a step.
+            elif self.snapshot_every is not None:
+                if self._steps_since_snapshot >= self.snapshot_every:
+                    self._steps_since_snapshot = 0
+                else:
+                    self._steps_since_snapshot += 1
+            self._base_version = version
+            self._pending = []
+            self._overwritten = False

libs/langgraph/langgraph/pregel/_loop.py

@@ -831,18 +831,8 @@ class PregelLoop:
             # parent. For forks (source=update/fork), use the fork's parent
             # checkpoint ID since the fork was created after the subgraph's
             # checkpoints from the original execution.
-            #
-            # Only gate on is_time_traveling (not is_replaying). When the
-            # client resumes with an explicit checkpoint_id that happens to
-            # point at the current head (e.g. LangGraph Studio sending
-            # `checkpoint: {checkpoint_id}` alongside Command(resume=...)),
-            # is_replaying is True but is_time_traveling is False. In that
-            # case subgraphs should load their latest checkpoint normally,
-            # not go through ReplayState's before-bound lookup which would
-            # miss subgraph checkpoints created during processing of the
-            # current parent step.
             replay_state: ReplayState | None = None
-            if is_time_traveling:
+            if self.is_replaying:
                 replay_checkpoint_id = self.checkpoint["id"]
                 if (
                     self.checkpoint_metadata.get("source")

libs/langgraph/langgraph/pregel/_messages.py

@@ -14,7 +14,7 @@ from langchain_core.messages import BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
 from pydantic import BaseModel
 
-from langgraph._internal._constants import NS_SEP
+from langgraph._internal._constants import NS_END, NS_SEP
 from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
 from langgraph.pregel.protocol import StreamChunk
 from langgraph.types import Command
@@ -132,15 +132,23 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
         **kwargs: Any,
     ) -> Any:
         if metadata and (not tags or (TAG_NOSTREAM not in tags)):
-            ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))[
-                :-1
-            ]
+            task_checkpoint_ns = cast(str, metadata["langgraph_checkpoint_ns"])
+            checkpoint_ns = (
+                f"{task_checkpoint_ns.rsplit(NS_END, 1)[0]}{NS_END}"
+                if NS_END in task_checkpoint_ns
+                else task_checkpoint_ns
+            )
+            ns = tuple(task_checkpoint_ns.split(NS_SEP))[:-1]
             if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
                 return
+            stream_metadata = dict(metadata)
+            stream_metadata["langgraph_checkpoint_ns"] = checkpoint_ns
+            # Preserve backwards-compatible streamed checkpoint metadata shape.
+            stream_metadata["checkpoint_ns"] = checkpoint_ns
             if tags:
                 if filtered_tags := [t for t in tags if not t.startswith("seq:step")]:
-                    metadata["tags"] = filtered_tags
-            self.metadata[run_id] = (ns, metadata)
+                    stream_metadata["tags"] = filtered_tags
+            self.metadata[run_id] = (ns, stream_metadata)
 
     def on_llm_new_token(
         self,

libs/langgraph/langgraph/pregel/_utils.py

@@ -1,11 +1,9 @@
 from __future__ import annotations
 
 import ast
-import functools
 import inspect
 import re
 import textwrap
-import types
 from collections.abc import Callable
 from typing import Any
 
@@ -66,74 +64,46 @@ def find_subgraph_pregel(candidate: Runnable) -> PregelProtocol | None:
     return None
 
 
-@functools.lru_cache(maxsize=256)
-def _get_nonlocal_names(code: types.CodeType) -> frozenset[str]:
-    """Return the set of nonlocal variable names referenced by a function.
-
-    Cached by code object so the expensive source fetch + AST parse only
-    happens once per unique function definition across repeated graph compiles.
-
-    Args:
-        code: The code object of the function to analyse.
-
-    Returns:
-        Frozenset of variable names that the function reads from its enclosing
-        scope (free variables and globals referenced in function bodies).
-    """
-    try:
-        source = inspect.getsource(code)
-        tree = ast.parse(textwrap.dedent(source))
-        visitor = FunctionNonLocals()
-        visitor.visit(tree)
-        return frozenset(visitor.nonlocals)
-    except (SyntaxError, TypeError, OSError, SystemError):
-        return frozenset()
-
-
 def get_function_nonlocals(func: Callable) -> list[Any]:
     """Get the nonlocal variables accessed by a function.
 
-    The expensive source-parsing step is cached by code object; only the
-    cheap closure-variable lookup runs on every call.
-
     Args:
         func: The function to check.
 
     Returns:
         List[Any]: The nonlocal variables accessed by the function.
     """
-    actual_func = (
-        func.__wrapped__
-        if hasattr(func, "__wrapped__") and callable(func.__wrapped__)
-        else func
-    )
-    # Fast path: no free variables means nothing to scan.
-    if not actual_func.__code__.co_freevars:
-        return []
-
-    nonlocal_names = _get_nonlocal_names(actual_func.__code__)
-    if not nonlocal_names:
-        return []
-
-    closure = inspect.getclosurevars(actual_func)
-    candidates = {**closure.globals, **closure.nonlocals}
-    values: list[Any] = []
-    for k, v in candidates.items():
-        if k in nonlocal_names:
-            values.append(v)
-        for kk in nonlocal_names:
-            if "." in kk and kk.startswith(k):
-                vv = v
-                for part in kk.split(".")[1:]:
-                    if vv is None:
-                        break
-                    else:
-                        try:
-                            vv = getattr(vv, part)
-                        except AttributeError:
+    try:
+        code = inspect.getsource(func)
+        tree = ast.parse(textwrap.dedent(code))
+        visitor = FunctionNonLocals()
+        visitor.visit(tree)
+        values: list[Any] = []
+        closure = (
+            inspect.getclosurevars(func.__wrapped__)
+            if hasattr(func, "__wrapped__") and callable(func.__wrapped__)
+            else inspect.getclosurevars(func)
+        )
+        candidates = {**closure.globals, **closure.nonlocals}
+        for k, v in candidates.items():
+            if k in visitor.nonlocals:
+                values.append(v)
+            for kk in visitor.nonlocals:
+                if "." in kk and kk.startswith(k):
+                    vv = v
+                    for part in kk.split(".")[1:]:
+                        if vv is None:
                             break
-                else:
-                    values.append(vv)
+                        else:
+                            try:
+                                vv = getattr(vv, part)
+                            except AttributeError:
+                                break
+                    else:
+                        values.append(vv)
+    except (SyntaxError, TypeError, OSError, SystemError):
+        return []
+
     return values
 
 

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.1.9"
+version = "1.1.7a2"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -24,7 +24,7 @@ classifiers = [
     'Programming Language :: Python :: 3.13',
 ]
 dependencies = [
-    "langchain-core>=1.3.0,<2",
+    "langchain-core==1.3.0a2",
     "langgraph-checkpoint>=2.1.0,<5.0.0",
     "langgraph-sdk>=0.3.0,<0.4.0",
     "langgraph-prebuilt>=1.0.9,<1.1.0",

libs/langgraph/tests/test_channels.py

@@ -121,22 +121,26 @@ def test_untracked_value() -> None:
 
 def test_delta_channel_basic_two_steps() -> None:
     from langchain_core.messages import AIMessage, HumanMessage
-    from langgraph.checkpoint.base import DeltaChannelSentinel
+    from langgraph.checkpoint.base import DeltaValue
 
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
 
     ch = DeltaChannel(add_messages).from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
 
     # Step 1: one message added
     ch.update([HumanMessage(content="hi", id="h1")])
     d1 = ch.checkpoint()
-    assert isinstance(d1, DeltaChannelSentinel)
+    assert isinstance(d1, DeltaValue)
+    assert len(d1.delta) == 1
+    ch.after_checkpoint("v1", checkpoint_id="cid1")
 
     # Step 2: another message
     ch.update([AIMessage(content="hello", id="a1")])
     d2 = ch.checkpoint()
-    assert isinstance(d2, DeltaChannelSentinel)
+    assert len(d2.delta) == 1
+    ch.after_checkpoint("v2")
 
     # Full accumulated value is preserved in memory
     assert len(ch.get()) == 2
@@ -144,21 +148,40 @@ def test_delta_channel_basic_two_steps() -> None:
     assert ch.get()[1].content == "hello"
 
 
-def test_delta_channel_from_checkpoint_writes_list() -> None:
-    """from_checkpoint with a flat list of individual writes replays them through the operator."""
+def test_delta_channel_after_checkpoint_no_op_when_unchanged() -> None:
+    from langchain_core.messages import HumanMessage
+
+    from langgraph.channels.delta import DeltaChannel
+    from langgraph.graph.message import add_messages
+
+    ch = DeltaChannel(add_messages).from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
+    ch.update([HumanMessage(content="hi", id="h1")])
+    ch.after_checkpoint("v1")
+
+    # Same version: no-op
+    ch.after_checkpoint("v1")
+    assert ch._base_version == "v1"
+    assert ch._pending == []
+
+
+def test_delta_channel_from_checkpoint_chain() -> None:
     from langchain_core.messages import AIMessage, HumanMessage
+    from langgraph.checkpoint.base import DeltaChainValue
 
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
 
     spec = DeltaChannel(add_messages)
-    # Each element is one write value (as stored in checkpoint_writes)
-    writes = [
-        HumanMessage(content="hi", id="h1"),
-        AIMessage(content="hello", id="a1"),
-        HumanMessage(content="bye", id="h2"),
-    ]
-    ch = spec.from_checkpoint(writes)
+    chain = DeltaChainValue(
+        base=None,
+        deltas=[
+            [HumanMessage(content="hi", id="h1")],
+            [AIMessage(content="hello", id="a1")],
+            [HumanMessage(content="bye", id="h2")],
+        ],
+    )
+    ch = spec.from_checkpoint(chain)
     msgs = ch.get()
     assert len(msgs) == 3
     assert msgs[0].content == "hi"
@@ -172,45 +195,68 @@ def test_delta_channel_from_checkpoint_backwards_compat() -> None:
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
 
-    # Old BinaryOperatorAggregate checkpoint: plain list treated as backward compat
+    # Old BinaryOperatorAggregate checkpoint: plain list
     spec = DeltaChannel(add_messages)
     old_value = [HumanMessage(content="old", id="h1")]
     ch = spec.from_checkpoint(old_value)
     assert ch.get() == old_value
 
 
-def test_delta_channel_overwrite() -> None:
+def test_delta_channel_overwrite_resets_chain() -> None:
     from langchain_core.messages import HumanMessage
-    from langgraph.checkpoint.base import DeltaChannelSentinel
+    from langgraph.checkpoint.base import DeltaValue
 
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
     from langgraph.types import Overwrite
 
     ch = DeltaChannel(add_messages).from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
     ch.update([HumanMessage(content="old", id="h1")])
+    ch.after_checkpoint("v1")
 
     ch.update([Overwrite([HumanMessage(content="new", id="h2")])])
     d = ch.checkpoint()
-    assert isinstance(d, DeltaChannelSentinel)
-    # After overwrite, value is reset to only the new message
-    assert len(ch.get()) == 1
-    assert ch.get()[0].content == "new"
+    assert isinstance(d, DeltaValue)
+    assert len(d.delta) == 1
+    assert d.delta[0].content == "new"
+    # _overwritten flag must be set so next checkpoint acts as a chain root
+    assert ch._overwritten is True
 
 
-def test_delta_channel_remove_message_and_replay() -> None:
-    """RemoveMessage must round-trip correctly when writes are replayed."""
+def test_delta_channel_unsupported_saver_raises() -> None:
+    """from_checkpoint raises ValueError when the saver returns a raw DeltaValue."""
+    from langgraph.checkpoint.base import DeltaValue
+
+    from langgraph.channels.delta import DeltaChannel
+    from langgraph.graph.message import add_messages
+
+    spec = DeltaChannel(add_messages)
+    raw = DeltaValue(delta=[{"type": "human", "content": "hello"}])
+    with pytest.raises(
+        ValueError, match="does not support incremental channel storage"
+    ):
+        spec.from_checkpoint(raw)
+
+
+def test_delta_channel_remove_message_delta_and_replay() -> None:
+    """RemoveMessage stored in a delta must round-trip correctly through the chain."""
     from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
+    from langgraph.checkpoint.base import DeltaChainValue, DeltaValue
 
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
 
     spec = DeltaChannel(add_messages)
     ch = spec.from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
 
     # Step 1: add two messages
     ch.update([HumanMessage(content="hi", id="h1")])
     ch.update([AIMessage(content="hello", id="a1")])
+    d1 = ch.checkpoint()
+    assert isinstance(d1, DeltaValue)
+    ch.after_checkpoint("v1", checkpoint_id="cid1")
     assert ch.get() == [
         HumanMessage(content="hi", id="h1"),
         AIMessage(content="hello", id="a1"),
@@ -218,63 +264,127 @@ def test_delta_channel_remove_message_and_replay() -> None:
 
     # Step 2: remove the AI message
     ch.update([RemoveMessage(id="a1")])
+    d2 = ch.checkpoint()
+    assert isinstance(d2, DeltaValue)
+    assert any(isinstance(w, RemoveMessage) for w in d2.delta)
+    ch.after_checkpoint("v2", checkpoint_id="cid2")
     assert ch.get() == [HumanMessage(content="hi", id="h1")]
 
-    # Replay the writes list from scratch — must reproduce the post-remove state
-    writes = [
-        HumanMessage(content="hi", id="h1"),
-        AIMessage(content="hello", id="a1"),
-        RemoveMessage(id="a1"),
-    ]
-    ch2 = spec.from_checkpoint(writes)
+    # Replay the full chain from scratch — must reproduce the post-remove state
+    chain = DeltaChainValue(base=None, deltas=[d1.delta, d2.delta])
+    ch2 = spec.from_checkpoint(chain)
     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."""
+def test_delta_channel_update_by_id_delta_and_replay() -> None:
+    """Updating a message by ID stored in a delta must round-trip correctly."""
     from langchain_core.messages import HumanMessage
+    from langgraph.checkpoint.base import DeltaChainValue, DeltaValue
 
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
 
     spec = DeltaChannel(add_messages)
     ch = spec.from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
 
     # Step 1: add a message
     ch.update([HumanMessage(content="original", id="h1")])
+    d1 = ch.checkpoint()
+    assert isinstance(d1, DeltaValue)
+    ch.after_checkpoint("v1", checkpoint_id="cid1")
 
     # Step 2: update the same message by ID
     ch.update([HumanMessage(content="updated", id="h1")])
+    d2 = ch.checkpoint()
+    assert isinstance(d2, DeltaValue)
+    ch.after_checkpoint("v2", checkpoint_id="cid2")
     assert ch.get() == [HumanMessage(content="updated", id="h1")]
 
-    # Replay writes — must produce the updated message, not the original
-    writes = [
-        HumanMessage(content="original", id="h1"),
-        HumanMessage(content="updated", id="h1"),
-    ]
-    ch2 = spec.from_checkpoint(writes)
+    # Replay the full chain — must produce the updated message, not the original
+    chain = DeltaChainValue(base=None, deltas=[d1.delta, d2.delta])
+    ch2 = spec.from_checkpoint(chain)
     assert len(ch2.get()) == 1
     assert ch2.get()[0].content == "updated"
 
 
-def test_delta_channel_checkpoint_returns_sentinel() -> None:
-    """checkpoint() always returns DeltaChannelSentinel regardless of state."""
-    from langgraph.checkpoint.base import DeltaChannelSentinel
+def test_delta_channel_snapshot_every_emits_plain_list() -> None:
+    """snapshot_every=N causes a plain-list snapshot after N steps; next deltas chain to it."""
+    from langchain_core.messages import HumanMessage
+    from langgraph.checkpoint.base import DeltaValue
 
     from langgraph.channels.delta import DeltaChannel
     from langgraph.graph.message import add_messages
 
-    ch = DeltaChannel(add_messages).from_checkpoint(MISSING)
-    assert isinstance(ch.checkpoint(), DeltaChannelSentinel)
+    SNAP = 3
+    spec = DeltaChannel(add_messages, snapshot_every=SNAP)
+    ch = spec.from_checkpoint(MISSING)
+    # First after_checkpoint anchors _base_version without counting a step.
+    ch.after_checkpoint("v0", checkpoint_id="cid0")
 
-    from langchain_core.messages import HumanMessage
+    # Steps 1..SNAP: each should stay as DeltaValue; counter increments each step.
+    for i in range(1, SNAP + 1):
+        ch.update([HumanMessage(content=f"m{i}", id=f"h{i}")])
+        ckpt = ch.checkpoint()
+        assert isinstance(ckpt, DeltaValue), f"expected DeltaValue at step {i}"
+        ch.after_checkpoint(f"v{i}", checkpoint_id=f"cid{i}")
 
-    ch.update([HumanMessage(content="hi", id="h1")])
-    assert isinstance(ch.checkpoint(), DeltaChannelSentinel)
+    # Step SNAP+1: _steps_since_snapshot == SNAP → snapshot fires
+    ch.update([HumanMessage(content="snap", id="hsnap")])
+    snap = ch.checkpoint()
+    assert isinstance(snap, list), "expected plain-list snapshot at snapshot_every step"
+    assert len(snap) == SNAP + 1
+
+    # After snapshot, counter resets — next step is DeltaValue again
+    ch.after_checkpoint("vsnap", checkpoint_id="cidsnap")
+    ch.update([HumanMessage(content="post", id="hpost")])
+    post = ch.checkpoint()
+    assert isinstance(post, DeltaValue)
 
 
-def test_delta_channel_inmemory_saver_assembles_writes() -> None:
-    """InMemorySaver assembles writes from checkpoint_writes inside get_tuple."""
+def test_delta_channel_snapshot_every_end_to_end() -> None:
+    """Graph with snapshot_every: get_state returns correct accumulated value after snapshot."""
+    from typing import Annotated
+
+    from langchain_core.messages import AIMessage, HumanMessage
+    from langgraph.checkpoint.memory import InMemorySaver
+    from typing_extensions import TypedDict
+
+    from langgraph.channels.delta import DeltaChannel
+    from langgraph.graph import START, StateGraph
+    from langgraph.graph.message import add_messages
+
+    class State(TypedDict):
+        messages: Annotated[list, DeltaChannel(add_messages, snapshot_every=2)]
+
+    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")
+    graph = builder.compile(checkpointer=InMemorySaver())
+    config = {"configurable": {"thread_id": "snap-test"}}
+
+    # Run 5 turns — snapshot fires after 2 steps, then again after 2 more
+    for i in range(5):
+        graph.invoke({"messages": [HumanMessage(content=f"h{i}", id=f"h{i}")]}, config)
+
+    state = graph.get_state(config)
+    msgs = state.values["messages"]
+    # 5 human + 5 AI = 10 total
+    assert len(msgs) == 10, f"expected 10 messages, got {len(msgs)}: {msgs}"
+
+
+def test_delta_channel_inmemory_saver_assembles_chain() -> None:
+    """InMemorySaver assembles the delta chain inside get_tuple (no pregel involvement)."""
     from typing import Annotated
 
     from langchain_core.messages import AIMessage, HumanMessage
@@ -304,16 +414,14 @@ def test_delta_channel_inmemory_saver_assembles_writes() -> None:
     graph.invoke({"messages": [HumanMessage(content="hi", id="h1")]}, config)
     graph.invoke({"messages": [HumanMessage(content="bye", id="h2")]}, config)
 
-    # get_tuple must return a resolved list (not DeltaChannelSentinel)
-    from langgraph.checkpoint.base import DeltaChannelSentinel
+    # get_tuple must return a fully assembled DeltaChainValue, not raw DeltaValue
+    from langgraph.checkpoint.base import DeltaChainValue, DeltaValue
 
     saved = saver.get_tuple(config)
     assert saved is not None
     assert "messages" in saved.checkpoint["channel_values"]
-    assert not isinstance(
-        saved.checkpoint["channel_values"]["messages"], DeltaChannelSentinel
-    )
-    assert isinstance(saved.checkpoint["channel_values"]["messages"], list)
+    assert not isinstance(saved.checkpoint["channel_values"]["messages"], DeltaValue)
+    assert isinstance(saved.checkpoint["channel_values"]["messages"], DeltaChainValue)
 
     state = graph.get_state(config)
     assert len(state.values["messages"]) == 4  # 2 human + 2 AI
@@ -343,39 +451,48 @@ def test_delta_channel_dict_reducer_fresh_channel() -> None:
 
 def test_delta_channel_dict_reducer_basic_updates() -> None:
     """DeltaChannel with a dict reducer accumulates key/value pairs across steps."""
-    from langgraph.checkpoint.base import DeltaChannelSentinel
+    from langgraph.checkpoint.base import DeltaValue
 
     def merge_dicts(left: dict, right: dict) -> dict:
         return {**left, **right}
 
     ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
 
     ch.update([{"a": 1}])
     d1 = ch.checkpoint()
-    assert isinstance(d1, DeltaChannelSentinel)
+    assert isinstance(d1, DeltaValue)
+    assert d1.delta == [{"a": 1}]
+    ch.after_checkpoint("v1", checkpoint_id="cid1")
 
     ch.update([{"b": 2}])
     d2 = ch.checkpoint()
-    assert isinstance(d2, DeltaChannelSentinel)
+    assert d2.delta == [{"b": 2}]
+    ch.after_checkpoint("v2")
 
     assert ch.get() == {"a": 1, "b": 2}
 
 
-def test_delta_channel_dict_reducer_writes_reconstruction() -> None:
-    """from_checkpoint with a writes list replays correctly through a dict merge reducer."""
+def test_delta_channel_dict_reducer_chain_reconstruction() -> None:
+    """DeltaChainValue replays correctly through a dict merge reducer."""
+    from langgraph.checkpoint.base import DeltaChainValue
 
     def merge_dicts(left: dict, right: dict) -> dict:
         return {**left, **right}
 
     spec = _delta_channel_with_type(merge_dicts, dict)
-    # Each element is one write value (oldest→newest)
-    writes = [{"a": 1}, {"b": 2}, {"c": 3}]
-    ch = spec.from_checkpoint(writes)
+    chain = DeltaChainValue(
+        base={"a": 1},
+        deltas=[[{"b": 2}], [{"c": 3}]],
+    )
+    ch = spec.from_checkpoint(chain)
     assert ch.get() == {"a": 1, "b": 2, "c": 3}
+    assert ch._steps_since_snapshot == 2
 
 
 def test_delta_channel_dict_reducer_with_deletions() -> None:
     """Dict reducer that treats None values as deletions works end-to-end (deepagents pattern)."""
+    from langgraph.checkpoint.base import DeltaChainValue
 
     def merge_files(left: dict | None, right: dict) -> dict:
         if left is None:
@@ -389,19 +506,25 @@ def test_delta_channel_dict_reducer_with_deletions() -> None:
         return result
 
     ch = _delta_channel_with_type(merge_files, dict).from_checkpoint(MISSING)
+    ch.after_checkpoint(None)
 
     ch.update([{"file1.py": "content1", "file2.py": "content2"}])
+    ch.after_checkpoint("v1", checkpoint_id="cid1")
 
     # Delete file1, add file3
     ch.update([{"file1.py": None, "file3.py": "content3"}])
+    ch.after_checkpoint("v2", checkpoint_id="cid2")
 
     assert ch.get() == {"file2.py": "content2", "file3.py": "content3"}
 
-    # Confirm writes reconstruction produces the same result
-    writes = [
-        {"file1.py": "content1", "file2.py": "content2"},
-        {"file1.py": None, "file3.py": "content3"},
-    ]
+    # Confirm chain reconstruction produces the same result
+    chain = DeltaChainValue(
+        base={},
+        deltas=[
+            [{"file1.py": "content1", "file2.py": "content2"}],
+            [{"file1.py": None, "file3.py": "content3"}],
+        ],
+    )
     spec = _delta_channel_with_type(merge_files, dict)
-    ch2 = spec.from_checkpoint(writes)
+    ch2 = spec.from_checkpoint(chain)
     assert ch2.get() == {"file2.py": "content2", "file3.py": "content3"}

libs/langgraph/tests/test_delta_channel_benchmark.py

@@ -8,11 +8,6 @@ Simulates realistic multi-turn conversations with paragraph-length messages
 
 Token estimates: 1 token ≈ 4 chars; each turn ≈ 200 tokens (human + AI).
 A 1M-token conversation ≈ 5,000 turns of realistic messages.
-
-DeltaChannel stores only a zero-byte sentinel in checkpoint_blobs; the actual
-write data lives in checkpoint_writes (already stored there). Reconstruction
-walks the parent chain and replays writes through the operator — O(N) total
-storage vs O(N²) for plain add_messages.
 """
 
 from __future__ import annotations
@@ -47,6 +42,8 @@ try:
 except ImportError:
     _POSTGRES_AVAILABLE = False
 
+SNAPSHOT_EVERY = 50
+
 # ---------------------------------------------------------------------------
 # Realistic message payload (~100 tokens / ~400 chars each)
 # ---------------------------------------------------------------------------
@@ -124,6 +121,10 @@ class DeltaState(TypedDict):
     messages: Annotated[list, DeltaChannel(add_messages)]
 
 
+class DeltaSnapshotState(TypedDict):
+    messages: Annotated[list, DeltaChannel(add_messages, snapshot_every=SNAPSHOT_EVERY)]
+
+
 # ---------------------------------------------------------------------------
 # Graph factory
 # ---------------------------------------------------------------------------
@@ -219,7 +220,7 @@ def _approx_tokens(n_turns: int) -> str:
 
 # Turn counts chosen to demonstrate O(N²) vs O(N) storage growth without running too long.
 # Extrapolation: 5,000 turns × ~200 tokens/turn ≈ 1M tokens (Claude's full context window).
-TURN_COUNTS = [10, 25, 50, 100, 500]
+TURN_COUNTS = [10, 25, 50, 100]
 
 
 def _checkpointer_factories() -> list[tuple[str, Any]]:
@@ -238,13 +239,7 @@ def run_benchmark() -> None:
 
     checkpointers: list[tuple[str, Any]] = [("InMemory", None)]
     if _POSTGRES_AVAILABLE:
-        try:
-            import psycopg
-
-            psycopg.connect(_POSTGRES_URI).close()
-            checkpointers.append(("Postgres (recursive CTE)", "postgres"))
-        except Exception:
-            pass
+        checkpointers.append(("Postgres (recursive CTE)", "postgres"))
 
     for cp_label, cp_hint in checkpointers:
         print(f"--- Checkpointer: {cp_label} ---")
@@ -282,28 +277,30 @@ def _run_benchmark_for_checkpointer(cp_hint: Any) -> None:
             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))
+        with _make_saver() as saver:
+            s_wt, s_rt, s_bytes = _run_turns(turns, DeltaSnapshotState, saver)
+        rows.append((turns, b_bytes, d_bytes, s_bytes, b_rt, d_rt, s_rt))
 
     # ── Table 1: Storage ─────────────────────────────────────────────────────
-    W = 70
+    W = 80
     print("Storage (checkpoint blob bytes)")
     print("=" * W)
     print(
-        f"{'turns':>6}  {'ctx size':>10}  {'add_msgs':>12}  {'delta':>12}  {'savings':>8}"
+        f"{'turns':>6}  {'ctx size':>10}  {'add_msgs':>12}  {'delta':>12}  {'delta+snap':>12}  {'savings':>8}"
     )
     print("-" * W)
     storage_results = []
-    for turns, b_bytes, d_bytes, b_rt, d_rt in rows:
+    for turns, b_bytes, d_bytes, s_bytes, *_ in rows:
         if b_bytes < 0:
             print(
-                f"{turns:>6}  {_approx_tokens(turns):>10}  {'n/a':>12}  {'n/a':>12}  {'n/a':>8}"
+                f"{turns:>6}  {_approx_tokens(turns):>10}  {'n/a':>12}  {'n/a':>12}  {'n/a':>12}  {'n/a':>8}"
             )
         else:
-            ratio = b_bytes / d_bytes if d_bytes else float("inf")
-            storage_results.append((turns, b_bytes, d_bytes, ratio))
+            ratio = b_bytes / s_bytes if s_bytes else float("inf")
+            storage_results.append((turns, b_bytes, s_bytes, ratio))
             print(
                 f"{turns:>6}  {_approx_tokens(turns):>10}  "
-                f"{_fmt_bytes(b_bytes):>12}  {_fmt_bytes(d_bytes):>12}  "
+                f"{_fmt_bytes(b_bytes):>12}  {_fmt_bytes(d_bytes):>12}  {_fmt_bytes(s_bytes):>12}  "
                 f"{ratio:>7.0f}x"
             )
     print("=" * W)
@@ -312,30 +309,35 @@ def _run_benchmark_for_checkpointer(cp_hint: Any) -> None:
     # ── Table 2: Read latency ─────────────────────────────────────────────────
     print("Read latency (avg of 5 get_state calls)")
     print("=" * W)
-    print(f"{'turns':>6}  {'ctx size':>10}  {'add_msgs':>12}  {'delta':>12}")
+    print(
+        f"{'turns':>6}  {'ctx size':>10}  {'add_msgs':>12}  {'delta':>12}  {'delta+snap':>12}"
+    )
     print("-" * W)
-    for turns, b_bytes, d_bytes, b_rt, d_rt in rows:
+    for turns, b_bytes, d_bytes, s_bytes, b_rt, d_rt, s_rt in rows:
         print(
             f"{turns:>6}  {_approx_tokens(turns):>10}  "
-            f"{b_rt * 1000:>10.1f}ms  {d_rt * 1000:>10.1f}ms"
+            f"{b_rt * 1000:>10.1f}ms  {d_rt * 1000:>10.1f}ms  {s_rt * 1000:>10.1f}ms"
         )
     print("=" * W)
     print()
 
     if storage_results:
-        turns, b_bytes, d_bytes, ratio = storage_results[-1]
-        b_rt = rows[-1][-2]
-        d_rt = rows[-1][-1]
+        best = storage_results[-1]
+        turns, b_bytes, s_bytes, ratio = best
+        _, _, _, _, b_rt, _, s_rt = rows[-1]
         print(
-            f"At {turns} turns: {_fmt_bytes(b_bytes)} → {_fmt_bytes(d_bytes)} ({ratio:.0f}x less storage); "
-            f"read {b_rt * 1000:.1f}ms → {d_rt * 1000:.1f}ms"
+            f"At {turns} turns: {_fmt_bytes(b_bytes)} → {_fmt_bytes(s_bytes)} ({ratio:.0f}x less storage); "
+            f"read {b_rt * 1000:.1f}ms → {s_rt * 1000:.1f}ms"
         )
         print()
 
     print("Legend:")
-    print("  add_msgs = Annotated[list, add_messages]  — O(N²) storage")
+    print("  add_msgs    = Annotated[list, add_messages]              — O(N²) storage")
     print(
-        "  delta    = DeltaChannel(add_messages)     — O(N) storage, full chain replay"
+        "  delta       = DeltaChannel(add_messages)                 — O(N) storage, unbounded chain"
+    )
+    print(
+        f"  delta+snap  = DeltaChannel(add_messages, snapshot_every={SNAPSHOT_EVERY})  — O(N) storage, bounded read depth"
     )
     print()
 
@@ -357,10 +359,15 @@ def test_delta_channel_benchmark(capsys: Any) -> None:
     for turns in [25, 50]:
         _, _, b_bytes = _run_turns(turns, BinaryState)
         _, _, d_bytes = _run_turns(turns, DeltaState)
+        _, _, s_bytes = _run_turns(turns, DeltaSnapshotState)
         assert d_bytes < b_bytes, (
             f"DeltaChannel should use less storage at {turns} turns, "
             f"got delta={d_bytes} binary={b_bytes}"
         )
+        assert s_bytes < b_bytes, (
+            f"DeltaChannel+snapshot should use less storage at {turns} turns, "
+            f"got snapshot={s_bytes} binary={b_bytes}"
+        )
 
 
 # ---------------------------------------------------------------------------

libs/langgraph/tests/test_graph_callbacks.py

@@ -275,70 +275,3 @@ def test_graph_callbacks_accept_base_callback_manager() -> None:
 
     assert "__interrupt__" in first
     assert len(graph_handler.interrupt_events) == 1
-
-
-def test_non_graph_handler_via_add_handler_does_not_crash() -> None:
-    """Non-GraphCallbackHandler added via add_handler should not raise.
-
-    Libraries like opentelemetry-instrumentation-langchain monkey-patch
-    BaseCallbackManager.__init__ and inject handlers via add_handler().
-    These handlers inherit from BaseCallbackHandler, not
-    GraphCallbackHandler. They must be silently accepted — graph lifecycle
-    events will simply not be dispatched to them.
-    """
-    from langgraph.callbacks import _GraphCallbackManager
-
-    manager = _GraphCallbackManager()
-    plain_handler = _LangChainCustomEventHandler()
-
-    manager.add_handler(plain_handler, inherit=True)
-    assert plain_handler in manager.handlers
-
-
-def test_non_graph_handler_does_not_receive_lifecycle_events() -> None:
-    """Non-GraphCallbackHandler added alongside a GraphCallbackHandler
-    should not interfere with lifecycle event dispatch."""
-    graph = _build_interrupt_graph()
-    graph_handler = _GraphEventHandler()
-    plain_handler = _LangChainCustomEventHandler()
-
-    config = {
-        "configurable": {"thread_id": "graph-callback-mixed-handlers"},
-        "callbacks": [plain_handler, graph_handler],
-    }
-
-    first = graph.invoke({"answer": None}, config)
-    assert "__interrupt__" in first
-
-    assert len(graph_handler.interrupt_events) == 1
-    assert plain_handler.events == []
-
-    resumed = graph.invoke(Command(resume="done"), config)
-    assert resumed == {"answer": "done"}
-    assert len(graph_handler.resume_events) == 1
-    assert plain_handler.events == []
-
-
-@pytest.mark.anyio
-@NEEDS_CONTEXTVARS
-async def test_non_graph_handler_does_not_receive_lifecycle_events_async() -> None:
-    """Async variant: non-GraphCallbackHandler should not interfere."""
-    graph = _build_interrupt_graph()
-    graph_handler = _GraphEventHandler()
-    plain_handler = _LangChainCustomEventHandler()
-
-    config = {
-        "configurable": {"thread_id": "graph-callback-mixed-handlers-async"},
-        "callbacks": [plain_handler, graph_handler],
-    }
-
-    first = await graph.ainvoke({"answer": None}, config)
-    assert "__interrupt__" in first
-
-    assert len(graph_handler.interrupt_events) == 1
-    assert plain_handler.events == []
-
-    resumed = await graph.ainvoke(Command(resume="done"), config)
-    assert resumed == {"answer": "done"}
-    assert len(graph_handler.resume_events) == 1
-    assert plain_handler.events == []

libs/langgraph/tests/test_rehydrate_sweep.py

@@ -0,0 +1,185 @@
+"""Sweep snapshot_every values to find the storage vs. time-travel tradeoff.
+
+Run directly:  python tests/test_rehydrate_sweep.py
+Run via pytest: pytest tests/test_rehydrate_sweep.py -s
+"""
+
+from __future__ import annotations
+
+import sys
+import time
+from typing import Annotated, Any
+
+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 add_messages
+
+# ---------------------------------------------------------------------------
+# Config
+# ---------------------------------------------------------------------------
+
+REHYDRATE_SWEEP = [5, 10, 25, 50, 100, None]  # None = no rehydration (pure diff)
+TURN_COUNTS = [50, 100, 250, 500]
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+def _make_state(snapshot_every: int | None) -> type:
+    channel = DeltaChannel(add_messages, snapshot_every=snapshot_every)
+    return TypedDict("S", {"messages": Annotated[list, channel]})
+
+
+def _make_graph(state_cls: type) -> Any:
+    def human_node(state: Any) -> dict:
+        return {}
+
+    def ai_node(state: Any) -> dict:
+        last = state["messages"][-1]
+        return {"messages": [AIMessage(content=f"reply-to-{last.id}")]}
+
+    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=MemorySaver())
+
+
+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 _measure_time_travel_ms(graph: Any, config: dict) -> float:
+    """Time how long it takes to get state at the very first checkpoint (worst case)."""
+    history = list(graph.get_state_history(config))
+    if not history:
+        return 0.0
+    oldest = history[-1]
+    t0 = time.perf_counter()
+    graph.get_state(oldest.config)
+    return (time.perf_counter() - t0) * 1000
+
+
+def _run(n_turns: int, snapshot_every: int | None) -> tuple[float, int, float]:
+    """Returns (write_ms, blob_bytes, time_travel_ms)."""
+    state_cls = _make_state(snapshot_every)
+    graph = _make_graph(state_cls)
+    saver: MemorySaver = graph.checkpointer  # type: ignore[assignment]
+    config = {"configurable": {"thread_id": "sweep"}}
+
+    t0 = time.perf_counter()
+    for i in range(n_turns):
+        graph.invoke(
+            {"messages": [HumanMessage(content=f"msg-{i}", id=f"h{i}")]}, config
+        )
+    write_ms = (time.perf_counter() - t0) * 1000
+
+    blob_bytes = _total_blob_bytes(saver)
+    tt_ms = _measure_time_travel_ms(graph, config)
+    return write_ms, blob_bytes, tt_ms
+
+
+# ---------------------------------------------------------------------------
+# ASCII sparkline
+# ---------------------------------------------------------------------------
+
+
+def _sparkline(values: list[float], width: int = 20) -> str:
+    bars = " ▁▂▃▄▅▆▇█"
+    lo, hi = min(values), max(values)
+    span = hi - lo or 1
+    chars = [bars[round((v - lo) / span * (len(bars) - 1))] for v in values]
+    return "".join(chars).ljust(width)
+
+
+# ---------------------------------------------------------------------------
+# Main
+# ---------------------------------------------------------------------------
+
+
+def run_sweep() -> None:
+    label = {v: (str(v) if v is not None else "None(∞)") for v in REHYDRATE_SWEEP}
+
+    print()
+    print("snapshot_every sweep — storage vs time-travel cost")
+    print("=" * 90)
+
+    for turns in TURN_COUNTS:
+        print(f"\n--- {turns} turns ---")
+        col_w = 12
+        header = (
+            f"{'snapshot_every':>18}  "
+            f"{'blob_bytes':>{col_w}}  "
+            f"{'write_ms':>{col_w}}  "
+            f"{'time_travel_ms':>{col_w}}"
+        )
+        print(header)
+        print("-" * 60)
+
+        tt_vals: list[float] = []
+        byte_vals: list[int] = []
+        write_vals: list[float] = []
+        rows: list[tuple] = []
+
+        for rv in REHYDRATE_SWEEP:
+            write_ms, blob_bytes, tt_ms = _run(turns, rv)
+            rows.append((rv, blob_bytes, write_ms, tt_ms))
+            byte_vals.append(blob_bytes)
+            write_vals.append(write_ms)
+            tt_vals.append(tt_ms)
+
+        for rv, blob_bytes, write_ms, tt_ms in rows:
+            print(
+                f"{label[rv]:>18}  "
+                f"{blob_bytes:>{col_w},}  "
+                f"{write_ms:>{col_w}.1f}  "
+                f"{tt_ms:>{col_w}.2f}"
+            )
+
+        print()
+        print(
+            f"  bytes       spark: [{_sparkline(byte_vals)}]  "
+            f"lo={min(byte_vals):,}  hi={max(byte_vals):,}"
+        )
+        print(
+            f"  time-travel spark: [{_sparkline(tt_vals)}]  "
+            f"lo={min(tt_vals):.2f}ms  hi={max(tt_vals):.2f}ms"
+        )
+        print(
+            f"  write       spark: [{_sparkline(write_vals)}]  "
+            f"lo={min(write_vals):.1f}ms  hi={max(write_vals):.1f}ms"
+        )
+
+    print()
+    print("=" * 90)
+    print(
+        "snapshot_every=None means pure diff (no snapshots) — "
+        "lowest storage, highest time-travel cost."
+    )
+    print(
+        "Lower snapshot_every = more frequent full snapshots = "
+        "faster time-travel, more storage."
+    )
+    print()
+
+
+def test_rehydrate_sweep(capsys: Any) -> None:
+    with capsys.disabled():
+        run_sweep()
+
+
+if __name__ == "__main__":
+    run_sweep()
+    sys.exit(0)

libs/langgraph/tests/test_time_travel.py

@@ -1113,72 +1113,6 @@ def test_subgraph_interrupt_replay_from_parent_then_resume(
     ]
 
 
-def test_subgraph_interrupt_resume_with_explicit_head_checkpoint_id(
-    sync_checkpointer: BaseCheckpointSaver,
-) -> None:
-    """Resume with Command(resume=...) plus the current head checkpoint_id
-    in config. The subgraph must continue from the interrupted node, not
-    restart from scratch. Explicit checkpoint_id triggers is_replaying but
-    this is a resume, not a time-travel, so ReplayState should not apply."""
-
-    called: list[str] = []
-
-    def step_a(state: State) -> State:
-        called.append("step_a")
-        return {"value": ["sub_a"]}
-
-    def ask_human(state: State) -> State:
-        called.append("ask_human")
-        answer = interrupt("Provide input:")
-        return {"value": [f"human:{answer}"]}
-
-    def step_b(state: State) -> State:
-        called.append("step_b")
-        return {"value": ["sub_b"]}
-
-    subgraph = (
-        StateGraph(State)
-        .add_node("step_a", step_a)
-        .add_node("ask_human", ask_human)
-        .add_node("step_b", step_b)
-        .add_edge(START, "step_a")
-        .add_edge("step_a", "ask_human")
-        .add_edge("ask_human", "step_b")
-        .compile(checkpointer=True)
-    )
-
-    graph = (
-        StateGraph(State)
-        .add_node("subgraph_node", subgraph)
-        .add_edge(START, "subgraph_node")
-        .compile(checkpointer=sync_checkpointer)
-    )
-
-    config = {"configurable": {"thread_id": "1"}}
-
-    # Run until interrupt fires in subgraph
-    graph.invoke({"value": []}, config)
-    assert called == ["step_a", "ask_human"]
-
-    # Resume with explicit head checkpoint_id in config
-    head_checkpoint_id = graph.get_state(config).config["configurable"][
-        "checkpoint_id"
-    ]
-    called.clear()
-    resume_config = {
-        "configurable": {
-            "thread_id": "1",
-            "checkpoint_id": head_checkpoint_id,
-            "checkpoint_ns": "",
-        }
-    }
-    result = graph.invoke(Command(resume="answer"), resume_config)
-
-    assert called == ["ask_human", "step_b"]
-    assert "__interrupt__" not in result
-    assert result["value"] == ["sub_a", "human:answer", "sub_b"]
-
-
 def test_subgraph_replay_loads_accumulated_state_then_resume(
     sync_checkpointer: BaseCheckpointSaver,
 ) -> None:

libs/langgraph/tests/test_utils.py

@@ -427,49 +427,3 @@ def test_callback_manager_copies_configurable_ids_to_tracing_metadata() -> None:
         "thread_id": "th-123",
         "user_id": "uid-1",
     }
-
-
-def test_get_nonlocal_names_cached_by_code_object() -> None:
-    """_get_nonlocal_names caches by code object so repeated calls are cheap."""
-    from langgraph.pregel._utils import _get_nonlocal_names
-
-    x = 1
-
-    def my_func() -> int:
-        return x
-
-    result1 = _get_nonlocal_names(my_func.__code__)
-    result2 = _get_nonlocal_names(my_func.__code__)
-
-    # Same frozenset instance returned (cache hit)
-    assert result1 is result2
-    assert "x" in result1
-
-
-def test_get_function_nonlocals_fast_path_no_freevars() -> None:
-    """Functions with no free variables return [] without AST parsing."""
-    from langgraph.pregel._utils import _get_nonlocal_names, get_function_nonlocals
-
-    cache_info_before = _get_nonlocal_names.cache_info()
-
-    def pure_func(a: int, b: int) -> int:
-        return a + b
-
-    result = get_function_nonlocals(pure_func)
-
-    # Should have returned early without touching the cache
-    assert result == []
-    assert _get_nonlocal_names.cache_info().misses == cache_info_before.misses
-
-
-def test_get_function_nonlocals_returns_closure_values() -> None:
-    """get_function_nonlocals correctly extracts values from closures."""
-    from langgraph.pregel._utils import get_function_nonlocals
-
-    sentinel = object()
-
-    def my_func() -> object:
-        return sentinel
-
-    result = get_function_nonlocals(my_func)
-    assert sentinel in result

libs/langgraph/uv.lock

@@ -1348,7 +1348,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.3.0"
+version = "1.3.0a2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -1360,14 +1360,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/92/fe/20190232d9b513242899dbb0c2bb77e31b4d61e343743adbe90ebc2603d2/langchain_core-1.3.0.tar.gz", hash = "sha256:14a39f528bf459aa3aa40d0a7f7f1bae7520d435ef991ae14a4ceb74d8c49046", size = 860755, upload-time = "2026-04-17T14:51:38.298Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/af/bc/0bff31fcaff174d86031cc713471a3e85ed4ec8e5cd95ad0217f2aced20e/langchain_core-1.3.0a2.tar.gz", hash = "sha256:52d978c84552b74b9a3f16c1fced84f9e27cc96d7a67c601925ce6cbc4ea3cf9", size = 854580, upload-time = "2026-04-13T14:37:55.745Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f8/e2/dbfa347aa072a6dc4cd38d6f9ebfc730b4c14c258c47f480f4c5c546f177/langchain_core-1.3.0-py3-none-any.whl", hash = "sha256:baf16ee028475df177b9ab8869a751c79406d64a6f12125b93802991b566cced", size = 515140, upload-time = "2026-04-17T14:51:36.274Z" },
+    { url = "https://files.pythonhosted.org/packages/0e/14/03c09686602567059f26af29de0c44546a83af2f2aa29925e61040e43ea2/langchain_core-1.3.0a2-py3-none-any.whl", hash = "sha256:9e929a34f0b0c6c1255e395a1de34f8626893ceb4cdae550a22a0bd18c87be54", size = 510233, upload-time = "2026-04-13T14:37:54.277Z" },
 ]
 
 [[package]]
 name = "langgraph"
-version = "1.1.9"
+version = "1.1.7a2"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1439,7 +1439,7 @@ test = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.0,<2" },
+    { name = "langchain-core", specifier = "==1.3.0a2" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "../prebuilt" },
     { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -1706,7 +1706,7 @@ inmem = [
 requires-dist = [
     { name = "click", specifier = ">=8.1.7" },
     { name = "httpx", specifier = ">=0.24.0" },
-    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.9.0" },
+    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.8.0" },
     { name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.7" },
     { name = "langgraph-sdk", marker = "python_full_version >= '3.11'", specifier = ">=0.1.0" },
     { name = "pathspec", specifier = ">=0.11.0" },
@@ -1742,7 +1742,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.10"
+version = "1.0.9"
 source = { editable = "../prebuilt" }
 dependencies = [
     { name = "langchain-core" },

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -808,7 +808,6 @@ class ToolNode(RunnableCallable):
                 context=runtime.context,
                 store=runtime.store,
                 stream_writer=runtime.stream_writer,
-                tools=list(self.tools_by_name.values()),
                 execution_info=runtime.execution_info,
                 server_info=runtime.server_info,
             )
@@ -843,7 +842,6 @@ class ToolNode(RunnableCallable):
                 context=runtime.context,
                 store=runtime.store,
                 stream_writer=runtime.stream_writer,
-                tools=list(self.tools_by_name.values()),
                 execution_info=runtime.execution_info,
                 server_info=runtime.server_info,
             )
@@ -1578,7 +1576,6 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
     - `context`: Runtime context (shared with `Runtime`)
     - `store`: `BaseStore` instance for persistent storage (shared with `Runtime`)
     - `stream_writer`: `StreamWriter` for streaming output (shared with `Runtime`)
-    - `tools`: List of all available `BaseTool` instances
 
     No `Annotated` wrapper is needed - just use `runtime: ToolRuntime`
     as a parameter.
@@ -1621,7 +1618,6 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
     context: ContextT
     config: RunnableConfig
     stream_writer: StreamWriter
-    tools: list[BaseTool]
     tool_call_id: str | None
     store: BaseStore | None
     execution_info: ExecutionInfo | None = None
@@ -1842,17 +1838,9 @@ def _get_injection_from_type(
     return None
 
 
-# Cache keyed by tool object identity. Stores (tool, result) to keep a strong
-# reference that prevents GC from reusing the id for a different object.
-_INJECTED_ARGS_CACHE: dict[int, tuple[BaseTool, _InjectedArgs]] = {}
-
-
 def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
     """Extract all injected arguments from tool in a single pass.
 
-    Results are cached by tool identity so the expensive type-hint and schema
-    inspection only runs once per unique tool object across ToolNode instances.
-
     This function analyzes both the tool's input schema and function signature
     to identify all arguments that should be injected (state, store, runtime).
 
@@ -1862,11 +1850,6 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
     Returns:
         _InjectedArgs structure containing all detected injections.
     """
-    tool_id = id(tool)
-    entry = _INJECTED_ARGS_CACHE.get(tool_id)
-    if entry is not None and entry[0] is tool:
-        return entry[1]
-
     # Get annotations from both schema and function signature
     full_schema = tool.get_input_schema()
     schema_annotations = get_all_basemodel_annotations(full_schema)
@@ -1912,12 +1895,10 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
         if _get_injection_from_type(type_, ToolRuntime):
             runtime_arg = name
 
-    result = _InjectedArgs(
+    return _InjectedArgs(
         state=state_args,
         store=store_arg,
         runtime=runtime_arg,
         all_injected_keys=all_injected_keys,
         _optional_state_args=_optional_state_args,
     )
-    _INJECTED_ARGS_CACHE[tool_id] = (tool, result)
-    return result

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "1.0.10"
+version = "1.0.9"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"

libs/prebuilt/tests/test_injected_state_not_required.py

@@ -69,7 +69,6 @@ def _create_config_with_runtime(store=None, state=None):
         context={},
         store=store,
         stream_writer=None,
-        tools=[],
         tool_call_id="test_id",
     )
     return {

libs/prebuilt/tests/test_tool_node.py

@@ -2016,8 +2016,8 @@ async def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call_async()
     assert tool_message.tool_call_id == "call_dynamic_2"
 
 
-def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
-    """Test that execution_info, server_info, and tools are forwarded from Runtime to ToolRuntime."""
+def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
+    """Test that execution_info and server_info are forwarded from Runtime to ToolRuntime."""
     from langgraph.runtime import ExecutionInfo, ServerInfo
 
     exec_info = ExecutionInfo(
@@ -2043,15 +2043,9 @@ def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
         """Tool that captures runtime info."""
         captured["execution_info"] = runtime.execution_info
         captured["server_info"] = runtime.server_info
-        captured["tools"] = runtime.tools
         return "ok"
 
-    @dec_tool
-    def other_tool(y: int) -> str:
-        """Another tool available to the runtime."""
-        return str(y)
-
-    node = ToolNode([info_tool, other_tool])
+    node = ToolNode([info_tool])
     tool_call = {
         "name": "info_tool",
         "args": {"x": 1},
@@ -2060,21 +2054,17 @@ def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
     }
     msg = AIMessage("", tool_calls=[tool_call])
     config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
-    result = node.invoke({"messages": [msg]}, config=config)
+    node.invoke({"messages": [msg]}, config=config)
 
-    assert result["messages"][-1].content == "ok"
     assert captured["execution_info"] is exec_info
     assert captured["execution_info"].thread_id == "t-1"
     assert captured["execution_info"].task_id == "tk-1"
     assert captured["server_info"] is server_info
     assert captured["server_info"].assistant_id == "asst-1"
-    assert [tool.name for tool in captured["tools"]] == ["info_tool", "other_tool"]
 
 
-async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async() -> (
-    None
-):
-    """Test that execution_info, server_info, and tools are forwarded in async path."""
+async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> None:
+    """Test that execution_info and server_info are forwarded in async path."""
     from langgraph.runtime import ExecutionInfo, ServerInfo
 
     exec_info = ExecutionInfo(
@@ -2100,15 +2090,9 @@ async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async(
         """Async tool that captures runtime info."""
         captured["execution_info"] = runtime.execution_info
         captured["server_info"] = runtime.server_info
-        captured["tools"] = runtime.tools
         return "ok"
 
-    @dec_tool
-    async def other_tool_async(y: int) -> str:
-        """Another async tool available to the runtime."""
-        return str(y)
-
-    node = ToolNode([info_tool_async, other_tool_async])
+    node = ToolNode([info_tool_async])
     tool_call = {
         "name": "info_tool_async",
         "args": {"x": 1},
@@ -2117,17 +2101,12 @@ async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async(
     }
     msg = AIMessage("", tool_calls=[tool_call])
     config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
-    result = await node.ainvoke({"messages": [msg]}, config=config)
+    await node.ainvoke({"messages": [msg]}, config=config)
 
-    assert result["messages"][-1].content == "ok"
     assert captured["execution_info"] is exec_info
     assert captured["execution_info"].thread_id == "t-2"
     assert captured["server_info"] is server_info
     assert captured["server_info"].graph_id == "graph-2"
-    assert [tool.name for tool in captured["tools"]] == [
-        "info_tool_async",
-        "other_tool_async",
-    ]
 
 
 # --- InjectedToolArg security tests ---

libs/prebuilt/uv.lock

@@ -249,7 +249,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.3.0"
+version = "1.3.0a2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -261,14 +261,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/92/fe/20190232d9b513242899dbb0c2bb77e31b4d61e343743adbe90ebc2603d2/langchain_core-1.3.0.tar.gz", hash = "sha256:14a39f528bf459aa3aa40d0a7f7f1bae7520d435ef991ae14a4ceb74d8c49046", size = 860755, upload-time = "2026-04-17T14:51:38.298Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/af/bc/0bff31fcaff174d86031cc713471a3e85ed4ec8e5cd95ad0217f2aced20e/langchain_core-1.3.0a2.tar.gz", hash = "sha256:52d978c84552b74b9a3f16c1fced84f9e27cc96d7a67c601925ce6cbc4ea3cf9", size = 854580, upload-time = "2026-04-13T14:37:55.745Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f8/e2/dbfa347aa072a6dc4cd38d6f9ebfc730b4c14c258c47f480f4c5c546f177/langchain_core-1.3.0-py3-none-any.whl", hash = "sha256:baf16ee028475df177b9ab8869a751c79406d64a6f12125b93802991b566cced", size = 515140, upload-time = "2026-04-17T14:51:36.274Z" },
+    { url = "https://files.pythonhosted.org/packages/0e/14/03c09686602567059f26af29de0c44546a83af2f2aa29925e61040e43ea2/langchain_core-1.3.0a2-py3-none-any.whl", hash = "sha256:9e929a34f0b0c6c1255e395a1de34f8626893ceb4cdae550a22a0bd18c87be54", size = 510233, upload-time = "2026-04-13T14:37:54.277Z" },
 ]
 
 [[package]]
 name = "langgraph"
-version = "1.1.9"
+version = "1.1.7a2"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -281,7 +281,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.0,<2" },
+    { name = "langchain-core", specifier = "==1.3.0a2" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "." },
     { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -490,7 +490,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.10"
+version = "1.0.9"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },

libs/sdk-py/uv.lock

@@ -262,7 +262,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.3.0"
+version = "1.3.0a2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -274,14 +274,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/92/fe/20190232d9b513242899dbb0c2bb77e31b4d61e343743adbe90ebc2603d2/langchain_core-1.3.0.tar.gz", hash = "sha256:14a39f528bf459aa3aa40d0a7f7f1bae7520d435ef991ae14a4ceb74d8c49046", size = 860755, upload-time = "2026-04-17T14:51:38.298Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/af/bc/0bff31fcaff174d86031cc713471a3e85ed4ec8e5cd95ad0217f2aced20e/langchain_core-1.3.0a2.tar.gz", hash = "sha256:52d978c84552b74b9a3f16c1fced84f9e27cc96d7a67c601925ce6cbc4ea3cf9", size = 854580, upload-time = "2026-04-13T14:37:55.745Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f8/e2/dbfa347aa072a6dc4cd38d6f9ebfc730b4c14c258c47f480f4c5c546f177/langchain_core-1.3.0-py3-none-any.whl", hash = "sha256:baf16ee028475df177b9ab8869a751c79406d64a6f12125b93802991b566cced", size = 515140, upload-time = "2026-04-17T14:51:36.274Z" },
+    { url = "https://files.pythonhosted.org/packages/0e/14/03c09686602567059f26af29de0c44546a83af2f2aa29925e61040e43ea2/langchain_core-1.3.0a2-py3-none-any.whl", hash = "sha256:9e929a34f0b0c6c1255e395a1de34f8626893ceb4cdae550a22a0bd18c87be54", size = 510233, upload-time = "2026-04-13T14:37:54.277Z" },
 ]
 
 [[package]]
 name = "langgraph"
-version = "1.1.9"
+version = "1.1.7a2"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -294,7 +294,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.0,<2" },
+    { name = "langchain-core", specifier = "==1.3.0a2" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "../prebuilt" },
     { name = "langgraph-sdk", editable = "." },
@@ -413,7 +413,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.10"
+version = "1.0.9"
 source = { editable = "../prebuilt" }
 dependencies = [
     { name = "langchain-core" },

pr_delta_channel.md

@@ -1,133 +0,0 @@
-# feat(channels): DeltaChannel — O(N) incremental checkpoint storage
-
-## The problem
-
-LangGraph checkpoints store the **full accumulated value** of every channel on every step. For a `messages` channel backed by `add_messages`, that means each checkpoint blob contains the entire conversation history up to that point.
-
-Storage cost grows **O(N²)** in the number of turns:
-
-| Step | Checkpoint blob |
-|------|----------------|
-| 1    | [msg_1] |
-| 2    | [msg_1, msg_2] |
-| N    | [msg_1, ..., msg_N] |
-
-At 100K tokens of conversation data, a single thread accumulates ~250 MB; with large messages or file attachments costs scale even faster.
-
-## The fix: `DeltaChannel`
-
-`DeltaChannel` is an opt-in wrapper around any binary reducer that stores only a **sentinel marker** in `checkpoint_blobs` rather than the full accumulated value. The actual per-step writes stay in `checkpoint_writes` (which every checkpointer already writes unconditionally). At read time the saver walks the ancestor chain, collects all writes for the channel, and replays them through the reducer.
-
-Storage scales **O(N)** — the sentinel blob is effectively zero bytes, and the writes table already exists.
-
-```python
-from langgraph.channels.delta import DeltaChannel
-from langgraph.graph.message import add_messages
-
-class State(TypedDict):
-    # Before: O(N²) storage
-    messages: Annotated[list[AnyMessage], add_messages]
-
-    # After: O(N) storage
-    messages: Annotated[list[AnyMessage], DeltaChannel(add_messages)]
-```
-
-## Benchmarks
-
-Simulated with realistic paragraph-length messages (~100 tokens each, ~400 chars). Each turn = one human + one AI message (~200 tokens total).
-
-### Storage (InMemorySaver)
-
-| turns | ctx | add_msgs | delta | savings |
-|------:|----:|---------:|------:|--------:|
-| 10 | ~2K tok | 108.6 KB | 4.0 KB | 27x |
-| 25 | ~5K tok | 649.0 KB | 10.1 KB | 64x |
-| 50 | ~10K tok | 2.6 MB | 20.2 KB | 126x |
-| 100 | ~20K tok | 10.2 MB | 40.5 KB | 251x |
-| 500 | ~100K tok | 252.6 MB | 202.8 KB | 1245x |
-
-Savings grow with N because `add_messages` is O(N²) while `DeltaChannel` is O(N). The sentinel blob itself is essentially zero bytes.
-
-### Read latency (avg of 5 `get_state` calls = cost per `invoke`)
-
-| turns | ctx | add_msgs | delta |
-|------:|----:|---------:|------:|
-| 10 | ~2K tok | 0.1ms | 0.2ms |
-| 25 | ~5K tok | 0.2ms | 0.5ms |
-| 50 | ~10K tok | 0.4ms | 1.5ms |
-| 100 | ~20K tok | 0.7ms | 4.8ms |
-| 500 | ~100K tok | 5.8ms | 114.9ms |
-
-**This cost is paid once per `invoke`/`stream` call, not per node.** Within a single invocation, all channels are loaded into memory once at the start and shared across every node — there is no per-node reconstruction. The 114.9ms at 500 turns is what you pay each time a user sends a new message, not on each step of the graph.
-
-## How it works
-
-**Write:** `DeltaChannel.checkpoint()` always emits `DeltaChannelSentinel()` — a tiny marker (zero payload bytes) stored in `checkpoint_blobs`. Per-step writes flow into `checkpoint_writes` as they normally do for every channel.
-
-**Read:** The saver detects `DeltaChannelSentinel` values in `channel_values` and replaces them by calling `get_channel_writes` / `aget_channel_writes`, which walks the ancestor checkpoint chain and collects all writes for that channel (oldest→newest). `DeltaChannel.from_checkpoint()` replays those writes through the operator to reconstruct the full value.
-
-**Saver implementations:**
-- `InMemorySaver` — direct dict traversal of `self.storage` and `self.writes`, no I/O
-- `PostgresSaver` (sync + async) — two queries: one cheap ID walk across the thread, one `ANY()` fetch of writes; no recursive CTE
-- All other savers — `BaseCheckpointSaver.get_channel_writes` fallback via `list()`, with a re-entrancy guard to prevent infinite recursion
-
-## Changes
-
-**`libs/checkpoint`**
-- `base/__init__.py` — add `DeltaChannelSentinel` marker dataclass; add `get_channel_writes` / `aget_channel_writes` to `BaseCheckpointSaver` with a `list()`-based fallback and re-entrancy guard
-
-**`libs/checkpoint/memory`**
-- `memory/__init__.py` — `get_channel_writes` via direct dict traversal; `_resolve_delta_channels` helper called in `get_tuple` / `aget_tuple` to replace sentinels with reconstructed write lists
-
-**`libs/langgraph`**
-- `channels/delta.py` — `DeltaChannel` implementation: `checkpoint()` always emits sentinel, `from_checkpoint()` replays writes list
-- `channels/__init__.py` — export `DeltaChannel`
-- `graph/state.py` — recognize `DeltaChannel` as a valid channel annotation
-- `pregel/_checkpoint.py` / `pregel/_loop.py` — wire `after_checkpoint` hook; call it after each checkpointing step so `DeltaChannel` can advance internal state
-
-**`libs/checkpoint-postgres`**
-- `postgres/base.py` — `_get_channel_writes_cur` two-query ancestor walk (sync); `_resolve_delta_channels` called after `_load_blobs`
-- `postgres/aio.py` — `_aget_channel_writes_cur` (async counterpart)
-
-## Open questions
-
-**Should we add a compile-time capability check?**
-
-Currently misconfiguring `DeltaChannel` with an unsupported saver only errors at runtime on first reload. A protocol-based check at `compile()` time would give an early warning without requiring a manual boolean flag.
-
-**`snapshot_every` for bounded reconstruction cost?**
-
-Both per-invoke read latency and total write wall time grow O(N) per invoke / O(N²) total as the conversation lengthens. A `snapshot_every` parameter — periodically store a full snapshot in `checkpoint_blobs` to cap chain depth — would bound reconstruction cost and is a natural follow-up once the core design is stable.
-
-## Backwards compatibility
-
-| Scenario | Behaviour |
-|----------|-----------|
-| Existing graph using `add_messages` | Unaffected — no code or schema changes |
-| `DeltaChannel` loading an old full-list checkpoint blob | Handled via backwards-compat path in `from_checkpoint` |
-| `DeltaChannel` with `InMemorySaver` or `PostgresSaver` | Fully supported |
-| Time-travel to a past checkpoint | Ancestor walk uses the version at that checkpoint — correct by construction |
-| `Overwrite` value | Resets the effective chain; reconstruction starts from that step |
-
-## Test plan
-
-- [x] `DeltaChannel` unit tests: `update` → `checkpoint` lifecycle, `from_checkpoint` chain replay, backwards-compat with plain list, `Overwrite` resets chain
-- [x] `InMemorySaver` `get_channel_writes`: assembles write list from dict storage
-- [x] Serde round-trip for `DeltaChannelSentinel`
-- [x] End-to-end graph tests: multi-turn conversations accumulate correctly, time-travel reconstructs correct partial history
-- [x] `PostgresSaver` two-query chain reconstruction (sync + async)
-- [x] `BaseCheckpointSaver` fallback path via `list()` with re-entrancy guard
-- [x] Storage benchmark: `DeltaChannel` uses strictly less storage than `add_messages` at all measured turn counts
-
----
-
-## Changes from previous base branch
-
-The previous version stored `DeltaValue` objects (containing the per-step writes) directly in `checkpoint_blobs` and used a `DeltaChainValue` to represent the assembled chain. Reconstruction required a dedicated `get_delta_chain` / `aget_delta_chain` protocol and a recursive CTE in Postgres.
-
-This version pivots to a simpler design:
-- **Sentinel in blobs, writes in `checkpoint_writes`** — `checkpoint_blobs` stores only a zero-byte `DeltaChannelSentinel` marker. The actual per-step data already lives in `checkpoint_writes` (written unconditionally by every checkpointer), so blob storage is essentially free. This is why storage savings jump to 1245x at 500 turns.
-- **No custom serde type for the delta payload** — `DeltaValue` / `DeltaChainValue` and the `"delta"` serde type tag are gone. Writes are deserialized with the same serde path they were originally written with.
-- **Postgres: two queries instead of a recursive CTE** — fetch all `(checkpoint_id, parent_checkpoint_id)` pairs for the thread, walk the ancestor chain in Python, then fetch writes with a plain `ANY()` filter.
-- **Universal fallback on `BaseCheckpointSaver`** — the base class now provides `get_channel_writes` via `list()`, so any third-party saver works without modification.
-- **`snapshot_every` removed** — deferred as a follow-up; the simpler design is easier to reason about and delivers larger storage savings.