perf(sdk): lazy-load langgraph_sdk top-level exports

Converting __init__.py to use __getattr__ defers loading of Auth,
get_client/get_sync_client, Encryption, and EncryptionContext until
first access. This removes ~13ms from langgraph.runtime import time,
since importing BaseUser from langgraph_sdk.auth.types no longer
triggers the full client/auth/encryption module graph.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.gitignore

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

docs/superpowers/specs/2026-04-17-diff-channel-design.md

@@ -0,0 +1,405 @@
+# DiffChannel: Incremental Checkpoint Storage for Append-Style Reducers
+
+**Date:** 2026-04-17  
+**Status:** Approved for implementation  
+**Scope:** `libs/checkpoint`, `libs/langgraph`, `libs/checkpoint-postgres`
+
+---
+
+## Motivation
+
+LangGraph checkpoints today store the **full accumulated value** of every channel on every step. For a `messages` channel backed by `add_messages`, this means each checkpoint blob contains the entire conversation history. Storage cost grows O(N²) in the number of turns: step 1 stores 1 message, step 100 stores 100 messages, step 1000 stores 1000 messages. For long-running agentic conversations with high-token messages this is untenable.
+
+The fix is to store only the **delta** (new writes) per step, reconstructing the full accumulated value at load time by replaying the chain. This is an opt-in mechanism — existing graphs are unaffected.
+
+---
+
+## Non-Goals
+
+- **Compaction / materialized snapshots**: deferred. Load cost stays O(N) blob fetches but those fetches are batched into a single query — acceptable for now.
+- **SQLite saver support**: SQLite stores all channel values inline in one row (no per-channel blob table). Deferred to a follow-up.
+- **Automatic migration** of existing `BinaryOperatorAggregate` channels: users opt in explicitly. Old checkpoints load correctly via the backwards-compatibility path in `from_checkpoint`.
+
+---
+
+## Architecture Overview
+
+```
+User state definition
+  └── Annotated[list[AnyMessage], DiffChannel(add_messages)]
+
+Write path (per superstep)
+  DiffChannel.update()       — apply operator, accumulate writes in _pending
+  DiffChannel.checkpoint()   — return DiffDelta(delta=_pending, prev_version=_base_version)
+  serde.dumps_typed()        — serialize DiffDelta as ("diff", msgpack_bytes)
+  saver.put()                — store blob at (thread_id, ns, "messages", version_N)
+  DiffChannel.after_checkpoint(version_N) — advance _base_version, clear _pending
+
+Read path (on graph load or time-travel)
+  saver.get_tuple()          — fetch current-version blob per channel
+  saver._load_blobs()        — detect "diff" type → follow chain to reconstruct DiffChainValue
+  DiffChannel.from_checkpoint(DiffChainValue) — replay deltas with operator → full list
+  DiffChannel.after_checkpoint(version_N)     — set _base_version for next write
+```
+
+The pregel layer (`_checkpoint.py`, `_loop.py`) is unchanged except for two small additions to call the new `after_checkpoint` hook. The saver public interface (`BaseCheckpointSaver`) gains no new methods. All chain-following logic lives inside each saver's private `_load_blobs`.
+
+---
+
+## New Protocol Types
+
+**Location:** `libs/checkpoint/langgraph/checkpoint/base/__init__.py`
+
+Two dataclasses form the contract between `DiffChannel` and savers:
+
+```python
+@dataclass
+class DiffDelta:
+    """Returned by DiffChannel.checkpoint(). Written to the blob store."""
+    delta: list[Any]           # raw writes passed to update() this step
+    prev_version: str | None   # version of the previous diff blob; None = chain root
+```
+
+```python
+@dataclass
+class DiffChainValue:
+    """Passed to DiffChannel.from_checkpoint(). Assembled by _load_blobs()."""
+    base: list[Any] | None     # starting accumulated value (None = empty start)
+    deltas: list[list[Any]]    # write-sets ordered oldest → newest
+```
+
+`DiffDelta` lives in the checkpoint base package (not the channel module) so savers can import it without creating a circular dependency. `DiffChainValue` is there for the same reason.
+
+---
+
+## `BaseChannel.after_checkpoint()` Hook
+
+**Location:** `libs/langgraph/langgraph/channels/base.py`
+
+```python
+def after_checkpoint(self, version: Any) -> None:
+    """Called after checkpoint() (with the new version) and after from_checkpoint()
+    (with the current version). No-op by default; DiffChannel overrides."""
+    pass
+```
+
+This is a **non-abstract, no-op default** — fully backwards compatible. All existing channels inherit it silently. It is NOT in the abstract interface.
+
+---
+
+## `DiffChannel[V]`
+
+**Location:** `libs/langgraph/langgraph/channels/diff.py` (new file)
+
+### Internal state
+
+| Attribute | Type | Description |
+|---|---|---|
+| `value` | `list[V]` | Full accumulated value (the reconstructed list) |
+| `operator` | `Callable` | The binary reducer (e.g. `add_messages`) |
+| `_pending` | `list[Any]` | Raw writes accumulated since last `after_checkpoint` call |
+| `_base_version` | `str \| None` | Version this channel was last checkpointed at (= `prev_version` for next delta) |
+| `_overwritten` | `bool` | True if an `Overwrite` was applied since last `after_checkpoint`; makes next blob a chain root |
+
+### `update(values)`
+
+Mirrors `BinaryOperatorAggregate.update()` with two additions:
+
+1. For each non-Overwrite value: apply `self.operator(self.value, value)` as before; **also append the raw incoming value to `self._pending`**.
+2. For an `Overwrite(v)` value: set `self.value = v`; set `self._pending = list(v)` (full value becomes the new delta); set `self._overwritten = True`.
+
+The key: `_pending` stores the **incoming writes** (what was passed to `update()`), not the diff of `self.value`. This is important because `add_messages` handles removal and update-by-ID — replaying the writes with `operator` during reconstruction applies that logic correctly.
+
+### `checkpoint()`
+
+```python
+def checkpoint(self) -> DiffDelta:
+    return DiffDelta(
+        delta=self._pending[:],
+        prev_version=None if self._overwritten else self._base_version,
+    )
+```
+
+- Normal step: `prev_version = self._base_version` → chain link
+- After Overwrite: `prev_version = None` → chain root (reconstruction stops here and uses `delta` as the full base value)
+
+Returns `DiffDelta`, never the raw accumulated list. The serde handles serialization.
+
+### `from_checkpoint(checkpoint)`
+
+```python
+def from_checkpoint(self, checkpoint) -> Self:
+    new = DiffChannel(self.typ, self.operator)
+    new.key = self.key
+    if checkpoint is MISSING:
+        new.value = []
+    elif isinstance(checkpoint, DiffChainValue):
+        accumulated = checkpoint.base or []
+        for step_writes in checkpoint.deltas:
+            # Mirror update() exactly: apply each write individually so operator
+            # semantics (e.g. add_messages ID-based removal) are respected.
+            for write in step_writes:
+                accumulated = new.operator(accumulated, write)
+        new.value = accumulated
+    elif isinstance(checkpoint, DiffDelta):
+        # Unsupported saver: _load_blobs returned a raw DiffDelta instead of
+        # assembling a DiffChainValue. Raise rather than silently losing history.
+        raise ValueError(
+            "DiffChannel received a raw DiffDelta from the checkpoint saver. "
+            "Your saver does not support incremental channel storage. "
+            "Use InMemorySaver or PostgresSaver."
+        )
+    else:
+        # Backwards compat: plain list from old BinaryOperatorAggregate checkpoint.
+        new.value = checkpoint
+    new._pending = []
+    new._base_version = None  # set by the subsequent after_checkpoint() call
+    return new
+```
+
+The operator is available on `self` (the channel spec) so reconstruction is correct for any reducer — the saver never needs to know about `add_messages`.
+
+`_pending` stores **individual writes** (each `value` from `update()`'s `values` sequence), so each `step_writes` list in `DiffChainValue.deltas` is replayed write-by-write — identical to the `update()` loop.
+
+### `after_checkpoint(version)`
+
+```python
+def after_checkpoint(self, version: Any) -> None:
+    if version != self._base_version:
+        self._base_version = version
+        self._pending = []
+        self._overwritten = False
+```
+
+No-op when `version == self._base_version` (channel wasn't updated this step — blob was not written). Clears `_pending` and advances `_base_version` when the channel was actually checkpointed.
+
+### Opt-in API
+
+```python
+from langgraph.channels.diff import DiffChannel
+
+class State(TypedDict):
+    messages: Annotated[list[AnyMessage], DiffChannel(add_messages)]
+```
+
+`StateGraph` already handles `BaseChannel` instances as annotation metadata — `DiffChannel` inherits this without any changes to `StateGraph`.
+
+---
+
+## Serde Extension
+
+**Location:** `libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py`
+
+Add one branch to `dumps_typed` (before the `else` msgpack fallback), using the existing module-level `_msgpack_enc` so message ext-types (Pydantic v2, etc.) are handled correctly:
+
+```python
+elif isinstance(obj, DiffDelta):
+    return "diff", _msgpack_enc({"d": obj.delta, "p": obj.prev_version})
+```
+
+Add one branch to `loads_typed` so savers can decode diff blobs without importing `ormsgpack` directly:
+
+```python
+elif type_ == "diff":
+    return ormsgpack.unpackb(
+        data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
+    )
+    # returns {"d": [writes...], "p": prev_version_str_or_none}
+```
+
+Savers call `serde.loads_typed(("diff", raw_bytes))` to decode a diff blob into `{"d": ..., "p": ...}`, then check `type_tag == "diff"` to trigger chain traversal. The serde layer is the only place that knows about `ormsgpack`.
+
+---
+
+## Saver Changes
+
+### InMemorySaver
+
+**`put()` — `libs/checkpoint/langgraph/checkpoint/memory/__init__.py`**
+
+No change needed. The existing `self.serde.dumps_typed(values[k])` call already handles `DiffDelta` via the new serde branch above, storing it as `("diff", bytes)`.
+
+**`_load_blobs()` — same file**
+
+After checking `vv[0] != "empty"`, add a branch for `"diff"` before calling `serde.loads_typed`:
+
+```python
+def _load_blobs(self, thread_id, checkpoint_ns, versions):
+    channel_values = {}
+    diff_channels = {}  # channel_name -> current_version for diff channels
+
+    for k, v in versions.items():
+        kk = (thread_id, checkpoint_ns, k, v)
+        if kk not in self.blobs:
+            continue
+        type_tag, blob_bytes = self.blobs[kk]
+        if type_tag == "diff":
+            diff_channels[k] = v  # handle below
+        elif type_tag != "empty":
+            channel_values[k] = self.serde.loads_typed((type_tag, blob_bytes))
+
+    for k, current_version in diff_channels.items():
+        # Follow chain: newest → oldest, then reverse
+        chain_deltas = []
+        base = None
+        version = current_version
+        while version is not None:
+            kk = (thread_id, checkpoint_ns, k, version)
+            if kk not in self.blobs:
+                break
+            type_tag, blob_bytes = self.blobs[kk]
+            if type_tag == "diff":
+                # Use serde so we don't need to import ormsgpack directly
+                payload = self.serde.loads_typed((type_tag, blob_bytes))
+                chain_deltas.append(payload["d"])
+                version = payload["p"]  # prev_version; None = root
+            else:
+                # Old non-diff blob encountered: treat as base accumulated value
+                base = self.serde.loads_typed((type_tag, blob_bytes))
+                break
+        chain_deltas.reverse()
+        channel_values[k] = DiffChainValue(base=base, deltas=chain_deltas)
+
+    return channel_values
+```
+
+Each blob lookup is O(1) on the dict. Total: N dict lookups for a chain of depth N. Memory usage is identical to loading a single full-list blob (same total bytes, split across N entries).
+
+### PostgresSaver
+
+**`_load_blobs()` — `libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py`**
+
+The existing `SELECT_SQL` fetches one blob per channel via a JOIN. After running that query, detect any `"diff"` channels in the result and issue one additional range query:
+
+```python
+def _load_blobs(self, blob_values):
+    if not blob_values:
+        return {}
+
+    result = {}
+    diff_channels = {}  # channel_name -> current_version (as str)
+
+    for k, t, v in blob_values:
+        channel = k.decode()
+        type_tag = t.decode()
+        if type_tag == "diff":
+            # Decode via serde — no direct ormsgpack import needed
+            payload = self.serde.loads_typed((type_tag, v))
+            diff_channels[channel] = payload  # store for chain fetch
+        elif type_tag != "empty":
+            result[channel] = self.serde.loads_typed((type_tag, v))
+
+    if diff_channels:
+        result.update(self._load_diff_chains(diff_channels))
+
+    return result
+```
+
+`_load_diff_chains` issues one SQL query per diff channel (typically just `messages`):
+
+```sql
+SELECT version, type, blob
+FROM checkpoint_blobs
+WHERE thread_id = %s
+  AND checkpoint_ns = %s
+  AND channel = %s
+  AND version <= %s
+ORDER BY version ASC
+```
+
+In Python, iterate rows in ascending version order: if `type = "diff"`, accumulate the delta; if any other type is encountered, treat it as the base accumulated value and stop. Return `DiffChainValue(base=..., deltas=[...])`.
+
+This results in **at most 2 queries total** for a graph with one `DiffChannel` — existing behaviour for all other channels is unchanged.
+
+**`put()` / `_dump_blobs()`**
+
+No change needed. `_dump_blobs` calls `self.serde.dumps_typed(v)` for each channel value in `new_versions`. When `v` is a `DiffDelta`, the serde produces `("diff", bytes)` which is stored as `type = "diff"` in `checkpoint_blobs`. The `ON CONFLICT DO NOTHING` semantics are preserved.
+
+### SQLite
+
+Deferred. `SqliteSaver` stores the entire checkpoint as a single serialized row — it has no per-channel blob table. Supporting `DiffChannel` on SQLite would require adding a new blobs table, which is a separate migration tracked separately.
+
+---
+
+## Pregel Layer Changes
+
+### `channels_from_checkpoint` — `libs/langgraph/langgraph/pregel/_checkpoint.py`
+
+After constructing each channel from its checkpoint value, call `after_checkpoint` so the channel records its current version:
+
+```python
+channels = {}
+for k, v in channel_specs.items():
+    ch = v.from_checkpoint(checkpoint["channel_values"].get(k, MISSING))
+    ch.after_checkpoint(checkpoint["channel_versions"].get(k))
+    channels[k] = ch
+return channels, managed_specs
+```
+
+Existing channels get the no-op `after_checkpoint`. `DiffChannel` uses it to set `_base_version`.
+
+### `PregelLoop._put_checkpoint` — `libs/langgraph/langgraph/pregel/_loop.py`
+
+After `create_checkpoint(self.checkpoint, self.channels, self.step, ...)` returns and `do_checkpoint is True` and `self.channels is not None`, iterate channels and notify:
+
+```python
+if do_checkpoint and self.channels:
+    for k, ch in self.channels.items():
+        ch.after_checkpoint(self.checkpoint["channel_versions"].get(k))
+```
+
+This is called after `create_checkpoint` updates `self.checkpoint["channel_versions"]`, so `get(k)` returns the new version for updated channels and the old version for unchanged ones. `DiffChannel.after_checkpoint` only clears `_pending` when `version != _base_version`, so unchanged channels are no-ops.
+
+---
+
+## Backwards Compatibility
+
+| Scenario | Behaviour |
+|---|---|
+| Existing graph using `add_messages` (BinaryOperatorAggregate) | Unaffected — no code changes, no data migration |
+| New graph with `DiffChannel`, loading old checkpoint blobs | `from_checkpoint` receives a plain `list` → used directly as accumulated value |
+| `DiffChannel` with `InMemorySaver` or `PostgresSaver` | Fully supported |
+| `DiffChannel` with `SqliteSaver` | `from_checkpoint` receives a raw `DiffDelta` (SqliteSaver stores channel_values inline), raises `ValueError` with a clear message pointing to supported savers |
+| Time-travel / fork to past checkpoint | Chain traversal uses the version at that checkpoint → reconstruction is correct |
+| `update_state` | Treated as a normal step: writes are deltas chained to history |
+| `Overwrite` value | Resets chain: next blob has `prev_version=None`; reconstruction starts fresh |
+
+---
+
+## Testing Strategy
+
+1. **Unit tests for `DiffChannel`** (`libs/langgraph/tests/`):
+   - `update` → `checkpoint` → `after_checkpoint` → `checkpoint` lifecycle (2 steps, verify delta isolation)
+   - `from_checkpoint(DiffChainValue)` correctly replays multi-step chains using the operator
+   - `from_checkpoint(plain_list)` backwards-compat path
+   - `Overwrite` creates a root blob (`prev_version=None`) and reconstruction ignores prior chain
+   - `after_checkpoint` no-ops when version is unchanged
+
+2. **Integration tests with `InMemorySaver`** (`libs/langgraph/tests/`):
+   - 10-step conversation: verify final loaded state equals full accumulated messages
+   - Time-travel: fork to step 5, verify only messages 1–5 are present
+   - Mixed graph: some channels `BinaryOperatorAggregate`, one `DiffChannel` — both reconstruct correctly
+
+3. **Serde tests** (`libs/checkpoint/tests/`):
+   - `DiffDelta` round-trips through `dumps_typed` / saver storage
+   - Old `"msgpack"` blob for a channel → `DiffChannel.from_checkpoint` handles it
+
+4. **Postgres integration tests** (`libs/checkpoint-postgres/tests/`):
+   - Range query reconstructs correct full list after N steps
+   - Time-travel to checkpoint M reconstructs correct list of M messages
+
+---
+
+## Files Changed
+
+| File | Change |
+|---|---|
+| `libs/checkpoint/langgraph/checkpoint/base/__init__.py` | Add `DiffDelta`, `DiffChainValue` dataclasses |
+| `libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py` | Add `"diff"` branch in `dumps_typed` |
+| `libs/checkpoint/langgraph/checkpoint/memory/__init__.py` | Chain traversal in `_load_blobs` |
+| `libs/langgraph/langgraph/channels/base.py` | Add no-op `after_checkpoint` method |
+| `libs/langgraph/langgraph/channels/diff.py` | **New file** — `DiffChannel` implementation |
+| `libs/langgraph/langgraph/channels/__init__.py` | Export `DiffChannel` |
+| `libs/langgraph/langgraph/pregel/_checkpoint.py` | Call `after_checkpoint` in `channels_from_checkpoint` |
+| `libs/langgraph/langgraph/pregel/_loop.py` | Call `after_checkpoint` after `create_checkpoint` |
+| `libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py` | Range-query chain reconstruction in `_load_blobs` |

libs/checkpoint-conformance/uv.lock

@@ -306,7 +306,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.7.3"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -319,9 +319,9 @@ dependencies = [
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     { name = "zstandard" },
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+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
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+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
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@@ -623,7 +623,7 @@ wheels = [
 
 [[package]]
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-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -634,9 +634,9 @@ dependencies = [
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+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
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 [[package]]

libs/checkpoint-postgres/README.md

@@ -6,6 +6,11 @@ Implementation of LangGraph CheckpointSaver that uses Postgres.
 
 By default `langgraph-checkpoint-postgres` installs `psycopg` (Psycopg 3) without any extras. However, you can choose a specific installation that best suits your needs [here](https://www.psycopg.org/psycopg3/docs/basic/install.html) (for example, `psycopg[binary]`).
 
+## Security
+
+> [!IMPORTANT]
+> Set `LANGGRAPH_STRICT_MSGPACK=true` or pass an explicit `allowed_msgpack_modules` list when creating your checkpointer. This restricts checkpoint deserialization to known-safe types, preventing code execution if the database is compromised. See the [langgraph-checkpoint README](https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint#serde) for details.
+
 ## Usage
 
 > [!IMPORTANT]

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

@@ -430,6 +430,43 @@ class PostgresSaver(BasePostgresSaver):
                 with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
+    def get_channel_blob(
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> Any:
+        """Look up a channel blob by checkpoint ID + channel via checkpoint_blobs."""
+        with self._cursor() as cur:
+            cur.execute(
+                """
+                SELECT cb.type, cb.blob
+                FROM checkpoint_blobs cb
+                WHERE cb.thread_id = %s
+                  AND cb.checkpoint_ns = %s
+                  AND cb.channel = %s
+                  AND cb.version = (
+                      SELECT checkpoint->'channel_versions'->>%s
+                      FROM checkpoints
+                      WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id = %s
+                  )
+                """,
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    channel,
+                    channel,
+                    thread_id,
+                    checkpoint_ns,
+                    checkpoint_id,
+                ),
+            )
+            row = cur.fetchone()
+        if row is None:
+            return NotImplemented
+        return self.serde.loads_typed((row["type"], row["blob"]))
+
     def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
         Convert a database row into a CheckpointTuple object.
@@ -442,6 +479,13 @@ class PostgresSaver(BasePostgresSaver):
             including its configuration, metadata, parent checkpoint (if any),
             and pending writes.
         """
+        with self._cursor() as cur:
+            channel_values = self._load_blobs(
+                value["channel_values"],
+                thread_id=value["thread_id"],
+                checkpoint_ns=value["checkpoint_ns"],
+                cur=cur,
+            )
         return CheckpointTuple(
             {
                 "configurable": {
@@ -454,7 +498,7 @@ class PostgresSaver(BasePostgresSaver):
                 **value["checkpoint"],
                 "channel_values": {
                     **(value["checkpoint"].get("channel_values") or {}),
-                    **self._load_blobs(value["channel_values"]),
+                    **channel_values,
                 },
             },
             value["metadata"],

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

@@ -391,6 +391,43 @@ class AsyncPostgresSaver(BasePostgresSaver):
                 async with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
+    async def aget_channel_blob(
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> Any:
+        """Async look up of a channel blob by checkpoint ID + channel name."""
+        async with self._cursor() as cur:
+            await cur.execute(
+                """
+                SELECT cb.type, cb.blob
+                FROM checkpoint_blobs cb
+                WHERE cb.thread_id = %s
+                  AND cb.checkpoint_ns = %s
+                  AND cb.channel = %s
+                  AND cb.version = (
+                      SELECT checkpoint->'channel_versions'->>%s
+                      FROM checkpoints
+                      WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id = %s
+                  )
+                """,
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    channel,
+                    channel,
+                    thread_id,
+                    checkpoint_ns,
+                    checkpoint_id,
+                ),
+            )
+            row = await cur.fetchone()
+        if row is None:
+            return NotImplemented
+        return self.serde.loads_typed((row["type"], row["blob"]))
+
     async def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
         Convert a database row into a CheckpointTuple object.
@@ -403,11 +440,19 @@ class AsyncPostgresSaver(BasePostgresSaver):
             including its configuration, metadata, parent checkpoint (if any),
             and pending writes.
         """
+        thread_id = value["thread_id"]
+        checkpoint_ns = value["checkpoint_ns"]
+        blob_values = value["channel_values"]
+
+        channel_values: dict[str, Any] = {}
+        if blob_values:
+            channel_values = self._load_blobs(blob_values)
+
         return CheckpointTuple(
             {
                 "configurable": {
-                    "thread_id": value["thread_id"],
-                    "checkpoint_ns": value["checkpoint_ns"],
+                    "thread_id": thread_id,
+                    "checkpoint_ns": checkpoint_ns,
                     "checkpoint_id": value["checkpoint_id"],
                 }
             },
@@ -415,15 +460,15 @@ class AsyncPostgresSaver(BasePostgresSaver):
                 **value["checkpoint"],
                 "channel_values": {
                     **(value["checkpoint"].get("channel_values") or {}),
-                    **self._load_blobs(value["channel_values"]),
+                    **channel_values,
                 },
             },
             value["metadata"],
             (
                 {
                     "configurable": {
-                        "thread_id": value["thread_id"],
-                        "checkpoint_ns": value["checkpoint_ns"],
+                        "thread_id": thread_id,
+                        "checkpoint_ns": checkpoint_ns,
                         "checkpoint_id": value["parent_checkpoint_id"],
                     }
                 }

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

@@ -185,15 +185,22 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
         )
 
     def _load_blobs(
-        self, blob_values: list[tuple[bytes, bytes, bytes]]
+        self,
+        blob_values: list[tuple[bytes, bytes, bytes]],
+        *,
+        thread_id: str = "",
+        checkpoint_ns: str = "",
+        cur: Any = None,
     ) -> dict[str, Any]:
         if not blob_values:
             return {}
-        return {
-            k.decode(): self.serde.loads_typed((t.decode(), v))
-            for k, t, v in blob_values
-            if t.decode() != "empty"
-        }
+        result: dict[str, Any] = {}
+        for k, t, v in blob_values:
+            channel = k.decode()
+            type_tag = t.decode()
+            if type_tag != "empty":
+                result[channel] = self.serde.loads_typed((type_tag, v))
+        return result
 
     def _dump_blobs(
         self,

libs/checkpoint-postgres/tests/test_async.py

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

libs/checkpoint-postgres/uv.lock

@@ -259,7 +259,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.2"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -382,7 +382,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.6.4"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -392,11 +392,12 @@ dependencies = [
     { name = "requests" },
     { name = "requests-toolbelt" },
     { name = "uuid-utils" },
+    { name = "xxhash" },
     { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/e7/85/9c7933052a997da1b85bc5c774f3865e9b1da1c8d71541ea133178b13229/langsmith-0.6.4.tar.gz", hash = "sha256:36f7223a01c218079fbb17da5e536ebbaf5c1468c028abe070aa3ae59bc99ec8", size = 919964, upload-time = "2026-01-15T20:02:28.873Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/66/0f/09a6637a7ba777eb307b7c80852d9ee26438e2bdafbad6fcc849ff9d9192/langsmith-0.6.4-py3-none-any.whl", hash = "sha256:ac4835860160be371042c7adbba3cb267bcf8d96a5ea976c33a8a4acad6c5486", size = 283503, upload-time = "2026-01-15T20:02:26.662Z" },
+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
 ]
 
 [[package]]
@@ -950,7 +951,7 @@ wheels = [
 
 [[package]]
 name = "pytest"
-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -961,9 +962,9 @@ dependencies = [
     { name = "pygments" },
     { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d1/db/7ef3487e0fb0049ddb5ce41d3a49c235bf9ad299b6a25d5780a89f19230f/pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11", size = 1568901, upload-time = "2025-12-06T21:30:51.014Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b", size = 374801, upload-time = "2025-12-06T21:30:49.154Z" },
+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
 ]
 
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 ]
 
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+version = "3.6.0"
+source = { registry = "https://pypi.org/simple" }
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+wheels = [
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+
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 name = "zstandard"
 version = "0.25.0"

libs/checkpoint-sqlite/README.md

@@ -2,6 +2,11 @@
 
 Implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via `aiosqlite`)
 
+## Security
+
+> [!IMPORTANT]
+> Set `LANGGRAPH_STRICT_MSGPACK=true` or pass an explicit `allowed_msgpack_modules` list when creating your checkpointer. This restricts checkpoint deserialization to known-safe types, preventing code execution if the database is compromised. See the [langgraph-checkpoint README](https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint#serde) for details.
+
 ## Usage
 
 ```python

libs/checkpoint-sqlite/uv.lock

@@ -249,7 +249,7 @@ wheels = [
 
 [[package]]
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+]
+
 [[package]]
 name = "zstandard"
 version = "0.25.0"

libs/checkpoint/README.md

@@ -26,6 +26,9 @@ You must pass these when invoking the graph as part of the configurable part of
 
 `langgraph_checkpoint` also defines protocol for serialization/deserialization (serde) and provides an default implementation (`langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer`) that handles a wide variety of types, including LangChain and LangGraph primitives, datetimes, enums and more.
 
+> [!IMPORTANT]
+> **Checkpoint deserialization security:** By default the serializer allows any Python type found in checkpoint data. New applications should set the environment variable `LANGGRAPH_STRICT_MSGPACK=true` or pass an explicit `allowed_msgpack_modules` list to `JsonPlusSerializer` to restrict deserialization to known-safe types.
+
 ### Pending writes
 
 When a graph node fails mid-execution at a given superstep, LangGraph stores pending checkpoint writes from any other nodes that completed successfully at that superstep, so that whenever we resume graph execution from that superstep we don't re-run the successful nodes.

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

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import copy
+import dataclasses
 import logging
 from collections.abc import AsyncIterator, Collection, Iterator, Mapping, Sequence
 from typing import (  # noqa: UP035
@@ -28,6 +29,26 @@ from langgraph.checkpoint.serde.types import (
 
 V = TypeVar("V", int, float, str)
 PendingWrite = tuple[str, str, Any]
+
+
+@dataclasses.dataclass
+class DeltaValue:
+    """Returned by DeltaChannel.checkpoint(). Represents one step's writes."""
+
+    delta: list[Any]
+    prev_checkpoint_id: (
+        str | None
+    )  # ID of checkpoint containing previous blob; None = chain root
+
+
+@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__)
 
 
@@ -457,6 +478,42 @@ class BaseCheckpointSaver(Generic[V]):
         """
         raise NotImplementedError
 
+    def get_channel_blob(
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> Any:
+        """Look up a single channel blob by checkpoint ID + channel name.
+
+        Returns NotImplemented if this saver does not support efficient
+        per-channel-version blob lookup. The pregel layer will fall back to
+        get_tuple() traversal in that case.
+
+        Savers with a dedicated blob store (InMemorySaver, PostgresSaver)
+        should override this for O(1) performance.
+        """
+        return NotImplemented
+
+    async def aget_channel_blob(
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> Any:
+        """Look up a single channel blob by checkpoint ID + channel name (async).
+
+        Returns NotImplemented if this saver does not support efficient
+        per-channel-version blob lookup. The pregel layer will fall back to
+        aget_tuple() traversal in that case.
+
+        Savers with a dedicated blob store (InMemorySaver, PostgresSaver)
+        should override this for O(1) performance.
+        """
+        return NotImplemented
+
     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

@@ -126,12 +126,46 @@ class InMemorySaver(
         channel_values: dict[str, Any] = {}
         for k, v in versions.items():
             kk = (thread_id, checkpoint_ns, k, v)
-            if kk in self.blobs:
-                vv = self.blobs[kk]
-                if vv[0] != "empty":
-                    channel_values[k] = self.serde.loads_typed(vv)
+            if kk not in self.blobs:
+                continue
+            vv = self.blobs[kk]
+            if vv[0] != "empty":
+                channel_values[k] = self.serde.loads_typed(vv)
         return channel_values
 
+    def get_channel_blob(
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> Any:
+        """Fast-path blob lookup: checkpoint → channel version → blob."""
+        ns_storage = self.storage.get(thread_id, {}).get(checkpoint_ns, {})
+        entry = ns_storage.get(checkpoint_id)
+        if entry is None:
+            return NotImplemented
+        checkpoint = self.serde.loads_typed(entry[0])
+        version = checkpoint["channel_versions"].get(channel)
+        if version is None:
+            return NotImplemented
+        kk = (thread_id, checkpoint_ns, channel, version)
+        if kk not in self.blobs:
+            return NotImplemented
+        vv = self.blobs[kk]
+        if vv[0] == "empty":
+            return NotImplemented
+        return self.serde.loads_typed(vv)
+
+    async def aget_channel_blob(
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        checkpoint_id: str,
+        channel: str,
+    ) -> Any:
+        return self.get_channel_blob(thread_id, checkpoint_ns, checkpoint_id, channel)
+
     def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
         """Get a checkpoint tuple from the in-memory storage.
 

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

@@ -1,3 +1,10 @@
+"""Msgpack deserialization safety controls.
+
+Set ``LANGGRAPH_STRICT_MSGPACK=true`` to restrict checkpoint deserialization
+to the types listed in ``SAFE_MSGPACK_TYPES``.  Without this, any Python
+callable stored in checkpoint data will be imported and executed on load.
+"""
+
 import os
 from collections.abc import Iterable
 from typing import cast
@@ -73,6 +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

@@ -47,6 +47,12 @@ EMPTY_BYTES = b""
 logger = logging.getLogger(__name__)
 
 
+def _is_delta_value(obj: Any) -> bool:
+    from langgraph.checkpoint.base import DeltaValue  # lazy import avoids circular dep
+
+    return isinstance(obj, DeltaValue)
+
+
 class JsonPlusSerializer(SerializerProtocol):
     """Serializer that uses ormsgpack, with optional fallbacks.
 
@@ -56,6 +62,10 @@ class JsonPlusSerializer(SerializerProtocol):
         class and called within the Pregel loop. It should not be used on untrusted
         python objects. If an attacker can write directly to your checkpoint database,
         they may be able to trigger code execution when data is deserialized.
+
+        Set the environment variable ``LANGGRAPH_STRICT_MSGPACK=true`` to restrict
+        deserialization to a built-in allowlist of safe types.  You can also pass
+        an explicit ``allowed_msgpack_modules`` to the constructor.
     """
 
     def __init__(
@@ -70,8 +80,11 @@ class JsonPlusSerializer(SerializerProtocol):
     ) -> None:
         if allowed_msgpack_modules is _lg_msgpack._SENTINEL:
             if _lg_msgpack.STRICT_MSGPACK_ENABLED:
+                # Strict: only SAFE_MSGPACK_TYPES are allowed.
                 allowed_msgpack_modules = None
             else:
+                # Permissive (default): all types allowed with a warning.
+                # Set LANGGRAPH_STRICT_MSGPACK=true to lock this down.
                 allowed_msgpack_modules = True
         self.pickle_fallback = pickle_fallback
         self._allowed_json_modules: set[tuple[str, ...]] | Literal[True] | None = (
@@ -232,6 +245,8 @@ class JsonPlusSerializer(SerializerProtocol):
             return "bytes", obj
         elif isinstance(obj, bytearray):
             return "bytearray", obj
+        elif _is_delta_value(obj):
+            return "delta", _msgpack_enc({"d": obj.delta, "c": obj.prev_checkpoint_id})
         else:
             try:
                 return "msgpack", _msgpack_enc(obj)
@@ -254,6 +269,13 @@ class JsonPlusSerializer(SerializerProtocol):
             return ormsgpack.unpackb(
                 data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
             )
+        elif type_ == "delta":
+            from langgraph.checkpoint.base import DeltaValue  # lazy import
+
+            raw = ormsgpack.unpackb(
+                data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
+            )
+            return DeltaValue(delta=raw["d"], prev_checkpoint_id=raw.get("c"))
         elif self.pickle_fallback and type_ == "pickle":
             return pickle.loads(data_)
         else:
@@ -530,7 +552,8 @@ def _create_msgpack_ext_hook(
             logger.warning(
                 "Deserializing unregistered type %s.%s from checkpoint. "
                 "This will be blocked in a future version. "
-                "Add to allowed_msgpack_modules to silence: [(%r, %r)]",
+                "Set LANGGRAPH_STRICT_MSGPACK=true to block now, or add "
+                "to allowed_msgpack_modules to allow explicitly: [(%r, %r)]",
                 module,
                 name,
                 module,

libs/checkpoint/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.2"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"

libs/checkpoint/tests/test_jsonplus.py

@@ -983,3 +983,31 @@ def test_msgpack_nested_pydantic_serializes_as_dict(
     # No blocking should occur - inner is serialized as dict, not ext
     assert "blocked" not in caplog.text.lower()
     assert result == obj
+
+
+def test_delta_value_serde_round_trip() -> None:
+    from langgraph.checkpoint.base import DeltaValue
+    from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
+    serde = JsonPlusSerializer()
+    original = DeltaValue(
+        delta=[{"type": "human", "content": "hi"}], prev_checkpoint_id="abc-123"
+    )
+    type_tag, blob = serde.dumps_typed(original)
+    assert type_tag == "delta"
+    loaded = serde.loads_typed((type_tag, blob))
+    assert isinstance(loaded, DeltaValue)
+    assert loaded.delta == original.delta
+    assert loaded.prev_checkpoint_id == "abc-123"
+
+
+def test_delta_value_serde_chain_root() -> None:
+    from langgraph.checkpoint.base import DeltaValue
+    from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
+    serde = JsonPlusSerializer()
+    original = DeltaValue(delta=[], prev_checkpoint_id=None)
+    type_tag, blob = serde.dumps_typed(original)
+    loaded = serde.loads_typed((type_tag, blob))
+    assert isinstance(loaded, DeltaValue)
+    assert loaded.prev_checkpoint_id is None

libs/checkpoint/tests/test_memory.py

@@ -308,3 +308,36 @@ def test_memory_saver_with_allowlist_proxy_isolated() -> None:
     assert direct is not None
     expected = obj.model_dump() if hasattr(obj, "model_dump") else obj.dict()
     assert direct.checkpoint["channel_values"]["foo"] == expected
+
+
+class TestInMemorySaverDeltaChannel:
+    def test_get_channel_blob(self) -> None:
+        """get_channel_blob returns the deserialized blob for a checkpoint+channel."""
+        from langgraph.checkpoint.base import DeltaValue, empty_checkpoint
+
+        saver = InMemorySaver()
+        serde = JsonPlusSerializer()
+
+        thread_id, ns, channel = "t1", "", "messages"
+        version = "00000000000000000000000000000001.0000000000000000"
+        delta = DeltaValue(delta=[{"content": "hi"}], prev_checkpoint_id=None)
+        saver.blobs[(thread_id, ns, channel, version)] = serde.dumps_typed(delta)
+
+        cp = empty_checkpoint()
+        cp["id"] = "cp1"
+        cp["channel_versions"][channel] = version
+        saver.storage[thread_id][ns] = {
+            "cp1": (serde.dumps_typed(cp), serde.dumps_typed({}), None)
+        }
+
+        result = saver.get_channel_blob(thread_id, ns, "cp1", channel)
+        assert isinstance(result, DeltaValue)
+        assert result.delta == [{"content": "hi"}]
+        assert result.prev_checkpoint_id is None
+
+    def test_get_channel_blob_missing(self) -> None:
+        """get_channel_blob returns NotImplemented when checkpoint or channel not found."""
+        saver = InMemorySaver()
+        assert (
+            saver.get_channel_blob("t1", "", "no-such-cp", "messages") is NotImplemented
+        )

libs/checkpoint/uv.lock

@@ -286,7 +286,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.2"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -369,7 +369,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.6.4"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -379,11 +379,12 @@ dependencies = [
     { name = "requests" },
     { name = "requests-toolbelt" },
     { name = "uuid-utils" },
+    { name = "xxhash" },
     { name = "zstandard" },
 ]
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+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
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 [[package]]
@@ -1117,7 +1118,7 @@ wheels = [
 
 [[package]]
 name = "pytest"
-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -1128,9 +1129,9 @@ dependencies = [
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 ]
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+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
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 ]
 
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 name = "zstandard"
 version = "0.25.0"

libs/cli/js-examples/yarn.lock

@@ -1086,11 +1086,6 @@
   resolved "https://registry.yarnpkg.com/@types/stack-utils/-/stack-utils-2.0.3.tgz#6209321eb2c1712a7e7466422b8cb1fc0d9dd5d8"
   integrity sha512-9aEbYZ3TbYMznPdcdr3SmIrLXwC/AKZXQeCf9Pgao5CKb8CyHuEX5jzWPTkvregvhRJHcpRO6BFoGW9ycaOkYw==
 
-"@types/uuid@^10.0.0":
-  version "10.0.0"
-  resolved "https://registry.yarnpkg.com/@types/uuid/-/uuid-10.0.0.tgz#e9c07fe50da0f53dc24970cca94d619ff03f6f6d"
-  integrity sha512-7gqG38EyHgyP1S+7+xomFtL+ZNHcKv6DwNaCZmJmo1vgMugyF3TCnXVg4t1uk89mLNwnLtnY3TpOpCOyp1/xHQ==
-
 "@types/yargs-parser@*":
   version "21.0.3"
   resolved "https://registry.yarnpkg.com/@types/yargs-parser/-/yargs-parser-21.0.3.tgz#815e30b786d2e8f0dcd85fd5bcf5e1a04d008f15"
@@ -1782,13 +1777,6 @@ concat-map@0.0.1:
   resolved "https://registry.yarnpkg.com/concat-map/-/concat-map-0.0.1.tgz#d8a96bd77fd68df7793a73036a3ba0d5405d477b"
   integrity sha512-/Srv4dswyQNBfohGpz9o6Yb3Gz3SrUDqBH5rTuhGR7ahtlbYKnVxw2bCFMRljaA7EXHaXZ8wsHdodFvbkhKmqg==
 
-console-table-printer@^2.12.1:
-  version "2.15.0"
-  resolved "https://registry.yarnpkg.com/console-table-printer/-/console-table-printer-2.15.0.tgz#5c808204640b8f024d545bde8aabe5d344dfadc1"
-  integrity sha512-SrhBq4hYVjLCkBVOWaTzceJalvn5K1Zq5aQA6wXC/cYjI3frKWNPEMK3sZsJfNNQApvCQmgBcc13ZKmFj8qExw==
-  dependencies:
-    simple-wcswidth "^1.1.2"
-
 convert-source-map@^2.0.0:
   version "2.0.0"
   resolved "https://registry.yarnpkg.com/convert-source-map/-/convert-source-map-2.0.0.tgz#4b560f649fc4e918dd0ab75cf4961e8bc882d82a"
@@ -3688,16 +3676,12 @@ keyv@^4.5.4:
     json-buffer "3.0.1"
 
 "langsmith@>=0.5.0 <1.0.0":
-  version "0.5.4"
-  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.4.tgz#f75b82b08e30db72a7d1d595b341e9666bd525e5"
-  integrity sha512-qYkNIoKpf0ZYt+cYzrDV+XI3FCexApmZmp8EMs3eDTMv0OvrHMLoxJ9IpkeoXJSX24+GPk0/jXjKx2hWerpy9w==
+  version "0.5.20"
+  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.20.tgz#4021847d2ccd5a86c5eb96060f9bb5f19f80eca5"
+  integrity sha512-ULhLM8RswvQDXufLtNtvclHrWCBx8Cb5UPI6lAZC+8Dq59iHsVPz/3Ac9khWNm1VIvChRsuykixD/WrmzuuA3Q==
   dependencies:
-    "@types/uuid" "^10.0.0"
-    chalk "^4.1.2"
-    console-table-printer "^2.12.1"
-    p-queue "^6.6.2"
-    semver "^7.6.3"
-    uuid "^10.0.0"
+    p-queue "6.6.2"
+    uuid "10.0.0"
 
 leven@^3.1.0:
   version "3.1.0"
@@ -4007,7 +3991,7 @@ p-locate@^5.0.0:
   dependencies:
     p-limit "^3.0.2"
 
-p-queue@^6.6.2:
+p-queue@6.6.2, p-queue@^6.6.2:
   version "6.6.2"
   resolved "https://registry.yarnpkg.com/p-queue/-/p-queue-6.6.2.tgz#2068a9dcf8e67dd0ec3e7a2bcb76810faa85e426"
   integrity sha512-RwFpb72c/BhQLEXIZ5K2e+AhgNVmIejGlTgiB9MzZ0e93GRvqZ7uSi0dvRF7/XIXDeNkra2fNHBxTyPDGySpjQ==
@@ -4303,7 +4287,7 @@ semver@^6.3.1:
   resolved "https://registry.yarnpkg.com/semver/-/semver-6.3.1.tgz#556d2ef8689146e46dcea4bfdd095f3434dffcb4"
   integrity sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA==
 
-semver@^7.5.3, semver@^7.5.4, semver@^7.6.3, semver@^7.7.2, semver@^7.7.3:
+semver@^7.5.3, semver@^7.5.4, semver@^7.7.2, semver@^7.7.3:
   version "7.7.4"
   resolved "https://registry.yarnpkg.com/semver/-/semver-7.7.4.tgz#28464e36060e991fa7a11d0279d2d3f3b57a7e8a"
   integrity sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA==
@@ -4411,11 +4395,6 @@ signal-exit@^4.0.1:
   resolved "https://registry.yarnpkg.com/signal-exit/-/signal-exit-4.1.0.tgz#952188c1cbd546070e2dd20d0f41c0ae0530cb04"
   integrity sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw==
 
-simple-wcswidth@^1.1.2:
-  version "1.1.2"
-  resolved "https://registry.yarnpkg.com/simple-wcswidth/-/simple-wcswidth-1.1.2.tgz#66722f37629d5203f9b47c5477b1225b85d6525b"
-  integrity sha512-j7piyCjAeTDSjzTSQ7DokZtMNwNlEAyxqSZeCS+CXH7fJ4jx3FuJ/mTW3mE+6JLs4VJBbcll0Kjn+KXI5t21Iw==
-
 slash@^3.0.0:
   version "3.0.0"
   resolved "https://registry.yarnpkg.com/slash/-/slash-3.0.0.tgz#6539be870c165adbd5240220dbe361f1bc4d4634"
@@ -4870,7 +4849,7 @@ uri-js@^4.2.2:
   dependencies:
     punycode "^2.1.0"
 
-uuid@^10.0.0:
+uuid@10.0.0, uuid@^10.0.0:
   version "10.0.0"
   resolved "https://registry.yarnpkg.com/uuid/-/uuid-10.0.0.tgz#5a95aa454e6e002725c79055fd42aaba30ca6294"
   integrity sha512-8XkAphELsDnEGrDxUOHB3RGvXz6TeuYSGEZBOjtTtPm2lwhGBjLgOzLHB63IUWfBpNucQjND6d3AOudO+H3RWQ==

libs/cli/js-monorepo-example/yarn.lock

@@ -217,11 +217,6 @@
   resolved "https://registry.yarnpkg.com/@types/json5/-/json5-0.0.29.tgz#ee28707ae94e11d2b827bcbe5270bcea7f3e71ee"
   integrity sha512-dRLjCWHYg4oaA77cxO64oO+7JwCwnIzkZPdrrC71jQmQtlhM556pwKo5bUzqvZndkVbeFLIIi+9TC40JNF5hNQ==
 
-"@types/uuid@^10.0.0":
-  version "10.0.0"
-  resolved "https://registry.yarnpkg.com/@types/uuid/-/uuid-10.0.0.tgz#e9c07fe50da0f53dc24970cca94d619ff03f6f6d"
-  integrity sha512-7gqG38EyHgyP1S+7+xomFtL+ZNHcKv6DwNaCZmJmo1vgMugyF3TCnXVg4t1uk89mLNwnLtnY3TpOpCOyp1/xHQ==
-
 "@typescript-eslint/eslint-plugin@^8.58.0":
   version "8.58.0"
   resolved "https://registry.yarnpkg.com/@typescript-eslint/eslint-plugin/-/eslint-plugin-8.58.0.tgz#ad40e492f1931f46da1bd888e52b9e56df9063aa"
@@ -343,13 +338,6 @@ ajv@^6.14.0:
     json-schema-traverse "^0.4.1"
     uri-js "^4.2.2"
 
-ansi-styles@^4.1.0:
-  version "4.3.0"
-  resolved "https://registry.yarnpkg.com/ansi-styles/-/ansi-styles-4.3.0.tgz#edd803628ae71c04c85ae7a0906edad34b648937"
-  integrity sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg==
-  dependencies:
-    color-convert "^2.0.1"
-
 ansi-styles@^5.0.0:
   version "5.2.0"
   resolved "https://registry.yarnpkg.com/ansi-styles/-/ansi-styles-5.2.0.tgz#07449690ad45777d1924ac2abb2fc8895dba836b"
@@ -508,38 +496,11 @@ camelcase@6:
   resolved "https://registry.yarnpkg.com/camelcase/-/camelcase-6.3.0.tgz#5685b95eb209ac9c0c177467778c9c84df58ba9a"
   integrity sha512-Gmy6FhYlCY7uOElZUSbxo2UCDH8owEk996gkbrpsgGtrJLM3J7jGxl9Ic7Qwwj4ivOE5AWZWRMecDdF7hqGjFA==
 
-chalk@^4.1.2:
-  version "4.1.2"
-  resolved "https://registry.yarnpkg.com/chalk/-/chalk-4.1.2.tgz#aac4e2b7734a740867aeb16bf02aad556a1e7a01"
-  integrity sha512-oKnbhFyRIXpUuez8iBMmyEa4nbj4IOQyuhc/wy9kY7/WVPcwIO9VA668Pu8RkO7+0G76SLROeyw9CpQ061i4mA==
-  dependencies:
-    ansi-styles "^4.1.0"
-    supports-color "^7.1.0"
-
-color-convert@^2.0.1:
-  version "2.0.1"
-  resolved "https://registry.yarnpkg.com/color-convert/-/color-convert-2.0.1.tgz#72d3a68d598c9bdb3af2ad1e84f21d896abd4de3"
-  integrity sha512-RRECPsj7iu/xb5oKYcsFHSppFNnsj/52OVTRKb4zP5onXwVF3zVmmToNcOfGC+CRDpfK/U584fMg38ZHCaElKQ==
-  dependencies:
-    color-name "~1.1.4"
-
-color-name@~1.1.4:
-  version "1.1.4"
-  resolved "https://registry.yarnpkg.com/color-name/-/color-name-1.1.4.tgz#c2a09a87acbde69543de6f63fa3995c826c536a2"
-  integrity sha512-dOy+3AuW3a2wNbZHIuMZpTcgjGuLU/uBL/ubcZF9OXbDo8ff4O8yVp5Bf0efS8uEoYo5q4Fx7dY9OgQGXgAsQA==
-
 concat-map@0.0.1:
   version "0.0.1"
   resolved "https://registry.yarnpkg.com/concat-map/-/concat-map-0.0.1.tgz#d8a96bd77fd68df7793a73036a3ba0d5405d477b"
   integrity sha512-/Srv4dswyQNBfohGpz9o6Yb3Gz3SrUDqBH5rTuhGR7ahtlbYKnVxw2bCFMRljaA7EXHaXZ8wsHdodFvbkhKmqg==
 
-console-table-printer@^2.12.1:
-  version "2.14.6"
-  resolved "https://registry.yarnpkg.com/console-table-printer/-/console-table-printer-2.14.6.tgz#edfe0bf311fa2701922ed509443145ab51e06436"
-  integrity sha512-MCBl5HNVaFuuHW6FGbL/4fB7N/ormCy+tQ+sxTrF6QtSbSNETvPuOVbkJBhzDgYhvjWGrTma4eYJa37ZuoQsPw==
-  dependencies:
-    simple-wcswidth "^1.0.1"
-
 cross-spawn@^7.0.6:
   version "7.0.6"
   resolved "https://registry.yarnpkg.com/cross-spawn/-/cross-spawn-7.0.6.tgz#8a58fe78f00dcd70c370451759dfbfaf03e8ee9f"
@@ -1059,11 +1020,6 @@ has-bigints@^1.0.2:
   resolved "https://registry.yarnpkg.com/has-bigints/-/has-bigints-1.1.0.tgz#28607e965ac967e03cd2a2c70a2636a1edad49fe"
   integrity sha512-R3pbpkcIqv2Pm3dUwgjclDRVmWpTJW2DcMzcIhEXEx1oh/CEMObMm3KLmRJOdvhM7o4uQBnwr8pzRK2sJWIqfg==
 
-has-flag@^4.0.0:
-  version "4.0.0"
-  resolved "https://registry.yarnpkg.com/has-flag/-/has-flag-4.0.0.tgz#944771fd9c81c81265c4d6941860da06bb59479b"
-  integrity sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ==
-
 has-property-descriptors@^1.0.0, has-property-descriptors@^1.0.2:
   version "1.0.2"
   resolved "https://registry.yarnpkg.com/has-property-descriptors/-/has-property-descriptors-1.0.2.tgz#963ed7d071dc7bf5f084c5bfbe0d1b6222586854"
@@ -1372,16 +1328,12 @@ keyv@^4.5.4:
     json-buffer "3.0.1"
 
 "langsmith@>=0.5.0 <1.0.0":
-  version "0.5.4"
-  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.4.tgz#f75b82b08e30db72a7d1d595b341e9666bd525e5"
-  integrity sha512-qYkNIoKpf0ZYt+cYzrDV+XI3FCexApmZmp8EMs3eDTMv0OvrHMLoxJ9IpkeoXJSX24+GPk0/jXjKx2hWerpy9w==
+  version "0.5.20"
+  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.20.tgz#4021847d2ccd5a86c5eb96060f9bb5f19f80eca5"
+  integrity sha512-ULhLM8RswvQDXufLtNtvclHrWCBx8Cb5UPI6lAZC+8Dq59iHsVPz/3Ac9khWNm1VIvChRsuykixD/WrmzuuA3Q==
   dependencies:
-    "@types/uuid" "^10.0.0"
-    chalk "^4.1.2"
-    console-table-printer "^2.12.1"
-    p-queue "^6.6.2"
-    semver "^7.6.3"
-    uuid "^10.0.0"
+    p-queue "6.6.2"
+    uuid "10.0.0"
 
 levn@^0.4.1:
   version "0.4.1"
@@ -1528,7 +1480,7 @@ p-locate@^5.0.0:
   dependencies:
     p-limit "^3.0.2"
 
-p-queue@^6.6.2:
+p-queue@6.6.2, p-queue@^6.6.2:
   version "6.6.2"
   resolved "https://registry.yarnpkg.com/p-queue/-/p-queue-6.6.2.tgz#2068a9dcf8e67dd0ec3e7a2bcb76810faa85e426"
   integrity sha512-RwFpb72c/BhQLEXIZ5K2e+AhgNVmIejGlTgiB9MzZ0e93GRvqZ7uSi0dvRF7/XIXDeNkra2fNHBxTyPDGySpjQ==
@@ -1690,11 +1642,6 @@ semver@^6.3.1:
   resolved "https://registry.yarnpkg.com/semver/-/semver-6.3.1.tgz#556d2ef8689146e46dcea4bfdd095f3434dffcb4"
   integrity sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA==
 
-semver@^7.6.3:
-  version "7.7.2"
-  resolved "https://registry.yarnpkg.com/semver/-/semver-7.7.2.tgz#67d99fdcd35cec21e6f8b87a7fd515a33f982b58"
-  integrity sha512-RF0Fw+rO5AMf9MAyaRXI4AV0Ulj5lMHqVxxdSgiVbixSCXoEmmX/jk0CuJw4+3SqroYO9VoUh+HcuJivvtJemA==
-
 semver@^7.7.3:
   version "7.7.4"
   resolved "https://registry.yarnpkg.com/semver/-/semver-7.7.4.tgz#28464e36060e991fa7a11d0279d2d3f3b57a7e8a"
@@ -1783,11 +1730,6 @@ side-channel@^1.1.0:
     side-channel-map "^1.0.1"
     side-channel-weakmap "^1.0.2"
 
-simple-wcswidth@^1.0.1:
-  version "1.1.2"
-  resolved "https://registry.yarnpkg.com/simple-wcswidth/-/simple-wcswidth-1.1.2.tgz#66722f37629d5203f9b47c5477b1225b85d6525b"
-  integrity sha512-j7piyCjAeTDSjzTSQ7DokZtMNwNlEAyxqSZeCS+CXH7fJ4jx3FuJ/mTW3mE+6JLs4VJBbcll0Kjn+KXI5t21Iw==
-
 stop-iteration-iterator@^1.1.0:
   version "1.1.0"
   resolved "https://registry.yarnpkg.com/stop-iteration-iterator/-/stop-iteration-iterator-1.1.0.tgz#f481ff70a548f6124d0312c3aa14cbfa7aa542ad"
@@ -1838,13 +1780,6 @@ strip-json-comments@^3.1.1:
   resolved "https://registry.yarnpkg.com/strip-json-comments/-/strip-json-comments-3.1.1.tgz#31f1281b3832630434831c310c01cccda8cbe006"
   integrity sha512-6fPc+R4ihwqP6N/aIv2f1gMH8lOVtWQHoqC4yK6oSDVVocumAsfCqjkXnqiYMhmMwS/mEHLp7Vehlt3ql6lEig==
 
-supports-color@^7.1.0:
-  version "7.2.0"
-  resolved "https://registry.yarnpkg.com/supports-color/-/supports-color-7.2.0.tgz#1b7dcdcb32b8138801b3e478ba6a51caa89648da"
-  integrity sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw==
-  dependencies:
-    has-flag "^4.0.0"
-
 supports-preserve-symlinks-flag@^1.0.0:
   version "1.0.0"
   resolved "https://registry.yarnpkg.com/supports-preserve-symlinks-flag/-/supports-preserve-symlinks-flag-1.0.0.tgz#6eda4bd344a3c94aea376d4cc31bc77311039e09"
@@ -1966,7 +1901,7 @@ uri-js@^4.2.2:
   dependencies:
     punycode "^2.1.0"
 
-uuid@^10.0.0:
+uuid@10.0.0, uuid@^10.0.0:
   version "10.0.0"
   resolved "https://registry.yarnpkg.com/uuid/-/uuid-10.0.0.tgz#5a95aa454e6e002725c79055fd42aaba30ca6294"
   integrity sha512-8XkAphELsDnEGrDxUOHB3RGvXz6TeuYSGEZBOjtTtPm2lwhGBjLgOzLHB63IUWfBpNucQjND6d3AOudO+H3RWQ==

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.21"
+__version__ = "0.4.22"

libs/cli/langgraph_cli/analytics.py

@@ -26,8 +26,15 @@ class LogData(TypedDict):
     params: dict[str, Any]
 
 
-def get_anonymized_params(kwargs: dict[str, Any]) -> dict[str, bool]:
-    params = {}
+def get_anonymized_params(
+    kwargs: dict[str, Any], *, cli_command: str
+) -> dict[str, bool | str]:
+    params: dict[str, bool | str] = {}
+
+    if cli_command == "deploy" and (
+        analytics_source := os.getenv("LANGGRAPH_CLI_ANALYTICS_SOURCE")
+    ):
+        params["source"] = analytics_source
 
     # anonymize params with values
     if config := kwargs.get("config"):
@@ -88,7 +95,7 @@ def log_command(func):
             "python_version": platform.python_version(),
             "cli_version": __version__,
             "cli_command": func.__name__,
-            "params": get_anonymized_params(kwargs),
+            "params": get_anonymized_params(kwargs, cli_command=func.__name__),
         }
 
         background_thread = threading.Thread(target=log_data, args=(data,))

libs/cli/uv-examples/monorepo/uv.lock

@@ -290,7 +290,7 @@ wheels = [
 
 [[package]]
 name = "langsmith"
-version = "0.7.26"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -303,9 +303,9 @@ dependencies = [
     { name = "xxhash" },
     { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/76/86/6de4f6f0451a9658f26f633e0bb090552a4dafd7df3f1ae7f0d40558e67e/langsmith-0.7.26.tar.gz", hash = "sha256:a3e06f3d689ce7195717aa6b8f91082319819ec7ea9b9a62cdcd3d9dc25bfc7b", size = 1146118, upload-time = "2026-04-06T15:01:03.336Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/81/8e/7eb7d65ce62e98e74b9f18f193ea7ac3996d4fbd71fffcc67d0f7ba3103e/langsmith-0.7.26-py3-none-any.whl", hash = "sha256:fe5c877972cea450c1c48251c8fae0f18543c8d19dfdb9ff9a9c4263763dde4e", size = 360160, upload-time = "2026-04-06T15:01:01.516Z" },
+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
 ]
 
 [[package]]

libs/cli/uv-examples/simple/uv.lock

@@ -266,7 +266,7 @@ wheels = [
 
 [[package]]
 name = "langsmith"
-version = "0.7.26"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -279,9 +279,9 @@ dependencies = [
     { name = "xxhash" },
     { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/76/86/6de4f6f0451a9658f26f633e0bb090552a4dafd7df3f1ae7f0d40558e67e/langsmith-0.7.26.tar.gz", hash = "sha256:a3e06f3d689ce7195717aa6b8f91082319819ec7ea9b9a62cdcd3d9dc25bfc7b", size = 1146118, upload-time = "2026-04-06T15:01:03.336Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/81/8e/7eb7d65ce62e98e74b9f18f193ea7ac3996d4fbd71fffcc67d0f7ba3103e/langsmith-0.7.26-py3-none-any.whl", hash = "sha256:fe5c877972cea450c1c48251c8fae0f18543c8d19dfdb9ff9a9c4263763dde4e", size = 360160, upload-time = "2026-04-06T15:01:01.516Z" },
+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
 ]
 
 [[package]]

libs/cli/uv.lock

@@ -907,7 +907,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.27"
+version = "1.2.28"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch", marker = "python_full_version >= '3.11'" },
@@ -919,9 +919,9 @@ dependencies = [
     { name = "typing-extensions", marker = "python_full_version >= '3.11'" },
     { name = "uuid-utils", marker = "python_full_version >= '3.11'" },
 ]
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 [[package]]

libs/langgraph/langgraph/_internal/_config.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from collections import ChainMap
-from collections.abc import Mapping, Sequence
+from collections.abc import Sequence
 from os import getenv
 from typing import Any, cast
 
@@ -217,14 +217,16 @@ def get_callback_manager_for_config(
             callbacks.add_tags(all_tags)
         if metadata := config.get("metadata"):
             callbacks.add_metadata(metadata)
-        return callbacks
+        manager = callbacks
     else:
         # otherwise create a new manager
-        return CallbackManager.configure(
+        manager = CallbackManager.configure(
             inheritable_callbacks=config.get("callbacks"),
             inheritable_tags=all_tags,
             inheritable_metadata=config.get("metadata"),
+            langsmith_inheritable_metadata=_get_tracing_metadata_defaults(config),
         )
+    return manager
 
 
 def get_async_callback_manager_for_config(
@@ -255,14 +257,16 @@ def get_async_callback_manager_for_config(
             callbacks.add_tags(all_tags)
         if metadata := config.get("metadata"):
             callbacks.add_metadata(metadata)
-        return callbacks
+        manager = callbacks
     else:
         # otherwise create a new manager
-        return AsyncCallbackManager.configure(
+        manager = AsyncCallbackManager.configure(
             inheritable_callbacks=config.get("callbacks"),
             inheritable_tags=all_tags,
             inheritable_metadata=config.get("metadata"),
+            langsmith_inheritable_metadata=_get_tracing_metadata_defaults(config),
         )
+    return manager
 
 
 def _is_not_empty(value: Any) -> bool:
@@ -308,22 +312,54 @@ def ensure_config(*configs: RunnableConfig | None) -> RunnableConfig:
         for k, v in config.items():
             if _is_not_empty(v) and k not in CONFIG_KEYS:
                 empty[CONF][k] = v
-    _empty_metadata = empty["metadata"]
-    for key, value in empty[CONF].items():
-        if _exclude_as_metadata(key, value, _empty_metadata):
-            continue
-        _empty_metadata[key] = value
+
+    configurable = empty.get("configurable")
+    metadata = empty.get("metadata")
+    if configurable and metadata is not None:
+        for key in _PROPAGATE_TO_METADATA:
+            if key in metadata:
+                continue
+            value = configurable.get(key)
+            if value:
+                metadata[key] = value
     return empty
 
 
 _OMIT = ("key", "token", "secret", "password", "auth")
 
 
-def _exclude_as_metadata(key: str, value: Any, metadata: Mapping[str, Any]) -> bool:
+def _exclude_as_metadata(key: str, value: Any) -> bool:
     key_lower = key.casefold()
     return (
         key.startswith("__")
         or not isinstance(value, (str, int, float, bool))
-        or key in metadata
         or any(substr in key_lower for substr in _OMIT)
     )
+
+
+def _get_tracing_metadata_defaults(
+    config: RunnableConfig,
+) -> dict[str, Any] | None:
+    """Get tracer-only metadata defaults from configurable values."""
+    configurable = config.get("configurable")
+    if not configurable:
+        return None
+    metadata: dict[str, Any] = {}
+    for key, value in configurable.items():
+        if _exclude_as_metadata(key, value):
+            continue
+        metadata[key] = value
+    return metadata or None
+
+
+_PROPAGATE_TO_METADATA = frozenset(
+    (
+        "thread_id",
+        "checkpoint_id",
+        "checkpoint_ns",
+        "task_id",
+        "run_id",
+        "assistant_id",
+        "graph_id",
+    )
+)

libs/langgraph/langgraph/channels/__init__.py

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

libs/langgraph/langgraph/channels/base.py

@@ -119,3 +119,12 @@ class BaseChannel(Generic[Value, Update, Checkpoint], ABC):
         Returns `True` if the channel was updated, `False` otherwise.
         """
         return False
+
+    def after_checkpoint(self, version: Any, checkpoint_id: str | None = None) -> None:
+        """Called after checkpoint() with the assigned version, and after
+        from_checkpoint() with the current channel version.
+
+        No-op by default. Override in channels that track their own version
+        for incremental checkpointing (e.g. DeltaChannel).
+        """
+        pass

libs/langgraph/langgraph/channels/delta.py

@@ -0,0 +1,206 @@
+from __future__ import annotations
+
+import collections.abc
+from collections.abc import Callable, Sequence
+from typing import Any, Generic
+
+from langgraph.checkpoint.base import DeltaChainValue, DeltaValue
+from typing_extensions import Self
+
+from langgraph._internal._typing import MISSING
+from langgraph.channels.base import BaseChannel, Value
+from langgraph.channels.binop import _get_overwrite, _strip_extras
+from langgraph.errors import EmptyChannelError
+
+__all__ = ("DeltaChannel",)
+
+
+class DeltaChannel(Generic[Value], BaseChannel[list[Value], Value, DeltaValue]):
+    """A channel that stores only per-step write deltas in checkpoints.
+
+    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 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)]
+    """
+
+    __slots__ = (
+        "value",
+        "operator",
+        "snapshot_every",
+        "_pending",
+        "_base_version",
+        "_last_checkpoint_id",
+        "_overwritten",
+        "_steps_since_snapshot",
+    )
+
+    def __init__(
+        self,
+        operator: Callable[[list[Value], Any], list[Value]],
+        typ: type = list,
+        *,
+        snapshot_every: int | None = None,
+    ) -> None:
+        typ = _strip_extras(typ)
+        if typ in (
+            collections.abc.Sequence,
+            collections.abc.MutableSequence,
+        ):
+            typ = list
+        super().__init__(typ)
+        self.operator = operator
+        self.snapshot_every = snapshot_every
+        try:
+            self.value: list[Value] = typ()
+        except Exception:
+            self.value = []
+        self._pending: list[Any] = []
+        self._base_version: str | None = None
+        self._last_checkpoint_id: 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>"
+        ):
+            return self.operator is other.operator
+        return True
+
+    @property
+    def ValueType(self) -> Any:
+        return list[self.typ]  # type: ignore[name-defined]
+
+    @property
+    def UpdateType(self) -> Any:
+        return self.typ | list[self.typ]  # type: ignore[name-defined]
+
+    def copy(self) -> Self:
+        new = DeltaChannel(self.operator, self.typ, snapshot_every=self.snapshot_every)
+        new.key = self.key
+        new.value = self.value[:]
+        new._pending = self._pending[:]
+        new._base_version = self._base_version
+        new._last_checkpoint_id = self._last_checkpoint_id
+        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, self.typ, snapshot_every=self.snapshot_every)
+        new.key = self.key
+        if checkpoint is MISSING:
+            new.value = []
+        elif isinstance(checkpoint, DeltaChainValue):
+            accumulated: list[Value] = list(checkpoint.base) if checkpoint.base else []
+            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):
+            # Should never reach here — the pregel layer assembles DeltaValues
+            # into DeltaChainValue before calling from_checkpoint.
+            raise AssertionError(
+                "DeltaChannel.from_checkpoint received a raw DeltaValue. "
+                "This is a bug in the pregel layer — chain assembly should have "
+                "occurred before from_checkpoint was called."
+            )
+        else:
+            # 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:
+        if not values:
+            return False
+        seen_overwrite = False
+        for value in values:
+            is_overwrite, overwrite_value = _get_overwrite(value)
+            if is_overwrite:
+                if seen_overwrite:
+                    from langgraph.errors import (
+                        ErrorCode,
+                        InvalidUpdateError,
+                        create_error_message,
+                    )
+
+                    msg = create_error_message(
+                        message="Can receive only one Overwrite value per super-step.",
+                        error_code=ErrorCode.INVALID_CONCURRENT_GRAPH_UPDATE,
+                    )
+                    raise InvalidUpdateError(msg)
+                self.value = (
+                    list(overwrite_value) if overwrite_value is not None else []
+                )
+                self._pending = list(self.value)
+                self._overwritten = True
+                seen_overwrite = True
+            elif not seen_overwrite:
+                self.value = self.operator(self.value, value)
+                self._pending.append(value)
+        return True
+
+    def get(self) -> list[Value]:
+        if self.value is MISSING:
+            raise EmptyChannelError()
+        return self.value
+
+    def is_available(self) -> bool:
+        return self.value is not MISSING
+
+    def checkpoint(self) -> Any:
+        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[:],
+            prev_checkpoint_id=None if self._overwritten else self._last_checkpoint_id,
+        )
+
+    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._last_checkpoint_id = checkpoint_id
+            self._pending = []
+            self._overwritten = False

libs/langgraph/langgraph/pregel/_checkpoint.py

@@ -1,9 +1,17 @@
 from __future__ import annotations
 
+import logging
 from collections.abc import Mapping
 from datetime import datetime, timezone
+from typing import Any
 
-from langgraph.checkpoint.base import Checkpoint
+from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import (
+    BaseCheckpointSaver,
+    Checkpoint,
+    DeltaChainValue,
+    DeltaValue,
+)
 from langgraph.checkpoint.base.id import uuid6
 
 from langgraph._internal._typing import MISSING
@@ -12,6 +20,171 @@ from langgraph.managed.base import ManagedValueMapping, ManagedValueSpec
 
 LATEST_VERSION = 4
 
+logger = logging.getLogger(__name__)
+
+_MISSING_SENTINEL = object()
+
+
+def _assemble_delta_channels(
+    checkpoint: Checkpoint,
+    config: RunnableConfig,
+    checkpointer: BaseCheckpointSaver,
+) -> dict[str, Any]:
+    """Resolve any DeltaValue entries in checkpoint channel_values to DeltaChainValue.
+
+    Returns a dict of only the channels that needed assembly (others are untouched).
+    Tries get_channel_blob fast-path first; falls back to get_tuple traversal.
+    """
+    thread_id = str(config["configurable"]["thread_id"])
+    checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+    current_checkpoint_id = checkpoint.get("id")
+    assembled: dict[str, Any] = {}
+
+    for channel, value in checkpoint["channel_values"].items():
+        if not isinstance(value, DeltaValue):
+            continue
+
+        chain_deltas: list[list[Any]] = []
+        base: list[Any] | None = None
+        cursor: DeltaValue = value
+        # Pre-seed with current checkpoint ID to guard against self-referential chains.
+        visited: set[str] = {current_checkpoint_id} if current_checkpoint_id else set()
+
+        while True:
+            chain_deltas.append(cursor.delta)
+            prev_id = cursor.prev_checkpoint_id
+            if prev_id is None:
+                break  # chain root
+            if prev_id in visited:
+                logger.warning(
+                    "DeltaChannel chain cycle at checkpoint %r for channel %r; breaking",
+                    prev_id,
+                    channel,
+                )
+                break
+            visited.add(prev_id)
+
+            # Fast path: saver has a dedicated blob store.
+            blob = checkpointer.get_channel_blob(
+                thread_id, checkpoint_ns, prev_id, channel
+            )
+            if blob is not NotImplemented:
+                if isinstance(blob, DeltaValue):
+                    cursor = blob
+                    continue
+                else:
+                    base = blob  # plain list = snapshot root
+                    break
+
+            # Fallback: load the full checkpoint and extract channel value.
+            parent_config: RunnableConfig = {
+                "configurable": {
+                    "thread_id": thread_id,
+                    "checkpoint_ns": checkpoint_ns,
+                    "checkpoint_id": prev_id,
+                }
+            }
+            parent_tuple = checkpointer.get_tuple(parent_config)
+            if parent_tuple is None:
+                logger.warning(
+                    "DeltaChannel chain broken: checkpoint %r not found for channel %r",
+                    prev_id,
+                    channel,
+                )
+                break
+            prev_val = parent_tuple.checkpoint["channel_values"].get(
+                channel, _MISSING_SENTINEL
+            )
+            if prev_val is _MISSING_SENTINEL:
+                break
+            elif isinstance(prev_val, DeltaValue):
+                cursor = prev_val
+            else:
+                base = prev_val
+                break
+
+        chain_deltas.reverse()
+        assembled[channel] = DeltaChainValue(base=base, deltas=chain_deltas)
+
+    return assembled
+
+
+async def _aassemble_delta_channels(
+    checkpoint: Checkpoint,
+    config: RunnableConfig,
+    checkpointer: BaseCheckpointSaver,
+) -> dict[str, Any]:
+    """Async version of _assemble_delta_channels."""
+    thread_id = str(config["configurable"]["thread_id"])
+    checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+    current_checkpoint_id = checkpoint.get("id")
+    assembled: dict[str, Any] = {}
+
+    for channel, value in checkpoint["channel_values"].items():
+        if not isinstance(value, DeltaValue):
+            continue
+
+        chain_deltas: list[list[Any]] = []
+        base: list[Any] | None = None
+        cursor: DeltaValue = value
+        visited: set[str] = {current_checkpoint_id} if current_checkpoint_id else set()
+
+        while True:
+            chain_deltas.append(cursor.delta)
+            prev_id = cursor.prev_checkpoint_id
+            if prev_id is None:
+                break
+            if prev_id in visited:
+                logger.warning(
+                    "DeltaChannel chain cycle at checkpoint %r for channel %r; breaking",
+                    prev_id,
+                    channel,
+                )
+                break
+            visited.add(prev_id)
+
+            blob = await checkpointer.aget_channel_blob(
+                thread_id, checkpoint_ns, prev_id, channel
+            )
+            if blob is not NotImplemented:
+                if isinstance(blob, DeltaValue):
+                    cursor = blob
+                    continue
+                else:
+                    base = blob
+                    break
+
+            parent_config: RunnableConfig = {
+                "configurable": {
+                    "thread_id": thread_id,
+                    "checkpoint_ns": checkpoint_ns,
+                    "checkpoint_id": prev_id,
+                }
+            }
+            parent_tuple = await checkpointer.aget_tuple(parent_config)
+            if parent_tuple is None:
+                logger.warning(
+                    "DeltaChannel chain broken: checkpoint %r not found for channel %r",
+                    prev_id,
+                    channel,
+                )
+                break
+            prev_val = parent_tuple.checkpoint["channel_values"].get(
+                channel, _MISSING_SENTINEL
+            )
+            if prev_val is _MISSING_SENTINEL:
+                break
+            elif isinstance(prev_val, DeltaValue):
+                cursor = prev_val
+            else:
+                base = prev_val
+                break
+
+        chain_deltas.reverse()
+        assembled[channel] = DeltaChainValue(base=base, deltas=chain_deltas)
+
+    return assembled
+
 
 def empty_checkpoint() -> Checkpoint:
     return Checkpoint(
@@ -67,13 +240,12 @@ def channels_from_checkpoint(
             channel_specs[k] = v
         else:
             managed_specs[k] = v
-    return (
-        {
-            k: v.from_checkpoint(checkpoint["channel_values"].get(k, MISSING))
-            for k, v in channel_specs.items()
-        },
-        managed_specs,
-    )
+    channels: dict[str, BaseChannel] = {}
+    for k, v in channel_specs.items():
+        ch = v.from_checkpoint(checkpoint["channel_values"].get(k, MISSING))
+        ch.after_checkpoint(checkpoint["channel_versions"].get(k), checkpoint.get("id"))
+        channels[k] = ch
+    return channels, managed_specs
 
 
 def copy_checkpoint(checkpoint: Checkpoint) -> Checkpoint:

libs/langgraph/langgraph/pregel/_loop.py

@@ -92,6 +92,8 @@ from langgraph.pregel._algo import (
     task_path_str,
 )
 from langgraph.pregel._checkpoint import (
+    _aassemble_delta_channels,
+    _assemble_delta_channels,
     channels_from_checkpoint,
     copy_checkpoint,
     create_checkpoint,
@@ -692,7 +694,7 @@ class PregelLoop:
         # writes so that interrupt() calls re-fire instead of returning
         # stale values. But if we're actively resuming, keep them —
         # multi-interrupt scenarios need previously resolved values preserved.
-        if self.is_replaying and (
+        is_time_traveling = self.is_replaying and (
             # Time-travel to a subgraph checkpoint: the parent sets
             # RESUMING=True (it can't distinguish time-travel from resume),
             # so we check if this subgraph's own ns is in checkpoint_map.
@@ -710,7 +712,8 @@ class PregelLoop:
                 # (subgraph input is a Send arg, not a Command)
                 or configurable.get(CONFIG_KEY_RESUMING, False)
             )
-        ):
+        )
+        if is_time_traveling:
             self.checkpoint_pending_writes = [
                 w for w in self.checkpoint_pending_writes if w[1] != RESUME
             ]
@@ -765,6 +768,26 @@ class PregelLoop:
                 if k in self.checkpoint["channel_versions"]:
                     version = self.checkpoint["channel_versions"][k]
                     self.checkpoint["versions_seen"][INTERRUPT][k] = version
+            # When time-traveling (replaying from a specific checkpoint),
+            # save a fork checkpoint so the replayed execution creates a
+            # new branch. Without this, if the execution hits an interrupt
+            # before after_tick() runs, no new checkpoint is created —
+            # the parent's latest checkpoint remains the old one and
+            # subsequent resumes load the wrong state.
+            # Skip for update_state forks (source=update/fork) since they
+            # already have their own fork checkpoint.
+            if is_time_traveling and self.checkpoint_metadata.get("source") not in (
+                "update",
+                "fork",
+            ):
+                # Clear old INTERRUPT writes from the loaded checkpoint.
+                # The fork will have a new checkpoint_id which changes
+                # task IDs — stale interrupt writes would accumulate and
+                # confuse the multiple-interrupt check in future resumes.
+                self.checkpoint_pending_writes = [
+                    w for w in self.checkpoint_pending_writes if w[1] != INTERRUPT
+                ]
+                self._put_checkpoint({"source": "fork"})
             # produce values output
             self._emit(
                 "values", map_output_values, self.output_keys, True, self.channels
@@ -807,14 +830,18 @@ class PregelLoop:
         if not self.is_nested:
             # Pass the resolved before-bound checkpoint ID so subgraphs can
             # find their corresponding checkpoint without re-fetching the
-            # parent. For forks (source=update), use the fork's parent
+            # 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.
             replay_state: ReplayState | None = None
             if self.is_replaying:
                 replay_checkpoint_id = self.checkpoint["id"]
                 if (
-                    self.checkpoint_metadata.get("source") == "update"
+                    self.checkpoint_metadata.get("source")
+                    in (
+                        "update",
+                        "fork",
+                    )
                     and self.prev_checkpoint_config
                 ):
                     replay_checkpoint_id = self.prev_checkpoint_config[CONF].get(
@@ -856,6 +883,12 @@ class PregelLoop:
             id=self.checkpoint["id"] if exiting else None,
             updated_channels=self.updated_channels,
         )
+        if do_checkpoint and self.channels:
+            for k, ch in self.channels.items():
+                ch.after_checkpoint(
+                    self.checkpoint["channel_versions"].get(k),
+                    self.checkpoint.get("id"),
+                )
         # sanitize TASK channel in the checkpoint before saving (durability=="exit")
         if TASKS in self.checkpoint["channel_values"] and any(
             isinstance(channel, UntrackedValue) for channel in self.channels.values()
@@ -1237,6 +1270,19 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
             else []
         )
         self.submit = self.stack.enter_context(BackgroundExecutor(self.config))
+        # Assemble any DeltaChannel chains before constructing channel objects.
+        if self.checkpointer is not None:
+            assembled = _assemble_delta_channels(
+                self.checkpoint, self.checkpoint_config, self.checkpointer
+            )
+            if assembled:
+                self.checkpoint = {
+                    **self.checkpoint,
+                    "channel_values": {
+                        **self.checkpoint["channel_values"],
+                        **assembled,
+                    },
+                }
         self.channels, self.managed = channels_from_checkpoint(
             self.specs, self.checkpoint
         )
@@ -1441,6 +1487,18 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
         self.submit = await self.stack.enter_async_context(
             AsyncBackgroundExecutor(self.config)
         )
+        if self.checkpointer is not None:
+            assembled = await _aassemble_delta_channels(
+                self.checkpoint, self.checkpoint_config, self.checkpointer
+            )
+            if assembled:
+                self.checkpoint = {
+                    **self.checkpoint,
+                    "channel_values": {
+                        **self.checkpoint["channel_values"],
+                        **assembled,
+                    },
+                }
         self.channels, self.managed = channels_from_checkpoint(
             self.specs, self.checkpoint
         )

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/main.py

@@ -122,6 +122,8 @@ from langgraph.pregel._algo import (
 )
 from langgraph.pregel._call import identifier
 from langgraph.pregel._checkpoint import (
+    _aassemble_delta_channels,
+    _assemble_delta_channels,
     channels_from_checkpoint,
     copy_checkpoint,
     create_checkpoint,
@@ -1049,13 +1051,23 @@ class Pregel(
 
         step = saved.metadata.get("step", -1) + 1
         stop = step + 2
+        checkpoint = saved.checkpoint
+        if isinstance(self.checkpointer, BaseCheckpointSaver):
+            assembled = _assemble_delta_channels(
+                checkpoint, saved.config, self.checkpointer
+            )
+            if assembled:
+                checkpoint = {
+                    **checkpoint,
+                    "channel_values": {**checkpoint["channel_values"], **assembled},
+                }
         channels, managed = channels_from_checkpoint(
             self.channels,
-            saved.checkpoint,
+            checkpoint,
         )
         # tasks for this checkpoint
         next_tasks = prepare_next_tasks(
-            saved.checkpoint,
+            checkpoint,
             saved.pending_writes or [],
             self.nodes,
             channels,
@@ -1168,13 +1180,23 @@ class Pregel(
 
         step = saved.metadata.get("step", -1) + 1
         stop = step + 2
+        checkpoint = saved.checkpoint
+        if isinstance(self.checkpointer, BaseCheckpointSaver):
+            assembled = await _aassemble_delta_channels(
+                checkpoint, saved.config, self.checkpointer
+            )
+            if assembled:
+                checkpoint = {
+                    **checkpoint,
+                    "channel_values": {**checkpoint["channel_values"], **assembled},
+                }
         channels, managed = channels_from_checkpoint(
             self.channels,
-            saved.checkpoint,
+            checkpoint,
         )
         # tasks for this checkpoint
         next_tasks = prepare_next_tasks(
-            saved.checkpoint,
+            checkpoint,
             saved.pending_writes or [],
             self.nodes,
             channels,
@@ -1520,9 +1542,20 @@ class Pregel(
             saved = checkpointer.get_tuple(config)
             if saved is not None:
                 self._migrate_checkpoint(saved.checkpoint)
-            checkpoint = (
-                copy_checkpoint(saved.checkpoint) if saved else empty_checkpoint()
-            )
+            base_checkpoint = saved.checkpoint if saved else empty_checkpoint()
+            if saved:
+                assembled = _assemble_delta_channels(
+                    base_checkpoint, saved.config, checkpointer
+                )
+                if assembled:
+                    base_checkpoint = {
+                        **base_checkpoint,
+                        "channel_values": {
+                            **base_checkpoint["channel_values"],
+                            **assembled,
+                        },
+                    }
+            checkpoint = copy_checkpoint(base_checkpoint) if saved else base_checkpoint
             checkpoint_previous_versions = (
                 saved.checkpoint["channel_versions"].copy() if saved else {}
             )
@@ -1966,9 +1999,20 @@ class Pregel(
             saved = await checkpointer.aget_tuple(config)
             if saved is not None:
                 self._migrate_checkpoint(saved.checkpoint)
-            checkpoint = (
-                copy_checkpoint(saved.checkpoint) if saved else empty_checkpoint()
-            )
+            base_checkpoint = saved.checkpoint if saved else empty_checkpoint()
+            if saved:
+                assembled = await _aassemble_delta_channels(
+                    base_checkpoint, saved.config, checkpointer
+                )
+                if assembled:
+                    base_checkpoint = {
+                        **base_checkpoint,
+                        "channel_values": {
+                            **base_checkpoint["channel_values"],
+                            **assembled,
+                        },
+                    }
+            checkpoint = copy_checkpoint(base_checkpoint) if saved else base_checkpoint
             checkpoint_previous_versions = (
                 saved.checkpoint["channel_versions"].copy() if saved else {}
             )
@@ -3715,15 +3759,14 @@ def _coerce_checkpoint_values(payload: Any, mapper: Callable[[Any], Any]) -> Non
 def _build_server_info(
     config: RunnableConfig, parent_runtime: Runtime[Any]
 ) -> ServerInfo | None:
-    """Build ServerInfo from config metadata and configurable.
+    """Build ServerInfo from config configurable.
 
-    The server puts assistant_id/graph_id in config metadata and the
+    The server puts assistant_id/graph_id in config configurable and the
     authenticated user dict in configurable["langgraph_auth_user"].
     """
-    metadata = config.get("metadata") or {}
     configurable = config.get(CONF) or {}
-    assistant_id = metadata.get("assistant_id")
-    graph_id = metadata.get("graph_id")
+    assistant_id = configurable.get("assistant_id")
+    graph_id = configurable.get("graph_id")
 
     # Read authenticated user from configurable (set by LangGraph Server).
     # We prefer isinstance(BaseUser) but fall back to hasattr("identity")

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.1.7a1"
+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>=0.1",
+    "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

@@ -117,3 +117,408 @@ def test_untracked_value() -> None:
     new_channel = UntrackedValue(dict).from_checkpoint(checkpoint)
     with pytest.raises(EmptyChannelError):
         new_channel.get()
+
+
+def test_delta_channel_basic_two_steps() -> None:
+    from langchain_core.messages import AIMessage, 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)
+    ch.after_checkpoint(None)
+
+    # Step 1: one message added
+    ch.update([HumanMessage(content="hi", id="h1")])
+    d1 = ch.checkpoint()
+    assert isinstance(d1, DeltaValue)
+    assert len(d1.delta) == 1
+    assert d1.prev_checkpoint_id is None  # first ever step
+    ch.after_checkpoint("v1", checkpoint_id="cid1")
+
+    # Step 2: another message
+    ch.update([AIMessage(content="hello", id="a1")])
+    d2 = ch.checkpoint()
+    assert d2.prev_checkpoint_id == "cid1"
+    assert len(d2.delta) == 1
+    ch.after_checkpoint("v2")
+
+    # Full accumulated value is preserved in memory
+    assert len(ch.get()) == 2
+    assert ch.get()[0].content == "hi"
+    assert ch.get()[1].content == "hello"
+
+
+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)
+    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"
+    assert msgs[1].content == "hello"
+    assert msgs[2].content == "bye"
+
+
+def test_delta_channel_from_checkpoint_backwards_compat() -> None:
+    from langchain_core.messages import HumanMessage
+
+    from langgraph.channels.delta import DeltaChannel
+    from langgraph.graph.message import add_messages
+
+    # 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_resets_chain() -> None:
+    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
+    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")
+
+    # Overwrite should create a root blob (prev_checkpoint_id=None)
+    ch.update([Overwrite([HumanMessage(content="new", id="h2")])])
+    d = ch.checkpoint()
+    assert isinstance(d, DeltaValue)
+    assert d.prev_checkpoint_id is None  # chain root
+    assert len(d.delta) == 1
+    assert d.delta[0].content == "new"
+
+
+def test_delta_channel_assembly_fallback_via_get_tuple() -> None:
+    """Assembly falls back to get_tuple for savers without get_channel_blob."""
+    from unittest.mock import MagicMock
+
+    from langgraph.checkpoint.base import (
+        CheckpointTuple,
+        DeltaChainValue,
+        DeltaValue,
+        empty_checkpoint,
+    )
+
+    from langgraph.channels.delta import DeltaChannel
+    from langgraph.graph.message import add_messages
+    from langgraph.pregel._checkpoint import _assemble_delta_channels
+
+    msg1 = {"type": "human", "content": "hello"}
+    msg2 = {"type": "ai", "content": "world"}
+
+    cp1 = empty_checkpoint()
+    cp1["id"] = "cp1"
+    cp1["channel_values"]["messages"] = [msg1]
+
+    cp2 = empty_checkpoint()
+    cp2["id"] = "cp2"
+    cp2["channel_values"]["messages"] = DeltaValue(
+        delta=[msg2], prev_checkpoint_id="cp1"
+    )
+
+    saver = MagicMock()
+    saver.get_channel_blob.return_value = NotImplemented
+    saver.get_tuple.return_value = CheckpointTuple(
+        config={
+            "configurable": {
+                "thread_id": "t1",
+                "checkpoint_ns": "",
+                "checkpoint_id": "cp1",
+            }
+        },
+        checkpoint=cp1,
+        metadata={},
+        parent_config=None,
+        pending_writes=[],
+    )
+
+    config = {"configurable": {"thread_id": "t1", "checkpoint_ns": ""}}
+    assembled = _assemble_delta_channels(cp2, config, saver)
+
+    assert "messages" in assembled
+    chain = assembled["messages"]
+    assert isinstance(chain, DeltaChainValue)
+    assert chain.base == [msg1]
+    assert chain.deltas == [[msg2]]
+
+    from langchain_core.messages import AIMessage, HumanMessage
+
+    spec = DeltaChannel(add_messages)
+    ch = spec.from_checkpoint(chain)
+    result = ch.get()
+    assert len(result) == 2
+    assert isinstance(result[0], HumanMessage) and result[0].content == "hello"
+    assert isinstance(result[1], AIMessage) and result[1].content == "world"
+
+
+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"),
+    ]
+
+    # Step 2: remove the AI message
+    ch.update([RemoveMessage(id="a1")])
+    d2 = ch.checkpoint()
+    assert isinstance(d2, DeltaValue)
+    assert d2.prev_checkpoint_id == "cid1"
+    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 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_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)
+    assert d2.prev_checkpoint_id == "cid1"
+    ch.after_checkpoint("v2", checkpoint_id="cid2")
+    assert ch.get() == [HumanMessage(content="updated", id="h1")]
+
+    # 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_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
+
+    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")
+
+    # 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}")
+
+    # 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)
+    assert post.prev_checkpoint_id == "cidsnap"
+
+
+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_assembly_fast_path_returns_delta_value() -> None:
+    """get_channel_blob returning a DeltaValue continues chain traversal (fast-path)."""
+    from unittest.mock import MagicMock
+
+    from langgraph.checkpoint.base import (
+        DeltaChainValue,
+        DeltaValue,
+        empty_checkpoint,
+    )
+
+    from langgraph.channels.delta import DeltaChannel
+    from langgraph.graph.message import add_messages
+    from langgraph.pregel._checkpoint import _assemble_delta_channels
+
+    msg1 = {"type": "human", "content": "one"}
+    msg2 = {"type": "ai", "content": "two"}
+    msg3 = {"type": "human", "content": "three"}
+
+    # cp3 → cp2 (DeltaValue) → cp1 (base list)
+    dv_cp2 = DeltaValue(delta=[msg2], prev_checkpoint_id="cp1")
+    cp3 = empty_checkpoint()
+    cp3["id"] = "cp3"
+    cp3["channel_values"]["messages"] = DeltaValue(
+        delta=[msg3], prev_checkpoint_id="cp2"
+    )
+
+    saver = MagicMock()
+
+    def _get_blob(thread_id, ns, checkpoint_id, channel):
+        if checkpoint_id == "cp2":
+            return dv_cp2  # DeltaValue — chain continues
+        if checkpoint_id == "cp1":
+            return [msg1]  # plain list — chain root
+        return NotImplemented
+
+    saver.get_channel_blob.side_effect = _get_blob
+
+    config = {"configurable": {"thread_id": "t1", "checkpoint_ns": ""}}
+    assembled = _assemble_delta_channels(cp3, config, saver)
+
+    chain = assembled["messages"]
+    assert isinstance(chain, DeltaChainValue)
+    assert chain.base == [msg1]
+    assert chain.deltas == [[msg2], [msg3]]
+
+    spec = DeltaChannel(add_messages)
+    ch = spec.from_checkpoint(chain)
+    # add_messages converts dicts to message objects; check by type and content
+
+    result = ch.get()
+    assert len(result) == 3
+    assert result[0].content == "one"
+    assert result[1].content == "two"
+    assert result[2].content == "three"
+
+
+def test_delta_channel_assembly_broken_chain_logs_warning() -> None:
+    """If a prev_checkpoint_id points to a missing checkpoint, log a warning and use partial chain."""
+    from unittest.mock import MagicMock
+
+    from langgraph.checkpoint.base import DeltaValue, empty_checkpoint
+
+    from langgraph.pregel._checkpoint import _assemble_delta_channels
+
+    cp = empty_checkpoint()
+    cp["id"] = "cp2"
+    cp["channel_values"]["messages"] = DeltaValue(
+        delta=["msg2"], prev_checkpoint_id="cp-missing"
+    )
+
+    saver = MagicMock()
+    saver.get_channel_blob.return_value = NotImplemented
+    saver.get_tuple.return_value = None  # checkpoint not found
+
+    config = {"configurable": {"thread_id": "t1", "checkpoint_ns": ""}}
+
+    assembled = _assemble_delta_channels(cp, config, saver)
+
+    # Should still assemble — with partial chain (just the current delta, base=None)
+    assert "messages" in assembled
+    from langgraph.checkpoint.base import DeltaChainValue
+
+    chain = assembled["messages"]
+    assert isinstance(chain, DeltaChainValue)
+    assert chain.base is None
+    assert chain.deltas == [["msg2"]]

libs/langgraph/tests/test_delta_channel_benchmark.py

@@ -0,0 +1,356 @@
+"""Benchmark: DeltaChannel vs BinaryOperatorAggregate storage and time.
+
+Run directly:  python tests/test_delta_channel_benchmark.py
+Run via pytest: pytest tests/test_delta_channel_benchmark.py -s
+
+Simulates realistic multi-turn conversations with paragraph-length messages
+(~100 tokens each) scaling up to 1M-token-equivalent histories.
+
+Token estimates: 1 token ≈ 4 chars; each turn ≈ 200 tokens (human + AI).
+A 1M-token conversation ≈ 5,000 turns of realistic messages.
+"""
+
+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
+
+try:
+    from langgraph.checkpoint.sqlite import SqliteSaver
+
+    _SQLITE_AVAILABLE = True
+except ImportError:
+    _SQLITE_AVAILABLE = False
+
+SNAPSHOT_EVERY = 50
+
+# ---------------------------------------------------------------------------
+# Realistic message payload (~100 tokens / ~400 chars each)
+# ---------------------------------------------------------------------------
+
+_HUMAN_TEMPLATE = (
+    "I need help understanding the implications of {topic} on our system architecture. "
+    "Specifically, I'm concerned about how this interacts with our existing {concern} "
+    "and whether we need to refactor the {component} layer before proceeding."
+)
+
+_AI_TEMPLATE = (
+    "Great question about {topic}. The key insight here is that {concern} introduces "
+    "a subtle ordering dependency that most teams overlook until they hit it in production. "
+    "For your {component} layer specifically, I'd recommend starting with a careful audit "
+    "of the interface boundaries before making any structural changes. This will give you "
+    "a clear picture of the blast radius and let you sequence the migration safely."
+)
+
+_TOPICS = [
+    "distributed tracing",
+    "eventual consistency",
+    "schema migration",
+    "backpressure handling",
+    "idempotency guarantees",
+    "cache invalidation",
+    "connection pooling",
+    "rate limiting",
+    "circuit breaking",
+    "observability pipelines",
+]
+
+_CONCERNS = [
+    "concurrency model",
+    "retry semantics",
+    "state management",
+    "error propagation",
+    "latency budget",
+]
+
+_COMPONENTS = [
+    "persistence",
+    "routing",
+    "ingestion",
+    "aggregation",
+    "serialization",
+]
+
+
+def _human_content(i: int) -> str:
+    return _HUMAN_TEMPLATE.format(
+        topic=_TOPICS[i % len(_TOPICS)],
+        concern=_CONCERNS[i % len(_CONCERNS)],
+        component=_COMPONENTS[i % len(_COMPONENTS)],
+    )
+
+
+def _ai_content(i: int) -> str:
+    return _AI_TEMPLATE.format(
+        topic=_TOPICS[i % len(_TOPICS)],
+        concern=_CONCERNS[i % len(_CONCERNS)],
+        component=_COMPONENTS[i % len(_COMPONENTS)],
+    )
+
+
+# ---------------------------------------------------------------------------
+# State definitions
+# ---------------------------------------------------------------------------
+
+
+class BinaryState(TypedDict):
+    messages: Annotated[list, add_messages]
+
+
+class DeltaState(TypedDict):
+    messages: Annotated[list, DeltaChannel(add_messages)]
+
+
+class DeltaSnapshotState(TypedDict):
+    messages: Annotated[list, DeltaChannel(add_messages, snapshot_every=SNAPSHOT_EVERY)]
+
+
+# ---------------------------------------------------------------------------
+# Graph factory
+# ---------------------------------------------------------------------------
+
+
+def _make_graph(state_cls: type, checkpointer: Any = None) -> Any:
+    def human_node(state: Any) -> dict:
+        return {}
+
+    def ai_node(state: Any) -> dict:
+        i = len(state["messages"]) // 2
+        return {"messages": [AIMessage(content=_ai_content(i), id=f"a{i}")]}
+
+    g = StateGraph(state_cls)
+    g.add_node("human", human_node)
+    g.add_node("ai", ai_node)
+    g.add_edge("human", "ai")
+    g.add_edge("ai", END)
+    g.set_entry_point("human")
+    return g.compile(checkpointer=checkpointer or MemorySaver())
+
+
+# ---------------------------------------------------------------------------
+# Measurement helpers
+# ---------------------------------------------------------------------------
+
+
+def _total_blob_bytes(saver: MemorySaver) -> int:
+    total = 0
+    for (_, _, _, _), (type_tag, blob) in saver.blobs.items():
+        if blob is not None:
+            total += len(blob)
+    return total
+
+
+def _run_turns(
+    n_turns: int,
+    state_cls: type,
+    checkpointer: Any = None,
+) -> tuple[float, float, int]:
+    """Run n_turns conversation turns.
+
+    Returns (write_elapsed_s, read_elapsed_s, total_blob_bytes).
+    blob_bytes is -1 for savers without in-memory blob stores (e.g. SQLite).
+    Read latency is measured as the time to invoke the graph with no new
+    messages after the full history is built — this forces state rehydration.
+    """
+    graph = _make_graph(state_cls, checkpointer)
+    config = {"configurable": {"thread_id": "bench"}}
+
+    t0 = time.perf_counter()
+    for i in range(n_turns):
+        graph.invoke(
+            {"messages": [HumanMessage(content=_human_content(i), id=f"h{i}")]},
+            config,
+        )
+    write_elapsed = time.perf_counter() - t0
+
+    # Measure read/rehydration: get_state forces the channel to rebuild
+    t1 = time.perf_counter()
+    for _ in range(5):
+        graph.get_state(config)
+    read_elapsed = (time.perf_counter() - t1) / 5
+
+    if isinstance(graph.checkpointer, MemorySaver):
+        blob_bytes = _total_blob_bytes(graph.checkpointer)
+    else:
+        blob_bytes = -1
+    return write_elapsed, read_elapsed, blob_bytes
+
+
+def _fmt_bytes(n: int) -> str:
+    if n >= 1_000_000:
+        return f"{n / 1_000_000:.1f} MB"
+    if n >= 1_000:
+        return f"{n / 1_000:.1f} KB"
+    return f"{n} B"
+
+
+def _approx_tokens(n_turns: int) -> str:
+    # ~100 tokens human + ~100 tokens AI per turn
+    tokens = n_turns * 200
+    if tokens >= 1_000_000:
+        return f"~{tokens / 1_000_000:.1f}M tok"
+    if tokens >= 1_000:
+        return f"~{tokens / 1_000:.0f}K tok"
+    return f"~{tokens} tok"
+
+
+# ---------------------------------------------------------------------------
+# Benchmark matrix
+# ---------------------------------------------------------------------------
+
+# Turn counts chosen to span from a short session to a long-running agent conversation.
+# Storage and time complexity differences are clearly visible by 500 turns.
+# Extrapolation: 5,000 turns × ~200 tokens/turn ≈ 1M tokens (Claude's full context window).
+TURN_COUNTS = [50, 100, 200, 500]
+
+
+def _checkpointer_factories() -> list[tuple[str, Any]]:
+    """Return (label, context_manager_or_none) pairs for available checkpointers."""
+    factories: list[tuple[str, Any]] = [("InMemory", None)]
+    if _SQLITE_AVAILABLE:
+        import tempfile
+
+        factories.append(("SQLite", tempfile.NamedTemporaryFile(suffix=".db")))
+    return factories
+
+
+def run_benchmark() -> None:
+    print()
+    print(
+        "DeltaChannel vs add_messages (BinaryOperatorAggregate) — checkpoint storage & latency"
+    )
+    print("Simulating realistic multi-turn conversations up to ~1M-token histories")
+    print("(5,000 turns × ~200 tokens/turn ≈ 1M tokens — Claude's full context window)")
+    print()
+
+    checkpointers: list[tuple[str, Any]] = [("InMemory (fast-path)", None)]
+    if _SQLITE_AVAILABLE:
+        checkpointers.append(("SQLite (get_tuple fallback)", "sqlite"))
+
+    for cp_label, cp_hint in checkpointers:
+        print(f"--- Checkpointer: {cp_label} ---")
+        _run_benchmark_for_checkpointer(cp_hint)
+
+
+def _run_benchmark_for_checkpointer(cp_hint: Any) -> None:
+    import contextlib
+    import tempfile
+
+    @contextlib.contextmanager
+    def _make_saver():
+        if cp_hint is None:
+            yield None
+        else:
+            with tempfile.NamedTemporaryFile(suffix=".db") as f:
+                with SqliteSaver.from_conn_string(f.name) as saver:
+                    yield saver
+
+    W = 120
+    print("=" * W)
+    header = (
+        f"{'turns':>6}  {'ctx size':>10}  "
+        f"{'add_msgs (bytes)':>18}  {'delta (bytes)':>15}  {'delta+snap (bytes)':>18}  "
+        f"{'storage saved':>14}  "
+        f"{'read: add_msgs':>14}  {'read: delta+snap':>16}"
+    )
+    print(header)
+    print("-" * W)
+
+    results = []
+    for turns in TURN_COUNTS:
+        with _make_saver() as saver:
+            b_wt, b_rt, b_bytes = _run_turns(turns, BinaryState, saver)
+        with _make_saver() as saver:
+            d_wt, d_rt, d_bytes = _run_turns(turns, DeltaState, saver)
+        with _make_saver() as saver:
+            s_wt, s_rt, s_bytes = _run_turns(turns, DeltaSnapshotState, saver)
+
+        # For non-InMemory savers, blob_bytes are unavailable (-1); use read times only
+        if b_bytes < 0 or s_bytes < 0:
+            b_bytes_str = "n/a"
+            d_bytes_str = "n/a"
+            s_bytes_str = "n/a"
+            storage_ratio_str = "n/a"
+        else:
+            storage_ratio = b_bytes / s_bytes if s_bytes else float("inf")
+            b_bytes_str = _fmt_bytes(b_bytes)
+            d_bytes_str = _fmt_bytes(d_bytes)
+            s_bytes_str = _fmt_bytes(s_bytes)
+            storage_ratio_str = f"{storage_ratio:.1f}x"
+            results.append((turns, b_bytes, s_bytes, b_rt, s_rt, storage_ratio))
+
+        print(
+            f"{turns:>6}  {_approx_tokens(turns):>10}  "
+            f"{b_bytes_str:>18}  {d_bytes_str:>15}  {s_bytes_str:>18}  "
+            f"{storage_ratio_str:>14}  "
+            f"{b_rt * 1000:>12.1f}ms  {s_rt * 1000:>14.1f}ms"
+        )
+
+    print("=" * W)
+    print()
+
+    if results:
+        best = results[-1]
+        turns, b_bytes, s_bytes, b_rt, s_rt, ratio = best
+        print(f"Key findings at max scale ({turns} turns):")
+        print(
+            f"  Storage:  {_fmt_bytes(b_bytes)} (add_messages)  →  {_fmt_bytes(s_bytes)} (DeltaChannel+snapshot) — {ratio:.0f}x reduction"
+        )
+        print(
+            f"  Read latency: {b_rt * 1000:.1f}ms (add_messages)  vs  {s_rt * 1000:.1f}ms (DeltaChannel+snapshot)"
+        )
+        print()
+    print("Legend:")
+    print(
+        "  add_msgs      = Annotated[list, add_messages]  — current default, O(N²) storage"
+    )
+    print(
+        "  delta         = DeltaChannel(add_messages)     — O(N) storage, unbounded chain at read"
+    )
+    print(
+        f"  delta+snap    = DeltaChannel(add_messages, snapshot_every={SNAPSHOT_EVERY})  — O(N) storage, O(1) read depth"
+    )
+    print()
+
+
+# ---------------------------------------------------------------------------
+# Pytest entry point
+# ---------------------------------------------------------------------------
+
+
+def test_delta_channel_benchmark(capsys: Any) -> None:
+    """Storage grows O(N²) for add_messages, O(N) for DeltaChannel."""
+    with capsys.disabled():
+        run_benchmark()
+
+    # Correctness assertion: DeltaChannel must use less storage at scale.
+    for turns in [100, 200]:
+        _, _, 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}"
+        )
+
+
+# ---------------------------------------------------------------------------
+# Script entry point
+# ---------------------------------------------------------------------------
+
+if __name__ == "__main__":
+    run_benchmark()
+    sys.exit(0)

libs/langgraph/tests/test_large_cases.py

@@ -1396,7 +1396,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
                 "langgraph_path": (PULL, "agent"),
                 "langgraph_checkpoint_ns": AnyStr("agent:"),
                 "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "fakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -1459,7 +1458,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
                 "langgraph_path": (PULL, "agent"),
                 "langgraph_checkpoint_ns": AnyStr("agent:"),
                 "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "fakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -1512,7 +1510,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
                 "langgraph_path": (PULL, "agent"),
                 "langgraph_checkpoint_ns": AnyStr("agent:"),
                 "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "fakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -6884,7 +6881,6 @@ def test_weather_subgraph(
                     "langgraph_path": ("__pregel_pull", "router_node"),
                     "langgraph_checkpoint_ns": AnyStr("router_node:"),
                     "checkpoint_ns": AnyStr("router_node:"),
-                    "_type": "fake-messages-list-chat-model",
                     "ls_provider": "fakemessageslistchatmodel",
                     "ls_model_type": "chat",
                     "ls_integration": "langchain_chat_model",
@@ -6912,7 +6908,6 @@ def test_weather_subgraph(
                     "langgraph_path": ("__pregel_pull", "model_node"),
                     "langgraph_checkpoint_ns": AnyStr("weather_graph:"),
                     "checkpoint_ns": AnyStr("weather_graph:"),
-                    "_type": "fake-messages-list-chat-model",
                     "ls_provider": "fakemessageslistchatmodel",
                     "ls_model_type": "chat",
                     "ls_integration": "langchain_chat_model",
@@ -6949,7 +6944,6 @@ def test_weather_subgraph(
                 "langgraph_path": ("__pregel_pull", "router_node"),
                 "langgraph_checkpoint_ns": AnyStr("router_node:"),
                 "checkpoint_ns": AnyStr("router_node:"),
-                "_type": "fake-messages-list-chat-model",
                 "ls_provider": "fakemessageslistchatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",

libs/langgraph/tests/test_large_cases_async.py

@@ -1147,7 +1147,6 @@ async def test_prebuilt_tool_chat() -> None:
                 "langgraph_path": (PULL, "agent"),
                 "langgraph_checkpoint_ns": AnyStr("agent:"),
                 "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "fakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -1210,7 +1209,6 @@ async def test_prebuilt_tool_chat() -> None:
                 "langgraph_path": (PULL, "agent"),
                 "langgraph_checkpoint_ns": AnyStr("agent:"),
                 "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "fakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -1263,7 +1261,6 @@ async def test_prebuilt_tool_chat() -> None:
                 "langgraph_path": (PULL, "agent"),
                 "langgraph_checkpoint_ns": AnyStr("agent:"),
                 "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "fakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -3981,7 +3978,6 @@ async def test_weather_subgraph(
                     "langgraph_path": ("__pregel_pull", "router_node"),
                     "langgraph_checkpoint_ns": AnyStr("router_node:"),
                     "checkpoint_ns": AnyStr("router_node:"),
-                    "_type": "fake-messages-list-chat-model",
                     "ls_provider": "fakemessageslistchatmodel",
                     "ls_model_type": "chat",
                     "ls_integration": "langchain_chat_model",
@@ -4009,7 +4005,6 @@ async def test_weather_subgraph(
                     "langgraph_path": ("__pregel_pull", "model_node"),
                     "langgraph_checkpoint_ns": AnyStr("weather_graph:"),
                     "checkpoint_ns": AnyStr("weather_graph:"),
-                    "_type": "fake-messages-list-chat-model",
                     "ls_provider": "fakemessageslistchatmodel",
                     "ls_model_type": "chat",
                     "ls_integration": "langchain_chat_model",
@@ -4046,7 +4041,6 @@ async def test_weather_subgraph(
                 "langgraph_path": ("__pregel_pull", "router_node"),
                 "langgraph_checkpoint_ns": AnyStr("router_node:"),
                 "checkpoint_ns": AnyStr("router_node:"),
-                "_type": "fake-messages-list-chat-model",
                 "ls_provider": "fakemessageslistchatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",

libs/langgraph/tests/test_pregel.py

@@ -615,8 +615,11 @@ def test_run_from_checkpoint_id_retains_previous_writes(
         )
     ]
 
-    assert len(new_history) == len(history) + 1
-    for original, new in zip(history, new_history[1:]):
+    # +2: one fork checkpoint from time travel, one from the new execution
+    assert len(new_history) == len(history) + 2
+    # new_history[0] is the new execution result, new_history[1] is the fork
+    assert new_history[1].metadata["source"] == "fork"
+    for original, new in zip(history, new_history[2:]):
         assert original.values == new.values
         assert original.next == new.next
         assert original.metadata["step"] == new.metadata["step"]
@@ -624,7 +627,7 @@ def test_run_from_checkpoint_id_retains_previous_writes(
     def _get_tasks(hist: list, start: int):
         return [h.tasks for h in hist[start:]]
 
-    assert _get_tasks(new_history, 1) == _get_tasks(history, 0)
+    assert _get_tasks(new_history, 2) == _get_tasks(history, 0)
 
 
 def test_batch_two_processes_in_out() -> None:
@@ -6893,7 +6896,6 @@ def test_tags_stream_mode_messages() -> None:
                 "langgraph_path": ("__pregel_pull", "call_model"),
                 "langgraph_checkpoint_ns": AnyStr("call_model:"),
                 "checkpoint_ns": AnyStr("call_model:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "genericfakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -6903,6 +6905,60 @@ def test_tags_stream_mode_messages() -> None:
     ]
 
 
+def test_configurable_propagates_to_stream_metadata() -> None:
+    """Regression: thread_id, run_id, assistant_id, graph_id,
+    and langgraph_auth_user_id from configurable must appear
+    in stream_mode='messages' metadata."""
+
+    def my_node(state):
+        return {"messages": HumanMessage(content="hello")}
+
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("my_node", my_node)
+        .add_edge(START, "my_node")
+        .compile()
+    )
+
+    config = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+            # these should NOT be propagated into metadata
+            "some_api_key": "secret",
+            "custom_setting": {"nested": True},
+        },
+    }
+    results = list(graph.stream({"messages": []}, config, stream_mode="messages"))
+    assert len(results) == 1
+    _, metadata = results[0]
+    # propagated keys
+    assert metadata["thread_id"] == "th-123"
+    assert metadata["checkpoint_id"] == "ckpt-1"
+    assert metadata["checkpoint_ns"] == "ns-1"
+    assert metadata["task_id"] == "task-1"
+    assert metadata["run_id"] == "run-456"
+    assert metadata["assistant_id"] == "asst-789"
+    assert metadata["graph_id"] == "graph-0"
+    # These are only present in trace metadata by default as of langgraph 1.2
+    # assert metadata["model"] == "gpt-4o"
+    # assert metadata["user_id"] == "uid-1"
+    # assert metadata["cron_id"] == "cron-1"
+    # assert metadata["langgraph_auth_user_id"] == "user-1"
+    # non-allowlisted keys must not appear
+    assert "some_api_key" not in metadata
+    assert "custom_setting" not in metadata
+
+
 def test_stream_mode_messages_command() -> None:
     from langchain_core.messages import HumanMessage
 
@@ -9344,3 +9400,190 @@ def test_fork_does_not_apply_pending_writes(
 
     # Should be: 1 (input) + 20 (forked node_a) + 100 (node_b) = 121
     assert result == {"value": 121}
+
+
+async def test_delta_channel_end_to_end_inmemory() -> None:
+    """Full graph run: DeltaChannel accumulates correctly across multiple turns."""
+    from langchain_core.messages import AIMessage, HumanMessage
+    from langgraph.checkpoint.memory import InMemorySaver
+
+    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)]
+
+    def respond(state: State) -> dict:
+        n = len(state["messages"])
+        return {"messages": [AIMessage(content=f"reply-{n}", id=f"ai-{n}")]}
+
+    builder = StateGraph(State)
+    builder.add_node("respond", respond)
+    builder.add_edge(START, "respond")
+    graph = builder.compile(checkpointer=InMemorySaver())
+
+    config = {"configurable": {"thread_id": "diff-test-1"}}
+
+    # Turn 1
+    graph.invoke({"messages": [HumanMessage(content="hello", id="h1")]}, config)
+    # Turn 2
+    graph.invoke({"messages": [HumanMessage(content="world", id="h2")]}, config)
+    # Turn 3
+    graph.invoke({"messages": [HumanMessage(content="bye", id="h3")]}, config)
+
+    state = graph.get_state(config)
+    msgs = state.values["messages"]
+    # 3 human + 3 AI = 6 total
+    assert len(msgs) == 6, f"expected 6 messages, got {len(msgs)}: {msgs}"
+    assert msgs[0].content == "hello"
+    assert msgs[2].content == "world"
+    assert msgs[4].content == "bye"
+    assert msgs[1].content == "reply-1"
+    assert msgs[3].content == "reply-3"
+    assert msgs[5].content == "reply-5"
+
+
+async def test_delta_channel_time_travel() -> None:
+    """Time-travel back to turn-1 checkpoint and resume; continuation must not include turn-2 deltas."""
+    from langchain_core.messages import AIMessage, HumanMessage
+    from langgraph.checkpoint.memory import InMemorySaver
+
+    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)]
+
+    counter = {"n": 0}
+
+    def respond(state: State) -> dict:
+        counter["n"] += 1
+        return {
+            "messages": [
+                AIMessage(content=f"ai-{counter['n']}", id=f"ai-{counter['n']}")
+            ]
+        }
+
+    builder = StateGraph(State)
+    builder.add_node("respond", respond)
+    builder.add_edge(START, "respond")
+    saver = InMemorySaver()
+    graph = builder.compile(checkpointer=saver)
+
+    config = {"configurable": {"thread_id": "diff-time-travel"}}
+
+    # Run 2 turns: h1→ai-1, h2→ai-2
+    graph.invoke({"messages": [HumanMessage(content="h1", id="h1")]}, config)
+    graph.invoke({"messages": [HumanMessage(content="h2", id="h2")]}, config)
+
+    # Find the checkpoint after turn 1 (2 messages: h1 + ai-1)
+    history = list(graph.get_state_history(config))
+    after_turn1 = next(h for h in history if len(h.values.get("messages", [])) == 2)
+
+    assert len(after_turn1.values["messages"]) == 2
+    assert after_turn1.values["messages"][0].content == "h1"
+    assert after_turn1.values["messages"][1].content == "ai-1"
+
+    # Resume from turn-1 checkpoint: inject h3, expect 3 messages total (h1, ai-1, ai-N)
+    # NOT 5 messages (turn-2 deltas must not bleed into the resumed run)
+    result = graph.invoke(
+        {"messages": [HumanMessage(content="h3", id="h3")]},
+        after_turn1.config,
+    )
+    msgs = result["messages"]
+    # Should be: h1, ai-1, h3, ai-N — 4 messages total
+    assert len(msgs) == 4, (
+        f"expected 4 messages after time-travel resume, got {len(msgs)}: {msgs}"
+    )
+    assert msgs[0].content == "h1"
+    assert msgs[1].content == "ai-1"
+    assert msgs[2].content == "h3"
+
+
+async def test_delta_channel_remove_message_end_to_end() -> None:
+    """RemoveMessage inside a DeltaChannel graph must persist and reload correctly."""
+    from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
+    from langgraph.checkpoint.memory import InMemorySaver
+
+    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)]
+
+    def respond(state: State) -> dict:
+        return {"messages": [AIMessage(content="reply", id="ai-1")]}
+
+    def delete_first(state: State) -> dict:
+        # removes the first message
+        return {"messages": [RemoveMessage(id=state["messages"][0].id)]}
+
+    builder = StateGraph(State)
+    builder.add_node("respond", respond)
+    builder.add_node("delete_first", delete_first)
+    builder.add_edge(START, "respond")
+    builder.add_edge("respond", "delete_first")
+    graph = builder.compile(checkpointer=InMemorySaver())
+
+    config = {"configurable": {"thread_id": "diff-remove-test"}}
+    graph.invoke({"messages": [HumanMessage(content="hello", id="h1")]}, config)
+
+    state = graph.get_state(config)
+    msgs = state.values["messages"]
+    # h1 was removed, only ai-1 should remain
+    assert len(msgs) == 1, f"expected 1 message, got {len(msgs)}: {msgs}"
+    assert msgs[0].id == "ai-1"
+
+    # A subsequent turn must reconstruct from the checkpoint correctly
+    graph.invoke({"messages": [HumanMessage(content="again", id="h2")]}, config)
+    state = graph.get_state(config)
+    msgs = state.values["messages"]
+    # ai-1 + h2 + ai-1(second reply, same id overwrites) + h2 removed
+    # more simply: after second run we expect ai-1 updated + h2 remaining minus deleted h2
+    # just assert h1 is still gone
+    assert all(m.id != "h1" for m in msgs), (
+        "h1 should still be absent after second turn"
+    )
+
+
+async def test_delta_channel_update_by_id_end_to_end() -> None:
+    """Updating a message by ID via DeltaChannel must persist and reload correctly."""
+    from langchain_core.messages import HumanMessage
+    from langgraph.checkpoint.memory import InMemorySaver
+
+    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)]
+
+    def update_msg(state: State) -> dict:
+        # re-send h1 with updated content
+        return {"messages": [HumanMessage(content="updated", id="h1")]}
+
+    builder = StateGraph(State)
+    builder.add_node("update_msg", update_msg)
+    builder.add_edge(START, "update_msg")
+    graph = builder.compile(checkpointer=InMemorySaver())
+
+    config = {"configurable": {"thread_id": "diff-update-id-test"}}
+    graph.invoke({"messages": [HumanMessage(content="original", id="h1")]}, config)
+
+    state = graph.get_state(config)
+    msgs = state.values["messages"]
+    assert len(msgs) == 1, f"expected 1 message, got {len(msgs)}: {msgs}"
+    assert msgs[0].content == "updated"
+    assert msgs[0].id == "h1"
+
+    # Second turn: verify the updated state is the base for further accumulation
+    graph.invoke({"messages": [HumanMessage(content="new", id="h2")]}, config)
+    state = graph.get_state(config)
+    msgs = state.values["messages"]
+    ids = [m.id for m in msgs]
+    assert "h1" in ids  # h1 persists (updated, not duplicated)
+    assert "h2" in ids
+    assert ids.count("h1") == 1, "h1 must not be duplicated"

libs/langgraph/tests/test_pregel_async.py

@@ -20,6 +20,7 @@ from uuid import UUID
 
 import pytest
 from langchain_core.language_models import GenericFakeChatModel
+from langchain_core.messages import HumanMessage
 from langchain_core.runnables import RunnableConfig, RunnableLambda, RunnablePassthrough
 from langchain_core.utils.aiter import aclosing
 from langgraph.cache.base import BaseCache
@@ -2085,8 +2086,11 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
         )
     ]
 
-    assert len(new_history) == len(history) + 1
-    for original, new in zip(history, new_history[1:]):
+    # +2: one fork checkpoint from time travel, one from the new execution
+    assert len(new_history) == len(history) + 2
+    # new_history[0] is the new execution result, new_history[1] is the fork
+    assert new_history[1].metadata["source"] == "fork"
+    for original, new in zip(history, new_history[2:]):
         assert original.values == new.values
         assert original.next == new.next
         assert original.metadata["step"] == new.metadata["step"]
@@ -2094,7 +2098,7 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
     def _get_tasks(hist: list, start: int):
         return [h.tasks for h in hist[start:]]
 
-    assert _get_tasks(new_history, 1) == _get_tasks(history, 0)
+    assert _get_tasks(new_history, 2) == _get_tasks(history, 0)
 
 
 async def test_cond_edge_after_send() -> None:
@@ -7541,7 +7545,6 @@ async def test_tags_stream_mode_messages() -> None:
                 "langgraph_path": ("__pregel_pull", "call_model"),
                 "langgraph_checkpoint_ns": AnyStr("call_model:"),
                 "checkpoint_ns": AnyStr("call_model:"),
-                "_type": "generic-fake-chat-model",
                 "ls_provider": "genericfakechatmodel",
                 "ls_model_type": "chat",
                 "ls_integration": "langchain_chat_model",
@@ -7551,6 +7554,67 @@ async def test_tags_stream_mode_messages() -> None:
     ]
 
 
+async def test_configurable_propagates_to_stream_metadata() -> None:
+    """Regression: thread_id, run_id, assistant_id, graph_id,
+    and langgraph_auth_user_id from configurable must appear
+    in stream_mode='messages' metadata."""
+
+    def my_node(state):
+        return {"messages": HumanMessage(content="hello")}
+
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("my_node", my_node)
+        .add_edge(START, "my_node")
+        .compile()
+    )
+
+    config = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+            # these should NOT be propagated into metadata
+            "some_api_key": "secret",
+            "custom_setting": {"nested": True},
+        },
+    }
+    results = [
+        chunk
+        async for chunk in graph.astream(
+            {"messages": []}, config, stream_mode="messages"
+        )
+    ]
+    assert len(results) == 1
+    _, metadata = results[0]
+    # propagated keys
+    assert metadata["thread_id"] == "th-123"
+    assert metadata["checkpoint_id"] == "ckpt-1"
+    assert metadata["checkpoint_ns"] == "ns-1"
+    assert metadata["task_id"] == "task-1"
+    assert metadata["run_id"] == "run-456"
+    assert metadata["assistant_id"] == "asst-789"
+    assert metadata["graph_id"] == "graph-0"
+
+    # These will only be traced as of langgraph 1.2 and not present by default in
+    # metadata
+    # assert metadata["model"] == "gpt-4o"
+    # assert metadata["user_id"] == "uid-1"
+    # assert metadata["cron_id"] == "cron-1"
+    # assert metadata["langgraph_auth_user_id"] == "user-1"
+    # non-allowlisted keys must not appear
+    assert "some_api_key" not in metadata
+    assert "custom_setting" not in metadata
+
+
 async def test_stream_mode_messages_command() -> None:
     from langchain_core.messages import HumanMessage
 

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_runtime.py

@@ -501,13 +501,13 @@ async def test_execution_info_populated_in_graph_async() -> None:
     assert isinstance(info.node_first_attempt_time, float)
 
 
-def test_server_info_from_metadata() -> None:
-    """server_info is built from assistant_id/graph_id in config metadata."""
+def test_server_info_from_configurable() -> None:
+    """server_info is built from assistant_id/graph_id in config configurable."""
     captured: dict[str, Any] = {}
     compiled = _make_capture_graph(captured)
     compiled.invoke(
         {"message": "hi"},
-        config={"metadata": {"assistant_id": "asst-abc", "graph_id": "my-graph"}},
+        config={"configurable": {"assistant_id": "asst-abc", "graph_id": "my-graph"}},
     )
     si = captured["server_info"]
     assert si is not None
@@ -516,8 +516,8 @@ def test_server_info_from_metadata() -> None:
     assert si.user is None
 
 
-def test_server_info_none_without_metadata() -> None:
-    """server_info is None when no assistant_id/graph_id in metadata."""
+def test_server_info_none_without_configurable() -> None:
+    """server_info is None when no assistant_id/graph_id in configurable."""
     captured: dict[str, Any] = {}
     compiled = _make_capture_graph(captured)
     compiled.invoke({"message": "hi"})
@@ -579,8 +579,11 @@ def test_server_info_user_from_auth_user() -> None:
     compiled.invoke(
         {"message": "hi"},
         config={
-            "configurable": {"langgraph_auth_user": proxy},
-            "metadata": {"assistant_id": "asst-proxy", "graph_id": "graph-proxy"},
+            "configurable": {
+                "langgraph_auth_user": proxy,
+                "assistant_id": "asst-proxy",
+                "graph_id": "graph-proxy",
+            },
         },
     )
     si = captured["server_info"]

libs/langgraph/tests/test_time_travel.py

@@ -37,6 +37,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
     Returns a list of dicts (newest-first, matching get_state_history order) with:
       - id: short checkpoint id suffix (last 6 chars)
       - parent_id: short parent checkpoint id suffix or None
+      - source: checkpoint metadata source (input, loop, fork, update)
       - next: tuple of next node names
       - values: channel values snapshot
     """
@@ -52,6 +53,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
             {
                 "id": cid[-6:],
                 "parent_id": pid[-6:] if pid else None,
+                "source": s.metadata.get("source"),
                 "next": s.next,
                 "values": s.values,
             }
@@ -280,6 +282,116 @@ def test_replay_from_before_interrupt_refires(
     assert call_count["node_b"] == 1  # NOT re-executed (after interrupt)
 
 
+def test_replay_from_before_interrupt_then_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Replay from checkpoint before interrupt node, then resume with a new
+    answer and verify the graph completes with the new value.
+
+    Graph: START --> node_a --> ask_human (interrupt) --> node_b --> END
+
+    Original run:
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(node_a,)     values=[]
+      source=loop   next=(ask_human,)  values=[a]            <-- replay from here
+      source=loop   next=(node_b,)     values=[a, human:old_answer]
+      source=loop   next=()            values=[a, human:old_answer, b]
+
+    After replay (fork created) + resume with "new_answer":
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(node_a,)     values=[]
+      source=loop   next=(ask_human,)  values=[a]            <-- branch point
+      source=loop   next=(node_b,)     values=[a, human:old_answer]
+      source=loop   next=()            values=[a, human:old_answer, b]  (old branch)
+      source=fork   next=(ask_human,)  values=[a]            <-- fork from branch point
+      source=loop   next=(node_b,)     values=[a, human:new_answer]
+      source=loop   next=()            values=[a, human:new_answer, b]  (new branch)
+    """
+
+    called: list[str] = []
+
+    def node_a(state: State) -> State:
+        called.append("node_a")
+        return {"value": ["a"]}
+
+    def ask_human(state: State) -> State:
+        called.append("ask_human")
+        answer = interrupt("What is your input?")
+        return {"value": [f"human:{answer}"]}
+
+    def node_b(state: State) -> State:
+        called.append("node_b")
+        return {"value": ["b"]}
+
+    graph = (
+        StateGraph(State)
+        .add_node("node_a", node_a)
+        .add_node("ask_human", ask_human)
+        .add_node("node_b", node_b)
+        .add_edge(START, "node_a")
+        .add_edge("node_a", "ask_human")
+        .add_edge("ask_human", "node_b")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: invoke until interrupt, then resume to complete ---
+    graph.invoke({"value": []}, config)
+    graph.invoke(Command(resume="old_answer"), config)
+
+    original_history = list(graph.get_state_history(config))
+    original = _checkpoint_summary(original_history)
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Replay from checkpoint before ask_human ---
+    before_ask = next(s for s in original_history if s.next == ("ask_human",))
+
+    called.clear()
+    replay_result = graph.invoke(None, before_ask.config)
+    assert replay_result["__interrupt__"][0].value == "What is your input?"
+    assert "ask_human" in called
+    assert "node_a" not in called  # before the replay point, not re-executed
+
+    # A fork checkpoint is now the latest — it branches from the replay point
+    post_replay = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"]) for s in post_replay] == [
+        ("fork", ("ask_human",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("node_b",)),
+        ("loop", ("ask_human",)),  # branch point
+        ("loop", ("node_a",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer ---
+    called.clear()
+    final_result = graph.invoke(Command(resume="new_answer"), config)
+    assert final_result["value"] == ["a", "human:new_answer", "b"]
+    assert "ask_human" in called
+    assert "node_b" in called
+
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from fork)
+        ("loop", (), {"value": ["a", "human:new_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:new_answer"]}),
+        ("fork", ("ask_human",), {"value": ["a"]}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
 def test_replay_interrupt_stable_across_replays(
     sync_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -320,8 +432,14 @@ def test_replay_interrupt_stable_across_replays(
         r = graph.invoke(None, before_ask.config)
         results.append(r)
 
-    assert all(r == results[0] for r in results)
-    assert "__interrupt__" in results[0]
+    # Each replay creates a fork with a unique interrupt ID, so we compare
+    # interrupt values and state values rather than full equality.
+    assert all("__interrupt__" in r for r in results)
+    assert all(
+        r["__interrupt__"][0].value == results[0]["__interrupt__"][0].value
+        for r in results
+    )
+    assert all(r["value"] == results[0]["value"] for r in results)
 
 
 def test_fork_from_before_interrupt_refires(
@@ -854,6 +972,290 @@ def test_subgraph_interrupt_replay_from_interrupt_checkpoint(
     assert "step_b" not in called
 
 
+def test_subgraph_interrupt_replay_from_parent_then_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Replay from the parent checkpoint where a subgraph interrupt fired,
+    then resume with a new answer. Verifies that a fork is created and the
+    full graph completes. Checks full checkpoint history at each stage."""
+
+    called: list[str] = []
+
+    def router(state: State) -> State:
+        called.append("router")
+        return {"value": ["routed"]}
+
+    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)
+    )
+
+    def post_process(state: State) -> State:
+        called.append("post_process")
+        return {"value": ["post"]}
+
+    graph = (
+        StateGraph(State)
+        .add_node("router", router)
+        .add_node("subgraph_node", subgraph)
+        .add_node("post_process", post_process)
+        .add_edge(START, "router")
+        .add_edge("router", "subgraph_node")
+        .add_edge("subgraph_node", "post_process")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt, then resume to complete
+    graph.invoke({"value": []}, config)
+    graph.invoke(Command(resume="old_answer"), config)
+
+    # Original parent history (newest first)
+    original_history = list(graph.get_state_history(config))
+    assert [s.next for s in original_history] == [
+        (),  # done
+        ("post_process",),
+        ("subgraph_node",),  # subgraph ran, interrupt fired here
+        ("router",),
+        ("__start__",),
+    ]
+
+    # Find the parent checkpoint where the interrupt fired
+    interrupt_checkpoint = next(
+        s for s in original_history if s.next == ("subgraph_node",)
+    )
+
+    # Replay from parent checkpoint — subgraph re-executes, interrupt re-fires
+    called.clear()
+    replay_result = graph.invoke(None, interrupt_checkpoint.config)
+    assert "__interrupt__" in replay_result
+    assert replay_result["__interrupt__"][0].value == "Provide input:"
+    assert "step_a" in called
+    assert "ask_human" in called
+    assert "step_b" not in called
+
+    # Verify fork checkpoint was created
+    post_replay_history = list(graph.get_state_history(config))
+    assert [s.next for s in post_replay_history] == [
+        ("subgraph_node",),  # fork (interrupt pending)
+        (),  # original done
+        ("post_process",),
+        ("subgraph_node",),
+        ("router",),
+        ("__start__",),
+    ]
+    assert [s.metadata["source"] for s in post_replay_history] == [
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+    fork = post_replay_history[0]
+    assert (
+        fork.parent_config["configurable"]["checkpoint_id"]
+        == interrupt_checkpoint.config["configurable"]["checkpoint_id"]
+    )
+
+    # Resume with a new answer — full graph should complete
+    called.clear()
+    final_result = graph.invoke(Command(resume="new_answer"), config)
+    assert "__interrupt__" not in final_result
+    assert "human:new_answer" in final_result["value"]
+    assert "sub_b" in final_result["value"]
+    assert "post" in final_result["value"]
+    assert "ask_human" in called
+    assert "step_b" in called
+    assert "post_process" in called
+
+    # Final checkpoint history
+    final_history = list(graph.get_state_history(config))
+    assert [s.next for s in final_history] == [
+        (),  # new branch done
+        ("post_process",),  # new branch post_process
+        ("subgraph_node",),  # fork
+        (),  # original done
+        ("post_process",),
+        ("subgraph_node",),
+        ("router",),
+        ("__start__",),
+    ]
+    assert [s.metadata["source"] for s in final_history] == [
+        "loop",
+        "loop",
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+
+
+def test_subgraph_replay_loads_accumulated_state_then_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Two parent invocations, then replay from before the subgraph in the
+    2nd invocation. The subgraph (checkpointer=True) should load its
+    accumulated state from the 1st invocation via ReplayState, re-fire
+    the interrupt, and then resume + complete.
+
+    This tests the ReplayState path: the parent is replaying and the
+    subgraph uses list(before=parent_checkpoint_id) to find its
+    corresponding checkpoint from the original execution.
+    """
+
+    class SubState(TypedDict):
+        value: Annotated[list[str], operator.add]
+
+    class ParentState(TypedDict):
+        results: Annotated[list[str], operator.add]
+
+    started_state: list[dict] = []
+
+    def step_a(state: SubState) -> SubState:
+        started_state.append(dict(state))
+        answer = interrupt("question_a")
+        return {"value": [f"a:{answer}"]}
+
+    subgraph = (
+        StateGraph(SubState)
+        .add_node("step_a", step_a)
+        .add_edge(START, "step_a")
+        .compile(checkpointer=True)
+    )
+
+    def parent_node(state: ParentState) -> ParentState:
+        return {"results": ["p"]}
+
+    graph = (
+        StateGraph(ParentState)
+        .add_node("parent_node", parent_node)
+        .add_node("sub_node", subgraph)
+        .add_edge(START, "parent_node")
+        .add_edge("parent_node", "sub_node")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # === 1st invocation: complete with answer "a1" ===
+    graph.invoke({"results": []}, config)
+    graph.invoke(Command(resume="a1"), config)
+
+    # step_a saw empty state (fresh subgraph)
+    assert started_state[0] == {"value": []}
+
+    # === 2nd invocation: complete with answer "a2" ===
+    started_state.clear()
+    graph.invoke({"results": []}, config)
+    graph.invoke(Command(resume="a2"), config)
+
+    # Stateful subgraph retained state from 1st invocation
+    assert started_state[0] == {"value": ["a:a1"]}
+
+    # Original history (newest first)
+    original_history = list(graph.get_state_history(config))
+    assert [s.next for s in original_history] == [
+        (),  # 2nd done
+        ("sub_node",),  # 2nd sub_node
+        ("parent_node",),  # 2nd parent_node
+        ("__start__",),  # 2nd input
+        (),  # 1st done
+        ("sub_node",),  # 1st sub_node
+        ("parent_node",),  # 1st parent_node
+        ("__start__",),  # 1st input
+    ]
+
+    # Replay from before sub_node in 2nd invocation (newest match)
+    before_sub_2nd = [s for s in original_history if s.next == ("sub_node",)][0]
+    started_state.clear()
+    replay = graph.invoke(None, before_sub_2nd.config)
+    assert "__interrupt__" in replay
+
+    # Subgraph should see accumulated state from END of 1st invocation
+    assert started_state[0] == {"value": ["a:a1"]}
+
+    # Verify fork was created
+    post_replay_history = list(graph.get_state_history(config))
+    assert [s.next for s in post_replay_history] == [
+        ("sub_node",),  # fork (interrupt pending)
+        (),  # 2nd done
+        ("sub_node",),  # 2nd sub_node
+        ("parent_node",),  # 2nd parent_node
+        ("__start__",),  # 2nd input
+        (),  # 1st done
+        ("sub_node",),  # 1st sub_node
+        ("parent_node",),  # 1st parent_node
+        ("__start__",),  # 1st input
+    ]
+    assert [s.metadata["source"] for s in post_replay_history] == [
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+
+    # Resume with a new answer
+    started_state.clear()
+    final = graph.invoke(Command(resume="a3"), config)
+    assert "__interrupt__" not in final
+    assert final["results"] == ["p", "p"]
+
+    # Final history
+    final_history = list(graph.get_state_history(config))
+    assert [s.next for s in final_history] == [
+        (),  # new branch done
+        ("sub_node",),  # fork
+        (),  # 2nd done
+        ("sub_node",),  # 2nd sub_node
+        ("parent_node",),  # 2nd parent_node
+        ("__start__",),  # 2nd input
+        (),  # 1st done
+        ("sub_node",),  # 1st sub_node
+        ("parent_node",),  # 1st parent_node
+        ("__start__",),  # 1st input
+    ]
+    assert [s.metadata["source"] for s in final_history] == [
+        "loop",
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+
+
 def test_subgraph_interrupt_full_flow(
     sync_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -1290,6 +1692,321 @@ def test_subgraph_time_travel_to_second_interrupt(
     assert "ask_1" not in called
 
 
+def test_subgraph_time_travel_resume_from_first_interrupt(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the first interrupt, then
+    resume through both interrupts with new answers.
+
+    This verifies the key bug fix: after time-traveling to a subgraph
+    checkpoint with an interrupt, a fork checkpoint is created so that
+    subsequent resumes find the correct state (not the old branch tip).
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+
+    Parent history after original run completes:
+      source=input  next=(__start__,)   values=[]
+      source=loop   next=(executor,)    values=[]
+      source=loop   next=()             values=[step_a_done, ask_1:answer_1, ask_2:answer_2]
+
+    After time-traveling to 1st interrupt + resuming with new answers:
+      source=input  next=(__start__,)   values=[]
+      source=loop   next=(executor,)    values=[]          <-- branch point
+      source=loop   next=()             values=[..., ask_2:answer_2]  (old branch)
+      source=fork   next=(executor,)    values=[]          <-- fork from time travel
+      source=loop   next=()             values=[..., ask_2:new_answer_2]  (new branch)
+    """
+
+    called: list[str] = []
+
+    def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    graph.invoke({"value": []}, config)
+    sub_config_at_first = graph.get_state(config, subgraphs=True).tasks[0].state.config
+    graph.invoke(Command(resume="answer_1"), config)
+    graph.invoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to first interrupt's subgraph checkpoint ---
+    called.clear()
+    replay_result = graph.invoke(None, sub_config_at_first)
+    assert replay_result["__interrupt__"][0].value == "Question 1?"
+    assert "step_a" not in called  # before interrupt, not re-executed
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume both interrupts with new answers ---
+    called.clear()
+    resume_1 = graph.invoke(Command(resume="new_answer_1"), config)
+    assert resume_1["__interrupt__"][0].value == "Question 2?"
+    assert "ask_1" in called
+
+    called.clear()
+    resume_2 = graph.invoke(Command(resume="new_answer_2"), config)
+    assert resume_2["value"] == [
+        "step_a_done",
+        "ask_1:new_answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history: original branch preserved, new branch appended
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:new_answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+def test_subgraph_time_travel_resume_from_second_interrupt(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the second interrupt, then
+    resume with a new answer. The first interrupt's answer should be preserved.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+
+    Key assertion: after resuming from a time-travel to the 2nd interrupt,
+    the final state keeps ask_1's original answer but uses the new ask_2 answer.
+    """
+
+    called: list[str] = []
+
+    def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    graph.invoke({"value": []}, config)
+    graph.invoke(Command(resume="answer_1"), config)
+    sub_config_at_second = graph.get_state(config, subgraphs=True).tasks[0].state.config
+    graph.invoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to second interrupt ---
+    called.clear()
+    replay_result = graph.invoke(None, sub_config_at_second)
+    assert replay_result["__interrupt__"][0].value == "Question 2?"
+    assert "step_a" not in called
+    assert "ask_1" not in called  # already resolved, not re-executed
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer for ask_2 only ---
+    called.clear()
+    resume_result = graph.invoke(Command(resume="new_answer_2"), config)
+    # ask_1's original answer preserved, ask_2 uses the new answer
+    assert resume_result["value"] == [
+        "step_a_done",
+        "ask_1:answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history: original branch preserved, new branch appended
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+def test_subgraph_time_travel_checkpoint_pattern(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Verify the checkpoint pattern created by time travel to a subgraph
+    interrupt. A fork checkpoint should branch from the replay point and
+    become the latest parent checkpoint.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> ask (interrupt) --> END
+
+    Original run (after completing):
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(executor,)   values=[]          <-- replay point
+      source=loop   next=()            values=[a:first]
+
+    After time travel to interrupt + resume with "second":
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(executor,)   values=[]          <-- branch point
+      source=loop   next=()            values=[a:first]   (old branch)
+      source=fork   next=(executor,)   values=[]          <-- fork
+      source=loop   next=()            values=[a:second]  (new branch)
+    """
+
+    def ask(state: State) -> State:
+        answer = interrupt("Q?")
+        return {"value": [f"a:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("ask", ask)
+        .add_edge(START, "ask")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt, then complete
+    graph.invoke({"value": []}, config)
+    sub_config = graph.get_state(config, subgraphs=True).tasks[0].state.config
+    graph.invoke(Command(resume="first"), config)
+
+    original = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # Time travel to the interrupt
+    graph.invoke(None, sub_config)
+
+    # Fork is now the latest, branching from the original replay point
+    post_tt = list(graph.get_state_history(config))
+    post_tt_summary = _checkpoint_summary(post_tt)
+    assert [(s["source"], s["next"]) for s in post_tt_summary] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),
+        ("loop", ("executor",)),  # <-- replay point / fork parent
+        ("input", ("__start__",)),
+    ]
+    # Verify the fork's parent is the original replay point
+    replay_point_id = sub_config["configurable"]["checkpoint_map"][""]
+    assert post_tt[0].parent_config["configurable"]["checkpoint_id"] == replay_point_id
+
+    # Resume from the fork — graph completes with new answer
+    result = graph.invoke(Command(resume="second"), config)
+    assert result["value"] == ["a:second"]
+
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch
+        ("loop", (), {"value": ["a:second"]}),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
 def test_subgraph_time_travel_after_completion(
     sync_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -2283,14 +3000,16 @@ def test_replay_creates_branch_preserving_old_checkpoints(
     # -- Post-replay checkpoint history (newest first) --
     post_replay_history = list(graph.get_state_history(config))
     post_summary = _checkpoint_summary(post_replay_history)
-    assert len(post_summary) == 7  # 5 original + 2 new branch checkpoints
+    # 5 original + 1 fork + 2 new branch checkpoints = 8
+    assert len(post_summary) == 8
 
     # Verify the full shape after replay
     assert [s["next"] for s in post_summary] == [
-        (),  # new branch tip (C6)
-        ("node_c",),  # new branch (C5)
-        (),  # old branch tip (C4)
-        ("node_c",),  # old (C3)
+        (),  # new branch tip
+        ("node_c",),  # new branch
+        ("node_b",),  # fork from replay point
+        (),  # old branch tip
+        ("node_c",),  # old
         ("node_b",),  # branch point (C2)
         ("node_a",),  # old (C1)
         ("__start__",),  # old (C0)
@@ -2298,6 +3017,7 @@ def test_replay_creates_branch_preserving_old_checkpoints(
     assert [s["values"] for s in post_summary] == [
         {"value": ["a", "b2", "c"]},  # new branch tip
         {"value": ["a", "b2"]},  # new: node_b re-ran with call_count=2
+        {"value": ["a"]},  # fork from replay point
         {"value": ["a", "b1", "c"]},  # old branch tip preserved
         {"value": ["a", "b1"]},  # old
         {"value": ["a"]},  # branch point

libs/langgraph/tests/test_time_travel_async.py

@@ -46,6 +46,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
     Returns a list of dicts (newest-first, matching get_state_history order) with:
       - id: short checkpoint id suffix (last 6 chars)
       - parent_id: short parent checkpoint id suffix or None
+      - source: checkpoint metadata source (input, loop, fork, update)
       - next: tuple of next node names
       - values: channel values snapshot
     """
@@ -61,6 +62,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
             {
                 "id": cid[-6:],
                 "parent_id": pid[-6:] if pid else None,
+                "source": s.metadata.get("source"),
                 "next": s.next,
                 "values": s.values,
             }
@@ -335,8 +337,14 @@ async def test_replay_interrupt_stable_across_replays(
         r = await graph.ainvoke(None, before_ask.config)
         results.append(r)
 
-    assert all(r == results[0] for r in results)
-    assert "__interrupt__" in results[0]
+    # Each replay creates a fork with a unique interrupt ID, so we compare
+    # interrupt values and state values rather than full equality.
+    assert all("__interrupt__" in r for r in results)
+    assert all(
+        r["__interrupt__"][0].value == results[0]["__interrupt__"][0].value
+        for r in results
+    )
+    assert all(r["value"] == results[0]["value"] for r in results)
 
 
 @NEEDS_CONTEXTVARS
@@ -1261,6 +1269,391 @@ async def test_subgraph_time_travel_after_completion_async(
     assert "ask_2:answer_2" in replay_result["value"]
 
 
+@NEEDS_CONTEXTVARS
+async def test_replay_from_before_interrupt_then_resume_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Replay from checkpoint before interrupt node, then resume with a new
+    answer and verify the graph completes with the new value.
+
+    Graph: START --> node_a --> ask_human (interrupt) --> node_b --> END
+    """
+
+    called: list[str] = []
+
+    async def node_a(state: State) -> State:
+        called.append("node_a")
+        return {"value": ["a"]}
+
+    async def ask_human(state: State) -> State:
+        called.append("ask_human")
+        answer = interrupt("What is your input?")
+        return {"value": [f"human:{answer}"]}
+
+    async def node_b(state: State) -> State:
+        called.append("node_b")
+        return {"value": ["b"]}
+
+    graph = (
+        StateGraph(State)
+        .add_node("node_a", node_a)
+        .add_node("ask_human", ask_human)
+        .add_node("node_b", node_b)
+        .add_edge(START, "node_a")
+        .add_edge("node_a", "ask_human")
+        .add_edge("ask_human", "node_b")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: invoke until interrupt, then resume to complete ---
+    await graph.ainvoke({"value": []}, config)
+    await graph.ainvoke(Command(resume="old_answer"), config)
+
+    original_history = [s async for s in graph.aget_state_history(config)]
+    original = _checkpoint_summary(original_history)
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Replay from checkpoint before ask_human ---
+    before_ask = next(s for s in original_history if s.next == ("ask_human",))
+
+    called.clear()
+    replay_result = await graph.ainvoke(None, before_ask.config)
+    assert replay_result["__interrupt__"][0].value == "What is your input?"
+    assert "ask_human" in called
+    assert "node_a" not in called
+
+    # A fork checkpoint is now the latest
+    post_replay = _checkpoint_summary(
+        [s async for s in graph.aget_state_history(config)]
+    )
+    assert [(s["source"], s["next"]) for s in post_replay] == [
+        ("fork", ("ask_human",)),
+        ("loop", ()),
+        ("loop", ("node_b",)),
+        ("loop", ("ask_human",)),
+        ("loop", ("node_a",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer ---
+    called.clear()
+    final_result = await graph.ainvoke(Command(resume="new_answer"), config)
+    assert final_result["value"] == ["a", "human:new_answer", "b"]
+    assert "ask_human" in called
+    assert "node_b" in called
+
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from fork)
+        ("loop", (), {"value": ["a", "human:new_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:new_answer"]}),
+        ("fork", ("ask_human",), {"value": ["a"]}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+@NEEDS_CONTEXTVARS
+async def test_subgraph_time_travel_resume_from_first_interrupt_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the first interrupt, then
+    resume through both interrupts with new answers.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+    """
+
+    called: list[str] = []
+
+    async def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    async def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    async def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    await graph.ainvoke({"value": []}, config)
+    sub_config_at_first = (
+        (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
+    )
+    await graph.ainvoke(Command(resume="answer_1"), config)
+    await graph.ainvoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to first interrupt's subgraph checkpoint ---
+    called.clear()
+    replay_result = await graph.ainvoke(None, sub_config_at_first)
+    assert replay_result["__interrupt__"][0].value == "Question 1?"
+    assert "step_a" not in called
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume both interrupts with new answers ---
+    called.clear()
+    resume_1 = await graph.ainvoke(Command(resume="new_answer_1"), config)
+    assert resume_1["__interrupt__"][0].value == "Question 2?"
+    assert "ask_1" in called
+
+    called.clear()
+    resume_2 = await graph.ainvoke(Command(resume="new_answer_2"), config)
+    assert resume_2["value"] == [
+        "step_a_done",
+        "ask_1:new_answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history: original branch preserved, new branch appended
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:new_answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+@NEEDS_CONTEXTVARS
+async def test_subgraph_time_travel_resume_from_second_interrupt_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the second interrupt, then
+    resume with a new answer. The first interrupt's answer should be preserved.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+    """
+
+    called: list[str] = []
+
+    async def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    async def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    async def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    await graph.ainvoke({"value": []}, config)
+    await graph.ainvoke(Command(resume="answer_1"), config)
+    sub_config_at_second = (
+        (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
+    )
+    await graph.ainvoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to second interrupt ---
+    called.clear()
+    replay_result = await graph.ainvoke(None, sub_config_at_second)
+    assert replay_result["__interrupt__"][0].value == "Question 2?"
+    assert "step_a" not in called
+    assert "ask_1" not in called
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer for ask_2 only ---
+    called.clear()
+    resume_result = await graph.ainvoke(Command(resume="new_answer_2"), config)
+    assert resume_result["value"] == [
+        "step_a_done",
+        "ask_1:answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+@NEEDS_CONTEXTVARS
+async def test_subgraph_time_travel_checkpoint_pattern_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Verify the checkpoint pattern created by time travel to a subgraph
+    interrupt. A fork checkpoint should branch from the replay point.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> ask (interrupt) --> END
+    """
+
+    async def ask(state: State) -> State:
+        answer = interrupt("Q?")
+        return {"value": [f"a:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("ask", ask)
+        .add_edge(START, "ask")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt, then complete
+    await graph.ainvoke({"value": []}, config)
+    sub_config = (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
+    await graph.ainvoke(Command(resume="first"), config)
+
+    original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # Time travel to the interrupt
+    await graph.ainvoke(None, sub_config)
+
+    # Fork is now the latest, branching from the original replay point
+    post_tt = [s async for s in graph.aget_state_history(config)]
+    post_tt_summary = _checkpoint_summary(post_tt)
+    assert [(s["source"], s["next"]) for s in post_tt_summary] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),
+        ("loop", ("executor",)),  # <-- replay point / fork parent
+        ("input", ("__start__",)),
+    ]
+    # Verify the fork's parent is the original replay point
+    replay_point_id = sub_config["configurable"]["checkpoint_map"][""]
+    assert post_tt[0].parent_config["configurable"]["checkpoint_id"] == replay_point_id
+
+    # Resume from the fork
+    result = await graph.ainvoke(Command(resume="second"), config)
+    assert result["value"] == ["a:second"]
+
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch
+        ("loop", (), {"value": ["a:second"]}),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
 @NEEDS_CONTEXTVARS
 async def test_3_levels_deep_time_travel_to_first_interrupt_async(
     async_checkpointer: BaseCheckpointSaver,
@@ -2088,13 +2481,15 @@ async def test_replay_creates_branch_preserving_old_checkpoints(
     # -- Post-replay checkpoint history (newest first) --
     post_replay_history = [s async for s in graph.aget_state_history(config)]
     post_summary = _checkpoint_summary(post_replay_history)
-    assert len(post_summary) == 7  # 5 original + 2 new branch checkpoints
+    # 5 original + 1 fork + 2 new branch checkpoints = 8
+    assert len(post_summary) == 8
 
     assert [s["next"] for s in post_summary] == [
-        (),  # new branch tip (C6)
-        ("node_c",),  # new branch (C5)
-        (),  # old branch tip (C4)
-        ("node_c",),  # old (C3)
+        (),  # new branch tip
+        ("node_c",),  # new branch
+        ("node_b",),  # fork from replay point
+        (),  # old branch tip
+        ("node_c",),  # old
         ("node_b",),  # branch point (C2)
         ("node_a",),  # old (C1)
         ("__start__",),  # old (C0)
@@ -2102,6 +2497,7 @@ async def test_replay_creates_branch_preserving_old_checkpoints(
     assert [s["values"] for s in post_summary] == [
         {"value": ["a", "b2", "c"]},  # new branch tip
         {"value": ["a", "b2"]},  # new: node_b re-ran with call_count=2
+        {"value": ["a"]},  # fork from replay point
         {"value": ["a", "b1", "c"]},  # old branch tip preserved
         {"value": ["a", "b1"]},  # old
         {"value": ["a"]},  # branch point

libs/langgraph/tests/test_utils.py

@@ -11,13 +11,19 @@ from typing import (
     TypeVar,
     Union,
 )
-from unittest.mock import patch
+from unittest.mock import MagicMock, patch
 
 import langsmith
 import pytest
+from langchain_core.runnables import RunnableConfig
+from langchain_core.tracers import LangChainTracer
 from typing_extensions import NotRequired, Required, TypedDict
 
-from langgraph._internal._config import _is_not_empty, ensure_config
+from langgraph._internal._config import (
+    _is_not_empty,
+    ensure_config,
+    get_callback_manager_for_config,
+)
 from langgraph._internal._fields import (
     _is_optional_type,
     get_enhanced_type_hints,
@@ -298,7 +304,7 @@ def test_is_not_empty() -> None:
     assert not _is_not_empty({})
 
 
-def test_configurable_metadata():
+def test_configurable_metadata() -> None:
     config = {
         "configurable": {
             "a-key": "foo",
@@ -309,11 +315,115 @@ def test_configurable_metadata():
             "andme": 42,
             "nested": {"foo": "bar"},
             "nooverride": -2,
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
         },
         "metadata": {"nooverride": 18},
     }
-    expected = {"includeme", "andme", "nooverride"}
     merged = ensure_config(config)
     metadata = merged["metadata"]
-    assert metadata.keys() == expected
+    assert set(metadata) == {
+        "nooverride",
+        "assistant_id",
+        "thread_id",
+        "checkpoint_id",
+        "run_id",
+        "graph_id",
+        "checkpoint_ns",
+        "task_id",
+    }
     assert metadata["nooverride"] == 18
+
+
+def test_callback_manager_copies_whitelisted_configurable_ids_to_metadata() -> None:
+    config = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+        },
+        "metadata": {
+            "thread_id": "from-metadata",
+            "nooverride": 18,
+        },
+    }
+    manager = ensure_config(config)
+    callback_manager = get_callback_manager_for_config(manager)
+    assert callback_manager.metadata == {
+        "thread_id": "from-metadata",
+        "nooverride": 18,
+        "checkpoint_id": "ckpt-1",
+        "checkpoint_ns": "ns-1",
+        "task_id": "task-1",
+        "run_id": "run-456",
+        "assistant_id": "asst-789",
+        "graph_id": "graph-0",
+    }
+
+
+def test_callback_manager_copies_configurable_ids_to_tracing_metadata() -> None:
+    tracer = LangChainTracer(client=MagicMock())
+    config: RunnableConfig = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+            "includeme": "hi",
+            "andme": 42,
+            "__dontinclude": "bar",
+            "some_api_key": "secret",
+            "custom_setting": {"nested": True},
+        },
+        "metadata": {
+            "thread_id": "from-metadata",
+            "user_id": "from-metadata-user",
+            "includeme": "from-metadata",
+        },
+        "callbacks": [tracer],
+    }
+
+    manager = ensure_config(config)
+    callback_manager = get_callback_manager_for_config(manager)
+    handlers = callback_manager.handlers
+    tracers = [handler for handler in handlers if isinstance(handler, LangChainTracer)]
+    assert len(tracers) == 1
+    tracer = tracers[0]
+    assert tracer.tracing_metadata == {
+        "checkpoint_id": "ckpt-1",
+        "checkpoint_ns": "ns-1",
+        "task_id": "task-1",
+        "run_id": "run-456",
+        "assistant_id": "asst-789",
+        "graph_id": "graph-0",
+        "model": "gpt-4o",
+        "cron_id": "cron-1",
+        "andme": 42,
+        "includeme": "hi",
+        "thread_id": "th-123",
+        "user_id": "uid-1",
+    }

libs/langgraph/uv.lock

@@ -1348,7 +1348,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.22"
+version = "1.3.0a2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -1360,14 +1360,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
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 [[package]]
 name = "langgraph"
-version = "1.1.7a1"
+version = "1.1.7a2"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1439,7 +1439,7 @@ test = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.1" },
+    { name = "langchain-core", specifier = "==1.3.0a2" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "../prebuilt" },
     { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -1548,7 +1548,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.2"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -1852,7 +1852,7 @@ test = [
 
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-version = "0.6.4"
+version = "0.7.31"
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     { name = "httpx" },
@@ -1862,11 +1862,12 @@ dependencies = [
     { name = "requests" },
     { name = "requests-toolbelt" },
     { name = "uuid-utils" },
+    { name = "xxhash" },
     { name = "zstandard" },
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+version = "9.0.3"
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 [[package]]

libs/prebuilt/tests/test_injected_state_not_required.py

@@ -0,0 +1,284 @@
+"""Test InjectedState with NotRequired state fields.
+
+This tests the fix for https://github.com/langchain-ai/langchain/issues/35585
+
+When using InjectedState(<field>) on a tool parameter, and the referenced field is
+declared as NotRequired in the custom state schema, the ToolNode should gracefully
+handle missing fields by injecting None instead of raising KeyError.
+"""
+
+import sys
+from typing import Annotated
+
+import pytest
+from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, ToolMessage
+from langchain_core.tools import tool
+from langgraph.graph.message import add_messages
+from pydantic import BaseModel, Field
+from typing_extensions import NotRequired
+
+from langgraph.prebuilt import InjectedState, ToolNode, create_react_agent
+from langgraph.prebuilt.chat_agent_executor import AgentState
+
+from .model import FakeToolCallingModel
+
+
+class CustomAgentStateWithNotRequired(AgentState):
+    """Custom state with a NotRequired field (TypedDict style)."""
+
+    city: NotRequired[str]
+
+
+class CustomAgentStatePydanticWithDefault(BaseModel):
+    """Custom state with Optional field and default (Pydantic style)."""
+
+    messages: Annotated[list[AnyMessage], add_messages]
+    remaining_steps: int = Field(default=10)
+    city: str | None = Field(default=None)
+
+
+@tool
+def get_weather(city: Annotated[str | None, InjectedState("city")] = None) -> str:
+    """Get weather for a given city."""
+    if city is None:
+        return "No city provided"
+    return f"It's always sunny in {city}!"
+
+
+def _create_mock_runtime(
+    state: dict | None = None,
+    store=None,
+):
+    """Create a mock Runtime for testing ToolNode directly."""
+    from unittest.mock import Mock
+
+    from langgraph.runtime import Runtime
+
+    mock_runtime = Mock(spec=Runtime)
+    mock_runtime.context = {}
+    return mock_runtime
+
+
+def _create_config_with_runtime(store=None, state=None):
+    """Create a RunnableConfig with mocked runtime for direct ToolNode testing."""
+    from langgraph.prebuilt.tool_node import ToolRuntime
+
+    tool_runtime = ToolRuntime(
+        state=state or {},
+        config={},
+        context={},
+        store=store,
+        stream_writer=None,
+        tool_call_id="test_id",
+    )
+    return {
+        "configurable": {
+            "__pregel_runtime": _create_mock_runtime(),
+            "__tool_runtime__": tool_runtime,
+        }
+    }
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_injected_state_not_required_field_missing_injects_none():
+    """Test that InjectedState with NotRequired field injects None when field is missing.
+
+    This verifies the fix for https://github.com/langchain-ai/langchain/issues/35585
+    """
+    tool_node = ToolNode([get_weather])
+
+    tool_call = {
+        "name": "get_weather",
+        "args": {},
+        "id": "call_1",
+        "type": "tool_call",
+    }
+    ai_msg = AIMessage("Let me check the weather", tool_calls=[tool_call])
+
+    # State WITHOUT the "city" field - should inject None instead of raising KeyError
+    state_without_city: CustomAgentStateWithNotRequired = {
+        "messages": [HumanMessage("What's the weather?"), ai_msg],
+    }
+
+    result = tool_node.invoke(
+        state_without_city,
+        config=_create_config_with_runtime(state=state_without_city),
+    )
+
+    assert len(result["messages"]) == 1
+    tool_msg = result["messages"][0]
+    assert isinstance(tool_msg, ToolMessage)
+    assert "No city provided" in tool_msg.content
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_injected_state_not_required_field_present_works():
+    """Test that InjectedState with NotRequired field works when field IS present."""
+    tool_node = ToolNode([get_weather])
+
+    tool_call = {
+        "name": "get_weather",
+        "args": {},
+        "id": "call_1",
+        "type": "tool_call",
+    }
+    ai_msg = AIMessage("Let me check the weather", tool_calls=[tool_call])
+
+    # State WITH the "city" field - this should work
+    state_with_city: CustomAgentStateWithNotRequired = {
+        "messages": [HumanMessage("What's the weather?"), ai_msg],
+        "city": "San Francisco",
+    }
+
+    result = tool_node.invoke(
+        state_with_city,
+        config=_create_config_with_runtime(state=state_with_city),
+    )
+
+    assert len(result["messages"]) == 1
+    tool_msg = result["messages"][0]
+    assert isinstance(tool_msg, ToolMessage)
+    assert "San Francisco" in tool_msg.content
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_create_react_agent_injected_state_not_required_field_missing():
+    """Test create_react_agent with InjectedState using NotRequired field that is missing.
+
+    This verifies the fix for https://github.com/langchain-ai/langchain/issues/35585
+    """
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather],
+        state_schema=CustomAgentStateWithNotRequired,
+    )
+
+    # Invoke WITHOUT the city field - should work, injecting None
+    result = agent.invoke(
+        {"messages": [HumanMessage("What's the weather?")]},
+    )
+
+    # Check that the tool was called successfully with None injected
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "No city provided" in tool_messages[0].content
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_create_react_agent_injected_state_not_required_field_present():
+    """Test create_react_agent with InjectedState using NotRequired field that IS present."""
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather],
+        state_schema=CustomAgentStateWithNotRequired,
+    )
+
+    # Invoke WITH the city field
+    result = agent.invoke(
+        {
+            "messages": [HumanMessage("What's the weather?")],
+            "city": "San Francisco",
+        },
+    )
+
+    # Check that the tool was called successfully
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "San Francisco" in tool_messages[0].content
+
+
+@tool
+def get_weather_optional(city: Annotated[str | None, InjectedState("city")]) -> str:
+    """Get weather for a given city (accepts None)."""
+    if city is None:
+        return "Please provide a city!"
+    return f"It's always sunny in {city}!"
+
+
+def test_pydantic_state_with_default_field_missing_works():
+    """Test that Pydantic state with Optional field and default=None works when field is missing.
+
+    This is the workaround suggested in the issue comments - using Pydantic BaseModel
+    with `city: Optional[str] = Field(default=None)` instead of TypedDict with NotRequired.
+    """
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather_optional", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather_optional],
+        state_schema=CustomAgentStatePydanticWithDefault,
+    )
+
+    # Invoke WITHOUT the city field - should work because Pydantic provides default
+    result = agent.invoke(
+        {"messages": [HumanMessage("What's the weather?")]},
+    )
+
+    # Check that the tool was called successfully with None
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "Please provide a city!" in tool_messages[0].content
+
+
+def test_pydantic_state_with_default_field_present_works():
+    """Test that Pydantic state with Optional field works when field IS present."""
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather_optional", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather_optional],
+        state_schema=CustomAgentStatePydanticWithDefault,
+    )
+
+    # Invoke WITH the city field
+    result = agent.invoke(
+        {
+            "messages": [HumanMessage("What's the weather?")],
+            "city": "San Francisco",
+        },
+    )
+
+    # Check that the tool was called successfully
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "San Francisco" in tool_messages[0].content

libs/prebuilt/uv.lock

@@ -249,7 +249,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.25"
+version = "1.3.0a2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -261,14 +261,14 @@ dependencies = [
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+    { 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" },
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 [[package]]
 name = "langgraph"
-version = "1.1.7a1"
+version = "1.1.7a2"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -281,7 +281,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.1" },
+    { name = "langchain-core", specifier = "==1.3.0a2" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "." },
     { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -352,7 +352,7 @@ test = [
 
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-version = "4.0.1"
+version = "4.0.2"
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@@ -619,7 +619,7 @@ test = [
 
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+version = "0.7.31"
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@@ -629,11 +629,12 @@ dependencies = [
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+    { name = "xxhash" },
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 [[package]]

libs/sdk-py/langgraph_sdk/__init__.py

@@ -1,8 +1,30 @@
-from langgraph_sdk.auth import Auth
-from langgraph_sdk.client import get_client, get_sync_client
-from langgraph_sdk.encryption import Encryption
-from langgraph_sdk.encryption.types import EncryptionContext
+from __future__ import annotations
+
+import importlib
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from langgraph_sdk.auth import Auth
+    from langgraph_sdk.client import get_client, get_sync_client
+    from langgraph_sdk.encryption import Encryption
+    from langgraph_sdk.encryption.types import EncryptionContext
 
 __version__ = "0.3.13"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]
+
+_LAZY: dict[str, str] = {
+    "Auth": "langgraph_sdk.auth",
+    "get_client": "langgraph_sdk.client",
+    "get_sync_client": "langgraph_sdk.client",
+    "Encryption": "langgraph_sdk.encryption",
+    "EncryptionContext": "langgraph_sdk.encryption.types",
+}
+
+
+def __getattr__(name: str) -> object:
+    if name in _LAZY:
+        mod = importlib.import_module(_LAZY[name])
+        return getattr(mod, name)
+    msg = f"module {__name__!r} has no attribute {name!r}"
+    raise AttributeError(msg)

libs/sdk-py/uv.lock

@@ -262,7 +262,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.28"
+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/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
+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" }
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+    { 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 = "1.1.7a1"
+version = "1.1.7a2"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -294,7 +294,7 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.1" },
+    { name = "langchain-core", specifier = "==1.3.0a2" },
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "../prebuilt" },
     { name = "langgraph-sdk", editable = "." },
@@ -365,7 +365,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.2"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -534,7 +534,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.7.20"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -547,9 +547,9 @@ dependencies = [
     { name = "xxhash" },
     { name = "zstandard" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
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+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
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 [[package]]
@@ -1000,7 +1000,7 @@ wheels = [
 
 [[package]]
 name = "pytest"
-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -1011,9 +1011,9 @@ dependencies = [
     { name = "pygments" },
     { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
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+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
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 [[package]]