Merge branch 'main' into nh/namespace-keyed-subagents

Comment follow up

libs/checkpoint-conformance/README.md

@@ -63,6 +63,7 @@ The suite tests **base** capabilities (required) and **extended** capabilities (
 | `delete_for_runs` | no | `adelete_for_runs` |
 | `copy_thread` | no | `acopy_thread` |
 | `prune` | no | `aprune` |
+| `delta_channel_history` | no | `aget_delta_channel_history` |
 
 Extended capabilities are detected by checking whether the method is overridden from `BaseCheckpointSaver`. If not overridden, those tests are skipped.
 

libs/checkpoint-conformance/langgraph/checkpoint/conformance/capabilities.py

@@ -23,6 +23,7 @@ class Capability(str, Enum):
     DELETE_FOR_RUNS = "delete_for_runs"
     COPY_THREAD = "copy_thread"
     PRUNE = "prune"
+    DELTA_CHANNEL_HISTORY = "delta_channel_history"
 
 
 # Capabilities that every checkpointer must support.
@@ -42,6 +43,7 @@ EXTENDED_CAPABILITIES = frozenset(
         Capability.DELETE_FOR_RUNS,
         Capability.COPY_THREAD,
         Capability.PRUNE,
+        Capability.DELTA_CHANNEL_HISTORY,
     }
 )
 
@@ -57,6 +59,7 @@ _CAPABILITY_METHOD_MAP: dict[Capability, str] = {
     Capability.DELETE_FOR_RUNS: "adelete_for_runs",
     Capability.COPY_THREAD: "acopy_thread",
     Capability.PRUNE: "aprune",
+    Capability.DELTA_CHANNEL_HISTORY: "aget_delta_channel_history",
 }
 
 

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/__init__.py

@@ -9,6 +9,9 @@ from langgraph.checkpoint.conformance.spec.test_delete_for_runs import (
 from langgraph.checkpoint.conformance.spec.test_delete_thread import (
     run_delete_thread_tests,
 )
+from langgraph.checkpoint.conformance.spec.test_delta_channel_history import (
+    run_delta_channel_history_tests,
+)
 from langgraph.checkpoint.conformance.spec.test_get_tuple import run_get_tuple_tests
 from langgraph.checkpoint.conformance.spec.test_list import run_list_tests
 from langgraph.checkpoint.conformance.spec.test_prune import run_prune_tests
@@ -24,4 +27,5 @@ __all__ = [
     "run_delete_for_runs_tests",
     "run_copy_thread_tests",
     "run_prune_tests",
+    "run_delta_channel_history_tests",
 ]

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/_delta_fixtures.py

@@ -0,0 +1,99 @@
+"""Shared fixtures for delta-channel conformance tests.
+
+Builds a parent chain with `_DeltaSnapshot` blobs at known positions via
+direct `aput` / `aput_writes` calls. No langgraph or Pregel dependency.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Sequence
+from typing import Any
+from uuid import uuid4
+
+from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import BaseCheckpointSaver, Checkpoint
+from langgraph.checkpoint.base.id import uuid6
+
+from langgraph.checkpoint.conformance.test_utils import generate_metadata
+
+
+async def build_delta_chain(
+    saver: BaseCheckpointSaver,
+    *,
+    thread_id: str | None = None,
+    checkpoint_ns: str = "",
+    channel: str = "messages",
+    snapshots_at_steps: Sequence[int] = (0,),
+    total_steps: int = 6,
+    write_value_fn: Any | None = None,
+) -> list[RunnableConfig]:
+    """Build a parent chain with `_DeltaSnapshot` at known positions.
+
+    Args:
+        saver: Checkpointer instance.
+        thread_id: Defaults to a random UUID.
+        checkpoint_ns: Namespace (default root).
+        channel: Channel name used for snapshots and writes.
+        snapshots_at_steps: Steps at which a `_DeltaSnapshot` blob is stored
+            in `channel_values[channel]`. Step 0 is the oldest checkpoint.
+        total_steps: Number of checkpoints in the chain.
+        write_value_fn: Callable(step) -> write value. Defaults to step index.
+
+    Returns:
+        List of stored configs (oldest first), one per step.
+    """
+    if write_value_fn is None:
+
+        def write_value_fn(step: int) -> Any:
+            return step
+
+    from langgraph.checkpoint.serde.types import _DeltaSnapshot
+
+    thread_id = thread_id or str(uuid4())
+    snapshot_set = set(snapshots_at_steps)
+    stored: list[RunnableConfig] = []
+    parent_cfg: RunnableConfig | None = None
+
+    for step in range(total_steps):
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": checkpoint_ns,
+            }
+        }
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+
+        channel_values: dict[str, Any] = {}
+        channel_versions: dict[str, int] = {}
+        if step in snapshot_set:
+            channel_values[channel] = _DeltaSnapshot(
+                write_value_fn(step),
+            )
+            channel_versions[channel] = step + 1
+
+        cp = Checkpoint(
+            v=1,
+            id=str(uuid6(clock_seq=-1)),
+            ts="",
+            channel_values=channel_values,
+            channel_versions=channel_versions,
+            versions_seen={},
+            updated_channels=None,
+        )
+        new_versions = dict(channel_versions)
+        parent_cfg = await saver.aput(
+            config, cp, generate_metadata(step=step), new_versions
+        )
+        stored.append(parent_cfg)
+
+        # Write a pending write for non-snapshot steps so the walk has
+        # something to collect.
+        if step not in snapshot_set:
+            await saver.aput_writes(
+                parent_cfg, [(channel, write_value_fn(step))], str(uuid4())
+            )
+
+    return stored

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_delta_channel_history.py

@@ -0,0 +1,247 @@
+"""DELTA_CHANNEL_HISTORY capability tests — aget_delta_channel_history contract."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.spec._delta_fixtures import build_delta_chain
+
+
+async def test_history_returns_writes_oldest_first(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Writes are returned oldest-to-newest."""
+    tid = str(uuid4())
+    # 5 steps: snapshot at 0, writes at 1,2,3,4.
+    # Head is step 4. Walk starts at step 3 (parent of head).
+    # Collects writes from steps 1,2,3 (between snapshot at 0 and head's parent).
+    configs = await build_delta_chain(
+        saver, thread_id=tid, channel="ch", snapshots_at_steps=[0], total_steps=5
+    )
+    head = configs[-1]
+    result = await saver.aget_delta_channel_history(config=head, channels=["ch"])
+    writes = result["ch"]["writes"]
+    values = [w[2] for w in writes]
+    assert values == [1, 2, 3], f"Expected [1,2,3], got {values}"
+
+
+async def test_history_seed_is_nearest_snapshot(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Seed is the value from the nearest ancestor with channel_values populated."""
+    tid = str(uuid4())
+    # 6 steps: snapshots at 0 and 3, writes at 1,2,4,5.
+    # Head is step 5. Walk from step 4 backward stops at step 3 (snapshot).
+    # Collects writes from step 4 only (between step 3 and head's parent step 4).
+    configs = await build_delta_chain(
+        saver,
+        thread_id=tid,
+        channel="ch",
+        snapshots_at_steps=[0, 3],
+        total_steps=6,
+    )
+    head = configs[-1]
+    result = await saver.aget_delta_channel_history(config=head, channels=["ch"])
+    assert "seed" in result["ch"], "Expected seed from snapshot at step 3"
+    seed = result["ch"]["seed"]
+    from langgraph.checkpoint.serde.types import _DeltaSnapshot
+
+    actual_value = seed.value if isinstance(seed, _DeltaSnapshot) else seed
+    assert actual_value == 3, f"Expected seed value 3 (step 3), got {actual_value}"
+    writes = result["ch"]["writes"]
+    values = [w[2] for w in writes]
+    assert values == [4], f"Expected [4], got {values}"
+
+
+async def test_history_excludes_target_pending_writes(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Target's own pending_writes are NOT included in the history."""
+    tid = str(uuid4())
+    configs = await build_delta_chain(
+        saver, thread_id=tid, channel="ch", snapshots_at_steps=[0], total_steps=3
+    )
+    head = configs[-1]
+    # Add writes directly to the head checkpoint
+    await saver.aput_writes(head, [("ch", "extra")], str(uuid4()))
+    result = await saver.aget_delta_channel_history(config=head, channels=["ch"])
+    writes = result["ch"]["writes"]
+    values = [w[2] for w in writes]
+    assert "extra" not in values, f"Target's writes should be excluded, got {values}"
+
+
+async def test_history_multi_channel(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Multiple channels have independent walk termination."""
+    tid = str(uuid4())
+    configs: list = []
+    parent_cfg = None
+    from langgraph.checkpoint.base import Checkpoint
+    from langgraph.checkpoint.base.id import uuid6
+    from langgraph.checkpoint.serde.types import _DeltaSnapshot
+
+    from langgraph.checkpoint.conformance.test_utils import generate_metadata
+
+    for step in range(5):
+        config = {"configurable": {"thread_id": tid, "checkpoint_ns": ""}}
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cv: dict = {}
+        cvs: dict = {}
+        if step == 1:
+            cv["a"] = _DeltaSnapshot("snap_a")
+            cvs["a"] = step + 1
+        if step == 3:
+            cv["b"] = _DeltaSnapshot("snap_b")
+            cvs["b"] = step + 1
+        cp = Checkpoint(
+            v=1,
+            id=str(uuid6(clock_seq=-1)),
+            ts="",
+            channel_values=cv,
+            channel_versions=cvs,
+            versions_seen={},
+            updated_channels=None,
+        )
+        parent_cfg = await saver.aput(config, cp, generate_metadata(step=step), cvs)
+        configs.append(parent_cfg)
+        await saver.aput_writes(parent_cfg, [("a", step), ("b", step)], str(uuid4()))
+
+    head = configs[-1]
+    result = await saver.aget_delta_channel_history(config=head, channels=["a", "b"])
+    a_writes = [w[2] for w in result["a"]["writes"]]
+    b_writes = [w[2] for w in result["b"]["writes"]]
+    assert a_writes == [1, 2, 3], f"Expected a writes [1,2,3], got {a_writes}"
+    assert b_writes == [3], f"Expected b writes [3], got {b_writes}"
+
+
+async def test_history_empty_channels_returns_empty(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Empty channels list returns empty mapping."""
+    tid = str(uuid4())
+    configs = await build_delta_chain(
+        saver, thread_id=tid, channel="ch", snapshots_at_steps=[0], total_steps=3
+    )
+    result = await saver.aget_delta_channel_history(config=configs[-1], channels=[])
+    assert result == {}
+
+
+async def test_history_walk_to_root_no_seed(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Walk reaches root without finding seed — no 'seed' key in result."""
+    tid = str(uuid4())
+    configs = await build_delta_chain(
+        saver,
+        thread_id=tid,
+        channel="ch",
+        snapshots_at_steps=[],
+        total_steps=4,
+    )
+    head = configs[-1]
+    result = await saver.aget_delta_channel_history(config=head, channels=["ch"])
+    assert "seed" not in result["ch"], f"Expected no seed, got {result['ch']}"
+
+
+async def test_history_migration_plain_value_as_seed(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Pre-delta plain value in channel_values acts as seed (migration case).
+
+    When a thread was originally using a regular channel (BinaryOperatorAggregate)
+    and later switches to DeltaChannel, the old checkpoint has a plain value in
+    channel_values[ch] (not a _DeltaSnapshot). The walk should treat it as the
+    seed and terminate there.
+    """
+    from langgraph.checkpoint.base import Checkpoint
+    from langgraph.checkpoint.base.id import uuid6
+
+    from langgraph.checkpoint.conformance.test_utils import generate_metadata
+
+    tid = str(uuid4())
+    configs: list = []
+    parent_cfg = None
+
+    for step in range(4):
+        config = {"configurable": {"thread_id": tid, "checkpoint_ns": ""}}
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cv: dict = {}
+        cvs: dict = {}
+        # Step 1: plain value (migration case — old checkpoint before delta)
+        if step == 1:
+            cv["ch"] = [10, 20, 30]
+            cvs["ch"] = step + 1
+        cp = Checkpoint(
+            v=1,
+            id=str(uuid6(clock_seq=-1)),
+            ts="",
+            channel_values=cv,
+            channel_versions=cvs,
+            versions_seen={},
+            updated_channels=None,
+        )
+        parent_cfg = await saver.aput(config, cp, generate_metadata(step=step), cvs)
+        configs.append(parent_cfg)
+        if step != 1:
+            await saver.aput_writes(parent_cfg, [("ch", step)], str(uuid4()))
+
+    head = configs[-1]
+    result = await saver.aget_delta_channel_history(config=head, channels=["ch"])
+    # Seed should be the plain value from step 1
+    assert "seed" in result["ch"], "Expected seed from migration plain value at step 1"
+    seed = result["ch"]["seed"]
+    assert seed == [10, 20, 30], f"Expected plain value [10,20,30], got {seed}"
+    # Writes should be from step 2 only (between seed at step 1 and head's parent step 2)
+    writes = result["ch"]["writes"]
+    values = [w[2] for w in writes]
+    assert values == [2], f"Expected [2], got {values}"
+
+
+ALL_DELTA_CHANNEL_HISTORY_TESTS = [
+    test_history_returns_writes_oldest_first,
+    test_history_seed_is_nearest_snapshot,
+    test_history_excludes_target_pending_writes,
+    test_history_multi_channel,
+    test_history_empty_channels_returns_empty,
+    test_history_walk_to_root_no_seed,
+    test_history_migration_plain_value_as_seed,
+]
+
+
+async def run_delta_channel_history_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all delta_channel_history tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_DELTA_CHANNEL_HISTORY_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("delta_channel_history", test_fn.__name__, True, None)
+        except Exception:
+            failed += 1
+            msg = f"{test_fn.__name__}: {traceback.format_exc()}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result(
+                    "delta_channel_history",
+                    test_fn.__name__,
+                    False,
+                    traceback.format_exc(),
+                )
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/validate.py

@@ -19,6 +19,9 @@ from langgraph.checkpoint.conformance.spec.test_delete_for_runs import (
 from langgraph.checkpoint.conformance.spec.test_delete_thread import (
     run_delete_thread_tests,
 )
+from langgraph.checkpoint.conformance.spec.test_delta_channel_history import (
+    run_delta_channel_history_tests,
+)
 from langgraph.checkpoint.conformance.spec.test_get_tuple import run_get_tuple_tests
 from langgraph.checkpoint.conformance.spec.test_list import run_list_tests
 from langgraph.checkpoint.conformance.spec.test_prune import run_prune_tests
@@ -35,6 +38,7 @@ _RUNNERS = {
     Capability.DELETE_FOR_RUNS: run_delete_for_runs_tests,
     Capability.COPY_THREAD: run_copy_thread_tests,
     Capability.PRUNE: run_prune_tests,
+    Capability.DELTA_CHANNEL_HISTORY: run_delta_channel_history_tests,
 }
 
 

libs/checkpoint-conformance/pyproject.toml

@@ -43,7 +43,11 @@ asyncio_mode = "auto"
 # The extended methods (acopy_thread, adelete_for_runs, aprune) are checked
 # at runtime via capability detection and may not exist on the installed
 # base class. Dict literal inference is also overly strict for RunnableConfig.
+# Delta-channel tests import from `langgraph` (not a declared dep of this
+# package — at test time it is installed alongside); private `_DeltaSnapshot`
+# imports are intentional (beta surface).
 unresolved-attribute = "ignore"
+unresolved-import = "ignore"
 invalid-argument-type = "ignore"
 invalid-return-type = "ignore"
 
@@ -58,6 +62,9 @@ lint.select = [
 lint.ignore = ["E501", "B008"]
 target-version = "py310"
 
+[tool.uv.sources]
+langgraph-checkpoint = {path = "../checkpoint", editable = true}
+
 [[tool.uv.index]]
 name = "testpypi"
 url = "https://test.pypi.org/simple/"

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

@@ -279,8 +279,8 @@ def _build_delta_stage2_sql(
         )
     for _ in channels_with_seed:
         branches.append(
-            "SELECT 'b'::text, NULL, channel, "
-            "type, blob, NULL, NULL, version "
+            "SELECT 'b'::text AS _kind, NULL::text AS checkpoint_id, channel, "
+            "type, blob, NULL::text AS task_id, NULL::int AS idx, version "
             "FROM checkpoint_blobs "
             "WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s "
             "AND version = %s"

libs/checkpoint-sqlite/tests/test_conformance_delta.py

@@ -0,0 +1,35 @@
+"""Run delta-channel conformance capabilities against AsyncSqliteSaver."""
+
+from __future__ import annotations
+
+import pytest
+
+pytest.importorskip(
+    "langgraph.checkpoint.conformance",
+    reason="langgraph-checkpoint-conformance not installed",
+)
+pytest.importorskip("aiosqlite", reason="aiosqlite not installed")
+
+
+@pytest.mark.asyncio
+async def test_delta_channel_conformance():
+    from langgraph.checkpoint.conformance import validate
+    from langgraph.checkpoint.conformance.initializer import checkpointer_test
+
+    from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
+
+    @checkpointer_test(name="AsyncSqliteSaver")
+    async def sqlite_saver():
+        async with AsyncSqliteSaver.from_conn_string(":memory:") as saver:
+            yield saver
+
+    report = await validate(
+        sqlite_saver,
+        capabilities={
+            "delta_channel_history",
+        },
+    )
+    for cap, result in report.results.items():
+        if result.passed is False:
+            details = "\n".join(result.failures or [])
+            pytest.fail(f"Capability {cap} failed:\n{details}")

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

@@ -63,6 +63,11 @@ class CheckpointMetadata(TypedDict, total=False):
     delta_updates_since_snapshot: dict[str, int]
     """Per-channel update count since the last `_DeltaSnapshot` was written.
 
+    !!! warning "Beta"
+
+        This metadata field backs `DeltaChannel` (beta). The key name and
+        contents may change while the delta-channel design stabilizes.
+
     Maps channel name → number of supersteps that wrote to this channel
     since its last snapshot blob. Used by `pregel.create_checkpoint` to
     decide when to write the next snapshot (when the count reaches the
@@ -135,6 +140,11 @@ class CheckpointTuple(NamedTuple):
 class DeltaChannelHistory(TypedDict):
     """Per-channel result entry from `BaseCheckpointSaver.get_delta_channel_history`.
 
+    !!! warning "Beta"
+
+        Part of the `DeltaChannel` support surface; in beta. Field names and
+        semantics may change.
+
     Storage-level view of what one channel contributed across the ancestor
     chain of a target checkpoint:
 
@@ -317,6 +327,14 @@ class BaseCheckpointSaver(Generic[V]):
 
         Args:
             run_ids: The run IDs whose checkpoints should be deleted.
+
+        !!! warning "DeltaChannel"
+
+            Deleting a run that produced ancestor `checkpoint_writes` — or
+            the only `_DeltaSnapshot` blob — for a still-live thread will
+            break reconstruction of any `DeltaChannel` whose history
+            depended on those rows. See the `DeltaChannel` note on `prune`
+            for safe-recovery strategies.
         """
         raise NotImplementedError
 
@@ -330,6 +348,17 @@ class BaseCheckpointSaver(Generic[V]):
         Args:
             source_thread_id: The thread ID to copy from.
             target_thread_id: The thread ID to copy to.
+
+        !!! warning "DeltaChannel"
+
+            Implementations must copy the **complete** parent chain (all
+            ancestor checkpoints and their `checkpoint_writes`) — copying
+            only the head checkpoint will leave the target thread with
+            `DeltaChannel` state that cannot be reconstructed (no path back
+            to a `_DeltaSnapshot` ancestor). Equivalently, the copy must
+            include enough ancestors that every `DeltaChannel`-backed key
+            has either a `_DeltaSnapshot` in `channel_values` somewhere in
+            the chain, or a complete write history back to the chain root.
         """
         raise NotImplementedError
 
@@ -345,6 +374,34 @@ class BaseCheckpointSaver(Generic[V]):
             thread_ids: The thread IDs to prune.
             strategy: The pruning strategy. `"keep_latest"` retains only the most
                 recent checkpoint per namespace. `"delete"` removes all checkpoints.
+
+        !!! warning "DeltaChannel"
+
+            Custom implementations must be `DeltaChannel`-aware. `DeltaChannel`
+            stores only a sentinel in `channel_values` for non-snapshot steps;
+            reconstruction walks the parent chain via
+            `get_delta_channel_history`, accumulating rows from
+            `checkpoint_writes` until it reaches an ancestor whose
+            `channel_values` contains a `_DeltaSnapshot` blob (written every
+            `snapshot_frequency` updates).
+
+            A naive `"keep_latest"` that drops intermediate checkpoints and
+            their writes can sever that chain: the surviving "latest"
+            checkpoint is rarely a snapshot point itself, so its delta
+            channels would silently reconstruct as empty (no error raised —
+            `get_delta_channel_history` simply returns no `seed`). Safe
+            options when the graph uses `DeltaChannel`:
+
+            * Walk back from each kept checkpoint and preserve every
+              ancestor (plus its `checkpoint_writes`) up to the nearest one
+              whose `channel_values` already contains a `_DeltaSnapshot` for
+              every `DeltaChannel`-backed key.
+            * Force a fresh snapshot on the kept checkpoint before deleting
+              ancestors — rewrite `channel_values[k] = _DeltaSnapshot(value)`
+              for each delta channel `k` (resolving `value` via the existing
+              ancestor walk first), then prune.
+            * Skip pruning threads whose graph uses `DeltaChannel` until one
+              of the above is implemented.
         """
         raise NotImplementedError
 
@@ -461,6 +518,13 @@ class BaseCheckpointSaver(Generic[V]):
 
         Args:
             run_ids: The run IDs whose checkpoints should be deleted.
+
+        !!! warning "DeltaChannel"
+
+            See `delete_for_runs` — deleting rows a still-live thread's
+            `DeltaChannel` reconstruction depends on (writes between the
+            head and its nearest `_DeltaSnapshot` ancestor) will silently
+            corrupt that channel's state.
         """
         raise NotImplementedError
 
@@ -474,6 +538,13 @@ class BaseCheckpointSaver(Generic[V]):
         Args:
             source_thread_id: The thread ID to copy from.
             target_thread_id: The thread ID to copy to.
+
+        !!! warning "DeltaChannel"
+
+            See `copy_thread` — the copy must carry the complete parent
+            chain (or at least back to a `_DeltaSnapshot` ancestor for every
+            `DeltaChannel`) so the target thread can reconstruct delta
+            state.
         """
         raise NotImplementedError
 
@@ -489,6 +560,13 @@ class BaseCheckpointSaver(Generic[V]):
             thread_ids: The thread IDs to prune.
             strategy: The pruning strategy. `"keep_latest"` retains only the most
                 recent checkpoint per namespace. `"delete"` removes all checkpoints.
+
+        !!! warning "DeltaChannel"
+
+            See `prune` for the full `DeltaChannel` caveat. In short:
+            `"keep_latest"` must not drop ancestor checkpoints / writes that
+            sit between the kept checkpoint and the nearest `_DeltaSnapshot`
+            ancestor, or delta channels will silently reconstruct as empty.
         """
         raise NotImplementedError
 
@@ -497,6 +575,14 @@ class BaseCheckpointSaver(Generic[V]):
     ) -> Mapping[str, DeltaChannelHistory]:
         """Walk the parent chain returning per-channel writes + seed.
 
+        !!! warning "Beta"
+
+            This method is part of the `DeltaChannel` support surface and is
+            in beta. The signature, return shape (`DeltaChannelHistory`), and
+            interaction with `_DeltaSnapshot` blobs may change. Override at
+            your own risk; the default implementation will continue to work
+            against the public `BaseCheckpointSaver` contract.
+
         For each requested channel, walks ancestors of the checkpoint
         identified by `config` (following `parent_config`) and accumulates
         `pending_writes` for that channel. The walk terminates per-channel
@@ -556,7 +642,13 @@ class BaseCheckpointSaver(Generic[V]):
     async def aget_delta_channel_history(
         self, *, config: RunnableConfig, channels: Sequence[str]
     ) -> Mapping[str, DeltaChannelHistory]:
-        """Async version of `get_delta_channel_history`."""
+        """Async version of `get_delta_channel_history`.
+
+        !!! warning "Beta"
+
+            This method is part of the `DeltaChannel` support surface and is
+            in beta. See `get_delta_channel_history` for caveats.
+        """
         if not channels:
             return {}
         collected_by_ch: dict[str, list[PendingWrite]] = {c: [] for c in channels}

libs/checkpoint/tests/test_conformance_delta.py

@@ -0,0 +1,33 @@
+"""Run delta-channel conformance capabilities against InMemorySaver."""
+
+from __future__ import annotations
+
+import pytest
+
+conformance = pytest.importorskip(
+    "langgraph.checkpoint.conformance",
+    reason="langgraph-checkpoint-conformance not installed",
+)
+
+
+@pytest.mark.asyncio
+async def test_delta_channel_conformance():
+    from langgraph.checkpoint.conformance import validate
+    from langgraph.checkpoint.conformance.initializer import checkpointer_test
+
+    from langgraph.checkpoint.memory import InMemorySaver
+
+    @checkpointer_test(name="InMemorySaver")
+    async def mem_saver():
+        yield InMemorySaver()
+
+    report = await validate(
+        mem_saver,
+        capabilities={
+            "delta_channel_history",
+        },
+    )
+    for cap, result in report.results.items():
+        if result.passed is False:
+            details = "\n".join(result.failures or [])
+            pytest.fail(f"Capability {cap} failed:\n{details}")

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.24"
+__version__ = "0.4.25"

libs/langgraph/langgraph/channels/delta.py

@@ -26,6 +26,15 @@ class DeltaChannel(Generic[Value], BaseChannel[Any, Any, Any]):
     """Reducer channel that stores only a sentinel in checkpoint blobs and
     reconstructs state by replaying ancestor writes through the reducer.
 
+    !!! warning "Beta"
+
+        `DeltaChannel` is in beta. The API and on-disk representation may
+        change in future releases. Threads written with `DeltaChannel` today
+        are expected to remain readable, but the surrounding contract
+        (`BaseCheckpointSaver.get_delta_channel_history`, the
+        `_DeltaSnapshot` blob shape, the `delta_updates_since_snapshot`
+        metadata field) is not yet stable.
+
     The reducer receives the current accumulated value and a batch of writes
     in one call: `reducer(state, [write1, write2, ...]) -> new_state`.
 

libs/langgraph/langgraph/graph/message.py

@@ -249,15 +249,17 @@ def _messages_delta_reducer(
 ) -> list[AnyMessage]:
     """**Experimental.** Batch reducer for use with `DeltaChannel`.
 
-    Provides full `add_messages` parity: dedup by ID, `RemoveMessage`
-    tombstoning, `REMOVE_ALL_MESSAGES` reset, `BaseMessageChunk` coercion,
-    and UUID assignment for ID-less messages — all in a single batched pass.
+    Processes all writes in one pass — dedup by ID, `RemoveMessage`
+    tombstoning — without calling `add_messages`.
 
     This reducer is batching-invariant, as required by `DeltaChannel`:
     `reducer(reducer(state, xs), ys) == reducer(state, xs + ys)`.
 
     Raw dict / string / tuple inputs are coerced to typed `BaseMessage`
-    objects so that HTTP-driven graphs work without a separate coercion step.
+    objects so that HTTP-driven graphs work without a separate coercion
+    step. This is not full `add_messages` parity — `REMOVE_ALL_MESSAGES`,
+    unknown-id `RemoveMessage` errors, missing-id UUID assignment, and
+    `BaseMessageChunk` conversion are not handled here.
 
     Example::
 
@@ -278,51 +280,24 @@ def _messages_delta_reducer(
             flat.extend(w)
         else:
             flat.append(w)
-    # Steady state: the reducer's own output is already typed BaseMessages
-    # (never chunks), so skip convert_to_messages on the fast path.
+    # Steady state: the reducer's own output is already typed, so skip
+    # `convert_to_messages` on state when the first element is a BaseMessage.
     # Only raw input (initial dicts, deserialized blobs) hits the slow path.
     if state and isinstance(state[0], BaseMessage):
         state_msgs = state
     else:
-        state_msgs = cast(
-            "list[AnyMessage]",
-            [
-                message_chunk_to_message(cast(BaseMessageChunk, m))
-                for m in convert_to_messages(state)
-            ],
-        )
-    # Coerce chunks to full messages — streaming nodes can emit BaseMessageChunk.
-    msgs = cast(
-        "list[AnyMessage]",
-        [
-            message_chunk_to_message(cast(BaseMessageChunk, m))
-            for m in convert_to_messages(flat)
-        ],
-    )
+        state_msgs = cast("list[AnyMessage]", convert_to_messages(state))
+    msgs = cast("list[AnyMessage]", convert_to_messages(flat))
 
-    # REMOVE_ALL_MESSAGES resets everything; find the last sentinel and
-    # discard all state plus all writes before it.
-    remove_all_idx = None
-    for idx, m in enumerate(msgs):
-        if isinstance(m, RemoveMessage) and m.id == REMOVE_ALL_MESSAGES:
-            remove_all_idx = idx
-    if remove_all_idx is not None:
-        state_msgs = []
-        msgs = msgs[remove_all_idx + 1 :]
-
-    # Build index and assign missing IDs in one pass (parity with add_messages
-    # so that eviction and RemoveMessage tombstoning work on ID-less messages).
-    index: dict[str, int] = {}
-    for i, m in enumerate(state_msgs):
-        if m.id is None:
-            m.id = str(uuid.uuid4())
-        index[m.id] = i
+    index: dict[str, int] = {
+        m.id: i for i, m in enumerate(state_msgs) if m.id is not None
+    }
     result: list[AnyMessage | None] = list(state_msgs)
     for msg in msgs:
-        if msg.id is None:
-            msg.id = str(uuid.uuid4())
         mid = msg.id
-        if isinstance(msg, RemoveMessage):
+        if mid is None:
+            result.append(msg)
+        elif isinstance(msg, RemoveMessage):
             if mid in index:
                 result[index[mid]] = None
                 del index[mid]

libs/langgraph/langgraph/pregel/_checkpoint.py

@@ -34,28 +34,23 @@ def empty_checkpoint() -> Checkpoint:
     )
 
 
-def _should_snapshot_delta(
-    name: str,
-    ch: DeltaChannel,
-    updates_since_snapshot: Mapping[str, int],
-    *,
-    force: bool,
-) -> bool:
-    """Decide whether `ch` should write a `_DeltaSnapshot` this step.
+def delta_channels_to_snapshot(
+    channels: Mapping[str, BaseChannel],
+    counts: Mapping[str, int],
+) -> set[str]:
+    """Return the set of DeltaChannel names that should snapshot now.
 
-    Triggers:
-      * `force` — always snapshot (used by `durability="exit"`).
-      * Update-count: this channel has accumulated at least
-        `snapshot_frequency` updates since its last snapshot. The count
-        is supplied by the caller via `updates_since_snapshot[name]` and
-        is reset to `0` whenever a snapshot fires.
-
-    Version-format-independent: works for `int`, `float`, and `str`
-    versioning schemes alike.
+    A channel snapshots when its accumulated update count (since the last
+    snapshot) reaches or exceeds `snapshot_frequency`. This is a pure
+    predicate — no mutation.
     """
-    if force:
-        return True
-    return updates_since_snapshot.get(name, 0) >= ch.snapshot_frequency
+    return {
+        name
+        for name, ch in channels.items()
+        if isinstance(ch, DeltaChannel)
+        and ch.is_available()
+        and counts.get(name, 0) >= ch.snapshot_frequency
+    }
 
 
 def create_checkpoint(
@@ -66,34 +61,19 @@ def create_checkpoint(
     id: str | None = None,
     updated_channels: set[str] | None = None,
     get_next_version: GetNextVersion | None = None,
-    force_delta_snapshot: bool = False,
-    updates_since_snapshot: Mapping[str, int] | None = None,
-    new_updates_since_snapshot: dict[str, int] | None = None,
+    channels_to_snapshot: set[str] | None = None,
 ) -> Checkpoint:
-    """Create a checkpoint for the given channels.
+    """Build a new Checkpoint from the previous one and live channel state.
 
-    For each `DeltaChannel`, a `_DeltaSnapshot(value)` blob is written into
-    `channel_values[k]` when this channel has accumulated at least
-    `snapshot_frequency` updates since its last snapshot (counter supplied
-    via `updates_since_snapshot`). Otherwise the channel is omitted from
-    `channel_values`; its `channel_versions` entry still bumps so that the
-    saver tracks the channel and the ancestor walk can replay writes.
-
-    Snapshots are eager: even if the channel had no write this step, a
-    version bump is forced (via `get_next_version`) so `put()` includes
-    the channel in `new_versions` and stores the blob.
-
-    `force_delta_snapshot` ignores the cadence and always snapshots —
-    used by `durability="exit"` where intermediate writes are not stored
-    as ancestor `checkpoint_writes`.
-
-    If `new_updates_since_snapshot` is provided, the function resets the
-    counter to `0` for any channel that snapshotted this step. Counters
-    for channels that did not snapshot are left untouched (the caller is
-    responsible for incrementing them based on `updated_channels`).
+    For each name in `channels_to_snapshot`, a `_DeltaSnapshot(value)` blob
+    is written into `channel_values[k]`. Other delta channels are omitted
+    from `channel_values` — the ancestor walk reconstructs their state
+    from `checkpoint_writes`. Callers compute the set via
+    `delta_channels_to_snapshot(channels, counts)`; defaults to empty
+    (no snapshots) when not provided.
     """
     ts = datetime.now(timezone.utc).isoformat()
-    counts = updates_since_snapshot or {}
+    channels_to_snapshot = channels_to_snapshot or set()
     if channels is None:
         values = checkpoint["channel_values"]
         channel_versions = checkpoint["channel_versions"]
@@ -104,25 +84,23 @@ def create_checkpoint(
             if k not in channel_versions:
                 continue
             ch = channels[k]
-            if (
-                isinstance(ch, DeltaChannel)
-                and ch.is_available()
-                and _should_snapshot_delta(
-                    k,
-                    ch,
-                    counts,
-                    force=force_delta_snapshot,
-                )
-            ):
-                # Eager snapshot: bump version if not already written this step
-                # so put() includes this channel in new_versions and stores blob.
+            if k in channels_to_snapshot:
+                # In exit mode, the snapshot decision is deferred to exit
+                # time (intermediate steps have do_checkpoint=False). The
+                # channel's count may have reached snapshot_frequency over
+                # several supersteps, but the LAST superstep may not have
+                # written to this channel. In that case apply_writes()
+                # (in _algo.py) didn't bump this channel's version, so
+                # saver.put() wouldn't include it in new_versions and
+                # the snapshot blob would be silently dropped. The manual
+                # bump below closes the gap. In sync/async durability this
+                # branch is effectively dead code (the step that pushes
+                # the count to freq always writes the channel).
                 if get_next_version is not None and (
                     updated_channels is None or k not in updated_channels
                 ):
                     channel_versions[k] = get_next_version(channel_versions[k], None)
                 values[k] = _DeltaSnapshot(ch.get())
-                if new_updates_since_snapshot is not None:
-                    new_updates_since_snapshot[k] = 0
             else:
                 v = ch.checkpoint()
                 if v is not MISSING:

libs/langgraph/langgraph/pregel/_loop.py

@@ -100,6 +100,7 @@ from langgraph.pregel._checkpoint import (
     channels_from_checkpoint,
     copy_checkpoint,
     create_checkpoint,
+    delta_channels_to_snapshot,
     empty_checkpoint,
 )
 from langgraph.pregel._executor import (
@@ -194,8 +195,40 @@ class PregelLoop:
     _migrate_checkpoint: Callable[[Checkpoint], None] | None
     submit: Submit
     channels: Mapping[str, BaseChannel]
-    # Only set on AsyncPregelLoop; sync loops keep this as None.
+    # Futures from `checkpointer.put_writes` calls that produced delta-channel
+    # writes. `_checkpointer_put_after_previous` drains this list (swap to a
+    # local `futs` then reset to `[]` and wait/gather) before putting the
+    # next checkpoint, so a checkpoint never becomes durable before the
+    # writes that produced it. Initialised to `[]` in both sync and async
+    # `__enter__`; stays `None` only when no checkpointer.
     _delta_write_futs: list[Any] | None = None
+
+    # Exit-mode accumulator: every delta-channel write produced during this
+    # run (input writes from `_first` + per-superstep writes captured in
+    # `after_tick`). At exit, `_put_exit_delta_writes` filters out channels
+    # that will snapshot, then persists the rest under an anchor parent.
+    # `None` when not in exit mode (so the capture sites are no-ops).
+    # Each tuple is `(step, task_id, channel, value)` — `step` drives the
+    # synthetic step-prefixed task_id used to preserve chronological order
+    # under the saver's `ORDER BY task_id, idx` sorting.
+    _exit_delta_writes: list[tuple[int, str, str, Any]] | None = None
+
+    # The checkpoint_config that points at the parent loaded at `__enter__`
+    # (or the synthetic-empty checkpoint, on first run). We capture it
+    # eagerly because every `_put_checkpoint` advances `self.checkpoint_config`
+    # to the newly-saved checkpoint's id — by exit time the original parent
+    # config would otherwise be lost. `_put_exit_delta_writes` uses this:
+    # on resumed runs as the anchor for exit delta writes; on first runs
+    # to derive the lazy stub's config (its `checkpoint_id` is the
+    # synthetic-empty id we want the stub persisted under).
+    _initial_checkpoint_config: RunnableConfig
+
+    # True iff the saver actually returned a tuple at `__enter__`. False
+    # on the first-ever run for a thread (no parent persisted yet).
+    # `_put_exit_delta_writes` uses this to decide between anchoring on
+    # the existing parent (True) or creating a lazy stub (False).
+    _has_persisted_parent: bool = False
+
     managed: ManagedValueMapping
     checkpoint: Checkpoint
     checkpoint_id_saved: str
@@ -637,6 +670,11 @@ class PregelLoop:
             self._emit(
                 "values", map_output_values, self.output_keys, writes, self.channels
             )
+        # capture delta-channel writes for exit-mode accumulator before clearing
+        if self._exit_delta_writes is not None:
+            for tid, ch, v in self.checkpoint_pending_writes:
+                if isinstance(self.specs.get(ch), DeltaChannel):
+                    self._exit_delta_writes.append((self.step, tid, ch, v))
         # clear pending writes
         self.checkpoint_pending_writes.clear()
         # only replay (re-execute) done tasks on the first tick
@@ -854,6 +892,27 @@ class PregelLoop:
                 self.checkpointer_get_next_version,
                 self.trigger_to_nodes,
             )
+            # Input writes go through `apply_writes` directly (above) — they
+            # never enter `checkpoint_pending_writes`, so the after_tick
+            # capture site does not see them. In exit mode, capture them
+            # here so `_exit_delta_writes` includes the input's delta writes
+            # alongside per-superstep writes; otherwise the input would be
+            # lost on read (it's not in final_checkpoint.channel_values for
+            # sub-freq channels, and walks ignore target.pending_writes).
+            if self._exit_delta_writes is not None:
+                for c, v in input_writes:
+                    if isinstance(self.specs.get(c), DeltaChannel):
+                        self._exit_delta_writes.append((self.step, NULL_TASK_ID, c, v))
+            # Persist delta-channel input writes so sub-freq inputs are
+            # recoverable via ancestor walk (mirrors the Command input path).
+            if self.durability != "exit":
+                delta_input = [
+                    (c, v)
+                    for c, v in input_writes
+                    if isinstance(self.specs.get(c), DeltaChannel)
+                ]
+                if delta_input:
+                    self.put_writes(NULL_TASK_ID, delta_input)
             # save input checkpoint
             self.updated_channels = updated_channels
             self._put_checkpoint({"source": "input"})
@@ -905,36 +964,60 @@ class PregelLoop:
         return updated_channels
 
     def _put_checkpoint(self, metadata: CheckpointMetadata) -> None:
-        # assign step and parents
+        # `is` (object identity) — not `==`. Three of four call sites pass a
+        # fresh dict ({"source":"input"|"loop"|"fork"}); only
+        # `_suppress_interrupt`(will rename to _on_loop_exit soon)
+        # at exit reuses the existing `self.checkpoint_metadata` instance. So
+        # `metadata is self.checkpoint_metadata` is True only on the exit call,
+        # which is what we use to gate exit-only behaviour (skip count-bump,
+        # don't replace metadata). Could be replaced by an explicit
+        # `exiting: bool = False` parameter; left as-is to match the existing
+        # idiom in this file.
+        # TODO: replace with an explicit `exiting: bool = False` parameter.
         exiting = metadata is self.checkpoint_metadata
         if exiting and self.checkpoint["id"] == self.checkpoint_id_saved:
             # checkpoint already saved
             return
-        # Carry per-delta-channel update bookkeeping forward across
-        # supersteps. Capture from the OLD metadata before potentially
-        # replacing it with a fresh dict that wouldn't contain it. Then
-        # increment for any delta channel updated this step (so the count
-        # reflects "supersteps that wrote to this channel since last
-        # snapshot"). create_checkpoint will reset entries to 0 for any
-        # channel that fires a snapshot this step.
-        prev_counts = dict(
-            self.checkpoint_metadata.get("delta_updates_since_snapshot", {}) or {}
-        )
-        new_counts = dict(prev_counts)
-        if self.updated_channels:
-            for ch_name in self.updated_channels:
-                ch_obj = self.channels.get(ch_name)
-                if isinstance(ch_obj, DeltaChannel):
-                    new_counts[ch_name] = new_counts.get(ch_name, 0) + 1
+        # Per-delta-channel update bookkeeping.
+        #
+        # `_put_checkpoint` is called once per superstep with a fresh
+        # metadata dict (source="input"|"loop"|"fork") — those are the
+        # intermediate calls that bump the count by +1 for each delta
+        # channel touched that step. In exit mode,
+        # `_suppress_interrupt`(will rename to _on_loop_exit soon)
+        # additionally calls `_put_checkpoint(self.checkpoint_metadata)` AT
+        # EXIT to commit the final checkpoint — this runs *after* the last
+        # intermediate call already counted the last superstep. So the
+        # exit call must NOT bump again or it would double-count the last
+        # superstep. (Sync/async durability does not call `_put_checkpoint`
+        # at exit, so the issue only surfaces in exit mode. force_delta_snapshot
+        # used to mask this latent bug by resetting every count to 0.)
         if not exiting:
+            prev_counts = dict(
+                self.checkpoint_metadata.get("delta_updates_since_snapshot", {}) or {}
+            )
+            new_counts = dict(prev_counts)
+            if self.updated_channels:
+                for ch_name in self.updated_channels:
+                    if isinstance(self.channels.get(ch_name), DeltaChannel):
+                        new_counts[ch_name] = new_counts.get(ch_name, 0) + 1
             metadata["step"] = self.step
             metadata["parents"] = self.config[CONF].get(CONFIG_KEY_CHECKPOINT_MAP, {})
             self.checkpoint_metadata = metadata
+        else:
+            new_counts = dict(
+                self.checkpoint_metadata.get("delta_updates_since_snapshot", {}) or {}
+            )
         # do checkpoint?
         do_checkpoint = self._checkpointer_put_after_previous is not None and (
             exiting or self.durability != "exit"
         )
         # create new checkpoint
+        channels_to_snapshot = (
+            delta_channels_to_snapshot(self.channels, new_counts)
+            if do_checkpoint
+            else set()
+        )
         self.checkpoint = create_checkpoint(
             self.checkpoint,
             self.channels if do_checkpoint else None,
@@ -944,10 +1027,10 @@ class PregelLoop:
             get_next_version=self.checkpointer_get_next_version
             if do_checkpoint
             else None,
-            force_delta_snapshot=exiting and self.durability == "exit",
-            updates_since_snapshot=new_counts,
-            new_updates_since_snapshot=new_counts,
+            channels_to_snapshot=channels_to_snapshot,
         )
+        for k in channels_to_snapshot:
+            new_counts[k] = 0
         if new_counts:
             self.checkpoint_metadata["delta_updates_since_snapshot"] = new_counts
         elif "delta_updates_since_snapshot" in self.checkpoint_metadata:
@@ -1010,6 +1093,97 @@ class PregelLoop:
             # increment step
             self.step += 1
 
+    def _put_exit_delta_writes(self) -> None:
+        """Stage stub + accumulated delta writes so final_checkpoint's put
+        waits on them (visibility invariant: both must be durable before
+        final_checkpoint becomes visible to readers).
+
+        Stub is created lazily — only when no persisted parent exists AND at
+        least one delta channel has writes that won't be snapshotted.
+        """
+        if (
+            not self._exit_delta_writes
+            or self.checkpointer is None
+            or self._checkpointer_put_after_previous is None
+            or self.checkpointer_put_writes is None
+        ):
+            return
+
+        counts = self.checkpoint_metadata.get("delta_updates_since_snapshot", {}) or {}
+        channels_to_snapshot = delta_channels_to_snapshot(self.channels, counts)
+
+        pending = [
+            (step, tid, ch, v)
+            for (step, tid, ch, v) in self._exit_delta_writes
+            if ch not in channels_to_snapshot
+        ]
+        if not pending:
+            return
+
+        if self._has_persisted_parent:
+            # _initial_checkpoint_config's checkpoint_id is the saved parent's
+            # id (saver returned a real tuple at __enter__).
+            anchor_config = self._initial_checkpoint_config
+        else:
+            stub_cp = empty_checkpoint()
+            stub_cp["id"] = self.checkpoint_id_saved
+            stub_cp["ts"] = datetime.now(timezone.utc).isoformat()
+            # Stub has no parent (checkpoint_id=None in config).
+            stub_put_config = patch_configurable(
+                self._initial_checkpoint_config,
+                {CONFIG_KEY_CHECKPOINT_ID: None},
+            )
+            # Anchor config for put_writes: checkpoint_id = stub's id.
+            anchor_config = patch_configurable(
+                self._initial_checkpoint_config,
+                {CONFIG_KEY_CHECKPOINT_ID: stub_cp["id"]},
+            )
+            self._put_checkpoint_fut = self.submit(
+                self._checkpointer_put_after_previous,
+                getattr(self, "_put_checkpoint_fut", None),
+                stub_put_config,
+                stub_cp,
+                {"step": -2},
+                {},
+            )
+            # Set checkpoint_config so final_checkpoint's _put_checkpoint
+            # sees the stub as its parent.
+            self.checkpoint_config = anchor_config
+
+        # Step-prefixed synthetic task_id preserves chronological superstep
+        # order under the saver's ORDER BY task_id, idx sorting.
+        grouped: dict[tuple[int, str], list[tuple[str, Any]]] = {}
+        for step, tid, ch, v in pending:
+            grouped.setdefault((step, tid), []).append((ch, v))
+        anchor_write_config = patch_configurable(
+            anchor_config,
+            {
+                CONFIG_KEY_CHECKPOINT_NS: self.config[CONF].get(
+                    CONFIG_KEY_CHECKPOINT_NS, ""
+                ),
+                CONFIG_KEY_CHECKPOINT_ID: anchor_config[CONF][CONFIG_KEY_CHECKPOINT_ID],
+            },
+        )
+        for (step, tid), entries in grouped.items():
+            synth_tid = f"{step:08d}-{tid}"
+            if self.checkpointer_put_writes_accepts_task_path:
+                fut = self.submit(
+                    self.checkpointer_put_writes,
+                    anchor_write_config,
+                    entries,
+                    synth_tid,
+                    "",
+                )
+            else:
+                fut = self.submit(
+                    self.checkpointer_put_writes,
+                    anchor_write_config,
+                    entries,
+                    synth_tid,
+                )
+            if self._delta_write_futs is not None:
+                self._delta_write_futs.append(fut)
+
     def _suppress_interrupt(
         self,
         exc_type: type[BaseException] | None,
@@ -1025,6 +1199,7 @@ class PregelLoop:
             # or a nested graph with checkpointer=True
             or all(NS_END not in part for part in self.checkpoint_ns)
         ):
+            self._put_exit_delta_writes()
             self._put_checkpoint(self.checkpoint_metadata)
             self._put_pending_writes()
         # suppress interrupt
@@ -1230,6 +1405,9 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
         metadata: CheckpointMetadata,
         new_versions: ChannelVersions,
     ) -> RunnableConfig:
+        if self._delta_write_futs:
+            futs, self._delta_write_futs = self._delta_write_futs, []
+            concurrent.futures.wait(futs)
         try:
             if prev is not None:
                 prev.result()
@@ -1347,6 +1525,10 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
             # graph/thread. Returns None on first invocation.
             saved = self.checkpointer.get_tuple(self.checkpoint_config)
 
+        # Capture before the synthetic-empty fallback below overwrites `saved`.
+        # `_put_exit_delta_writes` uses this on first run (no persisted parent)
+        # to lazy-create a stub instead of anchoring delta writes on a parent.
+        self._has_persisted_parent = saved is not None
         if saved is None:
             saved = CheckpointTuple(
                 self.checkpoint_config, empty_checkpoint(), {"step": -2}, None, []
@@ -1362,6 +1544,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
                 **saved.config.get(CONF, {}),
             },
         }
+        self._initial_checkpoint_config = self.checkpoint_config
         self.prev_checkpoint_config = saved.parent_config
         self.checkpoint_id_saved = saved.checkpoint["id"]
         self.checkpoint = saved.checkpoint
@@ -1371,6 +1554,10 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
             if saved.pending_writes is not None
             else []
         )
+        self._delta_write_futs = []
+        self._exit_delta_writes = (
+            [] if self.durability == "exit" and self.checkpointer is not None else None
+        )
         self.submit = self.stack.enter_context(BackgroundExecutor(self.config))
         self.channels, self.managed = channels_from_checkpoint(
             self.specs,
@@ -1596,6 +1783,10 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
             # graph/thread. Returns None on first invocation.
             saved = await self.checkpointer.aget_tuple(self.checkpoint_config)
 
+        # Capture before the synthetic-empty fallback below overwrites `saved`.
+        # `_put_exit_delta_writes` uses this on first run (no persisted parent)
+        # to lazy-create a stub instead of anchoring delta writes on a parent.
+        self._has_persisted_parent = saved is not None
         if saved is None:
             saved = CheckpointTuple(
                 self.checkpoint_config, empty_checkpoint(), {"step": -2}, None, []
@@ -1611,6 +1802,7 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
                 **saved.config.get(CONF, {}),
             },
         }
+        self._initial_checkpoint_config = self.checkpoint_config
         self.prev_checkpoint_config = saved.parent_config
         self.checkpoint_id_saved = saved.checkpoint["id"]
         self.checkpoint = saved.checkpoint
@@ -1621,6 +1813,9 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
             else []
         )
         self._delta_write_futs = []
+        self._exit_delta_writes = (
+            [] if self.durability == "exit" and self.checkpointer is not None else None
+        )
         self.submit = await self.stack.enter_async_context(
             AsyncBackgroundExecutor(self.config)
         )

libs/langgraph/langgraph/stream/__init__.py

@@ -17,9 +17,9 @@ from langgraph.stream.transformers import (
     CheckpointsTransformer,
     CustomTransformer,
     DebugTransformer,
+    LifecycleEvent,
     LifecyclePayload,
     LifecycleTransformer,
-    SubgraphStatus,
     SubgraphTransformer,
     TasksTransformer,
     UpdatesTransformer,
@@ -32,13 +32,13 @@ __all__ = [
     "CustomTransformer",
     "DebugTransformer",
     "GraphRunStream",
+    "LifecycleEvent",
     "LifecyclePayload",
     "LifecycleTransformer",
     "ProtocolEvent",
     "StreamChannel",
     "StreamTransformer",
     "SubgraphRunStream",
-    "SubgraphStatus",
     "SubgraphTransformer",
     "TasksTransformer",
     "UpdatesTransformer",

libs/langgraph/langgraph/stream/run_stream.py

@@ -12,7 +12,7 @@ from langgraph.stream._mux import StreamMux
 from langgraph.stream._types import ProtocolEvent
 
 if TYPE_CHECKING:
-    from langgraph.stream.transformers import SubgraphStatus
+    from langgraph.stream.transformers import LifecycleEvent
 
 
 def _drive_until_done(pump: Callable[[], bool]) -> None:
@@ -523,8 +523,8 @@ class _SubgraphRunStreamMixin:
 
     path: tuple[str, ...]
     graph_name: str | None
-    trigger_call_id: str | None
-    status: SubgraphStatus
+    parent_task_id: str | None
+    status: LifecycleEvent
     error: str | None
     _seen_terminal: bool
 
@@ -538,7 +538,7 @@ class SubgraphRunStream(GraphRunStream, _SubgraphRunStreamMixin):
         *,
         path: tuple[str, ...],
         graph_name: str | None = None,
-        trigger_call_id: str | None = None,
+        parent_task_id: str | None = None,
     ) -> None:
         # Capture the parent-inherited pump before super().__init__
         # touches anything; we delegate to it from `_pump_next`.
@@ -550,7 +550,7 @@ class SubgraphRunStream(GraphRunStream, _SubgraphRunStreamMixin):
         )
         self.path = path
         self.graph_name = graph_name
-        self.trigger_call_id = trigger_call_id
+        self.parent_task_id = parent_task_id
         self.status = "started"
         self.error = None
         self._seen_terminal = False
@@ -581,7 +581,7 @@ class AsyncSubgraphRunStream(AsyncGraphRunStream, _SubgraphRunStreamMixin):
         *,
         path: tuple[str, ...],
         graph_name: str | None = None,
-        trigger_call_id: str | None = None,
+        parent_task_id: str | None = None,
     ) -> None:
         self._parent_apump_fn: Callable[[], Awaitable[bool]] | None = mux._apump_fn
         super().__init__(
@@ -591,7 +591,7 @@ class AsyncSubgraphRunStream(AsyncGraphRunStream, _SubgraphRunStreamMixin):
         )
         self.path = path
         self.graph_name = graph_name
-        self.trigger_call_id = trigger_call_id
+        self.parent_task_id = parent_task_id
         self.status = "started"
         self.error = None
         self._seen_terminal = False

libs/langgraph/langgraph/stream/transformers.py

@@ -327,11 +327,31 @@ class MessagesTransformer(StreamTransformer):
         self._by_run.clear()
 
 
-SubgraphStatus = Literal["started", "completed", "failed", "interrupted", "drained"]
+LifecycleEvent = Literal["started", "completed", "failed", "interrupted", "drained"]
+"""State transition surfaced on the `lifecycle` channel for a tracked subgraph.
+
+Each value:
+
+- `started` — first `tasks` event observed at the tracked namespace. Carries
+  `graph_name` / `parent_task_id` / optional `metadata` describing what spawned
+  the subgraph.
+- `completed` — the dispatching task's `TaskResultPayload` arrived with neither
+  error nor interrupts. Also emitted by `finalize` for any tracked namespace
+  still open at run end.
+- `failed` — the dispatching task's result carried an `error`, OR the run
+  failed at top level with a non-interrupt / non-drain exception. Carries
+  `error` (string).
+- `interrupted` — the dispatching task's result carried `interrupts` (takes
+  precedence over `error` if both present), OR the run failed with
+  `GraphInterrupt`.
+- `drained` — the run was cooperatively stopped at a superstep boundary via
+  `RunControl.request_drain()` (e.g. SIGTERM). The checkpoint is saved and
+  the run is resumable.
+"""
 
 
 def _parse_ns_segment(segment: str) -> tuple[str, str | None]:
-    """Split a namespace segment into `(graph_name, trigger_call_id)`.
+    """Split a namespace segment into `(graph_name, parent_task_id)`.
 
     Segments are formatted `node_name:task_id` by `prepare_next_tasks`.
     Returns `(segment, None)` if no `:` is present.
@@ -340,6 +360,36 @@ def _parse_ns_segment(segment: str) -> tuple[str, str | None]:
     return name, task_id if sep else None
 
 
+def _extract_dispatching_tool_call_id(payload: Any) -> str | None:
+    """Return the model-side `tool_call_id` from a per-call dispatched task's
+    `input`, or `None` if the payload doesn't match a recognised shape.
+
+    Two shapes are recognised; both are duck-typed so any tool runner
+    that mimics the layout participates without naming any specific
+    dispatcher's types:
+
+    1. Single-element list of tool-call dicts:
+       `[{"id": ..., "name": ..., "args": {...}}]`. The current public
+       shape — `langchain.agents.create_agent` Send-fans this out per
+       pending tool call.
+    2. Dict envelope wrapping a tool call:
+       `{"tool_call": {"id": ..., "args": {...}, ...}, ...}`. Older
+       prebuilt agent paths Send-fan-out this shape.
+    """
+    if isinstance(payload, dict):
+        tool_call = payload.get("tool_call")
+        if not isinstance(tool_call, dict):
+            return None
+    elif (
+        isinstance(payload, list) and len(payload) == 1 and isinstance(payload[0], dict)
+    ):
+        tool_call = payload[0]
+    else:
+        return None
+    raw_id = tool_call.get("id")
+    return raw_id if isinstance(raw_id, str) else None
+
+
 class LifecyclePayload(TypedDict, total=False):
     """Payload of a lifecycle event surfaced on the `lifecycle` channel.
 
@@ -349,11 +399,54 @@ class LifecyclePayload(TypedDict, total=False):
     `run.lifecycle`.
     """
 
-    event: SubgraphStatus
+    event: LifecycleEvent
+    """State transition. See `LifecycleEvent` for per-value semantics."""
     namespace: list[str]
+    """Checkpoint namespace of the subgraph the event is about. Always present.
+
+    A list of `node_name:task_id` segments, one per nesting level (root has
+    `[]`, a direct child of root has `["agent:abc123"]`, a grandchild has
+    `["agent:abc123", "tool:def456"]`, etc.). Stable identity across the
+    `started → terminal` pair for the same subgraph instance.
+    """
     graph_name: NotRequired[str]
-    trigger_call_id: NotRequired[str]
+    """Name of the parent-scope node that dispatched this subgraph
+    (`add_node` name, surrounding tool's name for in-tool invokes,
+    `Send` target name, etc.) — parsed from the namespace tail
+    segment. Absent when the segment has no `:` separator.
+    """
+    parent_task_id: str
+    """Pregel task id of the dispatching task — the task whose execution
+    spawned this subgraph.
+
+    Always present on every event for the same subgraph instance. This is
+    the join key for correlating `started` ↔ terminal events and for
+    matching a `started` back to its `tasks` parent. Each Send produces
+    its own pregel task with its own id, so the join is 1:1 even when a
+    model dispatches multiple parallel tool calls in one turn.
+    """
+    metadata: NotRequired[dict[str, Any]]
+    """Optional generic descriptor of *what triggered* this subgraph.
+    Forwarded by protocol layers as the wire `lifecycle.started.metadata` field.
+
+    Shape:
+
+    - `{"type": "tool_call", "tool_call_id": "<id>"}` — set when the subgraph
+      was triggered by a per-call tool dispatch (a model tool call routed
+      through whatever tool node the agent uses). `tool_call_id` is the
+      model-side id of the originating tool call, exposed so UI consumers
+      can anchor the lifecycle event back to the AI message that dispatched
+      it. The langgraph layer deliberately doesn't mine `args` — those live
+      on the AIMessage's `tool_calls[i].args` already, and consumers that
+      want descriptive intent (subagent type, prompt text, etc.) look it
+      up there to keep one source of truth.
+
+    Absent for structurally-triggered subgraphs (parallel branches via
+    `Send` with non-tool-call payloads, nested `graph.invoke()`, etc.) and
+    for tool dispatches whose envelope carried no `id`.
+    """
     error: NotRequired[str]
+    """Error string. Set on `failed` events; absent otherwise."""
 
 
 class _TasksLifecycleBase(StreamTransformer):
@@ -371,13 +464,13 @@ class _TasksLifecycleBase(StreamTransformer):
 
     - `_should_track(ns)` — scope filter (e.g. multi-depth vs
       direct-children-only).
-    - `_on_started(ns, graph_name, trigger_call_id)` — first sighting
-      action (push payload / build handle / etc.). Called once per
-      discovered namespace.
-    - `_on_terminal(ns, status, error)` — terminal action (push
-      terminal payload / mark handle status). Called once per
-      tracked namespace at result time, or via `finalize` / `fail`
-      sweeps if no parent result arrived.
+    - `_on_started(ns, graph_name, parent_task_id, tool_call_id)` —
+      first sighting action (push payload / build handle / etc.).
+      Called once per discovered namespace.
+    - `_on_terminal(ns, status, error, parent_task_id)` — terminal
+      action (push terminal payload / mark handle status). Called
+      once per tracked namespace at result time, or via `finalize` /
+      `fail` sweeps if no parent result arrived.
 
     Tasks events are suppressed from the main event log (`process`
     returns False) — they're folded into whichever projection the
@@ -390,9 +483,15 @@ class _TasksLifecycleBase(StreamTransformer):
     def __init__(self, scope: tuple[str, ...] = ()) -> None:
         super().__init__(scope)
         self._seen: set[tuple[str, ...]] = set()
-        # Maps tracked namespace -> task_id of the parent task whose
+        # Maps tracked namespace -> task_id of the dispatching task whose
         # `TaskResultPayload` will close it.
         self._open: dict[tuple[str, ...], str] = {}
+        # Maps task_id -> model-side `tool_call_id` for tasks whose `input`
+        # matched a recognized per-call tool-dispatch shape. The lifecycle
+        # hook joins on this when a child subgraph fires its first task
+        # event so it can anchor the lifecycle.started to the originating
+        # AI message tool call.
+        self._dispatching_tool_call_id: dict[str, str] = {}
 
     # --- Template-method hooks (subclass overrides) ---
 
@@ -404,19 +503,33 @@ class _TasksLifecycleBase(StreamTransformer):
         self,
         ns: tuple[str, ...],
         graph_name: str | None,
-        trigger_call_id: str | None,
+        parent_task_id: str | None,
+        tool_call_id: str | None = None,
     ) -> None:
-        """Fired once per discovered namespace (first observed task event)."""
+        """Fired once per discovered namespace (first observed task event).
+
+        `tool_call_id` is the model-side id of the originating tool call
+        (from the per-call dispatched task's `input`). `None` for
+        structurally-triggered subgraphs or per-call envelopes that omitted
+        an `id`. Consumers join on `parent_task_id` (the pregel task id)
+        for identity; `tool_call_id` is purely an anchor back to the AI
+        message that dispatched the subgraph.
+        """
         raise NotImplementedError
 
     def _on_terminal(
         self,
         ns: tuple[str, ...],
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
+        parent_task_id: str,
     ) -> None:
-        """Fired once per tracked namespace when its parent's result arrives,
-        or via finalize/fail safety-net sweeps.
+        """Fired once per tracked namespace when its dispatching task's
+        result arrives, or via finalize/fail safety-net sweeps.
+
+        `parent_task_id` is the same id paired with the namespace at
+        `_on_started` time, so subscribers can correlate the terminal
+        event back to its `started`.
         """
         raise NotImplementedError
 
@@ -430,56 +543,96 @@ class _TasksLifecycleBase(StreamTransformer):
         if "result" in data:
             self._handle_task_result(ns, data)
         else:
-            self._handle_task_start(ns)
+            self._handle_task_start(ns, data)
         # Tasks events are folded into the synthesized projections;
         # suppress from the main event log so iterators don't double-see
         # the same information in two shapes.
         return False
 
-    def _handle_task_start(self, ns: tuple[str, ...]) -> None:
+    def _handle_task_start(self, ns: tuple[str, ...], data: dict[str, Any]) -> None:
+        # Mine input shape on every tasks event (not just tracked ones)
+        # so we capture dispatching tasks that themselves live outside the
+        # tracked region but whose `id` will appear as `parent_task_id`
+        # for a child subgraph.
+        self._record_dispatching_tool_call_id(data)
         if not self._should_track(ns) or ns in self._seen:
             return
         self._seen.add(ns)
-        graph_name, trigger_call_id = _parse_ns_segment(ns[-1])
-        self._on_started(ns, graph_name or None, trigger_call_id)
-        if trigger_call_id is not None:
-            self._open[ns] = trigger_call_id
+        graph_name, parent_task_id = _parse_ns_segment(ns[-1])
+        tool_call_id = (
+            self._dispatching_tool_call_id.pop(parent_task_id, None)
+            if parent_task_id is not None
+            else None
+        )
+        self._on_started(
+            ns,
+            graph_name or None,
+            parent_task_id,
+            tool_call_id,
+        )
+        if parent_task_id is not None:
+            self._open[ns] = parent_task_id
+
+    def _record_dispatching_tool_call_id(self, data: dict[str, Any]) -> None:
+        """Remember `task_id -> tool_call_id` if the task input matches
+        a recognized per-call tool-dispatch shape.
+
+        Shape detection and id extraction both live in
+        `_extract_dispatching_tool_call_id`; this method just records the
+        mapping under the dispatching task's own `id` so the lifecycle hook
+        can anchor a child subgraph back to the originating AI message
+        tool call when that subgraph's first task event arrives.
+        """
+        task_id = data.get("id")
+        if not isinstance(task_id, str):
+            return
+        tool_call_id = _extract_dispatching_tool_call_id(data.get("input"))
+        if tool_call_id is None:
+            return
+        self._dispatching_tool_call_id[task_id] = tool_call_id
 
     def _pop_terminal_transitions(
         self, ns: tuple[str, ...], data: dict[str, Any]
-    ) -> list[tuple[tuple[str, ...], SubgraphStatus, str | None]]:
-        """Return and remove tracked children closed by this task result."""
+    ) -> list[tuple[tuple[str, ...], LifecycleEvent, str | None, str]]:
+        """Return and remove tracked children closed by this task result.
+
+        Each tuple is `(child_ns, status, error, parent_task_id)`.
+        `parent_task_id` is the dispatching task's id — the same id
+        we'd already paired with the namespace at `_on_started`.
+        """
         result_id = data.get("id")
         if not result_id:
             return []
-        transitions: list[tuple[tuple[str, ...], SubgraphStatus, str | None]] = []
-        for child_ns, parent_task_id in list(self._open.items()):
-            if child_ns[:-1] != ns or parent_task_id != result_id:
+        transitions: list[tuple[tuple[str, ...], LifecycleEvent, str | None, str]] = []
+        for child_ns, dispatching_task_id in list(self._open.items()):
+            if child_ns[:-1] != ns or dispatching_task_id != result_id:
                 continue
             status, error = _terminal_from_result(data)
-            transitions.append((child_ns, status, error))
+            transitions.append((child_ns, status, error, dispatching_task_id))
             del self._open[child_ns]
         return transitions
 
     def _handle_task_result(self, ns: tuple[str, ...], data: dict[str, Any]) -> None:
-        for child_ns, status, error in self._pop_terminal_transitions(ns, data):
-            self._on_terminal(child_ns, status, error)
+        for child_ns, status, error, parent_task_id in self._pop_terminal_transitions(
+            ns, data
+        ):
+            self._on_terminal(child_ns, status, error, parent_task_id)
 
     def finalize(self) -> None:
         """Emit `completed` for any tracked namespace still open at run end."""
-        for ns in list(self._open):
-            self._on_terminal(ns, "completed", None)
+        for ns, parent_task_id in list(self._open.items()):
+            self._on_terminal(ns, "completed", None, parent_task_id)
         self._open.clear()
 
     def fail(self, err: BaseException) -> None:
         """Emit terminal status for any tracked namespace still open."""
         status, error_str = _status_from_exception(err)
-        for ns in list(self._open):
-            self._on_terminal(ns, status, error_str)
+        for ns, parent_task_id in list(self._open.items()):
+            self._on_terminal(ns, status, error_str, parent_task_id)
         self._open.clear()
 
 
-def _status_from_exception(err: BaseException) -> tuple[SubgraphStatus, str | None]:
+def _status_from_exception(err: BaseException) -> tuple[LifecycleEvent, str | None]:
     """Map a run exception to a subgraph terminal status and error string."""
     if isinstance(err, GraphDrained):
         return "drained", None
@@ -490,7 +643,7 @@ def _status_from_exception(err: BaseException) -> tuple[SubgraphStatus, str | No
 
 def _terminal_from_result(
     payload: dict[str, Any],
-) -> tuple[SubgraphStatus, str | None]:
+) -> tuple[LifecycleEvent, str | None]:
     """Map a `TaskResultPayload` to a `(status, error)` pair.
 
     Order matters: a result with both `error` and `interrupts` prefers
@@ -539,26 +692,37 @@ class LifecycleTransformer(_TasksLifecycleBase):
         self,
         ns: tuple[str, ...],
         graph_name: str | None,
-        trigger_call_id: str | None,
+        parent_task_id: str | None,
+        tool_call_id: str | None = None,
     ) -> None:
-        if trigger_call_id is None:
-            # Without a task id we can't correlate a parent-result
+        if parent_task_id is None:
+            # Without a task id we can't correlate a dispatching-task-result
             # event back to this namespace — skip the started payload
             # and rely on finalize/fail to close.
             return
-        payload: LifecyclePayload = {"event": "started", "namespace": list(ns)}
+        payload: LifecyclePayload = {
+            "event": "started",
+            "namespace": list(ns),
+            "parent_task_id": parent_task_id,
+        }
         if graph_name:
             payload["graph_name"] = graph_name
-        payload["trigger_call_id"] = trigger_call_id
+        if tool_call_id is not None:
+            payload["metadata"] = {"type": "tool_call", "tool_call_id": tool_call_id}
         self._channel.push(payload)
 
     def _on_terminal(
         self,
         ns: tuple[str, ...],
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
+        parent_task_id: str,
     ) -> None:
-        payload: LifecyclePayload = {"event": status, "namespace": list(ns)}
+        payload: LifecyclePayload = {
+            "event": status,
+            "namespace": list(ns),
+            "parent_task_id": parent_task_id,
+        }
         if error is not None:
             payload["error"] = error
         self._channel.push(payload)
@@ -611,7 +775,8 @@ class SubgraphTransformer(_TasksLifecycleBase):
         self,
         ns: tuple[str, ...],
         graph_name: str | None,
-        trigger_call_id: str | None,
+        parent_task_id: str | None,
+        tool_call_id: str | None = None,  # noqa: ARG002
     ) -> None:
         if self._mux is None:
             return
@@ -624,7 +789,7 @@ class SubgraphTransformer(_TasksLifecycleBase):
             mux=child_mux,
             path=ns,
             graph_name=graph_name,
-            trigger_call_id=trigger_call_id,
+            parent_task_id=parent_task_id,
         )
         self._handles[ns] = handle
         self._log.push(handle)
@@ -632,8 +797,9 @@ class SubgraphTransformer(_TasksLifecycleBase):
     def _on_terminal(
         self,
         ns: tuple[str, ...],
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
+        parent_task_id: str,  # noqa: ARG002
     ) -> None:
         handle = self._handles.get(ns)
         if handle is None or not self._mark_terminal(handle, status, error):
@@ -643,8 +809,9 @@ class SubgraphTransformer(_TasksLifecycleBase):
     async def _aon_terminal(
         self,
         ns: tuple[str, ...],
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
+        parent_task_id: str,  # noqa: ARG002
     ) -> None:
         handle = self._handles.get(ns)
         if handle is None or not self._mark_terminal(handle, status, error):
@@ -654,7 +821,7 @@ class SubgraphTransformer(_TasksLifecycleBase):
     def _mark_terminal(
         self,
         handle: SubgraphRunStream | AsyncSubgraphRunStream,
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
     ) -> bool:
         """Mark a handle terminal once. Returns True on first transition."""
@@ -669,7 +836,7 @@ class SubgraphTransformer(_TasksLifecycleBase):
     def _close_or_fail_handle(
         self,
         handle: SubgraphRunStream | AsyncSubgraphRunStream,
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
     ) -> None:
         if handle._mux is None or handle._mux._events._closed:
@@ -682,7 +849,7 @@ class SubgraphTransformer(_TasksLifecycleBase):
     async def _aclose_or_fail_handle(
         self,
         handle: SubgraphRunStream | AsyncSubgraphRunStream,
-        status: SubgraphStatus,
+        status: LifecycleEvent,
         error: str | None,
     ) -> None:
         if handle._mux is None or handle._mux._events._closed:
@@ -721,10 +888,15 @@ class SubgraphTransformer(_TasksLifecycleBase):
             ns = tuple(event["params"]["namespace"])
             data = event["params"]["data"]
             if "result" in data:
-                for child_ns, status, error in self._pop_terminal_transitions(ns, data):
-                    await self._aon_terminal(child_ns, status, error)
+                for (
+                    child_ns,
+                    status,
+                    error,
+                    parent_task_id,
+                ) in self._pop_terminal_transitions(ns, data):
+                    await self._aon_terminal(child_ns, status, error, parent_task_id)
             else:
-                self._handle_task_start(ns)
+                self._handle_task_start(ns, data)
             keep = False
         else:
             keep = True
@@ -736,9 +908,9 @@ class SubgraphTransformer(_TasksLifecycleBase):
 
     def _complete_open_handles(self) -> BaseException | None:
         first_error: BaseException | None = None
-        for ns in list(self._open):
+        for ns, parent_task_id in list(self._open.items()):
             try:
-                self._on_terminal(ns, "completed", None)
+                self._on_terminal(ns, "completed", None, parent_task_id)
             except BaseException as e:
                 if first_error is None:
                     first_error = e
@@ -754,9 +926,9 @@ class SubgraphTransformer(_TasksLifecycleBase):
 
     async def _acomplete_open_handles(self) -> BaseException | None:
         first_error: BaseException | None = None
-        for ns in list(self._open):
+        for ns, parent_task_id in list(self._open.items()):
             try:
-                await self._aon_terminal(ns, "completed", None)
+                await self._aon_terminal(ns, "completed", None, parent_task_id)
             except BaseException as e:
                 if first_error is None:
                     first_error = e

libs/langgraph/tests/test_channels.py

@@ -3,12 +3,7 @@ from collections.abc import Sequence
 from typing import Annotated
 
 import pytest
-from langchain_core.messages import (
-    AIMessage,
-    AIMessageChunk,
-    HumanMessage,
-    RemoveMessage,
-)
+from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
 from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.checkpoint.serde.types import _DeltaSnapshot
 from typing_extensions import NotRequired, TypedDict
@@ -21,7 +16,7 @@ from langgraph.channels.topic import Topic
 from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.errors import EmptyChannelError, InvalidUpdateError
 from langgraph.graph import START, StateGraph
-from langgraph.graph.message import REMOVE_ALL_MESSAGES, _messages_delta_reducer
+from langgraph.graph.message import _messages_delta_reducer
 from langgraph.graph.state import _get_channel
 from langgraph.types import Overwrite
 
@@ -289,61 +284,6 @@ def test_messages_delta_reducer_tuple_write_is_one_message() -> None:
     assert result[0].content == "hi"
 
 
-def test_messages_delta_reducer_assigns_uuid_to_id_less_messages() -> None:
-    """Messages without IDs get UUIDs assigned, matching add_messages behavior.
-
-    Without UUID assignment, RemoveMessage tombstoning fails on messages that
-    were created without explicit IDs.
-    """
-    m1 = HumanMessage(content="hi")
-    m2 = AIMessage(content="hello")
-    assert m1.id is None
-    assert m2.id is None
-
-    result = _messages_delta_reducer([], [[m1, m2]])
-    assert len(result) == 2
-    assert result[0].id is not None
-    assert result[1].id is not None
-
-    # RemoveMessage tombstoning must work on the now-assigned IDs.
-    result2 = _messages_delta_reducer(result, [RemoveMessage(id=result[1].id)])
-    assert len(result2) == 1
-    assert result2[0].content == "hi"
-
-
-def test_messages_delta_reducer_remove_all_messages() -> None:
-    """REMOVE_ALL_MESSAGES sentinel clears all state and preceding writes."""
-    state = [HumanMessage(content="old", id="h1"), AIMessage(content="prior", id="a1")]
-
-    # Sentinel mid-batch: everything before it (including state) is discarded.
-    result = _messages_delta_reducer(
-        state,
-        [
-            [
-                RemoveMessage(id=REMOVE_ALL_MESSAGES),
-                HumanMessage(content="fresh", id="h2"),
-            ]
-        ],
-    )
-    assert len(result) == 1
-    assert result[0].content == "fresh"
-
-    # Batching-invariant: split across two calls must equal one combined call.
-    step1 = _messages_delta_reducer(state, [[RemoveMessage(id=REMOVE_ALL_MESSAGES)]])
-    step2 = _messages_delta_reducer(step1, [[HumanMessage(content="fresh", id="h2")]])
-    assert step2 == result
-
-
-def test_messages_delta_reducer_coerces_message_chunks() -> None:
-    """BaseMessageChunk writes are coerced to full messages."""
-    chunk = AIMessageChunk(content="hello", id="a1")
-    result = _messages_delta_reducer([], [[chunk]])
-    assert len(result) == 1
-    assert not isinstance(result[0], AIMessageChunk)
-    assert result[0].content == "hello"
-    assert result[0].id == "a1"
-
-
 def test_delta_channel_checkpoint_returns_missing() -> None:
     """checkpoint() always returns MISSING regardless of state.
 

libs/langgraph/tests/test_delta_channel_exit_mode.py

@@ -0,0 +1,365 @@
+"""Tests for exit-mode delta channel persistence redesign.
+
+Validates that `durability="exit"` correctly persists delta-channel writes
+using count-based snapshot decisions (rather than force-snapshotting every
+channel), lazy stub creation when no parent exists, and proper read-path
+reconstruction via ancestor walks.
+"""
+
+from typing import Annotated, Any
+
+import pytest
+from langchain_core.messages import AIMessage, HumanMessage
+from langgraph.checkpoint.memory import InMemorySaver
+from langgraph.checkpoint.serde.types import _DeltaSnapshot
+from typing_extensions import TypedDict
+
+from langgraph.channels.delta import DeltaChannel
+from langgraph.graph import START, StateGraph
+from langgraph.graph.message import _messages_delta_reducer
+
+pytestmark = pytest.mark.anyio
+
+
+def _build_graph(
+    checkpointer: InMemorySaver,
+    *,
+    freq: int = 1000,
+) -> Any:
+    channel = DeltaChannel(_messages_delta_reducer, snapshot_frequency=freq)
+    # Functional TypedDict form: class form can't reference `channel` (a
+    # local variable) inside Annotated due to forward-ref evaluation rules.
+    State = TypedDict("State", {"messages": Annotated[list, channel]})  # type: ignore[call-overload]  # noqa: UP013
+
+    def respond(state: dict) -> dict:
+        i = len(state["messages"])
+        return {"messages": [AIMessage(content=f"reply-{i}", id=f"ai{i}")]}
+
+    builder = StateGraph(State)
+    builder.add_node("respond", respond)
+    builder.add_edge(START, "respond")
+    return builder.compile(checkpointer=checkpointer)
+
+
+# ---------------------------------------------------------------------------
+# 8a. Write-path / structural tests
+# ---------------------------------------------------------------------------
+
+
+async def test_exit_first_run_no_delta_writes() -> None:
+    """Graph with delta channel invoked with input that doesn't touch it.
+    Only one checkpoint row, no stub."""
+    State = TypedDict(  # noqa: UP013
+        "State",
+        {
+            "messages": Annotated[list, DeltaChannel(_messages_delta_reducer)],
+            "value": str,
+        },
+    )  # type: ignore[call-overload]
+
+    def noop(state: dict) -> dict:
+        return {"value": "done"}
+
+    saver = InMemorySaver()
+    builder = StateGraph(State)
+    builder.add_node("noop", noop)
+    builder.add_edge(START, "noop")
+    graph = builder.compile(checkpointer=saver)
+    config = {"configurable": {"thread_id": "no-delta-writes"}}
+
+    graph.invoke({"value": "start"}, config, durability="exit")
+
+    checkpoints = list(saver.list(config))
+    assert len(checkpoints) == 1
+    stubs = [t for t in checkpoints if t.metadata.get("step") == -2]
+    assert len(stubs) == 0
+
+
+async def test_exit_first_run_all_snapshot() -> None:
+    """snapshot_frequency=1 forces every channel to snapshot.
+    No stub needed; final_checkpoint has _DeltaSnapshot."""
+    saver = InMemorySaver()
+    graph = _build_graph(saver, freq=1)
+    config = {"configurable": {"thread_id": "all-snapshot"}}
+
+    result = graph.invoke(
+        {"messages": [HumanMessage(content="hi", id="h1")]},
+        config,
+        durability="exit",
+    )
+    assert len(result["messages"]) == 2
+
+    checkpoints = list(saver.list(config))
+    stubs = [t for t in checkpoints if t.metadata.get("step") == -2]
+    assert len(stubs) == 0
+
+    head = saver.get_tuple(config)
+    assert head is not None
+    assert isinstance(head.checkpoint["channel_values"].get("messages"), _DeltaSnapshot)
+
+    state = graph.get_state(config)
+    assert [m.content for m in state.values["messages"]] == ["hi", "reply-1"]
+
+
+async def test_exit_first_run_sub_freq_with_writes() -> None:
+    """First run with default snapshot_frequency (1000), writes below threshold.
+    A stub is created; writes are anchored under it; get_state reconstructs."""
+    saver = InMemorySaver()
+    graph = _build_graph(saver)
+    config = {"configurable": {"thread_id": "sub-freq-first"}}
+
+    result = graph.invoke(
+        {"messages": [HumanMessage(content="hello", id="h1")]},
+        config,
+        durability="exit",
+    )
+    assert [m.content for m in result["messages"]] == ["hello", "reply-1"]
+
+    checkpoints = list(saver.list(config))
+    stubs = [t for t in checkpoints if t.metadata.get("step") == -2]
+    assert len(stubs) == 1, f"Expected 1 stub, got {len(stubs)}"
+
+    head = saver.get_tuple(config)
+    assert head is not None
+    assert "messages" not in head.checkpoint["channel_values"]
+    assert "messages" in head.checkpoint["channel_versions"]
+
+    state = graph.get_state(config)
+    assert [m.content for m in state.values["messages"]] == ["hello", "reply-1"]
+
+
+async def test_exit_resumed_run_sub_freq() -> None:
+    """Two consecutive exit runs. Second run anchors on the first's
+    final_checkpoint (no new stub). Ordering preserved."""
+    saver = InMemorySaver()
+    graph = _build_graph(saver)
+    config = {"configurable": {"thread_id": "resumed-sub-freq"}}
+
+    graph.invoke(
+        {"messages": [HumanMessage(content="msg1", id="h1")]},
+        config,
+        durability="exit",
+    )
+
+    graph.invoke(
+        {"messages": [HumanMessage(content="msg2", id="h2")]},
+        config,
+        durability="exit",
+    )
+
+    checkpoints = list(saver.list(config))
+    stubs = [t for t in checkpoints if t.metadata.get("step") == -2]
+    assert len(stubs) == 1
+
+    state = graph.get_state(config)
+    contents = [m.content for m in state.values["messages"]]
+    assert len(contents) == 4
+    assert contents[0] == "msg1"
+    assert contents[2] == "msg2"
+    assert contents[0:4:2] == ["msg1", "msg2"]
+
+
+async def test_exit_count_parity_sync_vs_exit() -> None:
+    """Sync and exit durability produce the same delta_updates_since_snapshot
+    after an equivalent run."""
+    for durability in ("sync", "exit"):
+        saver = InMemorySaver()
+        graph = _build_graph(saver)
+        config = {"configurable": {"thread_id": f"parity-{durability}"}}
+
+        graph.invoke(
+            {"messages": [HumanMessage(content="hi", id="h1")]},
+            config,
+            durability=durability,
+        )
+
+        head = saver.get_tuple(config)
+        assert head is not None
+        counts = head.metadata.get("delta_updates_since_snapshot", {})
+        assert counts.get("messages") == 2, (
+            f"durability={durability}: expected count=2, got {counts}"
+        )
+
+
+async def test_exit_snapshot_fires_at_frequency() -> None:
+    """With snapshot_frequency=3, after 3 exit runs (each incrementing count
+    by 2: input + superstep), the 2nd run hits count=4>=3, triggering snapshot.
+    After that run, count resets to 0 and channel_values has _DeltaSnapshot."""
+    saver = InMemorySaver()
+    graph = _build_graph(saver, freq=3)
+    config = {"configurable": {"thread_id": "snapshot-at-freq"}}
+
+    graph.invoke(
+        {"messages": [HumanMessage(content="m1", id="h1")]},
+        config,
+        durability="exit",
+    )
+    head = saver.get_tuple(config)
+    assert head is not None
+    count1 = head.metadata.get("delta_updates_since_snapshot", {}).get("messages", 0)
+    assert count1 == 2
+
+    graph.invoke(
+        {"messages": [HumanMessage(content="m2", id="h2")]},
+        config,
+        durability="exit",
+    )
+    head = saver.get_tuple(config)
+    assert head is not None
+    count2 = head.metadata.get("delta_updates_since_snapshot", {}).get("messages", 0)
+    assert count2 == 0, f"Expected reset to 0 after snapshot, got {count2}"
+    assert isinstance(head.checkpoint["channel_values"].get("messages"), _DeltaSnapshot)
+
+
+async def test_exit_mixed_snapshot_and_non_snapshot() -> None:
+    """One delta channel at freq=1 (always snapshot) and one at freq=1000
+    (never snapshot within this test). Verify correct behavior for both."""
+
+    fast_ch = DeltaChannel(_messages_delta_reducer, snapshot_frequency=1)
+    slow_ch = DeltaChannel(_messages_delta_reducer, snapshot_frequency=1000)
+    State = TypedDict(  # noqa: UP013
+        "State",
+        {"fast": Annotated[list, fast_ch], "slow": Annotated[list, slow_ch]},
+    )  # type: ignore[call-overload]
+
+    def respond(state: dict) -> dict:
+        return {
+            "fast": [AIMessage(content="fast-reply", id="f1")],
+            "slow": [AIMessage(content="slow-reply", id="s1")],
+        }
+
+    saver = InMemorySaver()
+    builder = StateGraph(State)
+    builder.add_node("respond", respond)
+    builder.add_edge(START, "respond")
+    graph = builder.compile(checkpointer=saver)
+    config = {"configurable": {"thread_id": "mixed-freq"}}
+
+    graph.invoke(
+        {
+            "fast": [HumanMessage(content="fast-in", id="fi")],
+            "slow": [HumanMessage(content="slow-in", id="si")],
+        },
+        config,
+        durability="exit",
+    )
+
+    head = saver.get_tuple(config)
+    assert head is not None
+    assert isinstance(head.checkpoint["channel_values"].get("fast"), _DeltaSnapshot)
+    assert "slow" not in head.checkpoint["channel_values"]
+
+    state = graph.get_state(config)
+    assert [m.content for m in state.values["fast"]] == ["fast-in", "fast-reply"]
+    assert [m.content for m in state.values["slow"]] == ["slow-in", "slow-reply"]
+
+
+# ---------------------------------------------------------------------------
+# 8b. Read-path tests
+# ---------------------------------------------------------------------------
+
+
+async def test_exit_multi_run_replay_chain() -> None:
+    """K=4 consecutive exit runs, each adding a message. After each run,
+    get_state returns all messages in chronological order."""
+    saver = InMemorySaver()
+    graph = _build_graph(saver)
+    config = {"configurable": {"thread_id": "replay-chain"}}
+
+    for i in range(4):
+        graph.invoke(
+            {"messages": [HumanMessage(content=f"user-{i}", id=f"h{i}")]},
+            config,
+            durability="exit",
+        )
+
+        state = graph.get_state(config)
+        contents = [m.content for m in state.values["messages"]]
+        user_msgs = [c for c in contents if c.startswith("user-")]
+        assert user_msgs == [f"user-{j}" for j in range(i + 1)], (
+            f"After run {i}: user messages out of order: {user_msgs}"
+        )
+        assert len(contents) == (i + 1) * 2
+
+
+async def test_exit_metadata_round_trip() -> None:
+    """K=5 consecutive exit runs with snapshot_frequency=5. Verify metadata
+    delta_updates_since_snapshot increments correctly across runs."""
+    freq = 5
+    saver = InMemorySaver()
+    graph = _build_graph(saver, freq=freq)
+    config = {"configurable": {"thread_id": "metadata-rt"}}
+
+    for i in range(1, 6):
+        graph.invoke(
+            {"messages": [HumanMessage(content=f"m{i}", id=f"h{i}")]},
+            config,
+            durability="exit",
+        )
+        head = saver.get_tuple(config)
+        assert head is not None
+        count = head.metadata.get("delta_updates_since_snapshot", {}).get("messages", 0)
+        cumulative = i * 2
+        if cumulative >= freq:
+            assert count == 0 or count == cumulative % freq or count < freq, (
+                f"After run {i}: count={count} should have reset or be partial"
+            )
+        else:
+            assert count == cumulative, (
+                f"After run {i}: expected {cumulative}, got {count}"
+            )
+
+
+async def test_exit_mixed_durability_round_trip() -> None:
+    """Alternate sync and exit durability; verify counts stay monotonic
+    and state accumulates correctly."""
+    saver = InMemorySaver()
+    graph = _build_graph(saver)
+    config = {"configurable": {"thread_id": "mixed-durability"}}
+
+    for i, dur in enumerate(["sync", "exit", "sync", "exit"]):
+        graph.invoke(
+            {"messages": [HumanMessage(content=f"msg-{i}", id=f"h{i}")]},
+            config,
+            durability=dur,
+        )
+
+        state = graph.get_state(config)
+        contents = [m.content for m in state.values["messages"]]
+        user_msgs = [c for c in contents if c.startswith("msg-")]
+        assert user_msgs == [f"msg-{j}" for j in range(i + 1)], (
+            f"After run {i} (durability={dur}): {user_msgs}"
+        )
+        assert len(contents) == (i + 1) * 2
+
+
+async def test_exit_snapshot_then_tail_deltas() -> None:
+    """Run 1 forces snapshot (freq=1). Run 2 at freq=1000 adds more writes
+    that don't snapshot. Reading after run 2 must combine the snapshot seed
+    with the tail deltas."""
+    saver = InMemorySaver()
+
+    graph1 = _build_graph(saver, freq=1)
+    config = {"configurable": {"thread_id": "snapshot-then-tail"}}
+    graph1.invoke(
+        {"messages": [HumanMessage(content="seed-msg", id="h1")]},
+        config,
+        durability="exit",
+    )
+
+    head = saver.get_tuple(config)
+    assert head is not None
+    assert isinstance(head.checkpoint["channel_values"].get("messages"), _DeltaSnapshot)
+
+    graph2 = _build_graph(saver, freq=1000)
+    graph2.invoke(
+        {"messages": [HumanMessage(content="tail-msg", id="h2")]},
+        config,
+        durability="exit",
+    )
+
+    state = graph2.get_state(config)
+    contents = [m.content for m in state.values["messages"]]
+    assert "seed-msg" in contents
+    assert "tail-msg" in contents
+    assert contents.index("seed-msg") < contents.index("tail-msg")

libs/langgraph/tests/test_retry.py

@@ -1674,15 +1674,28 @@ async def test_arun_with_retry_timeout_observer_tracks_attempts():
 async def test_arun_with_retry_timeout_observer_emits_progress_on_heartbeat():
     events: list = []
 
+    # `_TimedAttemptScope.__init__` sets `_last_progress` to `time.monotonic()`,
+    # but the watchdog itself doesn't start running until after `wrap_config`
+    # and task scheduling — under CI load that gap can be large enough to eat
+    # the entire idle window before the task body's first await even runs. We
+    # defend against that by:
+    #   1. Using a generous idle_timeout so scheduling slack stays well within it.
+    #   2. Calling `runtime.heartbeat()` BEFORE the first sleep, which resets
+    #      `_last_progress` to "now" the moment the task body actually starts.
+    idle_timeout_s = 1.0
+
     class HeartbeatProc:
         async def ainvoke(self, input, config):
             runtime = config[CONF][CONFIG_KEY_RUNTIME]
+            runtime.heartbeat()  # reset the idle clock at task-body entry
             for _ in range(8):
                 await asyncio.sleep(0.05)
                 runtime.heartbeat()
             return "ok"
 
-    task = _make_task(HeartbeatProc(), timeout=_idle_timeout(0.2), name="heartbeat")
+    task = _make_task(
+        HeartbeatProc(), timeout=_idle_timeout(idle_timeout_s), name="heartbeat"
+    )
     task.config[CONF][CONFIG_KEY_TIMED_ATTEMPT_OBSERVER] = events.append
     assert await arun_with_retry(task, retry_policy=None) == "ok"
 
@@ -1691,13 +1704,13 @@ async def test_arun_with_retry_timeout_observer_emits_progress_on_heartbeat():
     assert by_event[-1] == "finish"
     progress = [ev for ev in events if ev.event == "progress"]
     assert progress, "expected at least one progress event from heartbeat"
-    # Rate limit is `idle_timeout / 4` = 0.05s; with 8 heartbeats spaced ~0.05s
-    # we should see at most ~one progress event per heartbeat (well below 8).
+    # Rate limit is `idle_timeout / 4` = 0.25s; with the task running for
+    # ~400ms we expect 1–2 progress events (well below the 9 heartbeats).
     assert len(progress) <= len(by_event)
     for ev in progress:
         assert ev.context.task_name == "heartbeat"
         assert ev.context.attempt == 1
-        assert ev.context.idle_timeout_secs == 0.2
+        assert ev.context.idle_timeout_secs == idle_timeout_s
         assert isinstance(ev.progress_at, datetime)
 
 

libs/langgraph/tests/test_stream_lifecycle_transformer.py

@@ -35,8 +35,16 @@ def _tasks_start(
     *,
     task_id: str,
     name: str,
+    input: Any = None,
 ) -> dict[str, Any]:
-    """Build a `tasks` ProtocolEvent carrying a TaskPayload (start)."""
+    """Build a `tasks` ProtocolEvent carrying a TaskPayload (start).
+
+    Pass `input=[{"id": ..., "name": ..., "args": {...}}]` (the per-call
+    list shape `langchain.agents.create_agent` Send-fans out) or
+    `input={"tool_call": {"id": ..., ...}, ...}` (the dict envelope older
+    prebuilt agent paths emit) to exercise the lifecycle transformer's
+    `tool_call_id` mining for `lifecycle.started.metadata`.
+    """
     return {
         "type": "event",
         "method": "tasks",
@@ -46,7 +54,7 @@ def _tasks_start(
             "data": {
                 "id": task_id,
                 "name": name,
-                "input": None,
+                "input": input,
                 "triggers": [],
             },
         },
@@ -123,7 +131,220 @@ def test_started_emitted_on_first_direct_child_task() -> None:
     assert payload["event"] == "started"
     assert payload["namespace"] == ["agent:abc123"]
     assert payload["graph_name"] == "agent"
-    assert payload["trigger_call_id"] == "abc123"
+    assert payload["parent_task_id"] == "abc123"
+
+
+def test_started_carries_metadata_for_dict_envelope_input() -> None:
+    """When the dispatching task's `input` is a dict envelope with a
+    `tool_call` field (the shape older prebuilt agent paths Send-fan
+    out per call), the transformer mines `tool_call_id` from
+    `tool_call.id` and remembers it keyed by the dispatching task id.
+    When that task triggers a subgraph (the child's namespace ends in
+    `name:<dispatching_task_id>`), `lifecycle.started.metadata` carries
+    `{"type": "tool_call", "tool_call_id": ...}`. Identity correlation
+    still uses `parent_task_id`; `tool_call_id` is exposed so UI
+    consumers can anchor the lifecycle event back to the originating
+    AI message tool call. Args are deliberately NOT mined — they live
+    on the AIMessage and have a single source of truth there.
+    """
+    mux = _build_lifecycle_mux()
+    mux.push(
+        _tasks_start(
+            [],
+            task_id="abc123",
+            name="tools",
+            input={
+                "tool_call": {
+                    "id": "call_xyz",
+                    "name": "task",
+                    "args": {"subagent_type": "researcher"},
+                }
+            },
+        )
+    )
+    mux.push(_tasks_start(["agent:abc123"], task_id="t1", name="model"))
+
+    [payload] = _drain_lifecycle(mux)
+    assert payload["event"] == "started"
+    assert payload["parent_task_id"] == "abc123"
+    assert payload["metadata"] == {
+        "type": "tool_call",
+        "tool_call_id": "call_xyz",
+    }
+
+
+def test_started_carries_metadata_for_list_shape_per_call_input() -> None:
+    """`langchain.agents.create_agent` Send-fans out a per-call task
+    whose `input` is a single-element list of tool-call dicts:
+    `[{"id": ..., "name": ..., "args": {...}}]`. The transformer mines
+    `tool_call_id` exactly as for the dict envelope shape, so
+    `lifecycle.started.metadata` fires regardless of which agent factory
+    drove the dispatch.
+    """
+    mux = _build_lifecycle_mux()
+    mux.push(
+        _tasks_start(
+            [],
+            task_id="abc123",
+            name="tools",
+            input=[
+                {
+                    "id": "tc-1",
+                    "name": "task",
+                    "args": {"subagent_type": "researcher"},
+                }
+            ],
+        )
+    )
+    mux.push(_tasks_start(["agent:abc123"], task_id="t1", name="model"))
+
+    [payload] = _drain_lifecycle(mux)
+    assert payload["event"] == "started"
+    assert payload["parent_task_id"] == "abc123"
+    assert payload["metadata"] == {"type": "tool_call", "tool_call_id": "tc-1"}
+
+
+def test_started_carries_metadata_when_args_absent() -> None:
+    """`tool_call_id` is the only field metadata needs; the dispatching
+    envelope can omit `args` entirely (or have non-dict args) and we
+    still produce a metadata as long as `id` is a string."""
+    mux = _build_lifecycle_mux()
+    mux.push(
+        _tasks_start(
+            [],
+            task_id="abc123",
+            name="tools",
+            input=[{"id": "tc-1", "name": "some_tool"}],
+        )
+    )
+    mux.push(_tasks_start(["agent:abc123"], task_id="t1", name="model"))
+
+    [payload] = _drain_lifecycle(mux)
+    assert payload["metadata"] == {"type": "tool_call", "tool_call_id": "tc-1"}
+
+
+def test_list_shape_ignored_when_not_single_element() -> None:
+    """Only single-element lists are recognized as the per-call shape;
+    a 0- or 2+-element list is some other batched/multi-call payload
+    and must not be mined."""
+    # Two-element list — not the per-call shape.
+    mux = _build_lifecycle_mux()
+    mux.push(
+        _tasks_start(
+            [],
+            task_id="abc123",
+            name="tools",
+            input=[
+                {"id": "tc-1", "name": "task"},
+                {"id": "tc-2", "name": "task"},
+            ],
+        )
+    )
+    mux.push(_tasks_start(["agent:abc123"], task_id="t1", name="model"))
+
+    [payload] = _drain_lifecycle(mux)
+    assert "metadata" not in payload
+
+    # Empty list.
+    mux2 = _build_lifecycle_mux()
+    mux2.push(_tasks_start([], task_id="def456", name="tools", input=[]))
+    mux2.push(_tasks_start(["agent:def456"], task_id="t1", name="model"))
+    [payload2] = _drain_lifecycle(mux2)
+    assert "metadata" not in payload2
+
+
+def test_list_shape_robust_to_non_dict_or_missing_id() -> None:
+    """Duck-typing safety: a single-element list whose element isn't a
+    dict, or whose dict has no string `id`, must not raise — it just
+    leaves `metadata` absent."""
+    # Element is not a dict.
+    mux = _build_lifecycle_mux()
+    mux.push(_tasks_start([], task_id="t-a", name="tools", input=["not-a-dict"]))
+    mux.push(_tasks_start(["agent:t-a"], task_id="t1", name="model"))
+    [payload] = _drain_lifecycle(mux)
+    assert "metadata" not in payload
+
+    # Element has no `id`.
+    mux2 = _build_lifecycle_mux()
+    mux2.push(_tasks_start([], task_id="t-b", name="tools", input=[{"name": "task"}]))
+    mux2.push(_tasks_start(["agent:t-b"], task_id="t1", name="model"))
+    [payload2] = _drain_lifecycle(mux2)
+    assert "metadata" not in payload2
+
+    # Element's `id` is not a string.
+    mux3 = _build_lifecycle_mux()
+    mux3.push(_tasks_start([], task_id="t-c", name="tools", input=[{"id": 123}]))
+    mux3.push(_tasks_start(["agent:t-c"], task_id="t1", name="model"))
+    [payload3] = _drain_lifecycle(mux3)
+    assert "metadata" not in payload3
+
+
+def test_parallel_dispatches_attributed_to_correct_parent() -> None:
+    """Two dispatching task envelopes in the same model turn each fan
+    out to their own child subgraph; each child's `metadata.tool_call_id`
+    must reflect its own dispatching envelope, not the other.
+
+    Defends the `parent_task_id` (pregel task id) join: that id is
+    parsed from the child namespace segment and is unique per Send,
+    so it disambiguates parallel dispatches 1:1. Both children share
+    the same `subagent_type` (in args, not on metadata) — only the
+    pregel task id can tell them apart, so the `tool_call_id` must
+    follow the pregel id, not anything from `args`.
+    """
+    mux = _build_lifecycle_mux()
+    mux.push(
+        _tasks_start(
+            [],
+            task_id="parent_A",
+            name="tools",
+            input={
+                "tool_call": {
+                    "id": "call_1",
+                    "name": "task",
+                    "args": {"subagent_type": "researcher"},
+                }
+            },
+        )
+    )
+    mux.push(
+        _tasks_start(
+            [],
+            task_id="parent_B",
+            name="tools",
+            input={
+                "tool_call": {
+                    "id": "call_2",
+                    "name": "task",
+                    "args": {"subagent_type": "researcher"},
+                }
+            },
+        )
+    )
+    mux.push(_tasks_start(["agent:parent_A"], task_id="t1", name="model"))
+    mux.push(_tasks_start(["agent:parent_B"], task_id="t2", name="model"))
+
+    payloads = _drain_lifecycle(mux)
+    by_ns = {tuple(p["namespace"]): p for p in payloads}
+    assert by_ns[("agent:parent_A",)]["metadata"] == {
+        "type": "tool_call",
+        "tool_call_id": "call_1",
+    }
+    assert by_ns[("agent:parent_B",)]["metadata"] == {
+        "type": "tool_call",
+        "tool_call_id": "call_2",
+    }
+
+
+def test_started_omits_metadata_for_structurally_triggered_subgraph() -> None:
+    """Subgraphs triggered without a recognizable tool-call envelope on
+    the parent's input (Send with custom payloads, plain nested
+    `graph.invoke`, etc.) don't get a `metadata` field on
+    `lifecycle.started`."""
+    mux = _build_lifecycle_mux()
+    mux.push(_tasks_start(["agent:abc123"], task_id="t1", name="tool"))
+
+    [payload] = _drain_lifecycle(mux)
+    assert "metadata" not in payload
 
 
 def test_started_dedup_on_repeat_namespace() -> None:
@@ -188,8 +409,12 @@ def test_completed_on_parent_task_result() -> None:
     mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
     mux.push(_tasks_result([], task_id="abc", name="agent"))
 
-    events = [p["event"] for p in _drain_lifecycle(mux)]
-    assert events == ["started", "completed"]
+    payloads = _drain_lifecycle(mux)
+    assert [p["event"] for p in payloads] == ["started", "completed"]
+    # `parent_task_id` is required on every event for the same subgraph
+    # so consumers can correlate `started` ↔ terminal without joining
+    # via `namespace`.
+    assert all(p["parent_task_id"] == "abc" for p in payloads)
 
 
 def test_failed_on_parent_task_result_with_error() -> None:
@@ -265,6 +490,54 @@ def test_fail_emits_failed_for_other_exceptions() -> None:
     assert payloads[1]["error"] == "boom"
 
 
+def test_parent_task_id_present_on_every_terminal_path() -> None:
+    """Every exit path that emits a terminal event (parent-result with
+    error / interrupts, finalize sweep, fail sweep) must carry
+    `parent_task_id` so consumers can correlate the terminal event
+    back to its `started` without falling back to namespace joins."""
+    # Path 1: parent-result with error.
+    mux = _build_lifecycle_mux()
+    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
+    mux.push(_tasks_result([], task_id="abc", name="agent", error="boom"))
+    [_, terminal] = _drain_lifecycle(mux)
+    assert terminal["event"] == "failed"
+    assert terminal["parent_task_id"] == "abc"
+
+    # Path 2: parent-result with interrupts.
+    mux2 = _build_lifecycle_mux()
+    mux2.push(_tasks_start(["agent:def"], task_id="t1", name="tool"))
+    mux2.push(
+        _tasks_result([], task_id="def", name="agent", interrupts=[{"value": "pause"}])
+    )
+    [_, terminal2] = _drain_lifecycle(mux2)
+    assert terminal2["event"] == "interrupted"
+    assert terminal2["parent_task_id"] == "def"
+
+    # Path 3: finalize sweep (no parent result arrived).
+    mux3 = _build_lifecycle_mux()
+    mux3.push(_tasks_start(["agent:ghi"], task_id="t1", name="tool"))
+    mux3.close()
+    [_, terminal3] = _drain_lifecycle(mux3)
+    assert terminal3["event"] == "completed"
+    assert terminal3["parent_task_id"] == "ghi"
+
+    # Path 4: fail sweep with GraphInterrupt.
+    mux4 = _build_lifecycle_mux()
+    mux4.push(_tasks_start(["agent:jkl"], task_id="t1", name="tool"))
+    mux4.fail(GraphInterrupt())
+    [_, terminal4] = _drain_lifecycle(mux4)
+    assert terminal4["event"] == "interrupted"
+    assert terminal4["parent_task_id"] == "jkl"
+
+    # Path 5: fail sweep with generic exception.
+    mux5 = _build_lifecycle_mux()
+    mux5.push(_tasks_start(["agent:mno"], task_id="t1", name="tool"))
+    mux5.fail(RuntimeError("kaboom"))
+    [_, terminal5] = _drain_lifecycle(mux5)
+    assert terminal5["event"] == "failed"
+    assert terminal5["parent_task_id"] == "mno"
+
+
 def test_unrelated_methods_pass_through() -> None:
     """Non-`tasks` events are not consumed and don't emit lifecycle."""
     mux = _build_lifecycle_mux()

libs/langgraph/tests/test_stream_subgraph_transformer.py

@@ -195,7 +195,7 @@ def test_handle_created_on_first_direct_child_task() -> None:
     [handle] = _drain_subgraphs(mux)
     assert handle.path == ("agent:abc",)
     assert handle.graph_name == "agent"
-    assert handle.trigger_call_id == "abc"
+    assert handle.parent_task_id == "abc"
     assert handle.status == "started"
     _child_mux(handle)  # mini-mux backed
 

libs/langgraph/uv.lock

@@ -1849,14 +1849,14 @@ dev = [
     { name = "pytest-watch" },
     { name = "ruff", specifier = "==0.15.12" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.23" },
+    { name = "ty", specifier = "==0.0.33" },
 ]
 lint = [
     { name = "codespell" },
     { name = "mypy", specifier = "==1.20.2" },
     { name = "ruff", specifier = "==0.15.12" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.23" },
+    { name = "ty", specifier = "==0.0.33" },
 ]
 test = [
     { name = "pytest" },

libs/prebuilt/uv.lock

@@ -618,14 +618,14 @@ dev = [
     { name = "pytest-watch" },
     { name = "ruff", specifier = "==0.15.12" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.23" },
+    { name = "ty", specifier = "==0.0.33" },
 ]
 lint = [
     { name = "codespell" },
     { name = "mypy", specifier = "==1.20.2" },
     { name = "ruff", specifier = "==0.15.12" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.23" },
+    { name = "ty", specifier = "==0.0.33" },
 ]
 test = [
     { name = "pytest" },

libs/sdk-py/langgraph_sdk/_async/client.py

@@ -110,7 +110,7 @@ def get_client(
     if url is None:
         url = "http://api"
         if os.environ.get("__LANGGRAPH_DEFER_LOOPBACK_TRANSPORT") == "true":
-            transport = get_asgi_transport()(app=None, root_path="/noauth")  # type: ignore[invalid-argument-type]
+            transport = get_asgi_transport()(app=None, root_path="/noauth")  # ty: ignore[invalid-argument-type]
             _registered_transports.append(transport)
         else:
             try:
@@ -122,7 +122,7 @@ def get_client(
                     "Failed to connect to in-process LangGraph server. Deferring configuration.",
                     exc_info=True,
                 )
-                transport = get_asgi_transport()(app=None, root_path="/noauth")  # type: ignore[invalid-argument-type]
+                transport = get_asgi_transport()(app=None, root_path="/noauth")  # ty: ignore[invalid-argument-type]
                 _registered_transports.append(transport)
 
     if transport is None:
@@ -131,7 +131,7 @@ def get_client(
         base_url=url,
         transport=transport,
         timeout=(
-            httpx.Timeout(timeout)  # type: ignore[arg-type]
+            httpx.Timeout(timeout)  # ty: ignore[invalid-argument-type]
             if timeout is not None
             else httpx.Timeout(connect=5, read=300, write=300, pool=5)
         ),

libs/sdk-py/langgraph_sdk/_async/runs.py

@@ -49,7 +49,7 @@ async def _wrap_stream_v2(
     async for part in raw:
         v2 = _sse_to_v2_dict(part.event, part.data)
         if v2 is not None:
-            yield v2
+            yield v2  # ty: ignore[invalid-yield]
 
 
 class RunsClient:

libs/sdk-py/langgraph_sdk/_shared/utilities.py

@@ -144,8 +144,9 @@ def _resolve_timezone(tz: str | tzinfo | ZoneInfo | None) -> str | None:
         return tz
     if isinstance(tz, tzinfo):
         # ZoneInfo objects have a .key attribute with the IANA name
-        if hasattr(tz, "key"):
-            return tz.key  # type: ignore[union-attr]
+        key = getattr(tz, "key", None)
+        if isinstance(key, str):
+            return key
         # Fall back to tzname for fixed-offset timezones like datetime.timezone.utc
         name = tz.tzname(None)
         if name is not None:
@@ -209,7 +210,7 @@ def configure_loopback_transports(app: Any) -> None:
 @functools.lru_cache(maxsize=1)
 def get_asgi_transport() -> type[httpx.ASGITransport]:
     try:
-        from langgraph_api import asgi_transport  # type: ignore[unresolved-import]
+        from langgraph_api import asgi_transport  # ty: ignore[unresolved-import]
 
         return asgi_transport.ASGITransport
     except ImportError:

libs/sdk-py/langgraph_sdk/_sync/client.py

@@ -77,7 +77,7 @@ def get_sync_client(
         base_url=url,
         transport=transport,
         timeout=(
-            httpx.Timeout(timeout)  # type: ignore[arg-type]
+            httpx.Timeout(timeout)  # ty: ignore[invalid-argument-type]
             if timeout is not None
             else httpx.Timeout(connect=5, read=300, write=300, pool=5)
         ),

libs/sdk-py/langgraph_sdk/_sync/runs.py

@@ -49,7 +49,7 @@ def _wrap_stream_v2_sync(
     for part in raw:
         v2 = _sse_to_v2_dict(part.event, part.data)
         if v2 is not None:
-            yield v2
+            yield v2  # ty: ignore[invalid-yield]
 
 
 class SyncRunsClient:

libs/sdk-py/langgraph_sdk/cache.py

@@ -16,10 +16,10 @@ T = TypeVar("T")
 CacheStatus = Literal["miss", "fresh", "stale", "expired"]
 
 try:
-    from langgraph_api.cache import (  # type: ignore[unresolved-import]
+    from langgraph_api.cache import (  # ty: ignore[unresolved-import]
         cache_get as _cache_get,
     )
-    from langgraph_api.cache import (  # type: ignore[unresolved-import]
+    from langgraph_api.cache import (  # ty: ignore[unresolved-import]
         cache_set as _cache_set,
     )
 except ImportError:
@@ -28,8 +28,8 @@ except ImportError:
 
 
 try:
-    from langgraph_api.cache import SWRResult  # type: ignore[unresolved-import]
-    from langgraph_api.cache import swr as _api_swr  # type: ignore[unresolved-import]
+    from langgraph_api.cache import SWRResult  # ty: ignore[unresolved-import]
+    from langgraph_api.cache import swr as _api_swr  # ty: ignore[unresolved-import]
 
 except ImportError:
     _api_swr = None
@@ -40,7 +40,10 @@ except ImportError:
         value: T
         status: CacheStatus
 
-        async def mutate(self, value: T = ...) -> T:  # type: ignore[assignment]
+        async def mutate(
+            self,
+            value: T = ...,  # ty: ignore[invalid-parameter-default]
+        ) -> T:  # ty: ignore[empty-body]
             """Update or revalidate the cached value."""
             ...
 

libs/sdk-py/langgraph_sdk/errors.py

@@ -37,7 +37,7 @@ class APIError(httpx.HTTPStatusError, LangGraphError):
             req = response_or_request
             response = None
 
-        httpx.HTTPStatusError.__init__(self, message, request=req, response=response)  # type: ignore[arg-type]
+        httpx.HTTPStatusError.__init__(self, message, request=req, response=response)  # ty: ignore[invalid-argument-type]
         LangGraphError.__init__(self, message)
 
         self.request = req

libs/sdk-py/langgraph_sdk/runtime.py

@@ -156,7 +156,7 @@ class _ExecutionRuntime(_ServerRuntimeBase[ContextT], Generic[ContextT]):
         This API is in beta and may change in future releases.
     """
 
-    context: ContextT = field(default=None)  # type: ignore[assignment]
+    context: ContextT = field(default=None)  # ty: ignore[invalid-assignment]
     """The graph run context, typed by the graph's `context_schema`.
 
     Only available during `threads.create_run`.

libs/sdk-py/langgraph_sdk/sse.py

@@ -55,7 +55,7 @@ class BytesLineDecoder:
             # Include any existing buffer in the first portion of the
             # splitlines result.
             self.buffer.extend(lines[0])
-            lines = cast(list[BytesLike], [self.buffer, *lines[1:]])
+            lines = [self.buffer, *lines[1:]]
             self.buffer = bytearray()
 
         if not trailing_newline:
@@ -69,7 +69,7 @@ class BytesLineDecoder:
         if not self.buffer and not self.trailing_cr:
             return []
 
-        lines = [self.buffer]
+        lines: list[BytesLike] = [self.buffer]
         self.buffer = bytearray()
         self.trailing_cr = False
         return lines
@@ -102,7 +102,7 @@ class SSEDecoder:
 
             sse = StreamPart(
                 event=self._event,
-                data=orjson.loads(self._data) if self._data else None,  # type: ignore[invalid-argument-type]
+                data=orjson.loads(self._data) if self._data else None,  # ty: ignore[invalid-argument-type]
                 id=self.last_event_id,
             )
 

libs/sdk-py/pyproject.toml

@@ -33,7 +33,7 @@ lint = [
     "ruff==0.15.12",
     "codespell",
     "mypy==1.20.2",
-    "ty==0.0.23",
+    "ty==0.0.33",
     "starlette",
 ]
 dev = [

libs/sdk-py/tests/test_client_stream.py

@@ -388,7 +388,7 @@ async def test_async_stream_v2_client_side_conversion() -> None:
             event="values", data={"messages": [{"role": "user", "content": "hi"}]}
         )
         yield StreamPart(event="updates|sub:abc", data={"node": {"out": 1}})
-        yield StreamPart(event="end", data=None)  # type: ignore[arg-type]
+        yield StreamPart(event="end", data=None)  # ty: ignore[invalid-argument-type]
 
     parts: list[StreamPartV2] = [part async for part in _wrap_stream_v2(mock_stream())]
     assert len(parts) == 3
@@ -420,7 +420,7 @@ def test_sync_stream_v2_client_side_conversion() -> None:
     def mock_stream() -> Any:
         yield StreamPart(event="metadata", data={"run_id": "r1"})
         yield StreamPart(event="values", data={"state": "full"})
-        yield StreamPart(event="end", data=None)  # type: ignore[arg-type]
+        yield StreamPart(event="end", data=None)  # ty: ignore[invalid-argument-type]
 
     parts: list[StreamPartV2] = list(_wrap_stream_v2_sync(mock_stream()))
     assert len(parts) == 2

libs/sdk-py/tests/test_encryption.py

@@ -67,6 +67,6 @@ class TestHandlerValidation:
 
         with pytest.raises(TypeError, match="must accept exactly 2 parameters"):
 
-            @encryption.encrypt.blob  # type: ignore[arg-type]
+            @encryption.encrypt.blob  # ty: ignore[invalid-argument-type]
             async def wrong_params(ctx):
                 return ctx

libs/sdk-py/uv.lock

@@ -533,14 +533,14 @@ dev = [
     { name = "pytest-watch" },
     { name = "ruff", specifier = "==0.15.12" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.23" },
+    { name = "ty", specifier = "==0.0.33" },
 ]
 lint = [
     { name = "codespell" },
     { name = "mypy", specifier = "==1.20.2" },
     { name = "ruff", specifier = "==0.15.12" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.23" },
+    { name = "ty", specifier = "==0.0.33" },
 ]
 test = [
     { name = "pytest" },
@@ -1275,26 +1275,26 @@ wheels = [
 
 [[package]]
 name = "ty"
-version = "0.0.23"
+version = "0.0.33"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/75/ba/d3c998ff4cf6b5d75b39356db55fe1b7caceecc522b9586174e6a5dee6f7/ty-0.0.23.tar.gz", hash = "sha256:5fb05db58f202af366f80ef70f806e48f5237807fe424ec787c9f289e3f3a4ef", size = 5341461, upload-time = "2026-03-13T12:34:23.125Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/84/44/9478c50c266826c1bf30d1692e589755bffa8f1c0a3eb7af8a346c255991/ty-0.0.33.tar.gz", hash = "sha256:46d63bda07403322cb6c28ccfdd5536be916e13df725c29f7ccd0a21f06bd9e8", size = 5559373, upload-time = "2026-04-28T10:45:13.18Z" }
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