feat(langgraph): dispatch stream_events(version='v3') on Pregel (#7677)

## Summary
- Bumps `langgraph` 1.2.0a1 → 1.2.0a3
- Bumps `langgraph-checkpoint` 4.1.0a1 → 4.1.0a3
- Bumps `langgraph-checkpoint-postgres` 3.1.0a1 → 3.1.0a3
- Bumps min `langgraph-checkpoint` constraint in `langgraph` to
`>=4.1.0a3`
- Refreshes uv locks across the workspace

(Note: `a2` was already cut from another branch.)

## Test plan
- [ ] CI passes

.github/workflows/_integration_test.yml

@@ -116,13 +116,13 @@ jobs:
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
           echo "Finished starting up langgraph-test-h"
           LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
-          if [ "$LANGGRAPH_VERSION" != "1.1.2" ]; then
-            echo "LANGGRAPH_VERSION != 1.1.2; $LANGGRAPH_VERSION"
+          if [ "$LANGGRAPH_VERSION" != "1.1.5" ]; then
+            echo "LANGGRAPH_VERSION != 1.1.5; $LANGGRAPH_VERSION"
             exit 1
           fi
           LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
-          if [ "$LANGCHAIN_OPENAI_VERSION" != "1.0.1" ]; then
-            echo "LANGCHAIN_OPENAI_VERSION != 1.0.1; $LANGCHAIN_OPENAI_VERSION"
+          if [ "$LANGCHAIN_OPENAI_VERSION" != "1.1.14" ]; then
+            echo "LANGCHAIN_OPENAI_VERSION != 1.1.14; $LANGCHAIN_OPENAI_VERSION"
             exit 1
           fi
           LANGCHAIN_ANTHROPIC_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-anthropic'); print(v);")
@@ -136,3 +136,33 @@ jobs:
         working-directory: libs/cli/examples/graph_prerelease_reqs_fail
         run: |
           langgraph build -t langgraph-test-i || [ $? -eq 1 ]
+
+      - name: Build uv simple service
+        if: ${{ (steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch') &&matrix.example.name == 'A' }}
+        working-directory: libs/cli/uv-examples/simple
+        run: |
+          langgraph build -t langgraph-test-uv-simple
+      - name: Test uv simple service
+        if: ${{ (steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch') &&matrix.example.name == 'A' && env.HAS_LANGSMITH_API_KEY == 'true' }}
+        working-directory: libs/cli/uv-examples/simple
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
+        run: |
+          cp .env.example .env
+          echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-uv-simple
+
+      - name: Build uv monorepo service
+        if: ${{ (steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch') &&matrix.example.name == 'A' }}
+        working-directory: libs/cli/uv-examples/monorepo/apps/agent
+        run: |
+          langgraph build -t langgraph-test-uv-monorepo
+      - name: Test uv monorepo service
+        if: ${{ (steps.changed-files.outputs.all || github.event_name == 'workflow_dispatch') &&matrix.example.name == 'A' && env.HAS_LANGSMITH_API_KEY == 'true' }}
+        working-directory: libs/cli/uv-examples/monorepo/apps/agent
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
+        run: |
+          cp .env.example .env
+          echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env
+          timeout 60 python ../../../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-uv-monorepo

.gitignore

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

README.md

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

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

@@ -339,37 +339,6 @@ async def test_list_metadata_custom_keys(
     assert results[0].metadata["run_id"] == "run-abc"
 
 
-async def test_list_global_search(
-    saver: BaseCheckpointSaver,
-) -> None:
-    """alist(None, filter=...) searches across all threads."""
-    tid1, tid2 = str(uuid4()), str(uuid4())
-
-    # Use a unique marker so we don't collide with other tests' data
-    marker = str(uuid4())
-
-    cfg1 = generate_config(tid1)
-    cp1 = generate_checkpoint()
-    await saver.aput(cfg1, cp1, generate_metadata(source="input", marker=marker), {})
-
-    cfg2 = generate_config(tid2)
-    cp2 = generate_checkpoint()
-    await saver.aput(cfg2, cp2, generate_metadata(source="loop", marker=marker), {})
-
-    # Search across all threads with filter
-    results = []
-    async for tup in saver.alist(None, filter={"source": "input", "marker": marker}):
-        results.append(tup)
-    assert len(results) == 1
-    assert results[0].config["configurable"]["thread_id"] == tid1
-
-    # Search with marker only — should find both
-    results = []
-    async for tup in saver.alist(None, filter={"marker": marker}):
-        results.append(tup)
-    assert len(results) == 2
-
-
 ALL_LIST_TESTS = [
     test_list_all,
     test_list_by_thread,
@@ -380,7 +349,6 @@ ALL_LIST_TESTS = [
     test_list_metadata_filter_multiple_keys,
     test_list_metadata_filter_no_match,
     test_list_metadata_custom_keys,
-    test_list_global_search,
     test_list_before,
     test_list_limit,
     test_list_limit_plus_before,

libs/checkpoint-conformance/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-conformance"
-version = "0.0.1"
+version = "0.0.2"
 description = "Conformance test suite for LangGraph checkpointer implementations."
 authors = [{name = "William FH", email = "13333726+hinthornw@users.noreply.github.com"}]
 requires-python = ">=3.10"

libs/checkpoint-conformance/uv.lock

@@ -231,7 +231,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.22"
+version = "1.2.28"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -243,9 +243,9 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/b1/a3/c4cd6827a1df46c821e7214b7f7b7a28b189e6c9b84ef15c6d629c5e3179/langchain_core-1.2.22.tar.gz", hash = "sha256:8d8f726d03d3652d403da915126626bb6250747e8ba406537d849e68b9f5d058", size = 842487, upload-time = "2026-03-24T18:48:44.9Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c7/a6/2ffacf0f1a3788f250e75d0b52a24896c413be11be3a6d42bcdf46fbea48/langchain_core-1.2.22-py3-none-any.whl", hash = "sha256:7e30d586b75918e828833b9ec1efc25465723566845dd652c277baf751e9c04b", size = 506829, upload-time = "2026-03-24T18:48:43.286Z" },
+    { url = "https://files.pythonhosted.org/packages/a8/92/32f785f077c7e898da97064f113c73fbd9ad55d1e2169cf3a391b183dedb/langchain_core-1.2.28-py3-none-any.whl", hash = "sha256:80764232581eaf8057bcefa71dbf8adc1f6a28d257ebd8b95ba9b8b452e8c6ac", size = 508727, upload-time = "2026-04-08T18:19:32.823Z" },
 ]
 
 [[package]]
@@ -263,7 +263,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint-conformance"
-version = "0.0.1"
+version = "0.0.2"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -306,7 +306,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.7.3"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -319,9 +319,9 @@ dependencies = [
     { name = "xxhash" },
     { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/8d/bc/8172fefad4f2da888a6d564a27d1fb7d4dbf3c640899c2b40c46235cbe98/langsmith-0.7.3.tar.gz", hash = "sha256:0223b97021af62d2cf53c8a378a27bd22e90a7327e45b353e0069ae60d5d6f9e", size = 988575, upload-time = "2026-02-13T23:25:32.916Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f4/9d/5a68b6b5e313ffabbb9725d18a71edb48177fd6d3ad329c07801d2a8e862/langsmith-0.7.3-py3-none-any.whl", hash = "sha256:03659bf9274e6efcead361c9c31a7849ea565ae0d6c0d73e1d8b239029eff3be", size = 325718, upload-time = "2026-02-13T23:25:31.52Z" },
+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
 ]
 
 [[package]]
@@ -623,7 +623,7 @@ wheels = [
 
 [[package]]
 name = "pytest"
-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -634,9 +634,9 @@ dependencies = [
     { name = "pygments" },
     { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d1/db/7ef3487e0fb0049ddb5ce41d3a49c235bf9ad299b6a25d5780a89f19230f/pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11", size = 1568901, upload-time = "2025-12-06T21:30:51.014Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b", size = 374801, upload-time = "2025-12-06T21:30:49.154Z" },
+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
 ]
 
 [[package]]

libs/checkpoint-postgres/README.md

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

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

@@ -4,26 +4,35 @@ import threading
 from collections import defaultdict
 from collections.abc import Iterator, Sequence
 from contextlib import contextmanager
-from typing import Any
+from typing import Any, cast
 
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
+    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
+    _ChannelWritesHistory,
     get_checkpoint_id,
     get_serializable_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.base import SerializerProtocol
+from langgraph.checkpoint.serde.types import _DeltaSnapshot
 from psycopg import Capabilities, Connection, Cursor, Pipeline
 from psycopg.rows import DictRow, dict_row
 from psycopg.types.json import Jsonb
 from psycopg_pool import ConnectionPool
 
 from langgraph.checkpoint.postgres import _internal
-from langgraph.checkpoint.postgres.base import BasePostgresSaver
+from langgraph.checkpoint.postgres.base import (
+    SELECT_DELTA_STAGE1_SQL,
+    SELECT_DELTA_STAGE2_SQL,
+    BasePostgresSaver,
+    _DeltaStage1Row,
+    _DeltaStage2Row,
+)
 from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
 
 Conn = _internal.Conn  # For backward compatibility
@@ -302,7 +311,12 @@ class PostgresSaver(BasePostgresSaver):
         # others are stored in blobs table
         blob_values = {}
         for k, v in checkpoint["channel_values"].items():
-            if v is None or isinstance(v, (str, int, float, bool)):
+            if v is DELTA_SENTINEL:
+                copy["channel_values"].pop(k)
+            elif isinstance(v, _DeltaSnapshot):
+                blob_values[k] = copy["channel_values"].pop(k)
+                copy["channel_values"][k] = True
+            elif v is None or isinstance(v, (str, int, float, bool)):
                 pass
             else:
                 blob_values[k] = copy["channel_values"].pop(k)
@@ -430,6 +444,56 @@ class PostgresSaver(BasePostgresSaver):
                 with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
+    def _get_channel_writes_history(
+        self, config: RunnableConfig, channel: str
+    ) -> _ChannelWritesHistory:
+        """Fast-path override of `BaseCheckpointSaver._get_channel_writes_history`.
+
+        Two-stage query: stage 1 scans checkpoint metadata to walk the parent
+        chain and locate the nearest snapshot; stage 2 fetches only the
+        chain-limited writes and single seed blob.
+        """
+        thread_id = config["configurable"]["thread_id"]
+        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+        checkpoint_id = get_checkpoint_id(config)
+        if checkpoint_id is None:
+            target = self.get_tuple(config)
+            if target is None:
+                return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
+            checkpoint_id = target.config["configurable"]["checkpoint_id"]
+
+        with self._cursor() as cur:
+            cur.execute(
+                SELECT_DELTA_STAGE1_SQL,
+                (channel, channel, thread_id, checkpoint_ns),
+            )
+            stage1_rows = cur.fetchall()
+        chain_cids, seed_version = self._walk_stage1(
+            cast("list[_DeltaStage1Row]", stage1_rows), checkpoint_id
+        )
+        seed_versions = [seed_version] if seed_version else []
+        with self._cursor() as cur:
+            cur.execute(
+                SELECT_DELTA_STAGE2_SQL,
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    channel,
+                    chain_cids,
+                    thread_id,
+                    checkpoint_ns,
+                    channel,
+                    seed_versions,
+                ),
+            )
+            stage2_rows = cur.fetchall()
+        return self._build_delta_channel_writes_history(
+            channel=channel,
+            chain_cids=chain_cids,
+            seed_version=seed_version,
+            stage2_rows=cast("list[_DeltaStage2Row]", stage2_rows),
+        )
+
     def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
         Convert a database row into a CheckpointTuple object.

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

@@ -4,26 +4,35 @@ import asyncio
 from collections import defaultdict
 from collections.abc import AsyncIterator, Iterator, Sequence
 from contextlib import asynccontextmanager
-from typing import Any
+from typing import Any, cast
 
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
+    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
+    _ChannelWritesHistory,
     get_checkpoint_id,
     get_serializable_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.base import SerializerProtocol
+from langgraph.checkpoint.serde.types import _DeltaSnapshot
 from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
 from psycopg.rows import DictRow, dict_row
 from psycopg.types.json import Jsonb
 from psycopg_pool import AsyncConnectionPool
 
 from langgraph.checkpoint.postgres import _ainternal
-from langgraph.checkpoint.postgres.base import BasePostgresSaver
+from langgraph.checkpoint.postgres.base import (
+    SELECT_DELTA_STAGE1_SQL,
+    SELECT_DELTA_STAGE2_SQL,
+    BasePostgresSaver,
+    _DeltaStage1Row,
+    _DeltaStage2Row,
+)
 from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
 
 Conn = _ainternal.Conn  # For backward compatibility
@@ -261,7 +270,12 @@ class AsyncPostgresSaver(BasePostgresSaver):
         # others are stored in blobs table
         blob_values = {}
         for k, v in checkpoint["channel_values"].items():
-            if v is None or isinstance(v, (str, int, float, bool)):
+            if v is DELTA_SENTINEL:
+                copy["channel_values"].pop(k)
+            elif isinstance(v, _DeltaSnapshot):
+                blob_values[k] = copy["channel_values"].pop(k)
+                copy["channel_values"][k] = True
+            elif v is None or isinstance(v, (str, int, float, bool)):
                 pass
             else:
                 blob_values[k] = copy["channel_values"].pop(k)
@@ -391,6 +405,56 @@ class AsyncPostgresSaver(BasePostgresSaver):
                 async with conn.cursor(binary=True, row_factory=dict_row) as cur:
                     yield cur
 
+    async def _aget_channel_writes_history(
+        self, config: RunnableConfig, channel: str
+    ) -> _ChannelWritesHistory:
+        """Fast-path override of `BaseCheckpointSaver._aget_channel_writes_history`.
+
+        Two-stage query: stage 1 scans checkpoint metadata to walk the parent
+        chain and locate the nearest snapshot; stage 2 fetches only the
+        chain-limited writes and single seed blob.
+        """
+        thread_id = config["configurable"]["thread_id"]
+        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+        checkpoint_id = get_checkpoint_id(config)
+        if checkpoint_id is None:
+            target = await self.aget_tuple(config)
+            if target is None:
+                return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
+            checkpoint_id = target.config["configurable"]["checkpoint_id"]
+
+        async with self._cursor() as cur:
+            await cur.execute(
+                SELECT_DELTA_STAGE1_SQL,
+                (channel, channel, thread_id, checkpoint_ns),
+            )
+            stage1_rows = await cur.fetchall()
+        chain_cids, seed_version = self._walk_stage1(
+            cast("list[_DeltaStage1Row]", stage1_rows), checkpoint_id
+        )
+        seed_versions = [seed_version] if seed_version else []
+        async with self._cursor() as cur:
+            await cur.execute(
+                SELECT_DELTA_STAGE2_SQL,
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    channel,
+                    chain_cids,
+                    thread_id,
+                    checkpoint_ns,
+                    channel,
+                    seed_versions,
+                ),
+            )
+            stage2_rows = await cur.fetchall()
+        return self._build_delta_channel_writes_history(
+            channel=channel,
+            chain_cids=chain_cids,
+            seed_version=seed_version,
+            stage2_rows=cast("list[_DeltaStage2Row]", stage2_rows),
+        )
+
     async def _load_checkpoint_tuple(self, value: DictRow) -> CheckpointTuple:
         """
         Convert a database row into a CheckpointTuple object.

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

@@ -4,13 +4,16 @@ import random
 import warnings
 from collections.abc import Sequence
 from importlib.metadata import version as get_version
-from typing import Any, cast
+from typing import Any, TypedDict, cast
 
 from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
+    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
     ChannelVersions,
+    PendingWrite,
+    _ChannelWritesHistory,
     get_checkpoint_id,
 )
 from langgraph.checkpoint.serde.types import TASKS
@@ -153,6 +156,62 @@ INSERT_CHECKPOINT_WRITES_SQL = """
 """
 
 
+class _DeltaStage2Row(TypedDict, total=False):
+    """One row from `SELECT_DELTA_STAGE2_SQL` (a UNION ALL of writes and blobs)."""
+
+    _kind: str  # "w" or "b"
+    checkpoint_id: str | None  # "w" rows only
+    type: str | None
+    blob: bytes | None
+    task_id: str | None  # "w" rows only
+    idx: int | None  # "w" rows only
+    version: str | None  # "b" rows only
+
+
+# Two-stage DeltaChannel reconstruction.  Stage 1 scans checkpoint
+# metadata (no blob bytes) to walk the parent chain and locate the
+# nearest snapshot marker.  Stage 2 fetches only the chain-limited
+# writes and the single seed snapshot blob.
+#
+# Parameter order:
+#   stage1: (channel, channel, thread_id, checkpoint_ns)
+#   stage2: (thread_id, checkpoint_ns, channel, chain_cids[],
+#            thread_id, checkpoint_ns, channel, seed_versions[])
+
+SELECT_DELTA_STAGE1_SQL = """
+    SELECT checkpoint_id,
+           parent_checkpoint_id,
+           checkpoint -> 'channel_versions' ->> %s AS ver,
+           (checkpoint -> 'channel_values' -> %s) IS NOT NULL AS has_snapshot
+    FROM checkpoints
+    WHERE thread_id = %s AND checkpoint_ns = %s
+"""
+
+SELECT_DELTA_STAGE2_SQL = """
+    SELECT 'w'::text AS _kind,
+           checkpoint_id,
+           type, blob, task_id, idx, NULL::text AS version
+    FROM checkpoint_writes
+    WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s
+      AND checkpoint_id = ANY(%s)
+    UNION ALL
+    SELECT 'b', NULL,
+           type, blob, NULL, NULL, version
+    FROM checkpoint_blobs
+    WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s
+      AND version = ANY(%s)
+"""
+
+
+class _DeltaStage1Row(TypedDict):
+    """One row from `SELECT_DELTA_STAGE1_SQL`."""
+
+    checkpoint_id: str
+    parent_checkpoint_id: str | None
+    ver: str | None
+    has_snapshot: bool
+
+
 class BasePostgresSaver(BaseCheckpointSaver[str]):
     SELECT_SQL = SELECT_SQL
     SELECT_PENDING_SENDS_SQL = SELECT_PENDING_SENDS_SQL
@@ -195,6 +254,88 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
             if t.decode() != "empty"
         }
 
+    @staticmethod
+    def _walk_stage1(
+        stage1_rows: Sequence[_DeltaStage1Row],
+        target_id: str,
+    ) -> tuple[list[str], str | None]:
+        """Walk the parent chain from stage 1 metadata rows.
+
+        Returns (chain_cids, seed_version):
+          chain_cids: ancestor checkpoint IDs from target's parent down to
+                      the seed (or root), in newest-first order.
+          seed_version: the channel blob version at the nearest ancestor
+                        with has_snapshot=True, or None if pure delta.
+        """
+        parent_of: dict[str, str | None] = {}
+        ver_of: dict[str, str | None] = {}
+        snapshot_of: dict[str, bool] = {}
+        for r in stage1_rows:
+            cid = r["checkpoint_id"]
+            parent_of[cid] = r["parent_checkpoint_id"]
+            ver_of[cid] = r["ver"]
+            snapshot_of[cid] = r["has_snapshot"]
+
+        chain_cids: list[str] = []
+        seed_version: str | None = None
+        cur_cid: str | None = parent_of.get(target_id)
+        while cur_cid is not None:
+            chain_cids.append(cur_cid)
+            if snapshot_of.get(cur_cid, False):
+                seed_version = ver_of.get(cur_cid)
+                break
+            cur_cid = parent_of.get(cur_cid)
+        return chain_cids, seed_version
+
+    def _build_delta_channel_writes_history(
+        self,
+        *,
+        channel: str,
+        chain_cids: list[str],
+        seed_version: str | None,
+        stage2_rows: Sequence[_DeltaStage2Row],
+    ) -> _ChannelWritesHistory:
+        """Reconstruct delta channel history from two-stage query results.
+
+        chain_cids are in newest-first order (target's parent first).
+        stage2_rows contain only writes for chain_cids and the single
+        seed blob at seed_version.
+        """
+        writes_by_cid: dict[str, list[tuple[str, bytes, str, int]]] = {}
+        seed_blob: tuple[str, bytes] | None = None
+
+        for r in stage2_rows:
+            kind = r["_kind"]
+            if kind == "w":
+                cid = cast(str, r["checkpoint_id"])
+                writes_by_cid.setdefault(cid, []).append(
+                    cast(
+                        "tuple[str, bytes, str, int]",
+                        (r["type"], r["blob"], r["task_id"], r["idx"]),
+                    )
+                )
+            else:  # kind == "b"
+                seed_blob = cast("tuple[str, bytes]", (r["type"], r["blob"]))
+
+        for ws in writes_by_cid.values():
+            ws.sort(key=lambda w: (w[2], w[3]), reverse=True)
+
+        if not chain_cids:
+            return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
+
+        collected: list[PendingWrite] = []
+        for cid in chain_cids:
+            for type_tag, write_blob, task_id, _idx in writes_by_cid.get(cid, []):
+                val = self.serde.loads_typed((type_tag, write_blob))
+                collected.append((task_id, channel, val))
+
+        seed: Any = DELTA_SENTINEL
+        if seed_blob is not None and seed_blob[0] != "empty":
+            seed = self.serde.loads_typed(seed_blob)
+
+        collected.reverse()
+        return _ChannelWritesHistory(seed=seed, writes=collected)
+
     def _dump_blobs(
         self,
         thread_id: str,

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.5"
+version = "3.1.0a3"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-  "langgraph-checkpoint>=2.1.2,<5.0.0",
+  "langgraph-checkpoint>=4.1.0a3,<5.0.0",
   "orjson>=3.11.5",
   "psycopg>=3.2.0",
   "psycopg-pool>=3.2.0",
@@ -20,7 +20,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres"
-Twitter = "https://x.com/LangChain"
+Twitter = "https://x.com/langchain_oss"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint-postgres/tests/test_async.py

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

libs/checkpoint-postgres/uv.lock

@@ -240,7 +240,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.22"
+version = "1.2.28"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -252,14 +252,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/b1/a3/c4cd6827a1df46c821e7214b7f7b7a28b189e6c9b84ef15c6d629c5e3179/langchain_core-1.2.22.tar.gz", hash = "sha256:8d8f726d03d3652d403da915126626bb6250747e8ba406537d849e68b9f5d058", size = 842487, upload-time = "2026-03-24T18:48:44.9Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/a8/92/32f785f077c7e898da97064f113c73fbd9ad55d1e2169cf3a391b183dedb/langchain_core-1.2.28-py3-none-any.whl", hash = "sha256:80764232581eaf8057bcefa71dbf8adc1f6a28d257ebd8b95ba9b8b452e8c6ac", size = 508727, upload-time = "2026-04-08T18:19:32.823Z" },
 ]
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.1.0a3"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -307,7 +307,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.5"
+version = "3.1.0a3"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -382,7 +382,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.6.4"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -392,11 +392,12 @@ dependencies = [
     { name = "requests" },
     { name = "requests-toolbelt" },
     { name = "uuid-utils" },
+    { name = "xxhash" },
     { name = "zstandard" },
 ]
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 [[package]]
@@ -950,7 +951,7 @@ wheels = [
 
 [[package]]
 name = "pytest"
-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -961,9 +962,9 @@ dependencies = [
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 version = "0.25.0"

libs/checkpoint-sqlite/README.md

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

libs/checkpoint-sqlite/pyproject.toml

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

libs/checkpoint-sqlite/uv.lock

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-version = "4.0.1"
+version = "4.1.0a3"
 source = { editable = "../checkpoint" }
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 name = "zstandard"
 version = "0.25.0"

libs/checkpoint/README.md

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

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

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

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

@@ -14,16 +14,20 @@ from typing import Any
 from langchain_core.runnables import RunnableConfig
 
 from langgraph.checkpoint.base import (
+    DELTA_SENTINEL,
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
     CheckpointTuple,
+    PendingWrite,
     SerializerProtocol,
+    _ChannelWritesHistory,
     get_checkpoint_id,
     get_checkpoint_metadata,
 )
+from langgraph.checkpoint.serde.types import _DeltaSnapshot
 
 logger = logging.getLogger(__name__)
 
@@ -121,16 +125,114 @@ class InMemorySaver(
         return self.stack.__exit__(__exc_type, __exc_value, __traceback)
 
     def _load_blobs(
-        self, thread_id: str, checkpoint_ns: str, versions: ChannelVersions
+        self,
+        thread_id: str,
+        checkpoint_ns: str,
+        versions: ChannelVersions,
     ) -> dict[str, Any]:
-        channel_values: dict[str, Any] = {}
-        for k, v in versions.items():
-            kk = (thread_id, checkpoint_ns, k, v)
-            if kk in self.blobs:
-                vv = self.blobs[kk]
-                if vv[0] != "empty":
-                    channel_values[k] = self.serde.loads_typed(vv)
-        return channel_values
+        result: dict[str, Any] = {}
+        for k, ver in versions.items():
+            kk = (thread_id, checkpoint_ns, k, ver)
+            if kk not in self.blobs:
+                continue
+            vv = self.blobs[kk]
+            if vv[0] == "empty":
+                continue
+            result[k] = self.serde.loads_typed(vv)
+        return result
+
+    def _get_channel_writes_history(
+        self, config: RunnableConfig, channel: str
+    ) -> _ChannelWritesHistory:
+        thread_id = config["configurable"]["thread_id"]
+        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+        checkpoint_id = config["configurable"].get("checkpoint_id", "")
+        ns_storage = self.storage.get(thread_id, {}).get(checkpoint_ns, {})
+        # Walk the parent chain newest→oldest. Skip the target itself —
+        # writes stored AT `checkpoint_id` are pending for the next step
+        # (pregel applies them via `apply_writes`; they aren't part of the
+        # snapshot value AT `checkpoint_id`).
+        chain: list[str] = []
+        target_entry = ns_storage.get(checkpoint_id)
+        current: str | None = target_entry[2] if target_entry is not None else None
+        while current is not None:
+            entry = ns_storage.get(current)
+            if entry is None:
+                break
+            chain.append(current)
+            _, _, parent = entry
+            current = parent
+        # Scan newest→oldest. A pre-delta blob on an ancestor terminates the
+        # walk and is bound as `seed`; without this, a thread migrated from
+        # pre-delta storage would replay ancestor writes all the way to the
+        # root AND miss any value that lived only in the old blob (e.g. from
+        # `update_state`).
+        #
+        # At each ancestor, check the blob BEFORE processing its pending
+        # writes: a pre-delta blob represents the state AT that ancestor,
+        # which already subsumes any writes stored under it. Processing
+        # those writes first would fold them into the reconstructed value
+        # twice (once via the blob, once via replay).
+        collected: list[PendingWrite] = []  # newest first
+        for cp_id in chain:  # newest → oldest
+            entry = ns_storage.get(cp_id)
+            if entry is not None:
+                ckpt = self.serde.loads_typed(entry[0])
+                ver = ckpt.get("channel_versions", {}).get(channel)
+                if ver is not None:
+                    blob_entry = self.blobs.get(
+                        (thread_id, checkpoint_ns, channel, ver)
+                    )
+                    if blob_entry is not None and blob_entry[0] != "empty":
+                        blob_value = self.serde.loads_typed(blob_entry)
+                        if blob_value is not DELTA_SENTINEL:
+                            if isinstance(blob_value, _DeltaSnapshot):
+                                # Step-based snapshot: the blob is state AT this
+                                # ancestor, but the ancestor's pending_writes
+                                # encode the NEXT step's transition and are NOT
+                                # subsumed by the snapshot — collect them first.
+                                step_writes = self.writes.get(
+                                    (thread_id, checkpoint_ns, cp_id), {}
+                                )
+                                for (_task_id, _idx), (
+                                    tid,
+                                    ch,
+                                    serialized,
+                                    _,
+                                ) in sorted(step_writes.items(), reverse=True):
+                                    if ch != channel:
+                                        continue
+                                    collected.append(
+                                        (tid, ch, self.serde.loads_typed(serialized))
+                                    )
+                                collected.reverse()
+                                return _ChannelWritesHistory(
+                                    seed=blob_value, writes=collected
+                                )
+                            # Pre-delta blob: state AT this ancestor already
+                            # subsumes its pending_writes — skip them.
+                            collected.reverse()
+                            return _ChannelWritesHistory(
+                                seed=blob_value, writes=collected
+                            )
+
+            step_writes = self.writes.get((thread_id, checkpoint_ns, cp_id), {})
+            # Within a superstep, sorted by (task_id, idx) = oldest → newest;
+            # reverse for newest-first scan.
+            for (_task_id, _idx), (tid, ch, serialized, _) in sorted(
+                step_writes.items(), reverse=True
+            ):
+                if ch != channel:
+                    continue
+                val = self.serde.loads_typed(serialized)
+                collected.append((tid, ch, val))
+        collected.reverse()
+        return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=collected)
+
+    async def _aget_channel_writes_history(
+        self, config: RunnableConfig, channel: str
+    ) -> _ChannelWritesHistory:
+        return self._get_channel_writes_history(config, channel)
 
     def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
         """Get a checkpoint tuple from the in-memory storage.
@@ -350,7 +452,9 @@ class InMemorySaver(
         values: dict[str, Any] = c.pop("channel_values")  # type: ignore[misc]
         for k, v in new_versions.items():
             self.blobs[(thread_id, checkpoint_ns, k, v)] = (
-                self.serde.dumps_typed(values[k]) if k in values else ("empty", b"")
+                self.serde.dumps_typed(values[k])
+                if k in values and values[k] is not DELTA_SENTINEL
+                else ("empty", b"")
             )
         self.storage[thread_id][checkpoint_ns].update(
             {

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

@@ -1,3 +1,10 @@
+"""Msgpack deserialization safety controls.
+
+Set ``LANGGRAPH_STRICT_MSGPACK=true`` to restrict checkpoint deserialization
+to the types listed in ``SAFE_MSGPACK_TYPES``.  Without this, any Python
+callable stored in checkpoint data will be imported and executed on load.
+"""
+
 import os
 from collections.abc import Iterable
 from typing import cast
@@ -66,6 +73,7 @@ SAFE_MSGPACK_TYPES: frozenset[tuple[str, ...]] = frozenset(
         ("langchain_core.documents.base", "Document"),
         # langgraph
         ("langgraph.types", "Send"),
+        ("langgraph.types", "TimeoutPolicy"),
         ("langgraph.types", "Interrupt"),
         ("langgraph.types", "Command"),
         ("langgraph.types", "StateSnapshot"),

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

@@ -33,19 +33,51 @@ from langchain_core.load.load import Reviver
 from langgraph.checkpoint.serde import _msgpack as _lg_msgpack
 from langgraph.checkpoint.serde.base import SerializerProtocol
 from langgraph.checkpoint.serde.event_hooks import emit_serde_event
-from langgraph.checkpoint.serde.types import SendProtocol
+from langgraph.checkpoint.serde.types import (
+    SendProtocol,
+    _DeltaSnapshot,
+)
 from langgraph.store.base import Item
 
 if TYPE_CHECKING:
     from langgraph.checkpoint.serde._msgpack import (
         AllowedMsgpackModules,
     )
-    from langgraph.checkpoint.serde.types import SendProtocol
 
 LC_REVIVER = Reviver()
 EMPTY_BYTES = b""
 logger = logging.getLogger(__name__)
 
+# Dedup log warnings across process lifetime; cap bounds state if types are
+# dynamically generated (also acts as a circuit breaker on warning volume).
+# Dedup is best-effort: racing threads may each emit once for the same key,
+# and warnings are silently dropped once _MAX_WARNED_TYPES is reached.
+_MAX_WARNED_TYPES = 1000
+_warned_unregistered_types: set[tuple[str, str]] = set()
+_warned_blocked_types: set[tuple[str, str]] = set()
+
+
+def _is_safe_json_type(id_list: list[str]) -> bool:
+    """Return True if an lc=2 id refers to a type in SAFE_MSGPACK_TYPES.
+
+    Safe types bypass the ``allowed_json_modules`` gate so that old "json" format
+    checkpoints (written before the msgpack migration) can be resumed without
+    requiring users to configure an explicit allowlist.
+    """
+    if len(id_list) < 2:
+        return False
+    module_name = ".".join(id_list[:-1])
+    return (module_name, id_list[-1]) in _lg_msgpack.SAFE_MSGPACK_TYPES
+
+
+def _warn_once(
+    seen: set[tuple[str, str]], key: tuple[str, str], msg: str, *args: object
+) -> None:
+    if key in seen or len(seen) >= _MAX_WARNED_TYPES:
+        return
+    seen.add(key)
+    logger.warning(msg, *args)
+
 
 class JsonPlusSerializer(SerializerProtocol):
     """Serializer that uses ormsgpack, with optional fallbacks.
@@ -56,6 +88,10 @@ class JsonPlusSerializer(SerializerProtocol):
         class and called within the Pregel loop. It should not be used on untrusted
         python objects. If an attacker can write directly to your checkpoint database,
         they may be able to trigger code execution when data is deserialized.
+
+        Set the environment variable ``LANGGRAPH_STRICT_MSGPACK=true`` to restrict
+        deserialization to a built-in allowlist of safe types.  You can also pass
+        an explicit ``allowed_msgpack_modules`` to the constructor.
     """
 
     def __init__(
@@ -70,8 +106,11 @@ class JsonPlusSerializer(SerializerProtocol):
     ) -> None:
         if allowed_msgpack_modules is _lg_msgpack._SENTINEL:
             if _lg_msgpack.STRICT_MSGPACK_ENABLED:
+                # Strict: only SAFE_MSGPACK_TYPES are allowed.
                 allowed_msgpack_modules = None
             else:
+                # Permissive (default): all types allowed with a warning.
+                # Set LANGGRAPH_STRICT_MSGPACK=true to lock this down.
                 allowed_msgpack_modules = True
         self.pickle_fallback = pickle_fallback
         self._allowed_json_modules: set[tuple[str, ...]] | Literal[True] | None = (
@@ -140,19 +179,23 @@ class JsonPlusSerializer(SerializerProtocol):
         return out
 
     def _reviver(self, value: dict[str, Any]) -> Any:
-        if self._allowed_json_modules and (
+        if (
             value.get("lc", None) == 2
             and value.get("type", None) == "constructor"
             and value.get("id", None) is not None
         ):
-            try:
-                return self._revive_lc2(value)
-            except InvalidModuleError as e:
-                logger.warning(
-                    "Object %s is not in the deserialization allowlist.\n%s",
-                    value["id"],
-                    e.message,
-                )
+            id_list = value["id"]
+            is_safe = _is_safe_json_type(id_list)
+            if self._allowed_json_modules or is_safe:
+                try:
+                    return self._revive_lc2(value)
+                except InvalidModuleError as e:
+                    if not is_safe:
+                        logger.warning(
+                            "Object %s is not in the deserialization allowlist.\n%s",
+                            value["id"],
+                            e.message,
+                        )
 
         return LC_REVIVER(value)
 
@@ -200,6 +243,13 @@ class JsonPlusSerializer(SerializerProtocol):
             method_display = "<init>"
 
         dotted = ".".join(needed)
+        # Safe types (the same set already allowed for msgpack deserialization) are
+        # permitted without an explicit allowlist — they are known-safe LangGraph and
+        # LangChain types.  This restores backwards-compat for old "json" checkpoints
+        # that pre-date the msgpack migration without reopening the broader security gate.
+        if _is_safe_json_type(list(needed)):
+            return
+
         if not self._allowed_json_modules:
             raise InvalidModuleError(
                 f"Refused to deserialize JSON constructor: {dotted} (method: {method_display}). "
@@ -269,10 +319,13 @@ EXT_METHOD_SINGLE_ARG = 3
 EXT_PYDANTIC_V1 = 4
 EXT_PYDANTIC_V2 = 5
 EXT_NUMPY_ARRAY = 6
+EXT_DELTA_SNAPSHOT = 7
 
 
 def _msgpack_default(obj: Any) -> str | ormsgpack.Ext:
-    if hasattr(obj, "model_dump") and callable(obj.model_dump):  # pydantic v2
+    if isinstance(obj, _DeltaSnapshot):
+        return ormsgpack.Ext(EXT_DELTA_SNAPSHOT, _msgpack_enc(obj.value))
+    elif hasattr(obj, "model_dump") and callable(obj.model_dump):  # pydantic v2
         return ormsgpack.Ext(
             EXT_PYDANTIC_V2,
             _msgpack_enc(
@@ -444,10 +497,13 @@ def _msgpack_default(obj: Any) -> str | ormsgpack.Ext:
             ),
         )
     elif isinstance(obj, SendProtocol):
+        args: tuple[Any, ...] = (obj.node, obj.arg)
+        if (timeout := getattr(obj, "timeout", None)) is not None:
+            args = (obj.node, obj.arg, timeout)
         return ormsgpack.Ext(
             EXT_CONSTRUCTOR_POS_ARGS,
             _msgpack_enc(
-                (obj.__class__.__module__, obj.__class__.__name__, (obj.node, obj.arg)),
+                (obj.__class__.__module__, obj.__class__.__name__, args),
             ),
         )
     elif dataclasses.is_dataclass(obj):
@@ -498,6 +554,15 @@ def _msgpack_default(obj: Any) -> str | ormsgpack.Ext:
         raise TypeError(f"Object of type {obj.__class__.__name__} is not serializable")
 
 
+def _send_from_args(args: Sequence[Any]) -> Any:
+    # ya we have a cyclic import here ¯\_(ツ)_/¯
+    from langgraph.types import Send  # type: ignore
+
+    if len(args) == 2:
+        return Send(*args)
+    return Send(args[0], args[1], timeout=args[2])
+
+
 def _create_msgpack_ext_hook(
     allowed_modules: set[tuple[str, ...]] | Literal[True] | None,
 ) -> Callable[[int, bytes], Any]:
@@ -527,10 +592,13 @@ def _create_msgpack_ext_hook(
                     "name": name,
                 }
             )
-            logger.warning(
+            _warn_once(
+                _warned_unregistered_types,
+                key,
                 "Deserializing unregistered type %s.%s from checkpoint. "
                 "This will be blocked in a future version. "
-                "Add to allowed_msgpack_modules to silence: [(%r, %r)]",
+                "Set LANGGRAPH_STRICT_MSGPACK=true to block now, or add "
+                "to allowed_msgpack_modules to allow explicitly: [(%r, %r)]",
                 module,
                 name,
                 module,
@@ -548,7 +616,9 @@ def _create_msgpack_ext_hook(
                 "name": name,
             }
         )
-        logger.warning(
+        _warn_once(
+            _warned_blocked_types,
+            key,
             "Blocked deserialization of %s.%s - not in allowed_msgpack_modules. "
             "Add to allowed_msgpack_modules to allow: [(%r, %r)]",
             module,
@@ -581,7 +651,13 @@ def _create_msgpack_ext_hook(
         return False
 
     def ext_hook(code: int, data: bytes) -> Any:
-        if code == EXT_CONSTRUCTOR_SINGLE_ARG:
+        if code == EXT_DELTA_SNAPSHOT:
+            return _DeltaSnapshot(
+                ormsgpack.unpackb(
+                    data, ext_hook=ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
+                )
+            )
+        elif code == EXT_CONSTRUCTOR_SINGLE_ARG:
             try:
                 tup = ormsgpack.unpackb(
                     data, ext_hook=ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
@@ -602,6 +678,8 @@ def _create_msgpack_ext_hook(
                 )
                 if not _check_allowed(tup[0], tup[1]):
                     return tup[2]
+                if tup[0] == "langgraph.types" and tup[1] == "Send":
+                    return _send_from_args(tup[2])
                 # module, name, args
                 return getattr(importlib.import_module(tup[0]), tup[1])(*tup[2])
             except Exception:
@@ -715,9 +793,7 @@ def _msgpack_ext_hook_to_json(code: int, data: bytes) -> Any:
                 option=ormsgpack.OPT_NON_STR_KEYS,
             )
             if tup[0] == "langgraph.types" and tup[1] == "Send":
-                from langgraph.types import Send  # type: ignore
-
-                return Send(*tup[2])
+                return _send_from_args(tup[2])
             # module, name, args
             return tup[2]
         except Exception:

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

@@ -1,6 +1,7 @@
 from collections.abc import Sequence
 from typing import (
     Any,
+    NamedTuple,
     Protocol,
     TypeVar,
     runtime_checkable,
@@ -14,6 +15,37 @@ INTERRUPT = "__interrupt__"
 RESUME = "__resume__"
 TASKS = "__pregel_tasks"
 
+
+class _DeltaSentinel:
+    """In-memory marker for a DeltaChannel field with no snapshot.
+
+    Never serialized to storage — checkpointers strip it before writing.
+    Compare with `is DELTA_SENTINEL`; always the same module-level instance.
+    """
+
+    __slots__ = ()
+
+    def __repr__(self) -> str:
+        return "DELTA_SENTINEL"
+
+
+DELTA_SENTINEL = _DeltaSentinel()
+
+
+class _DeltaSnapshot(NamedTuple):
+    """Snapshot blob for a DeltaChannel with finite snapshot_frequency.
+
+    Stored in checkpoint_blobs via the `EXT_DELTA_SNAPSHOT` msgpack ext code.
+    The ancestor walk in `_get_channel_writes_history` terminates when it
+    encounters this type (any non-sentinel blob stops the walk).
+
+    `from_checkpoint` reconstructs the channel value directly from `.value`
+    without replaying writes — the snapshot IS the accumulated state.
+    """
+
+    value: Any
+
+
 Value = TypeVar("Value", covariant=True)
 Update = TypeVar("Update", contravariant=True)
 C = TypeVar("C")

libs/checkpoint/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.1.0a3"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"
@@ -18,7 +18,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint"
-Twitter = "https://x.com/LangChain"
+Twitter = "https://x.com/langchain_oss"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint/tests/test_encrypted.py

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

libs/checkpoint/tests/test_jsonplus.py

@@ -35,6 +35,8 @@ from langgraph.checkpoint.serde.jsonplus import (
     JsonPlusSerializer,
     _msgpack_enc,
     _msgpack_ext_hook_to_json,
+    _warned_blocked_types,
+    _warned_unregistered_types,
 )
 from langgraph.store.base import Item
 
@@ -331,6 +333,57 @@ def test_serde_jsonplus_bytes() -> None:
     assert serde.loads_typed(dumped) == some_bytes
 
 
+def test_lc2_json_safe_type_revives_without_allowlist() -> None:
+    """Old 'json' blobs with lc=2 for safe types must revive without an explicit allowlist.
+
+    Regression test for: https://github.com/langchain-ai/langgraph/issues/7498
+    Threads checkpointed before v1.0.1 (pre-msgpack) stored messages as lc=2 JSON
+    constructor dicts. Resuming those threads must reconstruct proper BaseMessage objects
+    rather than returning raw dicts that cause MESSAGE_COERCION_FAILURE in add_messages.
+    """
+    from langchain_core.messages import AIMessage
+
+    serde = JsonPlusSerializer()  # default: _allowed_json_modules=None
+
+    human_blob = {
+        "lc": 2,
+        "type": "constructor",
+        "id": ["langchain_core", "messages", "human", "HumanMessage"],
+        "kwargs": {"content": "hello", "type": "human"},
+    }
+    ai_blob = {
+        "lc": 2,
+        "type": "constructor",
+        "id": ["langchain_core", "messages", "ai", "AIMessage"],
+        "kwargs": {"content": "hi there", "type": "ai"},
+    }
+    result = serde.loads_typed(("json", json.dumps([human_blob, ai_blob]).encode()))
+
+    assert len(result) == 2
+    assert isinstance(result[0], HumanMessage), (
+        f"Expected HumanMessage, got {type(result[0])}: {result[0]!r}\n"
+        "lc=2 JSON blobs for safe types must deserialize without an explicit allowlist"
+    )
+    assert result[0].content == "hello"
+    assert isinstance(result[1], AIMessage)
+    assert result[1].content == "hi there"
+
+
+def test_lc2_json_unknown_type_stays_blocked_without_allowlist() -> None:
+    """lc=2 JSON blobs for types NOT in SAFE_MSGPACK_TYPES still require an allowlist."""
+    serde = JsonPlusSerializer()
+    load = {
+        "lc": 2,
+        "type": "constructor",
+        "id": ["pprint", "pprint"],
+        "kwargs": {"object": "HELLO"},
+    }
+    # No allowlist configured → raw dict returned (not raised, not reconstructed)
+    result = serde.loads_typed(("json", json.dumps(load).encode()))
+    assert isinstance(result, dict), "Unknown lc=2 type must stay as raw dict"
+    assert result.get("lc") == 2
+
+
 def test_deserde_invalid_module() -> None:
     serde = JsonPlusSerializer()
     load = {
@@ -580,6 +633,14 @@ def test_msgpack_safe_types_no_warning(caplog: pytest.LogCaptureFixture) -> None
         assert result is not None
 
 
+@pytest.fixture(autouse=True)
+def _reset_warned_types() -> None:
+    # Warning dedup state is process-global; reset per-test so each case sees
+    # a fresh slate and assertions about warning emission are stable.
+    _warned_unregistered_types.clear()
+    _warned_blocked_types.clear()
+
+
 def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) -> None:
     """Pydantic models not in allowlist should log warning but still deserialize."""
     current = _lg_msgpack.STRICT_MSGPACK_ENABLED
@@ -595,6 +656,12 @@ def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) ->
     assert "unregistered type" in caplog.text.lower()
     assert "allowed_msgpack_modules" in caplog.text
     assert result == obj
+
+    # Second deserialization of the same type should NOT produce another warning
+    caplog.clear()
+    result2 = serde.loads_typed(dumped)
+    assert "unregistered type" not in caplog.text.lower()
+    assert result2 == obj
     _lg_msgpack.STRICT_MSGPACK_ENABLED = current
 
 
@@ -639,7 +706,6 @@ def test_msgpack_allowlist_silences_warning(caplog: pytest.LogCaptureFixture) ->
 
 def test_msgpack_none_blocks_unregistered(caplog: pytest.LogCaptureFixture) -> None:
     """allowed_msgpack_modules=None should block unregistered types."""
-
     serde = JsonPlusSerializer(allowed_msgpack_modules=None)
 
     obj = MyPydantic(foo="test", bar=42, inner=InnerPydantic(hello="world"))
@@ -657,7 +723,6 @@ def test_msgpack_allowlist_blocks_non_listed(
     caplog: pytest.LogCaptureFixture,
 ) -> None:
     """Allowlists should block unregistered types even if msgpack is enabled."""
-
     serde = JsonPlusSerializer(
         allowed_msgpack_modules=[("tests.test_jsonplus", "MyPydantic")]
     )

libs/checkpoint/tests/test_memory.py

@@ -6,19 +6,32 @@ from langchain_core.runnables import RunnableConfig
 from pydantic import BaseModel
 
 from langgraph.checkpoint.base import (
+    DELTA_SENTINEL,
     Checkpoint,
     CheckpointMetadata,
     create_checkpoint,
     empty_checkpoint,
 )
 from langgraph.checkpoint.memory import InMemorySaver
-from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+from langgraph.checkpoint.serde.jsonplus import (
+    JsonPlusSerializer,
+    _warned_blocked_types,
+    _warned_unregistered_types,
+)
 
 
 class MemoryPydantic(BaseModel):
     foo: str
 
 
+@pytest.fixture(autouse=True)
+def _reset_warned_types() -> None:
+    # Warning dedup state is process-global; reset per-test so each case sees
+    # a fresh slate and assertions about warning emission are stable.
+    _warned_unregistered_types.clear()
+    _warned_blocked_types.clear()
+
+
 class TestMemorySaver:
     @pytest.fixture(autouse=True)
     def setup(self) -> None:
@@ -196,8 +209,6 @@ class TestMemorySaver:
 
 
 async def test_memory_saver() -> None:
-    from langgraph.checkpoint.memory import InMemorySaver
-
     memory_saver = InMemorySaver()
     assert isinstance(memory_saver, InMemorySaver)
 
@@ -308,3 +319,338 @@ def test_memory_saver_with_allowlist_proxy_isolated() -> None:
     assert direct is not None
     expected = obj.model_dump() if hasattr(obj, "model_dump") else obj.dict()
     assert direct.checkpoint["channel_values"]["foo"] == expected
+
+
+class TestInMemorySaverDeltaChannel:
+    def test_load_blobs_omits_delta_channel(self) -> None:
+        """_load_blobs omits delta channels (stored as 'empty'); reconstruction deferred."""
+        saver = InMemorySaver()
+
+        thread_id, ns, channel = "t1", "", "messages"
+        v1 = "00000000000000000000000000000001.0000000000000000"
+
+        saver.blobs[(thread_id, ns, channel, v1)] = ("empty", b"")
+
+        result = saver._load_blobs(thread_id, ns, {channel: v1})
+        assert channel not in result
+
+    def test_get_channel_writes_collects_ancestor_writes_only(self) -> None:
+        """_get_channel_writes_history collects ancestor writes oldest→newest,
+        and excludes writes stored at the target checkpoint itself (those are
+        pending writes for the next step, applied separately by pregel)."""
+        saver = InMemorySaver()
+        serde = JsonPlusSerializer()
+
+        thread_id, ns, channel = "t1", "", "messages"
+
+        cp1 = empty_checkpoint()
+        cp1["id"] = "cp1"
+        cp2 = empty_checkpoint()
+        cp2["id"] = "cp2"
+        saver.storage[thread_id][ns] = {
+            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
+            "cp2": (serde.dumps_typed(cp2), serde.dumps_typed({}), "cp1"),
+        }
+        # Writes stored at cp1 produced the cp1 snapshot; part of history.
+        saver.writes[(thread_id, ns, "cp1")][("task1", 0)] = (
+            "task1",
+            channel,
+            serde.dumps_typed({"content": "hi"}),
+            "",
+        )
+        # Writes stored at cp2 are pending — they will produce cp3 when the
+        # step that loaded cp2 completes. They MUST NOT appear in the
+        # reconstructed snapshot value at cp2.
+        saver.writes[(thread_id, ns, "cp2")][("task2", 0)] = (
+            "task2",
+            channel,
+            serde.dumps_typed({"content": "pending"}),
+            "",
+        )
+
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": "cp2",
+            }
+        }
+        result = saver._get_channel_writes_history(config, channel)
+        assert result.seed is DELTA_SENTINEL
+        values = [v for _, _, v in result.writes]
+        assert values == [{"content": "hi"}]
+
+    def test_get_channel_writes_at_root_returns_empty(self) -> None:
+        """Reconstructing the root checkpoint's state: no ancestors → []."""
+        saver = InMemorySaver()
+        serde = JsonPlusSerializer()
+        thread_id, ns, channel = "t1", "", "messages"
+
+        cp1 = empty_checkpoint()
+        cp1["id"] = "cp1"
+        saver.storage[thread_id][ns] = {
+            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
+        }
+        saver.writes[(thread_id, ns, "cp1")][("task1", 0)] = (
+            "task1",
+            channel,
+            serde.dumps_typed({"content": "pending"}),
+            "",
+        )
+
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": "cp1",
+            }
+        }
+        result = saver._get_channel_writes_history(config, channel)
+        assert result.seed is DELTA_SENTINEL
+        assert result.writes == []
+
+
+class TestBaseFallbackGetChannelWrites:
+    """Exercises the `BaseCheckpointSaver._get_channel_writes_history` default
+    implementation — the path third-party savers inherit when they don't
+    override `_get_channel_writes_history` themselves.
+
+    Regression guard for a bug where the fallback passed the caller's config
+    (with `checkpoint_id`) straight to `self.list()`, which most savers
+    collapse to a single row — causing the fallback to return `[]`.
+    """
+
+    def _build_saver_with_chain(self) -> tuple[InMemorySaver, str, str]:
+        """Build an InMemorySaver with a 3-checkpoint chain and per-step writes
+        for a `messages` channel.
+
+        Returns `(saver, thread_id, namespace)`. The saver subclass deletes the
+        InMemorySaver override so the base class fallback is exercised.
+        """
+
+        class _ThirdPartyStyleSaver(InMemorySaver):
+            _get_channel_writes_history = (
+                InMemorySaver.__mro__[1]._get_channel_writes_history  # type: ignore[attr-defined]
+            )
+            _aget_channel_writes_history = (
+                InMemorySaver.__mro__[1]._aget_channel_writes_history  # type: ignore[attr-defined]
+            )
+
+        saver = _ThirdPartyStyleSaver()
+        serde = JsonPlusSerializer()
+        thread_id, ns, channel = "t1", "", "messages"
+
+        cp0 = empty_checkpoint()
+        cp0["id"] = "00000000000000000000000000000001.0000000000000000"
+        cp1 = empty_checkpoint()
+        cp1["id"] = "00000000000000000000000000000002.0000000000000000"
+        cp2 = empty_checkpoint()
+        cp2["id"] = "00000000000000000000000000000003.0000000000000000"
+        saver.storage[thread_id][ns] = {
+            cp0["id"]: (serde.dumps_typed(cp0), serde.dumps_typed({}), None),
+            cp1["id"]: (serde.dumps_typed(cp1), serde.dumps_typed({}), cp0["id"]),
+            cp2["id"]: (serde.dumps_typed(cp2), serde.dumps_typed({}), cp1["id"]),
+        }
+        # Writes under cp0 produced cp1's state; writes under cp1 produced cp2's.
+        saver.writes[(thread_id, ns, cp0["id"])][("task1", 0)] = (
+            "task1",
+            channel,
+            serde.dumps_typed({"content": "first"}),
+            "",
+        )
+        saver.writes[(thread_id, ns, cp1["id"])][("task2", 0)] = (
+            "task2",
+            channel,
+            serde.dumps_typed({"content": "second"}),
+            "",
+        )
+        return saver, thread_id, ns
+
+    def test_fallback_returns_ancestor_writes_oldest_first(self) -> None:
+        saver, thread_id, ns = self._build_saver_with_chain()
+        target_id = "00000000000000000000000000000003.0000000000000000"
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": target_id,
+            }
+        }
+
+        result = saver._get_channel_writes_history(config, "messages")
+
+        assert result.seed is DELTA_SENTINEL
+        values = [v for _, _, v in result.writes]
+        assert values == [{"content": "first"}, {"content": "second"}]
+
+    async def test_async_fallback_returns_ancestor_writes_oldest_first(self) -> None:
+        saver, thread_id, ns = self._build_saver_with_chain()
+        target_id = "00000000000000000000000000000003.0000000000000000"
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": target_id,
+            }
+        }
+
+        result = await saver._aget_channel_writes_history(config, "messages")
+
+        assert result.seed is DELTA_SENTINEL
+        values = [v for _, _, v in result.writes]
+        assert values == [{"content": "first"}, {"content": "second"}]
+
+    async def test_async_fallback_concurrent_tasks_do_not_interfere(self) -> None:
+        """Regression: the re-entrancy guard must be task-local, not thread-local.
+
+        Two concurrent `_aget_channel_writes_history` calls on the same
+        event-loop thread must each see their full reconstructed writes. A
+        `threading.local()` guard would let whichever task set it first
+        short-circuit the other to `writes=[]`.
+        """
+        import asyncio
+
+        saver, thread_id, ns = self._build_saver_with_chain()
+
+        # Force the two tasks to interleave across the `set(True)` boundary:
+        # each `aget_tuple` yields control, so if the guard were thread-local
+        # the second task would observe `active=True` set by the first.
+        orig_aget_tuple = saver.aget_tuple
+
+        async def slow_aget_tuple(config: RunnableConfig) -> Any:
+            await asyncio.sleep(0)
+            return await orig_aget_tuple(config)
+
+        saver.aget_tuple = slow_aget_tuple  # type: ignore[method-assign]
+
+        target_id = "00000000000000000000000000000003.0000000000000000"
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": target_id,
+            }
+        }
+
+        results = await asyncio.gather(
+            saver._aget_channel_writes_history(config, "messages"),
+            saver._aget_channel_writes_history(config, "messages"),
+        )
+
+        expected_values = [{"content": "first"}, {"content": "second"}]
+        for result in results:
+            assert result.seed is DELTA_SENTINEL
+            values = [v for _, _, v in result.writes]
+            assert values == expected_values
+
+
+class TestPreDeltaBlobTerminator:
+    """Verify the pre-delta blob terminator: when the ancestor walk hits a
+    checkpoint whose blob for the channel is a real value (not
+    DELTA_SENTINEL), reconstruction seeds from it and stops. This guards
+
+      * back-compat: a thread written by pre-delta code, then extended under
+        delta — reconstruction must return the correct value without walking
+        past the last pre-delta ancestor;
+      * perf: without the terminator, every reconstruct-after-migration would
+        walk all the way to the thread root.
+    """
+
+    def _build_mixed_thread(self) -> tuple[InMemorySaver, str, str, str, str]:
+        """Three-checkpoint chain: cp1 (pre-delta, blob=[A]), cp2 (delta,
+        write=B), cp3 (delta, write=C). Reconstructing at cp3 must yield
+        seed=[A] + writes=[B, C].
+
+        Returns `(saver, thread_id, ns, channel, cp3_id)`.
+        """
+        saver = InMemorySaver()
+        serde = JsonPlusSerializer()
+        thread_id, ns, channel = "t1", "", "messages"
+
+        v1 = "00000000000000000000000000000001.0"
+        v2 = "00000000000000000000000000000002.0"
+        v3 = "00000000000000000000000000000003.0"
+
+        # Pre-delta: cp1 stored a real blob for the channel.
+        saver.blobs[(thread_id, ns, channel, v1)] = serde.dumps_typed(["A"])
+        # Delta-era: cp2 and cp3 store "empty"; real writes in checkpoint_writes.
+        saver.blobs[(thread_id, ns, channel, v2)] = ("empty", b"")
+        saver.blobs[(thread_id, ns, channel, v3)] = ("empty", b"")
+
+        cp1 = empty_checkpoint()
+        cp1["id"] = "cp1"
+        cp1["channel_versions"][channel] = v1
+        cp2 = empty_checkpoint()
+        cp2["id"] = "cp2"
+        cp2["channel_versions"][channel] = v2
+        cp3 = empty_checkpoint()
+        cp3["id"] = "cp3"
+        cp3["channel_versions"][channel] = v3
+
+        saver.storage[thread_id][ns] = {
+            "cp1": (serde.dumps_typed(cp1), serde.dumps_typed({}), None),
+            "cp2": (serde.dumps_typed(cp2), serde.dumps_typed({}), "cp1"),
+            "cp3": (serde.dumps_typed(cp3), serde.dumps_typed({}), "cp2"),
+        }
+        # Write under cp1 would be from the pre-delta era and MUST be ignored
+        # (the blob already captures it). We add one and assert it is not
+        # folded into the reconstructed result.
+        saver.writes[(thread_id, ns, "cp1")][("task0", 0)] = (
+            "task0",
+            channel,
+            serde.dumps_typed("PRE-DELTA-WRITE"),
+            "",
+        )
+        saver.writes[(thread_id, ns, "cp2")][("task2", 0)] = (
+            "task2",
+            channel,
+            serde.dumps_typed("B"),
+            "",
+        )
+        saver.writes[(thread_id, ns, "cp3")][("task3", 0)] = (
+            "task3",
+            channel,
+            serde.dumps_typed("PENDING-AT-TARGET"),
+            "",
+        )
+        return saver, thread_id, ns, channel, "cp3"
+
+    def test_seed_from_pre_delta_ancestor_blob(self) -> None:
+        saver, thread_id, ns, channel, target = self._build_mixed_thread()
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": target,
+            }
+        }
+
+        result = saver._get_channel_writes_history(config, channel)
+
+        # Seed came from the pre-delta blob at cp1.
+        assert result.seed == ["A"]
+        # Delta-era writes from cp2 replay through the reducer on top of seed.
+        # cp3 is the target — its own write is pending for the NEXT step and
+        # must be excluded.
+        values = [v for _, _, v in result.writes]
+        assert values == ["B"]
+
+    def test_pre_delta_blob_terminates_walk_before_older_writes(self) -> None:
+        """Writes stored at the pre-delta ancestor itself must not be replayed
+        (the blob subsumes them)."""
+        saver, thread_id, ns, channel, target = self._build_mixed_thread()
+        config: RunnableConfig = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": ns,
+                "checkpoint_id": target,
+            }
+        }
+
+        result = saver._get_channel_writes_history(config, channel)
+
+        values = [v for _, _, v in result.writes]
+        # The pre-delta write under cp1 must not appear (the blob subsumes it).
+        assert "PRE-DELTA-WRITE" not in values
+        # And the pending write at the target is never folded in.
+        assert "PENDING-AT-TARGET" not in values

libs/checkpoint/uv.lock

@@ -267,7 +267,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.23"
+version = "1.2.28"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -279,14 +279,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/1d/47/a5f21b651e9cbd7a26c3e5809336d10a0be94ef7bdf6bea47f2ad9fff1a8/langchain_core-1.2.23.tar.gz", hash = "sha256:fdec64f90cfea25317e88d9803c44684af1f4e30dec4e58320dd7393bb0f0785", size = 841684, upload-time = "2026-03-27T23:28:14.6Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
 wheels = [
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+]
+
 [[package]]
 name = "zstandard"
 version = "0.25.0"

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

@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langgraph==1.1.2"
+  "langgraph==1.1.5"
 ]

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

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

libs/cli/examples/graph_prerelease_reqs/pyproject.toml

@@ -5,9 +5,9 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.0.0a2",
+  "langchain-openai==1.1.14",
   "langchain-anthropic==1.0.0a5",
-  "langgraph==1.1.2"
+  "langgraph==1.1.5"
 ]
 
 [tool.uv]

libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml

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

libs/cli/generate_schema.py

@@ -159,8 +159,8 @@ def generate_schema():
         if k not in python_specific_props and k not in node_specific_props
     ]
 
-    # Create Python schema with python_version and pip_config_file
-    python_schema = {
+    # Create legacy Python schema with python_version and pip_config_file
+    legacy_python_schema = {
         "type": "object",
         "properties": {
             # Include Python-specific properties
@@ -170,10 +170,45 @@ def generate_schema():
         },
         "required": ["dependencies", "graphs"],
     }
+    legacy_python_schema["properties"]["pip_installer"] = {
+        "anyOf": [
+            {"type": "string", "enum": ["auto", "pip", "uv"]},
+            {"type": "null"},
+        ]
+    }
+
+    uv_source_python_schema = {
+        "type": "object",
+        "properties": {
+            **{
+                k: config_schema["properties"][k].copy()
+                for k in python_specific_props + common_props
+            },
+        },
+        "required": ["graphs", "source"],
+    }
+    # source must be a UvSource object (not null)
+    uv_source_python_schema["properties"]["source"] = {"$ref": "#/$defs/UvSource"}
+    uv_source_python_schema["properties"]["pip_installer"] = {
+        "anyOf": [
+            {"type": "string", "enum": ["auto", "pip", "uv"]},
+            {"type": "null"},
+        ]
+    }
 
     # Add enum constraint for python_version
-    if "python_version" in python_schema["properties"]:
-        python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12", "3.13"]
+    if "python_version" in legacy_python_schema["properties"]:
+        legacy_python_schema["properties"]["python_version"]["enum"] = [
+            "3.11",
+            "3.12",
+            "3.13",
+        ]
+    if "python_version" in uv_source_python_schema["properties"]:
+        uv_source_python_schema["properties"]["python_version"]["enum"] = [
+            "3.11",
+            "3.12",
+            "3.13",
+        ]
 
     # Create Node.js schema with node_version
     node_schema = {
@@ -186,6 +221,12 @@ def generate_schema():
         },
         "required": ["node_version", "graphs"],
     }
+    node_schema["properties"]["pip_installer"] = {
+        "anyOf": [
+            {"type": "string", "enum": ["auto", "pip", "uv"]},
+            {"type": "null"},
+        ]
+    }
 
     # Add enum constraint for node_version
     if "node_version" in node_schema["properties"]:
@@ -202,7 +243,11 @@ def generate_schema():
         ]
 
     # Replace the Config schema with a oneOf constraint
-    config_schema["oneOf"] = [python_schema, node_schema]
+    config_schema["oneOf"] = [
+        legacy_python_schema,
+        uv_source_python_schema,
+        node_schema,
+    ]
 
     # Remove the properties field as it's now defined in the oneOf subschemas
     if "properties" in config_schema:

libs/cli/js-examples/yarn.lock

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

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

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

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.19"
+__version__ = "0.4.24"

libs/cli/langgraph_cli/_ignore.py

@@ -0,0 +1,124 @@
+"""Shared ignore-file handling for local source filtering."""
+
+import pathlib
+from dataclasses import dataclass
+
+import pathspec
+
+_ALWAYS_EXCLUDE = [
+    "__pycache__/",
+    ".git/",
+    ".venv/",
+    "venv/",
+    "node_modules/",
+    ".tox/",
+    ".mypy_cache/",
+]
+_ALWAYS_EXCLUDE_NAMES = frozenset(
+    pattern.rstrip("/").split("/")[-1] for pattern in _ALWAYS_EXCLUDE
+)
+_GLOB_CHARS = frozenset("*?[")
+
+
+@dataclass(frozen=True, slots=True)
+class _NegatedDockerignoreHints:
+    exact_dirs: frozenset[pathlib.PurePosixPath] = frozenset()
+    wildcard_prefixes: frozenset[pathlib.PurePosixPath] = frozenset()
+    recurse_all: bool = False
+
+    def requires_dir_walk(self, path: pathlib.PurePosixPath) -> bool:
+        if self.recurse_all or path in self.exact_dirs:
+            return True
+        return any(
+            path == prefix or path in prefix.parents or prefix in path.parents
+            for prefix in self.wildcard_prefixes
+        )
+
+
+def _build_ignore_spec(
+    directory: pathlib.Path, *, include_gitignore: bool = True
+) -> pathspec.PathSpec:
+    """Build a PathSpec combining built-in exclusions with ignore files.
+
+    Always excludes common non-source directories (`_ALWAYS_EXCLUDE`). On top
+    of that, patterns from `.dockerignore` are merged in. `.gitignore` patterns
+    are optional because some callers need Docker build-context semantics,
+    while archive creation wants both files.
+    """
+    lines: list[str] = list(_ALWAYS_EXCLUDE)
+    ignore_files = [".dockerignore"]
+    if include_gitignore:
+        ignore_files.append(".gitignore")
+    for name in ignore_files:
+        ignore_file = directory / name
+        if ignore_file.is_file():
+            lines.extend(ignore_file.read_text(encoding="utf-8").splitlines())
+    return pathspec.PathSpec.from_lines("gitwildmatch", lines)
+
+
+def _is_always_excluded(path: pathlib.PurePosixPath, *, is_dir: bool) -> bool:
+    """Whether `path` lives inside a built-in excluded directory."""
+    parent_parts = path.parts if is_dir else path.parts[:-1]
+    return any(part in _ALWAYS_EXCLUDE_NAMES for part in parent_parts)
+
+
+def _build_dockerignore_negation_hints(
+    directory: pathlib.Path,
+) -> _NegatedDockerignoreHints:
+    """Summarize which ignored directories must still be traversed.
+
+    Most negations only require walking a small, concrete chain of parent
+    directories (for example `!assets/keep.txt` requires entering `assets/`).
+    Broader glob negations may force a wider walk.
+    """
+    ignore_file = directory / ".dockerignore"
+    if not ignore_file.is_file():
+        return _NegatedDockerignoreHints()
+
+    exact_dirs: set[pathlib.PurePosixPath] = set()
+    wildcard_prefixes: set[pathlib.PurePosixPath] = set()
+    recurse_all = False
+
+    for raw_line in ignore_file.read_text(encoding="utf-8").splitlines():
+        line = raw_line.strip()
+        if not line or line.startswith("#") or line.startswith("\\!"):
+            continue
+        if line.startswith("\\#"):
+            line = line[1:]
+        if not line.startswith("!"):
+            continue
+
+        pattern = line[1:].lstrip("/")
+        while pattern.startswith("./"):
+            pattern = pattern[2:]
+        pattern = pattern.rstrip("/")
+        parts = [part for part in pattern.split("/") if part and part != "."]
+        if not parts:
+            recurse_all = True
+            continue
+
+        wildcard_index = next(
+            (
+                idx
+                for idx, part in enumerate(parts)
+                if any(char in part for char in _GLOB_CHARS)
+            ),
+            None,
+        )
+        if wildcard_index is not None:
+            literal_parts = parts[:wildcard_index]
+            if not literal_parts:
+                recurse_all = True
+                continue
+            wildcard_prefixes.add(pathlib.PurePosixPath(*literal_parts))
+            continue
+
+        parent_parts = parts[:-1]
+        for idx in range(1, len(parent_parts) + 1):
+            exact_dirs.add(pathlib.PurePosixPath(*parent_parts[:idx]))
+
+    return _NegatedDockerignoreHints(
+        exact_dirs=frozenset(exact_dirs),
+        wildcard_prefixes=frozenset(wildcard_prefixes),
+        recurse_all=recurse_all,
+    )

libs/cli/langgraph_cli/analytics.py

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

libs/cli/langgraph_cli/archive.py

@@ -9,35 +9,12 @@ from contextlib import contextmanager
 import click
 import pathspec
 
+from langgraph_cli._ignore import _build_ignore_spec
 from langgraph_cli.config import Config, _assemble_local_deps
 
 _WARN_SIZE = 50 * 1024 * 1024  # 50 MB
 _MAX_SIZE = 200 * 1024 * 1024  # 200 MB
 
-_ALWAYS_EXCLUDE = [
-    "__pycache__/",
-    ".git/",
-    ".venv/",
-    "venv/",
-    "node_modules/",
-    ".tox/",
-    ".mypy_cache/",
-]
-
-
-def _build_ignore_spec(directory: pathlib.Path) -> pathspec.PathSpec:
-    """Build a PathSpec combining built-in exclusions with .dockerignore and .gitignore.
-
-    Always excludes common non-source directories (_ALWAYS_EXCLUDE).  On top of
-    that, patterns from .dockerignore and .gitignore (if present) are merged in.
-    """
-    lines: list[str] = list(_ALWAYS_EXCLUDE)
-    for name in (".dockerignore", ".gitignore"):
-        ignore_file = directory / name
-        if ignore_file.is_file():
-            lines.extend(ignore_file.read_text(encoding="utf-8").splitlines())
-    return pathspec.PathSpec.from_lines("gitwildmatch", lines)
-
 
 def _tar_filter(tarinfo: tarfile.TarInfo) -> tarfile.TarInfo | None:
     """Strip symlinks, hardlinks, and traversal paths from archive."""

libs/cli/langgraph_cli/cli.py

@@ -817,6 +817,48 @@ def dev(
     )
 
 
+# ---------------------------------------------------------------------------
+# validate command
+# ---------------------------------------------------------------------------
+
+
+@OPT_CONFIG
+@cli.command(help="✅ Validate the LangGraph configuration file.")
+@log_command
+def validate(config: pathlib.Path):
+    import json
+
+    try:
+        with open(config) as f:
+            raw_config = json.load(f)
+    except json.JSONDecodeError as e:
+        raise click.UsageError(f"Invalid JSON in {config}: {e.args[0]}") from None
+
+    # Check for unknown keys before validation so they show alongside any error.
+    unknown_warnings = langgraph_cli.config.get_unknown_keys(raw_config)
+
+    try:
+        config_json = langgraph_cli.config.validate_config_file(config)
+    except (click.UsageError, ValueError) as e:
+        click.secho(f"Error: {e}", fg="red", err=True)
+        if unknown_warnings:
+            click.echo(err=True)
+            for warning in unknown_warnings:
+                click.secho(f"  warning: {warning}", fg="yellow", err=True)
+        raise SystemExit(1) from None
+
+    num_graphs = len(config_json.get("graphs", {}))
+    click.secho(
+        f"Configuration file {config} is valid. "
+        f"({num_graphs} graph{'s' if num_graphs != 1 else ''} found)",
+        fg="green",
+    )
+    if unknown_warnings:
+        click.echo()
+        for warning in unknown_warnings:
+            click.secho(f"  warning: {warning}", fg="yellow")
+
+
 # ---------------------------------------------------------------------------
 # new command
 # ---------------------------------------------------------------------------

libs/cli/langgraph_cli/config.py

@@ -3,6 +3,7 @@ import json
 import os
 import pathlib
 import re
+import shlex
 import textwrap
 from collections import Counter
 from typing import Literal, NamedTuple
@@ -10,6 +11,7 @@ from typing import Literal, NamedTuple
 import click
 
 from langgraph_cli.schemas import Config, Distros
+from langgraph_cli.uv_lock import python_config_to_docker_uv_lock
 
 MIN_NODE_VERSION = "20"
 DEFAULT_NODE_VERSION = "20"
@@ -139,6 +141,14 @@ def _is_node_graph(spec: str | dict) -> bool:
     ]
 
 
+def _get_source_kind(config: Config) -> str | None:
+    source = config.get("source")
+    if not isinstance(source, dict):
+        return None
+    kind = source.get("kind")
+    return kind if isinstance(kind, str) else None
+
+
 def validate_config(config: Config) -> Config:
     """Validate a configuration dictionary."""
 
@@ -157,6 +167,8 @@ def validate_config(config: Config) -> Config:
     image_distro = config.get("image_distro", DEFAULT_IMAGE_DISTRO)
     internal_docker_tag = config.get("_INTERNAL_docker_tag")
     api_version = config.get("api_version")
+    legacy_project_root = config.get("project_root")
+    legacy_package = config.get("package")
     if internal_docker_tag:
         if api_version:
             raise click.UsageError(
@@ -170,13 +182,18 @@ def validate_config(config: Config) -> Config:
                     "Version must be major or major.minor or major.minor.patch."
                 )
         except TypeError:
-            raise click.UsageError(f"Invalid version format: {api_version}") from None
+            raise click.UsageError(
+                f"Invalid version format: {api_version}.\n\n"
+                "Pin to a minor version, e.g.:\n"
+                '  "api_version": "0.8"'
+            ) from None
 
     config = {
         "node_version": node_version,
         "python_version": python_version,
         "pip_config_file": config.get("pip_config_file"),
         "pip_installer": config.get("pip_installer", "auto"),
+        "source": config.get("source"),
         "base_image": config.get("base_image"),
         "image_distro": image_distro,
         "dependencies": config.get("dependencies", []),
@@ -207,25 +224,51 @@ def validate_config(config: Config) -> Config:
             if major < min_major:
                 raise click.UsageError(
                     f"Node.js version {node_version} is not supported. "
-                    f"Minimum required version is {MIN_NODE_VERSION}."
+                    f"Minimum required version is {MIN_NODE_VERSION}.\n\n"
+                    f"Set node_version to {MIN_NODE_VERSION} or higher:\n"
+                    f'  "node_version": "{MIN_NODE_VERSION}"'
                 )
         except ValueError as e:
             raise click.UsageError(str(e)) from None
 
+    if pip_installer := config.get("pip_installer"):
+        if pip_installer not in ["auto", "pip", "uv"]:
+            raise click.UsageError(
+                f"Invalid pip_installer: '{pip_installer}'. "
+                "Consider using uv-based source management instead:\n\n"
+                '  "source": {"kind": "uv", "root": ".."}'
+            )
+
+    source = config.get("source")
+    source_kind = _get_source_kind(config)
+    if source is not None and not isinstance(source, dict):
+        raise click.UsageError(
+            "`source` must be an object, e.g.:\n"
+            '  "source": {"kind": "uv", "root": ".."}'
+        )
+    if source is not None and source_kind != "uv":
+        raise click.UsageError(
+            "Invalid source.kind. The only supported value is 'uv':\n"
+            '  "source": {"kind": "uv", "root": ".."}'
+        )
+
     if config.get("python_version"):
         pyversion = config["python_version"]
         if not pyversion.count(".") == 1 or not all(
             part.isdigit() for part in pyversion.split("-")[0].split(".")
         ):
+            parts = pyversion.split("-")[0].split(".")
+            fix = f"{parts[0]}.{parts[1]}" if len(parts) >= 2 else MIN_PYTHON_VERSION
             raise click.UsageError(
                 f"Invalid Python version format: {pyversion}. "
-                "Use 'major.minor' format (e.g., '3.11'). "
-                "Patch version cannot be specified."
+                "Use 'major.minor' format — patch version cannot be specified.\n\n"
+                f'  "python_version": "{fix}"'
             )
         if _parse_version(pyversion) < _parse_version(MIN_PYTHON_VERSION):
             raise click.UsageError(
                 f"Python version {pyversion} is not supported. "
-                f"Minimum required version is {MIN_PYTHON_VERSION}."
+                f"Minimum required version is {MIN_PYTHON_VERSION}.\n\n"
+                f'  "python_version": "{MIN_PYTHON_VERSION}"'
             )
         if "bullseye" in pyversion:
             raise click.UsageError(
@@ -233,15 +276,19 @@ def validate_config(config: Config) -> Config:
                 "Please use 'bookworm' or 'debian' instead."
             )
 
-        if not config["dependencies"]:
+        if source_kind != "uv" and not config["dependencies"]:
             raise click.UsageError(
                 "No dependencies found in config. "
-                "Add at least one dependency to 'dependencies' list."
+                "Consider using uv-based source management:\n\n"
+                '  "source": {"kind": "uv", "root": ".."}'
             )
 
     if not config.get("graphs"):
         raise click.UsageError(
-            "No graphs found in config. Add at least one graph to 'graphs' dictionary."
+            "No graphs found in config. Add at least one graph, e.g.:\n"
+            '  "graphs": {\n'
+            '    "agent": "./my_agent/graph.py:graph"\n'
+            "  }"
         )
 
     # Validate image_distro config
@@ -254,15 +301,46 @@ def validate_config(config: Config) -> Config:
         if image_distro not in Distros.__args__:
             raise click.UsageError(
                 f"Invalid image_distro: '{image_distro}'. "
-                "Must be one of 'debian', 'wolfi', or 'bookworm'."
+                f"Must be one of: {', '.join(repr(d) for d in Distros.__args__)}.\n\n"
+                '  "image_distro": "wolfi"  (recommended)'
             )
 
-    if pip_installer := config.get("pip_installer"):
-        if pip_installer not in ["auto", "pip", "uv"]:
-            raise click.UsageError(
-                f"Invalid pip_installer: '{pip_installer}'. "
-                "Must be 'auto', 'pip', or 'uv'."
+    if source_kind == "uv":
+        errors: list[str] = []
+        if not config.get("python_version"):
+            errors.append(
+                "source.kind 'uv' requires `python_version` — "
+                "it is a Python-only deployment mode. "
+                "Node.js-only graphs are not supported."
             )
+        if config["dependencies"]:
+            errors.append(
+                "Remove `dependencies` from your config. With "
+                '`source.kind = "uv"`, all dependencies '
+                "are read from your pyproject.toml and uv.lock instead."
+            )
+        root = source.get("root", ".") if source else "."
+        if not isinstance(root, str):
+            errors.append(f"`source.root` must be a string, got {type(root).__name__}.")
+        elif not root.strip():
+            errors.append('`source.root` must be a non-empty string. Use `"."`.')
+        package_name = source.get("package") if source else None
+        if package_name is not None and (
+            not isinstance(package_name, str) or not package_name.strip()
+        ):
+            errors.append("`source.package` must be a non-empty string.")
+        if errors:
+            detail = "\n".join(f"  - {e}" for e in errors)
+            raise click.UsageError(
+                "source.kind 'uv' requires a different "
+                f"config shape than dependency-based installs:\n{detail}"
+            )
+
+    if legacy_project_root or legacy_package:
+        raise click.UsageError(
+            "Top-level `project_root` and `package` are no longer supported. "
+            "Use `source.root` and `source.package` instead."
+        )
 
     # Validate auth config
     if auth_conf := config.get("auth"):
@@ -306,6 +384,51 @@ def validate_config(config: Config) -> Config:
     return config
 
 
+# Keys recognized by validate_config (used to detect unknown fields).
+_KNOWN_CONFIG_KEYS = {
+    "python_version",
+    "node_version",
+    "api_version",
+    "base_image",
+    "image_distro",
+    "pip_config_file",
+    "pip_installer",
+    "source",
+    "dependencies",
+    "dockerfile_lines",
+    "graphs",
+    "env",
+    "store",
+    "auth",
+    "encryption",
+    "http",
+    "webhooks",
+    "checkpointer",
+    "ui",
+    "ui_config",
+    "keep_pkg_tools",
+    # Internal / legacy (still recognized, may error separately)
+    "_INTERNAL_docker_tag",
+    "project_root",
+    "package",
+}
+
+
+def get_unknown_keys(raw_config: dict) -> list[str]:
+    """Return warnings for unrecognized top-level keys (typos, etc.)."""
+    import difflib
+
+    unknown = set(raw_config) - _KNOWN_CONFIG_KEYS
+    warnings: list[str] = []
+    for key in sorted(unknown):
+        close = difflib.get_close_matches(key, _KNOWN_CONFIG_KEYS, n=1)
+        if close:
+            warnings.append(f"Unknown key '{key}' — did you mean '{close[0]}'?")
+        else:
+            warnings.append(f"Unknown key '{key}' is not a recognized config field.")
+    return warnings
+
+
 def validate_config_file(config_path: pathlib.Path) -> Config:
     """Load and validate a configuration file."""
     with open(config_path) as f:
@@ -807,9 +930,65 @@ def _update_http_app_path(
         http_config["app"] = f"{module_str}:{attr_str}"
 
 
-def _get_node_pm_install_cmd(config_path: pathlib.Path, config: Config) -> str:
+def _build_python_install_commands(
+    config: Config, install_cmd: str
+) -> tuple[str, str, str]:
+    base_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt"
+    local_reqs_pip_install = base_install
+    global_reqs_pip_install = base_install
+
+    if config.get("pip_config_file"):
+        local_reqs_pip_install = (
+            f"PIP_CONFIG_FILE=/pipconfig.txt {local_reqs_pip_install}"
+        )
+        global_reqs_pip_install = (
+            f"PIP_CONFIG_FILE=/pipconfig.txt {global_reqs_pip_install}"
+        )
+
+    pip_config_file_str = (
+        f"ADD {config['pip_config_file']} /pipconfig.txt"
+        if config.get("pip_config_file")
+        else ""
+    )
+    return local_reqs_pip_install, global_reqs_pip_install, pip_config_file_str
+
+
+def _build_runtime_env_vars(config: Config) -> list[str]:
+    env_vars = []
+
+    if (store_config := config.get("store")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_STORE='{json.dumps(store_config)}'")
+
+    if (auth_config := config.get("auth")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_AUTH='{json.dumps(auth_config)}'")
+
+    if (encryption_config := config.get("encryption")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_ENCRYPTION='{json.dumps(encryption_config)}'")
+
+    if (http_config := config.get("http")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_HTTP='{json.dumps(http_config)}'")
+
+    if (webhooks_config := config.get("webhooks")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_WEBHOOKS='{json.dumps(webhooks_config)}'")
+
+    if (checkpointer_config := config.get("checkpointer")) is not None:
+        env_vars.append(
+            f"ENV LANGGRAPH_CHECKPOINTER='{json.dumps(checkpointer_config)}'"
+        )
+
+    if (ui := config.get("ui")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_UI='{json.dumps(ui)}'")
+
+    if (ui_config := config.get("ui_config")) is not None:
+        env_vars.append(f"ENV LANGGRAPH_UI_CONFIG='{json.dumps(ui_config)}'")
+
+    env_vars.append(f"ENV LANGSERVE_GRAPHS='{json.dumps(config['graphs'])}'")
+    return env_vars
+
+
+def _get_node_pm_install_cmd(project_dir: pathlib.Path) -> str:
     def test_file(file_name):
-        full_path = config_path.parent / file_name
+        full_path = project_dir / file_name
         try:
             return full_path.is_file()
         except OSError:
@@ -818,7 +997,7 @@ def _get_node_pm_install_cmd(config_path: pathlib.Path, config: Config) -> str:
     # inspired by `package-manager-detector`
     def get_pkg_manager_name():
         try:
-            with open(config_path.parent / "package.json") as f:
+            with open(project_dir / "package.json") as f:
                 pkg = json.load(f)
 
                 if (pkg_manager_name := pkg.get("packageManager")) and isinstance(
@@ -914,8 +1093,17 @@ def python_config_to_docker(
     escape_variables: bool = False,
 ) -> tuple[str, dict[str, str]]:
     """Generate a Dockerfile from the configuration."""
+    source_kind = _get_source_kind(config)
     pip_installer = config.get("pip_installer", "auto")
     build_tools_to_uninstall = get_build_tools_to_uninstall(config)
+    if source_kind == "uv":
+        return python_config_to_docker_uv_lock(
+            config_path,
+            config,
+            base_image,
+            api_version=api_version,
+            build_tools_to_uninstall=build_tools_to_uninstall,
+        )
     if pip_installer == "auto":
         if _image_supports_uv(base_image):
             pip_installer = "uv"
@@ -928,21 +1116,11 @@ def python_config_to_docker(
     else:
         raise ValueError(f"Invalid pip_installer: {pip_installer}")
 
-    # configure pip
-    local_reqs_pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt"
-    global_reqs_pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt"
-    if config.get("pip_config_file"):
-        local_reqs_pip_install = (
-            f"PIP_CONFIG_FILE=/pipconfig.txt {local_reqs_pip_install}"
-        )
-        global_reqs_pip_install = (
-            f"PIP_CONFIG_FILE=/pipconfig.txt {global_reqs_pip_install}"
-        )
-    pip_config_file_str = (
-        f"ADD {config['pip_config_file']} /pipconfig.txt"
-        if config.get("pip_config_file")
-        else ""
-    )
+    (
+        local_reqs_pip_install,
+        global_reqs_pip_install,
+        pip_config_file_str,
+    ) = _build_python_install_commands(config, install_cmd)
 
     # collect dependencies
     pypi_deps = [dep for dep in config["dependencies"] if not dep.startswith(".")]
@@ -998,7 +1176,7 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-{fullpath.name}/pyproject.toml; \\
+        echo "$line" >> {shlex.quote(f"/deps/outer-{fullpath.name}/pyproject.toml")}; \\
     done
 # -- End of non-package dependency {fullpath.name} --"""
         for fullpath, (relpath, destpath) in local_deps.faux_pkgs.items()
@@ -1017,56 +1195,50 @@ ADD {relpath} /deps/{name}
         for fullpath, (relpath, name) in local_deps.real_pkgs.items()
     )
 
+    additional_contexts: dict[str, str] = {}
+    additional_context_names: dict[pathlib.Path, str] = {}
+    used_context_names: set[str] = set()
+
+    def register_additional_context(path: pathlib.Path, preferred_name: str) -> str:
+        if path in additional_context_names:
+            return additional_context_names[path]
+
+        name = preferred_name
+        suffix = 1
+        while name in used_context_names:
+            name = f"{preferred_name}_{suffix}"
+            suffix += 1
+
+        used_context_names.add(name)
+        additional_context_names[path] = name
+        additional_contexts[name] = str(path)
+        return name
+
+    for p in local_deps.additional_contexts:
+        if p in local_deps.real_pkgs:
+            preferred_name = local_deps.real_pkgs[p][1]
+        elif p in local_deps.faux_pkgs:
+            preferred_name = f"outer-{p.name}"
+        else:
+            raise RuntimeError(f"Unknown additional context: {p}")
+        register_additional_context(p, preferred_name)
+
     install_node_str: str = (
         "RUN /storage/install-node.sh"
         if (config.get("ui") or config.get("node_version")) and local_deps.working_dir
         else ""
     )
 
+    install_steps = [install_node_str, pip_config_file_str, pip_pkgs_str, pip_reqs_str]
+    install_steps.extend([local_pkgs_str, faux_pkgs_str])
     installs = f"{os.linesep}{os.linesep}".join(
         filter(
             None,
-            [
-                install_node_str,
-                pip_config_file_str,
-                pip_pkgs_str,
-                pip_reqs_str,
-                local_pkgs_str,
-                faux_pkgs_str,
-            ],
+            install_steps,
         )
     )
 
-    env_vars = []
-
-    if (store_config := config.get("store")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_STORE='{json.dumps(store_config)}'")
-
-    if (auth_config := config.get("auth")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_AUTH='{json.dumps(auth_config)}'")
-
-    if (encryption_config := config.get("encryption")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_ENCRYPTION='{json.dumps(encryption_config)}'")
-
-    if (http_config := config.get("http")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_HTTP='{json.dumps(http_config)}'")
-
-    # Inject webhooks configuration if provided
-    if (webhooks_config := config.get("webhooks")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_WEBHOOKS='{json.dumps(webhooks_config)}'")
-
-    if (checkpointer_config := config.get("checkpointer")) is not None:
-        env_vars.append(
-            f"ENV LANGGRAPH_CHECKPOINTER='{json.dumps(checkpointer_config)}'"
-        )
-
-    if (ui := config.get("ui")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_UI='{json.dumps(ui)}'")
-
-    if (ui_config := config.get("ui_config")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_UI_CONFIG='{json.dumps(ui_config)}'")
-
-    env_vars.append(f"ENV LANGSERVE_GRAPHS='{json.dumps(config['graphs'])}'")
+    env_vars = _build_runtime_env_vars(config)
 
     js_inst_str: str = ""
     if (config.get("ui") or config.get("node_version")) and local_deps.working_dir:
@@ -1074,7 +1246,8 @@ ADD {relpath} /deps/{name}
             [
                 "# -- Installing JS dependencies --",
                 f"ENV NODE_VERSION={config.get('node_version') or DEFAULT_NODE_VERSION}",
-                f"RUN cd {local_deps.working_dir} && {_get_node_pm_install_cmd(config_path, config)} && tsx /api/langgraph_api/js/build.mts",
+                f"WORKDIR {local_deps.working_dir}",
+                f"RUN {_get_node_pm_install_cmd(config_path.parent)} && tsx /api/langgraph_api/js/build.mts",
                 "# -- End of JS dependencies install --",
             ]
         )
@@ -1084,7 +1257,7 @@ ADD {relpath} /deps/{name}
     docker_file_contents = []
 
     # Add syntax directive if we have additional contexts (requires BuildKit frontend.contexts capability)
-    if local_deps.additional_contexts:
+    if additional_contexts:
         docker_file_contents.extend(
             [
                 "# syntax=docker/dockerfile:1.4",
@@ -1094,6 +1267,13 @@ ADD {relpath} /deps/{name}
 
     # Add main dockerfile content
     dep_vname = "$$dep" if escape_variables else "$dep"
+    local_deps_install_str = f"""RUN for dep in /deps/*; do \
+            echo "Installing {dep_vname}"; \
+            if [ -d "{dep_vname}" ]; then \
+                echo "Installing {dep_vname}"; \
+                (cd "{dep_vname}" && {global_reqs_pip_install} -e .); \
+            fi; \
+        done"""
     docker_file_contents.extend(
         [
             f"FROM {image_str}",
@@ -1103,13 +1283,7 @@ ADD {relpath} /deps/{name}
             installs,
             "",
             "# -- Installing all local dependencies --",
-            f"""RUN for dep in /deps/*; do \
-            echo "Installing {dep_vname}"; \
-            if [ -d "{dep_vname}" ]; then \
-                echo "Installing {dep_vname}"; \
-                (cd "{dep_vname}" && {global_reqs_pip_install} -e .); \
-            fi; \
-        done""",
+            local_deps_install_str,
             "# -- End of local dependencies install --",
             os.linesep.join(env_vars),
             "",
@@ -1126,16 +1300,6 @@ ADD {relpath} /deps/{name}
         ]
     )
 
-    additional_contexts: dict[str, str] = {}
-    for p in local_deps.additional_contexts:
-        if p in local_deps.real_pkgs:
-            name = local_deps.real_pkgs[p][1]
-        elif p in local_deps.faux_pkgs:
-            name = f"outer-{p.name}"
-        else:
-            raise RuntimeError(f"Unknown additional context: {p}")
-        additional_contexts[name] = str(p)
-
     return os.linesep.join(docker_file_contents), additional_contexts
 
 
@@ -1149,6 +1313,10 @@ def node_config_to_docker(
     build_context: str | None = None,
 ) -> tuple[str, dict[str, str]]:
     # Calculate paths for monorepo support
+    install_root = (
+        pathlib.Path(build_context).resolve() if build_context else config_path.parent
+    )
+    install_cmd = install_command or _get_node_pm_install_cmd(install_root)
     if build_context:
         relative_workdir = _calculate_relative_workdir(config_path, build_context)
         container_name = pathlib.Path(build_context).name
@@ -1160,60 +1328,32 @@ def node_config_to_docker(
         # Backward compatibility: use the original behavior
         faux_path = f"/deps/{config_path.parent.name}"
 
-    # Use custom install command or auto-detect
-    if install_command:
-        install_cmd = install_command
-    else:
-        install_cmd = _get_node_pm_install_cmd(config_path, config)
-
     image_str = docker_tag(config, base_image, api_version)
 
-    env_vars: list[str] = []
-
-    if (store_config := config.get("store")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_STORE='{json.dumps(store_config)}'")
-
-    if (auth_config := config.get("auth")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_AUTH='{json.dumps(auth_config)}'")
-
-    if (encryption_config := config.get("encryption")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_ENCRYPTION='{json.dumps(encryption_config)}'")
-
-    if (http_config := config.get("http")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_HTTP='{json.dumps(http_config)}'")
-
-    # Inject webhooks configuration if provided
-    if (webhooks_config := config.get("webhooks")) is not None:
-        env_vars.append(f"ENV LANGGRAPH_WEBHOOKS='{json.dumps(webhooks_config)}'")
-
-    if (checkpointer_config := config.get("checkpointer")) is not None:
-        env_vars.append(
-            f"ENV LANGGRAPH_CHECKPOINTER='{json.dumps(checkpointer_config)}'"
-        )
-
-    if ui := config.get("ui"):
-        env_vars.append(f"ENV LANGGRAPH_UI='{json.dumps(ui)}'")
-
-    if ui_config := config.get("ui_config"):
-        env_vars.append(f"ENV LANGGRAPH_UI_CONFIG='{json.dumps(ui_config)}'")
-
-    env_vars.append(f"ENV LANGSERVE_GRAPHS='{json.dumps(config['graphs'])}'")
+    env_vars = _build_runtime_env_vars(config)
 
     # For monorepo support, we need to handle install and build commands differently
     if build_context:
         # Monorepo case: install from root, build from config directory
         container_root = f"/deps/{pathlib.Path(build_context).name}"
-        install_step = f"RUN cd {container_root} && {install_cmd}"
+        install_workdir = container_root
+        install_step = f"RUN {install_cmd}"
 
         if build_command:
-            build_step = f"RUN cd {faux_path} && {build_command}"
+            build_step = f"RUN {build_command}"
         else:
             build_step = 'RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts'
     else:
         # Original behavior: everything happens in the same directory
-        install_step = f"RUN cd {faux_path} && {install_cmd}"
+        install_workdir = faux_path
+        install_step = f"RUN {install_cmd}"
         build_step = 'RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts'
 
+    if build_context:
+        build_workdir = faux_path
+    else:
+        build_workdir = faux_path
+
     docker_file_contents = [
         f"FROM {image_str}",
         "",
@@ -1221,11 +1361,13 @@ def node_config_to_docker(
         "",
         f"ADD . {faux_path if not build_context else container_root}",
         "",
+        f"WORKDIR {install_workdir}",
+        "",
         install_step,
         "",
         os.linesep.join(env_vars),
         "",
-        f"WORKDIR {faux_path}",
+        f"WORKDIR {build_workdir}",
         "",
         build_step,
     ]

libs/cli/langgraph_cli/schemas.py

@@ -1,5 +1,7 @@
 from typing import Any, Literal, TypedDict
 
+from typing_extensions import Required
+
 Distros = Literal["debian", "wolfi", "bookworm"]
 MiddlewareOrders = Literal["auth_first", "middleware_first"]
 
@@ -9,20 +11,20 @@ class TTLConfig(TypedDict, total=False):
 
     refresh_on_read: bool
     """Default behavior for refreshing TTLs on read operations (`GET` and `SEARCH`).
-    
+
     If `True`, TTLs will be refreshed on read operations (get/search) by default.
     This can be overridden per-operation by explicitly setting `refresh_ttl`.
     Defaults to `True` if not configured.
     """
     default_ttl: float | None
     """Optional. Default TTL (time-to-live) in minutes for new items.
-    
+
     If provided, all new items will have this TTL unless explicitly overridden.
     If omitted, items will have no TTL by default.
     """
     sweep_interval_minutes: int | None
     """Optional. Interval in minutes between TTL sweep iterations.
-    
+
     If provided, the store will periodically delete expired items based on the TTL.
     If omitted, no automatic sweeping will occur.
     """
@@ -36,10 +38,10 @@ class IndexConfig(TypedDict, total=False):
 
     dims: int
     """Required. Dimensionality of the embedding vectors you will store.
-    
+
     Must match the output dimension of your selected embedding model or custom embed function.
     If mismatched, you will likely encounter shape/size errors when inserting or querying vectors.
-    
+
     Common embedding model output dimensions:
         - openai:text-embedding-3-large: 3072
         - openai:text-embedding-3-small: 1536
@@ -52,7 +54,7 @@ class IndexConfig(TypedDict, total=False):
 
     embed: str
     """Required. Identifier or reference to the embedding model or a custom embedding function.
-    
+
     The format can vary:
       - "<provider>:<model_name>" for recognized providers (e.g., "openai:text-embedding-3-large")
       - "path/to/module.py:function_name" for your own local embedding function
@@ -62,17 +64,17 @@ class IndexConfig(TypedDict, total=False):
         - "openai:text-embedding-3-large"
         - "cohere:embed-multilingual-v3.0"
         - "src/app.py:embeddings"
-    
+
     Note: Must return embeddings of dimension `dims`.
     """
 
     fields: list[str] | None
     """Optional. List of JSON fields to extract before generating embeddings.
-    
+
     Defaults to ["$"], which means the entire JSON object is embedded as one piece of text.
     If you provide multiple fields (e.g. ["title", "content"]), each is extracted and embedded separately,
     often saving token usage if you only care about certain parts of the data.
-    
+
     Example:
         fields=["title", "abstract", "author.biography"]
     """
@@ -87,18 +89,18 @@ class StoreConfig(TypedDict, total=False):
 
     index: IndexConfig | None
     """Optional. Defines the vector-based semantic search configuration.
-    
+
     If provided, the store will:
       - Generate embeddings according to `index.embed`
       - Enforce the embedding dimension given by `index.dims`
       - Embed only specified JSON fields (if any) from `index.fields`
-    
+
     If omitted, no vector index is initialized.
     """
 
     ttl: TTLConfig | None
     """Optional. Defines the TTL (time-to-live) behavior configuration.
-    
+
     If provided, the store will apply TTL settings according to the configuration.
     If omitted, no TTL behavior is configured.
     """
@@ -129,11 +131,11 @@ class SerdeConfig(TypedDict, total=False):
 
     allowed_json_modules: list[list[str]] | bool | None
     """Optional. List of allowed python modules to de-serialize custom objects from JSON.
-    
+
     If provided, only the specified modules will be allowed to be deserialized.
     If omitted, no modules are allowed, and the object returned will simply be a json object OR
     a deserialized langchain object.
-    
+
     Example:
     {...
         "serde": {
@@ -178,11 +180,11 @@ class SerdeConfig(TypedDict, total=False):
             "allowed_msgpack_modules": null
         }
     }
-    
+
     """
     pickle_fallback: bool
     """Optional. Whether to allow pickling as a fallback for deserialization.
-    
+
     If True, pickling will be allowed as a fallback for deserialization.
     If False, pickling will not be allowed as a fallback for deserialization.
     Defaults to True if not configured."""
@@ -216,7 +218,7 @@ class CheckpointerConfig(TypedDict, total=False):
 
     ttl: ThreadTTLConfig | None
     """Optional. Defines the TTL (time-to-live) behavior configuration.
-    
+
     If provided, the checkpointer will apply TTL settings according to the configuration.
     If omitted, no TTL behavior is configured.
     """
@@ -239,7 +241,7 @@ class SecurityConfig(TypedDict, total=False):
 
     securitySchemes: dict[str, dict[str, Any]]
     """Describe each security scheme recognized by your OpenAPI spec.
-    
+
     Keys are scheme names (e.g. "OAuth2", "ApiKeyAuth") and values are their definitions.
     Example:
         {
@@ -256,7 +258,7 @@ class SecurityConfig(TypedDict, total=False):
     """
     security: list[dict[str, list[str]]]
     """Global security requirements across all endpoints.
-    
+
     Each element in the list maps a security scheme (e.g. "OAuth2") to a list of scopes (e.g. ["read", "write"]).
     Example:
         [
@@ -267,11 +269,11 @@ class SecurityConfig(TypedDict, total=False):
     # path => {method => security}
     paths: dict[str, dict[str, list[dict[str, list[str]]]]]
     """Path-specific security overrides.
-    
+
     Keys are path templates (e.g., "/items/{item_id}"), mapping to:
       - Keys that are HTTP methods (e.g., "GET", "POST"),
       - Values are lists of security definitions (just like `security`) for that method.
-    
+
     Example:
         {
             "/private_data": {
@@ -285,19 +287,19 @@ class SecurityConfig(TypedDict, total=False):
 class CacheConfig(TypedDict, total=False):
     cache_keys: list[str]
     """Optional. List of header keys to use for caching.
-    
+
     Example:
         ["user_id", "workspace_id"]
     """
     ttl_seconds: int
     """Optional. Time-to-live in seconds for cached items.
-    
+
     Example:
         3600
     """
     max_size: int
     """Optional. Maximum size of the cache.
-    
+
     Example:
         100
     """
@@ -308,19 +310,19 @@ class AuthConfig(TypedDict, total=False):
 
     path: str
     """Required. Path to an instance of the Auth() class that implements custom authentication.
-    
+
     Format: "path/to/file.py:my_auth"
     """
     disable_studio_auth: bool
-    """Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio. 
-    
+    """Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio.
+
     Defaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header
     value is a valid API key for the deployment's workspace. If `True`, all requests will go through your custom
     authentication logic, regardless of origin of the request.
     """
     openapi: SecurityConfig
     """The security configuration to include in your server's OpenAPI spec.
-    
+
     Example (OAuth2):
         {
             "securitySchemes": {
@@ -341,7 +343,7 @@ class AuthConfig(TypedDict, total=False):
     """
     cache: CacheConfig
     """Optional. Cache configuration for the server.
-    
+
     Example:
         {
             "cache_keys": ["user_id", "workspace_id"],
@@ -380,32 +382,32 @@ class CorsConfig(TypedDict, total=False):
 
     allow_origins: list[str]
     """Optional. List of allowed origins (e.g., "https://example.com").
-    
-    Default is often an empty list (no external origins). 
+
+    Default is often an empty list (no external origins).
     Use "*" only if you trust all origins, as that bypasses most restrictions.
     """
     allow_methods: list[str]
     """Optional. HTTP methods permitted for cross-origin requests (e.g. ["GET", "POST"]).
-    
+
     Default might be ["GET", "POST", "OPTIONS"] depending on your server framework.
     """
     allow_headers: list[str]
     """Optional. HTTP headers that can be used in cross-origin requests (e.g. ["Content-Type", "Authorization"])."""
     allow_credentials: bool
     """Optional. If `True`, cross-origin requests can include credentials (cookies, auth headers).
-    
+
     Default False to avoid accidentally exposing secured endpoints to untrusted sites.
     """
     allow_origin_regex: str
     """Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.
-    
+
     Example: "^https://.*\\.mycompany\\.com$"
     """
     expose_headers: list[str]
     """Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."""
     max_age: int
     """Optional. How many seconds the browser may cache preflight responses.
-    
+
     Default might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.
     """
 
@@ -442,61 +444,61 @@ class HttpConfig(TypedDict, total=False):
 
     app: str
     """Optional. Import path to a custom Starlette/FastAPI application to mount.
-    
+
     Format: "path/to/module.py:app_var"
     If provided, it can override or extend the default routes.
     """
     disable_assistants: bool
     """Optional. If `True`, /assistants routes are removed from the server.
-    
+
     Default is False (meaning /assistants is enabled).
     """
     disable_threads: bool
     """Optional. If `True`, /threads routes are removed.
-    
+
     Default is False.
     """
     disable_runs: bool
     """Optional. If `True`, /runs routes are removed.
-    
+
     Default is False.
     """
     disable_store: bool
     """Optional. If `True`, /store routes are removed, disabling direct store interactions via HTTP.
-    
+
     Default is False.
     """
     disable_mcp: bool
     """Optional. If `True`, /mcp routes are removed, disabling default support to expose the deployment as an MCP server.
-    
+
     Default is False.
     """
     disable_a2a: bool
     """Optional. If `True`, /a2a routes are removed, disabling default support to expose the deployment as an agent-to-agent (A2A) server.
-    
+
     Default is False.
     """
     disable_meta: bool
     """Optional. Remove meta endpoints.
-    
+
     Set to True to disable the following endpoints: /openapi.json, /info, /metrics, /docs.
     This will also make the /ok endpoint skip any DB or other checks, always returning {"ok": True}.
-    
+
     Default is False.
     """
     disable_ui: bool
     """Optional. If `True`, /ui routes are removed, disabling the UI server.
-    
+
     Default is False.
     """
     disable_webhooks: bool
     """Optional. If `True`, webhooks are disabled. Runs created with an associated webhook will
     still be executed, but the webhook event will not be sent.
-    
+
     Default is False.
     """
     cors: CorsConfig | None
-    """Optional. Defines CORS restrictions. If omitted, no special rules are set and 
+    """Optional. Defines CORS restrictions. If omitted, no special rules are set and
     cross-origin behavior depends on default server settings.
     """
     configurable_headers: ConfigurableHeaderConfig | None
@@ -527,7 +529,7 @@ class HttpConfig(TypedDict, total=False):
     """
     mount_prefix: str
     """Optional. URL prefix to prepend to all the routes.
-    
+
     Example:
         "/api"
     """
@@ -588,11 +590,33 @@ class WebhooksConfig(TypedDict, total=False):
     """
 
 
+class UvSource(TypedDict, total=False):
+    """Deployment source rooted at a uv project or workspace."""
+
+    kind: Required[Literal["uv"]]
+    """Discriminator for uv-backed deployment mode."""
+
+    root: str
+    """Relative path from langgraph.json to the authoritative uv project root.
+
+    The resolved directory must contain `pyproject.toml` and `uv.lock`. If the
+    root is a workspace, package discovery happens within this root.
+    """
+
+    package: str
+    """Optional. Workspace package name to deploy when the target is ambiguous.
+
+    If omitted, the CLI tries to infer the target package from the location of
+    `langgraph.json`, or falls back to the only package if the root contains
+    exactly one candidate.
+    """
+
+
 class Config(TypedDict, total=False):
     """Top-level config for langgraph-cli or similar deployment tooling."""
 
     python_version: str
-    """Optional. Python version in 'major.minor' format (e.g. '3.11'). 
+    """Optional. Python version in 'major.minor' format (e.g. '3.11').
     Must be at least 3.11 or greater for this deployment to function properly.
     """
 
@@ -603,7 +627,7 @@ class Config(TypedDict, total=False):
 
     api_version: str | None
     """Optional. Which semantic version of the LangGraph API server to use.
-    
+
     Defaults to latest. Check the
     [changelog](https://docs.langchain.com/langgraph-platform/langgraph-server-changelog)
     for more information."""
@@ -614,12 +638,12 @@ class Config(TypedDict, total=False):
 
     base_image: str | None
     """Optional. Base image to use for the LangGraph API server.
-    
+
     Defaults to langchain/langgraph-api or langchain/langgraphjs-api."""
 
     image_distro: Distros | None
     """Optional. Linux distribution for the base image.
-    
+
     Must be one of 'wolfi', 'debian', or 'bookworm'.
     If omitted, defaults to 'debian' ('latest').
     """
@@ -627,22 +651,30 @@ class Config(TypedDict, total=False):
     pip_config_file: str | None
     """Optional. Path to a pip config file (e.g., "/etc/pip.conf" or "pip.ini") for controlling
     package installation (custom indices, credentials, etc.).
-    
+
     Only relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.
     """
 
     pip_installer: str | None
-    """Optional. Python package installer to use ('auto', 'pip', 'uv').
-    
+    """Optional. Python package installer to use ('auto', 'pip', or 'uv').
+
     - 'auto' (default): Use uv for supported base images, otherwise pip
     - 'pip': Force use of pip regardless of base image support
     - 'uv': Force use of uv (will fail if base image doesn't support it)
     """
 
+    source: UvSource | None
+    """Optional. Explicit deployment source configuration.
+
+    Use `{ "kind": "uv", "root": "." }` to deploy from a uv project rooted at
+    `root/pyproject.toml` and `root/uv.lock`. If `root` is a workspace and the
+    target is ambiguous, set `package` to the desired workspace member.
+    """
+
     dockerfile_lines: list[str]
     """Optional. Additional Docker instructions that will be appended to your base Dockerfile.
-    
-    Useful for installing OS packages, setting environment variables, etc. 
+
+    Useful for installing OS packages, setting environment variables, etc.
     Example:
         dockerfile_lines=[
             "RUN apt-get update && apt-get install -y libmagic-dev",
@@ -652,12 +684,14 @@ class Config(TypedDict, total=False):
 
     dependencies: list[str]
     """List of Python dependencies to install, either from PyPI or local paths.
-    
+
     Examples:
       - "." or "./src" if you have a local Python package
       - str (aka "anthropic") for a PyPI package
       - "git+https://github.com/org/repo.git@main" for a Git-based package
     Defaults to an empty list, meaning no additional packages installed beyond your base environment.
+
+    This field is not supported when `source.kind` is `uv`.
     """
 
     graphs: dict[str, str | GraphDef]
@@ -682,10 +716,10 @@ class Config(TypedDict, total=False):
 
     env: dict[str, str] | str
     """Optional. Environment variables to set for your deployment.
-    
+
     - If given as a dict, keys are variable names and values are their values.
     - If given as a string, it must be a path to a file containing lines in KEY=VALUE format.
-    
+
     Example as a dict:
         env={"API_TOKEN": "abc123", "DEBUG": "true"}
     Example as a file path:
@@ -694,13 +728,13 @@ class Config(TypedDict, total=False):
 
     store: StoreConfig | None
     """Optional. Configuration for the built-in long-term memory store, including semantic search indexing.
-    
+
     If omitted, no vector index is set up (the object store will still be present, however).
     """
 
     checkpointer: CheckpointerConfig | None
     """Optional. Configuration for the built-in checkpointer, which handles checkpointing of state.
-    
+
     If omitted, no checkpointer is set up (the object store will still be present, however).
     """
 
@@ -733,7 +767,7 @@ class Config(TypedDict, total=False):
 
     keep_pkg_tools: bool | list[str] | None
     """Optional. Control whether to retain Python packaging tools in the final image.
-    
+
     Allowed tools are: "pip", "setuptools", "wheel".
     You can also set to true to include all packaging tools.
     """

libs/cli/pyproject.toml

@@ -17,18 +17,19 @@ dependencies = [
     "langgraph-sdk>=0.1.0 ; python_version >= '3.11'",
     "pathspec>=0.11.0",
     "python-dotenv>=0.8.0",
+    "tomli>=2.0.1 ; python_version < '3.11'",
 ]
 [tool.hatch.version]
 path = "langgraph_cli/__init__.py"
 [project.optional-dependencies]
 inmem = [
-    "langgraph-api>=0.5.35,<0.8.0 ; python_version >= '3.11'",
+    "langgraph-api>=0.5.35,<0.9.0 ; python_version >= '3.11'",
     "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
 ]
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/cli"
-Twitter = "https://x.com/LangChain"
+Twitter = "https://x.com/langchain_oss"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/cli/schemas/schema.json

@@ -184,13 +184,28 @@
             "pip_installer": {
               "anyOf": [
                 {
-                  "type": "string"
+                  "type": "string",
+                  "enum": [
+                    "auto",
+                    "pip",
+                    "uv"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ]
+            },
+            "source": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/UvSource"
                 },
                 {
                   "type": "null"
                 }
               ],
-              "description": "Optional. Python package installer to use ('auto', 'pip', 'uv').\n\n"
+              "description": "Optional. Explicit deployment source configuration.\n\n`root/pyproject.toml` and `root/uv.lock`. If `root` is a workspace and the\ntarget is ambiguous, set `package` to the desired workspace member.\n"
             },
             "store": {
               "anyOf": [
@@ -234,6 +249,240 @@
             "graphs"
           ]
         },
+        {
+          "type": "object",
+          "properties": {
+            "python_version": {
+              "type": "string",
+              "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
+              "enum": [
+                "3.11",
+                "3.12",
+                "3.13"
+              ]
+            },
+            "pip_config_file": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Path to a pip config file (e.g., \"/etc/pip.conf\" or \"pip.ini\") for controlling\npackage installation (custom indices, credentials, etc.).\n\nOnly relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.\n"
+            },
+            "_INTERNAL_docker_tag": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Internal use only.\n"
+            },
+            "api_version": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
+            },
+            "auth": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/AuthConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
+            },
+            "base_image": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Base image to use for the LangGraph API server.\n\nDefaults to langchain/langgraph-api or langchain/langgraphjs-api.\n"
+            },
+            "checkpointer": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/CheckpointerConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in checkpointer, which handles checkpointing of state.\n\nIf omitted, no checkpointer is set up (the object store will still be present, however).\n"
+            },
+            "dependencies": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
+            },
+            "dockerfile_lines": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
+            },
+            "encryption": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/EncryptionConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom at-rest encryption config, including the path to your Python encryption logic.\n\nAllows you to implement custom encryption for sensitive data stored in the database.\n"
+            },
+            "env": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "string"
+                }
+              ],
+              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
+            },
+            "graphs": {
+              "type": "object",
+              "additionalProperties": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "$ref": "#/$defs/GraphDef"
+                  }
+                ]
+              },
+              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n\nor objects with a \"path\" key and optional \"description\" key."
+            },
+            "http": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/HttpConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
+            },
+            "image_distro": {
+              "anyOf": [
+                {
+                  "enum": [
+                    "bookworm",
+                    "debian",
+                    "wolfi"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+            },
+            "keep_pkg_tools": {
+              "anyOf": [
+                {
+                  "type": "boolean"
+                },
+                {
+                  "type": "array",
+                  "items": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Control whether to retain Python packaging tools in the final image.\n\nYou can also set to true to include all packaging tools.\n"
+            },
+            "pip_installer": {
+              "anyOf": [
+                {
+                  "type": "string",
+                  "enum": [
+                    "auto",
+                    "pip",
+                    "uv"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ]
+            },
+            "source": {
+              "$ref": "#/$defs/UvSource"
+            },
+            "store": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/StoreConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
+            },
+            "ui": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.\n"
+            },
+            "webhooks": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/WebhooksConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Webhooks configuration for outbound event delivery.\n\nForwarded into the container as `LANGGRAPH_WEBHOOKS`. See `WebhooksConfig`\nfor URL policy and header templating details.\n"
+            }
+          },
+          "required": [
+            "graphs",
+            "source"
+          ]
+        },
         {
           "type": "object",
           "properties": {
@@ -405,13 +654,28 @@
             "pip_installer": {
               "anyOf": [
                 {
-                  "type": "string"
+                  "type": "string",
+                  "enum": [
+                    "auto",
+                    "pip",
+                    "uv"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ]
+            },
+            "source": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/UvSource"
                 },
                 {
                   "type": "null"
                 }
               ],
-              "description": "Optional. Python package installer to use ('auto', 'pip', 'uv').\n\n"
+              "description": "Optional. Explicit deployment source configuration.\n\n`root/pyproject.toml` and `root/uv.lock`. If `root` is a workspace and the\ntarget is ambiguous, set `package` to the desired workspace member.\n"
             },
             "store": {
               "anyOf": [
@@ -906,6 +1170,27 @@
       },
       "required": []
     },
+    "UvSource": {
+      "title": "UvSource",
+      "description": "Deployment source rooted at a uv project or workspace.",
+      "type": "object",
+      "properties": {
+        "kind": {
+          "enum": [
+            "uv"
+          ]
+        },
+        "package": {
+          "type": "string"
+        },
+        "root": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "kind"
+      ]
+    },
     "StoreConfig": {
       "title": "StoreConfig",
       "description": "Configuration for the built-in long-term memory store.\n\nThis store can optionally perform semantic search. If you omit `index`,\nthe store will just handle traditional (non-embedded) data without vector lookups.",

libs/cli/schemas/schema.v0.json

@@ -184,13 +184,28 @@
             "pip_installer": {
               "anyOf": [
                 {
-                  "type": "string"
+                  "type": "string",
+                  "enum": [
+                    "auto",
+                    "pip",
+                    "uv"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ]
+            },
+            "source": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/UvSource"
                 },
                 {
                   "type": "null"
                 }
               ],
-              "description": "Optional. Python package installer to use ('auto', 'pip', 'uv').\n\n"
+              "description": "Optional. Explicit deployment source configuration.\n\n`root/pyproject.toml` and `root/uv.lock`. If `root` is a workspace and the\ntarget is ambiguous, set `package` to the desired workspace member.\n"
             },
             "store": {
               "anyOf": [
@@ -234,6 +249,240 @@
             "graphs"
           ]
         },
+        {
+          "type": "object",
+          "properties": {
+            "python_version": {
+              "type": "string",
+              "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
+              "enum": [
+                "3.11",
+                "3.12",
+                "3.13"
+              ]
+            },
+            "pip_config_file": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Path to a pip config file (e.g., \"/etc/pip.conf\" or \"pip.ini\") for controlling\npackage installation (custom indices, credentials, etc.).\n\nOnly relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.\n"
+            },
+            "_INTERNAL_docker_tag": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Internal use only.\n"
+            },
+            "api_version": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
+            },
+            "auth": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/AuthConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
+            },
+            "base_image": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Base image to use for the LangGraph API server.\n\nDefaults to langchain/langgraph-api or langchain/langgraphjs-api.\n"
+            },
+            "checkpointer": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/CheckpointerConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in checkpointer, which handles checkpointing of state.\n\nIf omitted, no checkpointer is set up (the object store will still be present, however).\n"
+            },
+            "dependencies": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
+            },
+            "dockerfile_lines": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
+            },
+            "encryption": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/EncryptionConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom at-rest encryption config, including the path to your Python encryption logic.\n\nAllows you to implement custom encryption for sensitive data stored in the database.\n"
+            },
+            "env": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "string"
+                }
+              ],
+              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
+            },
+            "graphs": {
+              "type": "object",
+              "additionalProperties": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "$ref": "#/$defs/GraphDef"
+                  }
+                ]
+              },
+              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n\nor objects with a \"path\" key and optional \"description\" key."
+            },
+            "http": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/HttpConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
+            },
+            "image_distro": {
+              "anyOf": [
+                {
+                  "enum": [
+                    "bookworm",
+                    "debian",
+                    "wolfi"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+            },
+            "keep_pkg_tools": {
+              "anyOf": [
+                {
+                  "type": "boolean"
+                },
+                {
+                  "type": "array",
+                  "items": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Control whether to retain Python packaging tools in the final image.\n\nYou can also set to true to include all packaging tools.\n"
+            },
+            "pip_installer": {
+              "anyOf": [
+                {
+                  "type": "string",
+                  "enum": [
+                    "auto",
+                    "pip",
+                    "uv"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ]
+            },
+            "source": {
+              "$ref": "#/$defs/UvSource"
+            },
+            "store": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/StoreConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
+            },
+            "ui": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.\n"
+            },
+            "webhooks": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/WebhooksConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Webhooks configuration for outbound event delivery.\n\nForwarded into the container as `LANGGRAPH_WEBHOOKS`. See `WebhooksConfig`\nfor URL policy and header templating details.\n"
+            }
+          },
+          "required": [
+            "graphs",
+            "source"
+          ]
+        },
         {
           "type": "object",
           "properties": {
@@ -405,13 +654,28 @@
             "pip_installer": {
               "anyOf": [
                 {
-                  "type": "string"
+                  "type": "string",
+                  "enum": [
+                    "auto",
+                    "pip",
+                    "uv"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ]
+            },
+            "source": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/UvSource"
                 },
                 {
                   "type": "null"
                 }
               ],
-              "description": "Optional. Python package installer to use ('auto', 'pip', 'uv').\n\n"
+              "description": "Optional. Explicit deployment source configuration.\n\n`root/pyproject.toml` and `root/uv.lock`. If `root` is a workspace and the\ntarget is ambiguous, set `package` to the desired workspace member.\n"
             },
             "store": {
               "anyOf": [
@@ -906,6 +1170,27 @@
       },
       "required": []
     },
+    "UvSource": {
+      "title": "UvSource",
+      "description": "Deployment source rooted at a uv project or workspace.",
+      "type": "object",
+      "properties": {
+        "kind": {
+          "enum": [
+            "uv"
+          ]
+        },
+        "package": {
+          "type": "string"
+        },
+        "root": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "kind"
+      ]
+    },
     "StoreConfig": {
       "title": "StoreConfig",
       "description": "Configuration for the built-in long-term memory store.\n\nThis store can optionally perform semantic search. If you omit `index`,\nthe store will just handle traditional (non-embedded) data without vector lookups.",

libs/cli/tests/unit_tests/test_archive.py

@@ -99,6 +99,13 @@ class TestBuildIgnoreSpec:
         assert spec.match_file("app.log")
         assert spec.match_file("mod.pyc")
 
+    def test_can_skip_gitignore(self, tmp_path):
+        (tmp_path / ".dockerignore").write_text("*.log\n")
+        (tmp_path / ".gitignore").write_text("*.pyc\n")
+        spec = _build_ignore_spec(tmp_path, include_gitignore=False)
+        assert spec.match_file("app.log")
+        assert not spec.match_file("mod.pyc")
+
     def test_no_ignore_files_only_builtins(self, tmp_path):
         spec = _build_ignore_spec(tmp_path)
         assert spec.match_file("__pycache__/")

libs/cli/uv-examples/monorepo/apps/agent/.env.example

@@ -0,0 +1 @@
+OPENAI_API_KEY=

libs/cli/uv-examples/monorepo/apps/agent/langgraph.json

@@ -0,0 +1,12 @@
+{
+  "python_version": "3.12",
+  "graphs": {
+    "agent": "./src/agent/graph.py:graph"
+  },
+  "source": {
+    "kind": "uv",
+    "root": "../..",
+    "package": "agent"
+  },
+  "env": ".env"
+}

libs/cli/uv-examples/monorepo/apps/agent/pyproject.toml

@@ -0,0 +1,20 @@
+[project]
+name = "agent"
+version = "0.0.1"
+description = "Agent for the uv monorepo example"
+requires-python = ">=3.11"
+dependencies = [
+    "langgraph>=0.6.0,<2",
+    "langchain-core>=0.2.14",
+    "shared",
+]
+
+[build-system]
+requires = ["setuptools>=73.0.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+packages = ["agent"]
+
+[tool.setuptools.package-dir]
+"agent" = "src/agent"

libs/cli/uv-examples/monorepo/apps/agent/src/agent/graph.py

@@ -0,0 +1,31 @@
+from collections.abc import Sequence
+from typing import Annotated, TypedDict
+
+from langchain_core.messages import AIMessage, BaseMessage
+from langgraph.graph import END, START, StateGraph
+from langgraph.graph.message import add_messages
+from shared import get_dummy_message
+
+
+class State(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+def call_model(state: State) -> dict:
+    dummy_message = get_dummy_message()
+    message = AIMessage(content=f"Agent says: {dummy_message}")
+    return {"messages": [message]}
+
+
+def should_continue(state: State):
+    if len(state["messages"]) > 0:
+        return END
+    return "call_model"
+
+
+workflow = StateGraph(State)
+workflow.add_node("call_model", call_model)
+workflow.add_edge(START, "call_model")
+workflow.add_conditional_edges("call_model", should_continue)
+
+graph = workflow.compile()

libs/cli/uv-examples/monorepo/libs/shared/pyproject.toml

@@ -0,0 +1,16 @@
+[project]
+name = "shared"
+version = "0.0.1"
+description = "Shared utilities for the uv monorepo example"
+requires-python = ">=3.11"
+dependencies = []
+
+[build-system]
+requires = ["setuptools>=73.0.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+packages = ["shared"]
+
+[tool.setuptools.package-dir]
+"shared" = "src/shared"

libs/cli/uv-examples/monorepo/libs/shared/src/shared/__init__.py

@@ -0,0 +1,3 @@
+from .utils import get_dummy_message
+
+__all__ = ["get_dummy_message"]

libs/cli/uv-examples/monorepo/libs/shared/src/shared/utils.py

@@ -0,0 +1,2 @@
+def get_dummy_message() -> str:
+    return "Hello from shared library!"

libs/cli/uv-examples/monorepo/pyproject.toml

@@ -0,0 +1,22 @@
+[project]
+name = "uv-monorepo-example"
+version = "0.0.1"
+description = "uv workspace monorepo example for LangGraph CLI integration test"
+requires-python = ">=3.11"
+dependencies = [
+    "langgraph>=0.6.0,<2",
+    "langchain-core>=0.2.14",
+]
+
+[tool.uv.workspace]
+members = ["apps/*", "libs/*"]
+
+[tool.uv.sources]
+shared = { workspace = true }
+
+[tool.uv]
+package = false
+
+[build-system]
+requires = ["setuptools>=73.0.0", "wheel"]
+build-backend = "setuptools.build_meta"

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

@@ -0,0 +1,893 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+
+[manifest]
+members = [
+    "agent",
+    "shared",
+    "uv-monorepo-example",
+]
+
+[[package]]
+name = "agent"
+version = "0.0.1"
+source = { editable = "apps/agent" }
+dependencies = [
+    { name = "langchain-core" },
+    { name = "langgraph" },
+    { name = "shared" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "langchain-core", specifier = ">=0.2.14" },
+    { name = "langgraph", specifier = ">=0.6.0,<2" },
+    { name = "shared", editable = "libs/shared" },
+]
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
+]
+
+[[package]]
+name = "anyio"
+version = "4.13.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "idna" },
+    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
+]
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libs/cli/uv-examples/simple/.env.example

@@ -0,0 +1 @@
+OPENAI_API_KEY=

libs/cli/uv-examples/simple/langgraph.json

@@ -0,0 +1,11 @@
+{
+  "python_version": "3.12",
+  "graphs": {
+    "agent": "./src/agent/graph.py:graph"
+  },
+  "source": {
+    "kind": "uv",
+    "root": "."
+  },
+  "env": ".env"
+}

libs/cli/uv-examples/simple/pyproject.toml

@@ -0,0 +1,19 @@
+[project]
+name = "simple-uv-agent"
+version = "0.1.0"
+description = "Simple single-package uv example for LangGraph CLI integration test"
+requires-python = ">=3.11"
+dependencies = [
+    "langgraph>=0.6.0,<2",
+    "langchain-core>=0.2.14",
+]
+
+[build-system]
+requires = ["setuptools>=73.0.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+packages = ["agent"]
+
+[tool.setuptools.package-dir]
+"agent" = "src/agent"

libs/cli/uv-examples/simple/src/agent/graph.py

@@ -0,0 +1,29 @@
+from collections.abc import Sequence
+from typing import Annotated, TypedDict
+
+from langchain_core.messages import AIMessage, BaseMessage
+from langgraph.graph import END, START, StateGraph
+from langgraph.graph.message import add_messages
+
+
+class State(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+def call_model(state: State) -> dict:
+    message = AIMessage(content="Hello from simple uv agent!")
+    return {"messages": [message]}
+
+
+def should_continue(state: State):
+    if len(state["messages"]) > 0:
+        return END
+    return "call_model"
+
+
+workflow = StateGraph(State)
+workflow.add_node("call_model", call_model)
+workflow.add_edge(START, "call_model")
+workflow.add_conditional_edges("call_model", should_continue)
+
+graph = workflow.compile()

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libs/langgraph/README.md

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

libs/langgraph/langgraph/_internal/_config.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from collections import ChainMap
-from collections.abc import Mapping, Sequence
+from collections.abc import Sequence
 from os import getenv
 from typing import Any, cast
 
@@ -76,32 +76,6 @@ def patch_checkpoint_map(
         return config
 
 
-def _merge_callbacks(base: Callbacks, new: Callbacks) -> Callbacks:
-    # callbacks can be either None, list[handler] or manager
-    # so merging two callbacks values has 6 cases
-    if base is None:
-        if isinstance(new, (list, BaseCallbackManager)):
-            return new.copy()
-        return new
-    if isinstance(new, list):
-        if isinstance(base, list):
-            return base + new
-        if isinstance(base, BaseCallbackManager):
-            mngr = base.copy()
-            for cb in new:
-                mngr.add_handler(cb, inherit=True)
-            return mngr
-    elif isinstance(new, BaseCallbackManager):
-        if isinstance(base, list):
-            mngr = new.copy()
-            for cb in base:
-                mngr.add_handler(cb, inherit=True)
-            return mngr
-        if isinstance(base, BaseCallbackManager):
-            return base.merge(new)
-    raise NotImplementedError(f"Unsupported callback types: {type(base)}, {type(new)}")
-
-
 def merge_configs(*configs: RunnableConfig | None) -> RunnableConfig:
     """Merge multiple configs into one.
 
@@ -136,9 +110,34 @@ def merge_configs(*configs: RunnableConfig | None) -> RunnableConfig:
                 else:
                     base[key] = value
             elif key == "callbacks":
-                base["callbacks"] = _merge_callbacks(
-                    base.get("callbacks"), cast(Callbacks, value)
-                )
+                base_callbacks = base.get("callbacks")
+                # callbacks can be either None, list[handler] or manager
+                # so merging two callbacks values has 6 cases
+                if isinstance(value, list):
+                    if base_callbacks is None:
+                        base["callbacks"] = value.copy()
+                    elif isinstance(base_callbacks, list):
+                        base["callbacks"] = base_callbacks + value
+                    else:
+                        # base_callbacks is a manager
+                        mngr = base_callbacks.copy()
+                        for callback in value:
+                            mngr.add_handler(callback, inherit=True)
+                        base["callbacks"] = mngr
+                elif isinstance(value, BaseCallbackManager):
+                    # value is a manager
+                    if base_callbacks is None:
+                        base["callbacks"] = value.copy()
+                    elif isinstance(base_callbacks, list):
+                        mngr = value.copy()
+                        for callback in base_callbacks:
+                            mngr.add_handler(callback, inherit=True)
+                        base["callbacks"] = mngr
+                    else:
+                        # base_callbacks is also a manager
+                        base["callbacks"] = base_callbacks.merge(value)
+                else:
+                    raise NotImplementedError
             elif key == "recursion_limit":
                 if config["recursion_limit"] != DEFAULT_RECURSION_LIMIT:
                     base["recursion_limit"] = config["recursion_limit"]
@@ -218,14 +217,16 @@ def get_callback_manager_for_config(
             callbacks.add_tags(all_tags)
         if metadata := config.get("metadata"):
             callbacks.add_metadata(metadata)
-        return callbacks
+        manager = callbacks
     else:
         # otherwise create a new manager
-        return CallbackManager.configure(
+        manager = CallbackManager.configure(
             inheritable_callbacks=config.get("callbacks"),
             inheritable_tags=all_tags,
             inheritable_metadata=config.get("metadata"),
+            langsmith_inheritable_metadata=_get_tracing_metadata_defaults(config),
         )
+    return manager
 
 
 def get_async_callback_manager_for_config(
@@ -256,14 +257,16 @@ def get_async_callback_manager_for_config(
             callbacks.add_tags(all_tags)
         if metadata := config.get("metadata"):
             callbacks.add_metadata(metadata)
-        return callbacks
+        manager = callbacks
     else:
         # otherwise create a new manager
-        return AsyncCallbackManager.configure(
+        manager = AsyncCallbackManager.configure(
             inheritable_callbacks=config.get("callbacks"),
             inheritable_tags=all_tags,
             inheritable_metadata=config.get("metadata"),
+            langsmith_inheritable_metadata=_get_tracing_metadata_defaults(config),
         )
+    return manager
 
 
 def _is_not_empty(value: Any) -> bool:
@@ -304,29 +307,59 @@ def ensure_config(*configs: RunnableConfig | None) -> RunnableConfig:
             if _is_not_empty(v) and k in CONFIG_KEYS:
                 if k == CONF:
                     empty[k] = cast(dict, v).copy()
-                elif k == "callbacks" and isinstance(v, (list, BaseCallbackManager)):
-                    empty["callbacks"] = _merge_callbacks(empty.get("callbacks"), v)
                 else:
                     empty[k] = v  # type: ignore[literal-required]
         for k, v in config.items():
             if _is_not_empty(v) and k not in CONFIG_KEYS:
                 empty[CONF][k] = v
-    _empty_metadata = empty["metadata"]
-    for key, value in empty[CONF].items():
-        if _exclude_as_metadata(key, value, _empty_metadata):
-            continue
-        _empty_metadata[key] = value
+
+    configurable = empty.get("configurable")
+    metadata = empty.get("metadata")
+    if configurable and metadata is not None:
+        for key in _PROPAGATE_TO_METADATA:
+            if key in metadata:
+                continue
+            value = configurable.get(key)
+            if value:
+                metadata[key] = value
     return empty
 
 
 _OMIT = ("key", "token", "secret", "password", "auth")
 
 
-def _exclude_as_metadata(key: str, value: Any, metadata: Mapping[str, Any]) -> bool:
+def _exclude_as_metadata(key: str, value: Any) -> bool:
     key_lower = key.casefold()
     return (
         key.startswith("__")
         or not isinstance(value, (str, int, float, bool))
-        or key in metadata
         or any(substr in key_lower for substr in _OMIT)
     )
+
+
+def _get_tracing_metadata_defaults(
+    config: RunnableConfig,
+) -> dict[str, Any] | None:
+    """Get tracer-only metadata defaults from configurable values."""
+    configurable = config.get("configurable")
+    if not configurable:
+        return None
+    metadata: dict[str, Any] = {}
+    for key, value in configurable.items():
+        if _exclude_as_metadata(key, value):
+            continue
+        metadata[key] = value
+    return metadata or None
+
+
+_PROPAGATE_TO_METADATA = frozenset(
+    (
+        "thread_id",
+        "checkpoint_id",
+        "checkpoint_ns",
+        "task_id",
+        "run_id",
+        "assistant_id",
+        "graph_id",
+    )
+)

libs/langgraph/langgraph/_internal/_constants.py

@@ -12,6 +12,9 @@ RESUME = sys.intern("__resume__")
 # for values passed to resume a node after an interrupt
 ERROR = sys.intern("__error__")
 # for errors raised by nodes
+ERROR_SOURCE_NODE = sys.intern("__error_source_node__")
+# failed source node name for node-level error handlers
+# value format in pending writes: `(task_id, ERROR_SOURCE_NODE, node_name: str)`
 NO_WRITES = sys.intern("__no_writes__")
 # marker to signal node didn't write anything
 TASKS = sys.intern("__pregel_tasks")
@@ -56,6 +59,8 @@ CONFIG_KEY_CHECKPOINT_NS = sys.intern("checkpoint_ns")
 # holds the current checkpoint_ns, "" for root graph
 CONFIG_KEY_NODE_FINISHED = sys.intern("__pregel_node_finished")
 # holds a callback to be called when a node is finished
+CONFIG_KEY_TIMED_ATTEMPT_OBSERVER = sys.intern("__pregel_timed_attempt_observer")
+# holds a callback to be called when an idle-timed node attempt starts or finishes
 CONFIG_KEY_SCRATCHPAD = sys.intern("__pregel_scratchpad")
 # holds a mutable dict for temporary storage scoped to the current task
 CONFIG_KEY_RUNNER_SUBMIT = sys.intern("__pregel_runner_submit")
@@ -66,6 +71,13 @@ CONFIG_KEY_RUNTIME = sys.intern("__pregel_runtime")
 # holds a `Runtime` instance with context, store, stream writer, etc.
 CONFIG_KEY_RESUME_MAP = sys.intern("__pregel_resume_map")
 # holds a mapping of task ns -> resume value for resuming tasks
+CONFIG_KEY_STREAM_MESSAGES_V2 = sys.intern("__pregel_stream_messages_v2")
+# when True, attach StreamMessagesHandlerV2 so content-block (v2) events
+# flow through stream_mode="messages"; set by StreamingHandler only.
+CONFIG_KEY_NODE_ERROR = sys.intern("__pregel_node_error")
+# holds a `NodeError` (failed source node + exception) for the current
+# node-level error handler invocation, injected when handler signature
+# requests `error: NodeError`
 
 # --- Other constants ---
 PUSH = sys.intern("__pregel_push")
@@ -93,6 +105,7 @@ RESERVED = {
     INTERRUPT,
     RESUME,
     ERROR,
+    ERROR_SOURCE_NODE,
     NO_WRITES,
     # reserved config.configurable keys
     CONFIG_KEY_SEND,
@@ -106,7 +119,9 @@ RESERVED = {
     CONFIG_KEY_CHECKPOINT_MAP,
     CONFIG_KEY_CHECKPOINT_ID,
     CONFIG_KEY_CHECKPOINT_NS,
+    CONFIG_KEY_TIMED_ATTEMPT_OBSERVER,
     CONFIG_KEY_RESUME_MAP,
+    CONFIG_KEY_STREAM_MESSAGES_V2,
     # other constants
     PUSH,
     PULL,

libs/langgraph/langgraph/_internal/_runnable.py

@@ -51,9 +51,11 @@ from langgraph._internal._config import (
 )
 from langgraph._internal._constants import (
     CONF,
+    CONFIG_KEY_NODE_ERROR,
     CONFIG_KEY_RUNTIME,
 )
 from langgraph._internal._typing import MISSING
+from langgraph.errors import NodeError
 from langgraph.types import StreamWriter
 
 try:
@@ -117,6 +119,19 @@ def set_config_context(
         ctx.run(_unset_config_context, config_token, run)
 
 
+def create_task_in_config_context(
+    coro_factory: Callable[[], Coroutine[Any, Any, Any]], config: RunnableConfig
+) -> asyncio.Task[Any]:
+    """Create an asyncio.Task that inherits `config` as the child runnable context.
+
+    `asyncio.create_task` snapshots the current contextvars onto the new task,
+    so calling `create_task` while the config context is set ensures the task
+    sees `config` via `var_child_runnable_config` and any tracing parent.
+    """
+    with set_config_context(config) as context:
+        return context.run(lambda: asyncio.create_task(coro_factory()))
+
+
 # Before Python 3.11 native StrEnum is not available
 class StrEnum(str, enum.Enum):
     """A string enum."""
@@ -181,6 +196,15 @@ KWARGS_CONFIG_KEYS: tuple[tuple[str, tuple[Any, ...], str, Any], ...] = (
         "N/A",
         inspect.Parameter.empty,
     ),
+    (
+        "error",
+        (NodeError, "NodeError"),
+        # we never hit this block, we read directly from configurable
+        "N/A",
+        # default to None so non-handler nodes that happen to type a parameter
+        # `error: NodeError` don't blow up; handlers always receive a NodeError.
+        None,
+    ),
 )
 """List of kwargs that can be passed to functions, and their corresponding
 config keys, default values and type annotations.
@@ -354,6 +378,8 @@ class RunnableCallable(Runnable):
             kw_value: Any = MISSING
             if kw == "config":
                 kw_value = config
+            elif kw == "error":
+                kw_value = config.get(CONF, {}).get(CONFIG_KEY_NODE_ERROR, MISSING)
             elif runtime:
                 if kw == "runtime":
                     kw_value = runtime
@@ -426,6 +452,8 @@ class RunnableCallable(Runnable):
             kw_value: Any = MISSING
             if kw == "config":
                 kw_value = config
+            elif kw == "error":
+                kw_value = config.get(CONF, {}).get(CONFIG_KEY_NODE_ERROR, MISSING)
             elif runtime:
                 if kw == "runtime":
                     kw_value = runtime

libs/langgraph/langgraph/_internal/_timeout.py

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

libs/langgraph/langgraph/callbacks.py

@@ -0,0 +1,394 @@
+"""Graph lifecycle callback interfaces and event payloads.
+
+This module defines the public callback surface for observing LangGraph-specific
+lifecycle transitions such as interrupt and resume.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Sequence
+from dataclasses import dataclass
+from typing import Any, Literal, TypeAlias, TypeVar
+from uuid import UUID
+
+from langchain_core.callbacks import BaseCallbackHandler, BaseCallbackManager
+from langchain_core.callbacks.manager import ahandle_event, handle_event
+from langchain_core.runnables import RunnableConfig
+
+from langgraph.types import Interrupt
+
+__all__ = (
+    "GraphCallbackHandler",
+    "GraphInterruptEvent",
+    "GraphLifecycleEvent",
+    "GraphLifecycleStatus",
+    "GraphResumeEvent",
+    "get_async_graph_callback_manager_for_config",
+    "get_sync_graph_callback_manager_for_config",
+)
+
+
+GraphLifecycleStatus: TypeAlias = Literal[
+    "input",
+    "pending",
+    "done",
+    "interrupt_before",
+    "interrupt_after",
+    "out_of_steps",
+]
+"""Allowed lifecycle statuses reported in graph lifecycle callback events."""
+
+
+@dataclass(frozen=True)
+class GraphInterruptEvent:
+    """Graph lifecycle event emitted when execution pauses for interrupts."""
+
+    run_id: UUID | None
+    """Run id for the current graph execution, if available."""
+
+    status: GraphLifecycleStatus
+    """Loop status when the interrupt was captured."""
+
+    checkpoint_id: str
+    """Checkpoint id associated with the interrupted execution."""
+
+    checkpoint_ns: tuple[str, ...]
+    """Checkpoint namespace path for the current graph or subgraph."""
+
+    interrupts: tuple[Interrupt, ...]
+    """Interrupt payloads that caused the graph to pause."""
+
+
+@dataclass(frozen=True)
+class GraphResumeEvent:
+    """Graph lifecycle event emitted when execution resumes from a checkpoint."""
+
+    run_id: UUID | None
+    """Run id for the current graph execution, if available."""
+
+    status: GraphLifecycleStatus
+    """Loop status when the resume was captured."""
+
+    checkpoint_id: str
+    """Checkpoint id the graph resumed from."""
+
+    checkpoint_ns: tuple[str, ...]
+    """Checkpoint namespace path for the current graph or subgraph."""
+
+
+GraphLifecycleEvent: TypeAlias = GraphInterruptEvent | GraphResumeEvent
+"""Union of all public graph lifecycle callback event payloads.
+
+Use this alias when a callback or helper can receive either interrupt or resume
+lifecycle events.
+"""
+
+
+class GraphCallbackHandler(BaseCallbackHandler):
+    """Base class for graph-level lifecycle callbacks.
+
+    Subclass this handler to observe graph lifecycle transitions that are
+    specific to LangGraph execution, rather than generic LangChain runnable
+    callbacks.
+
+    Instances can be passed through `config["callbacks"]` when invoking a
+    graph. Only handlers that inherit from `GraphCallbackHandler` receive these
+    lifecycle events.
+    """
+
+    def on_interrupt(self, event: GraphInterruptEvent) -> Any:
+        """Run when graph execution pauses due to one or more interrupts.
+
+        Args:
+            event: Interrupt lifecycle event payload.
+        """
+
+    def on_resume(self, event: GraphResumeEvent) -> Any:
+        """Run when graph execution resumes from a persisted checkpoint.
+
+        Args:
+            event: Resume lifecycle event payload.
+        """
+
+
+_MISSING = object()
+
+
+def _filter_graph_handlers(
+    handlers: list[BaseCallbackHandler],
+) -> list[GraphCallbackHandler]:
+    return [h for h in handlers if isinstance(h, GraphCallbackHandler)]
+
+
+def _init_base_manager(
+    manager: BaseCallbackManager,
+    handlers: Sequence[GraphCallbackHandler] | None,
+    inheritable_handlers: Sequence[GraphCallbackHandler] | None,
+    parent_run_id: UUID | None,
+    *,
+    tags: list[str] | None,
+    inheritable_tags: list[str] | None,
+    metadata: dict[str, Any] | None,
+    inheritable_metadata: dict[str, Any] | None,
+    run_id: UUID | None,
+) -> None:
+    base_handlers: list[BaseCallbackHandler] = []
+    base_inheritable_handlers: list[BaseCallbackHandler] = []
+    if handlers is not None:
+        base_handlers.extend(handlers)
+    if inheritable_handlers is not None:
+        base_inheritable_handlers.extend(inheritable_handlers)
+    BaseCallbackManager.__init__(
+        manager,
+        handlers=base_handlers,
+        inheritable_handlers=base_inheritable_handlers,
+        parent_run_id=parent_run_id,
+        tags=tags,
+        inheritable_tags=inheritable_tags,
+        metadata=metadata,
+        inheritable_metadata=inheritable_metadata,
+    )
+    manager.run_id = run_id  # type: ignore[attr-defined]
+
+
+def _configure_graph_callbacks(
+    cls: type[_GraphManagerT],
+    callbacks: object | None,
+    *,
+    run_id: UUID | None,
+) -> _GraphManagerT:
+    if callbacks is None:
+        return cls(run_id=run_id)
+    if isinstance(callbacks, cls):
+        return callbacks.copy(run_id=run_id)
+    if isinstance(callbacks, (_GraphCallbackManager, _AsyncGraphCallbackManager)):
+        # Cross-type: extract handlers into the requested cls.
+        return cls(
+            handlers=_filter_graph_handlers(callbacks.handlers),
+            inheritable_handlers=_filter_graph_handlers(callbacks.inheritable_handlers),
+            parent_run_id=callbacks.parent_run_id,
+            tags=callbacks.tags.copy(),
+            inheritable_tags=callbacks.inheritable_tags.copy(),
+            metadata=callbacks.metadata.copy(),
+            inheritable_metadata=callbacks.inheritable_metadata.copy(),
+            run_id=run_id,
+        )
+    if isinstance(callbacks, BaseCallbackManager):
+        return cls(
+            handlers=_filter_graph_handlers(callbacks.handlers),
+            inheritable_handlers=_filter_graph_handlers(callbacks.inheritable_handlers),
+            parent_run_id=callbacks.parent_run_id,
+            tags=callbacks.tags.copy(),
+            inheritable_tags=callbacks.inheritable_tags.copy(),
+            metadata=callbacks.metadata.copy(),
+            inheritable_metadata=callbacks.inheritable_metadata.copy(),
+            run_id=run_id,
+        )
+    if isinstance(callbacks, GraphCallbackHandler):
+        return cls((callbacks,), run_id=run_id)
+    if isinstance(callbacks, (str, bytes)) or not isinstance(callbacks, Sequence):
+        raise TypeError("callbacks must be a handler, sequence, or manager")
+    return cls(_filter_graph_handlers(list(callbacks)), run_id=run_id)
+
+
+def _copy_graph_manager(
+    manager: _GraphCallbackManager | _AsyncGraphCallbackManager,
+    cls: type[_GraphManagerT],
+    run_id: UUID | None | object,
+) -> _GraphManagerT:
+    resolved_run_id: UUID | None
+    if run_id is _MISSING:
+        resolved_run_id = manager.run_id
+    else:
+        if run_id is not None and not isinstance(run_id, UUID):
+            raise TypeError("run_id must be a UUID or None")
+        resolved_run_id = run_id
+
+    return cls(
+        handlers=_filter_graph_handlers(manager.handlers),
+        inheritable_handlers=_filter_graph_handlers(manager.inheritable_handlers),
+        parent_run_id=manager.parent_run_id,
+        tags=manager.tags.copy(),
+        inheritable_tags=manager.inheritable_tags.copy(),
+        metadata=manager.metadata.copy(),
+        inheritable_metadata=manager.inheritable_metadata.copy(),
+        run_id=resolved_run_id,
+    )
+
+
+class _GraphCallbackManager(BaseCallbackManager):
+    """Sync dispatcher for graph lifecycle events."""
+
+    run_id: UUID | None
+
+    def __init__(
+        self,
+        handlers: Sequence[GraphCallbackHandler] | None = None,
+        inheritable_handlers: Sequence[GraphCallbackHandler] | None = None,
+        parent_run_id: UUID | None = None,
+        *,
+        tags: list[str] | None = None,
+        inheritable_tags: list[str] | None = None,
+        metadata: dict[str, Any] | None = None,
+        inheritable_metadata: dict[str, Any] | None = None,
+        run_id: UUID | None = None,
+    ) -> None:
+        _init_base_manager(
+            self,
+            handlers,
+            inheritable_handlers,
+            parent_run_id,
+            tags=tags,
+            inheritable_tags=inheritable_tags,
+            metadata=metadata,
+            inheritable_metadata=inheritable_metadata,
+            run_id=run_id,
+        )
+
+    def copy(
+        self,
+        *,
+        run_id: UUID | None | object = _MISSING,
+    ) -> _GraphCallbackManager:
+        return _copy_graph_manager(self, _GraphCallbackManager, run_id)
+
+    @classmethod
+    def configure(
+        cls,
+        callbacks: object | None = None,
+        *,
+        run_id: UUID | None = None,
+    ) -> _GraphCallbackManager:
+        return _configure_graph_callbacks(cls, callbacks, run_id=run_id)
+
+    def on_interrupt(self, event: GraphInterruptEvent) -> None:
+        handle_event(
+            self.handlers,
+            "on_interrupt",
+            None,
+            event,
+        )
+
+    def on_resume(self, event: GraphResumeEvent) -> None:
+        handle_event(
+            self.handlers,
+            "on_resume",
+            None,
+            event,
+        )
+
+
+class _AsyncGraphCallbackManager(BaseCallbackManager):
+    """Async dispatcher for graph lifecycle events."""
+
+    run_id: UUID | None
+
+    @property
+    def is_async(self) -> bool:
+        """Return whether the manager is async."""
+        return True
+
+    def __init__(
+        self,
+        handlers: Sequence[GraphCallbackHandler] | None = None,
+        inheritable_handlers: Sequence[GraphCallbackHandler] | None = None,
+        parent_run_id: UUID | None = None,
+        *,
+        tags: list[str] | None = None,
+        inheritable_tags: list[str] | None = None,
+        metadata: dict[str, Any] | None = None,
+        inheritable_metadata: dict[str, Any] | None = None,
+        run_id: UUID | None = None,
+    ) -> None:
+        _init_base_manager(
+            self,
+            handlers,
+            inheritable_handlers,
+            parent_run_id,
+            tags=tags,
+            inheritable_tags=inheritable_tags,
+            metadata=metadata,
+            inheritable_metadata=inheritable_metadata,
+            run_id=run_id,
+        )
+
+    def copy(
+        self,
+        *,
+        run_id: UUID | None | object = _MISSING,
+    ) -> _AsyncGraphCallbackManager:
+        return _copy_graph_manager(self, _AsyncGraphCallbackManager, run_id)
+
+    @classmethod
+    def configure(
+        cls,
+        callbacks: object | None = None,
+        *,
+        run_id: UUID | None = None,
+    ) -> _AsyncGraphCallbackManager:
+        return _configure_graph_callbacks(cls, callbacks, run_id=run_id)
+
+    async def on_interrupt(self, event: GraphInterruptEvent) -> None:
+        await ahandle_event(
+            self.handlers,
+            "on_interrupt",
+            None,
+            event,
+        )
+
+    async def on_resume(self, event: GraphResumeEvent) -> None:
+        await ahandle_event(
+            self.handlers,
+            "on_resume",
+            None,
+            event,
+        )
+
+
+_GraphManagerT = TypeVar(
+    "_GraphManagerT", _GraphCallbackManager, _AsyncGraphCallbackManager
+)
+
+GraphCallbacks: TypeAlias = (
+    _GraphCallbackManager
+    | _AsyncGraphCallbackManager
+    | BaseCallbackManager
+    | GraphCallbackHandler
+    | Sequence[BaseCallbackHandler]
+    | Sequence[GraphCallbackHandler]
+    | None
+)
+
+
+def get_sync_graph_callback_manager_for_config(
+    config: RunnableConfig,
+    *,
+    run_id: UUID | None = None,
+) -> _GraphCallbackManager:
+    """Build a sync graph lifecycle callback manager from a runnable config.
+
+    This helper filters `config["callbacks"]` down to handlers that inherit
+    from `GraphCallbackHandler` and binds the provided `run_id` onto the
+    returned manager.
+    """
+    return _GraphCallbackManager.configure(
+        config.get("callbacks"),
+        run_id=run_id,
+    )
+
+
+def get_async_graph_callback_manager_for_config(
+    config: RunnableConfig,
+    *,
+    run_id: UUID | None = None,
+) -> _AsyncGraphCallbackManager:
+    """Build an async graph lifecycle callback manager from a runnable config.
+
+    This helper filters `config["callbacks"]` down to handlers that inherit
+    from `GraphCallbackHandler` and binds the provided `run_id` onto the
+    returned manager.
+    """
+    return _AsyncGraphCallbackManager.configure(
+        config.get("callbacks"),
+        run_id=run_id,
+    )

libs/langgraph/langgraph/channels/__init__.py

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

libs/langgraph/langgraph/channels/binop.py

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

libs/langgraph/langgraph/channels/delta.py

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

libs/langgraph/langgraph/errors.py

@@ -1,8 +1,9 @@
 from __future__ import annotations
 
 from collections.abc import Sequence
+from dataclasses import dataclass
 from enum import Enum
-from typing import Any
+from typing import Any, Literal
 from warnings import warn
 
 # EmptyChannelError is re-exported from langgraph.channels.base
@@ -15,11 +16,14 @@ from langgraph.warnings import LangGraphDeprecatedSinceV10
 __all__ = (
     "EmptyChannelError",
     "ErrorCode",
+    "GraphDrained",
     "GraphRecursionError",
     "InvalidUpdateError",
     "GraphBubbleUp",
     "GraphInterrupt",
+    "NodeError",
     "NodeInterrupt",
+    "NodeTimeoutError",
     "ParentCommand",
     "EmptyInputError",
     "TaskNotFound",
@@ -42,6 +46,23 @@ def create_error_message(*, message: str, error_code: ErrorCode) -> str:
     )
 
 
+class GraphBubbleUp(Exception):
+    pass
+
+
+class GraphDrained(GraphBubbleUp):
+    """Raised when a graph run exits early due to a drain request.
+
+    This indicates the graph stopped cooperatively at a superstep boundary
+    because `RunControl.request_drain()` was called (e.g., in response to
+    SIGTERM). The checkpoint is saved and the run can be resumed later.
+    """
+
+    def __init__(self, reason: str = "shutdown") -> None:
+        self.reason = reason
+        super().__init__(f"Graph drained: {reason}")
+
+
 class GraphRecursionError(RecursionError):
     """Raised when the graph has exhausted the maximum number of steps.
 
@@ -77,10 +98,6 @@ class InvalidUpdateError(Exception):
     pass
 
 
-class GraphBubbleUp(Exception):
-    pass
-
-
 class GraphInterrupt(GraphBubbleUp):
     """Raised when a subgraph is interrupted, suppressed by the root graph.
     Never raised directly, or surfaced to the user."""
@@ -125,3 +142,77 @@ class TaskNotFound(Exception):
     """Raised when the executor is unable to find a task (for distributed mode)."""
 
     pass
+
+
+@dataclass(frozen=True, slots=True)
+class NodeError:
+    """Failure context passed to a node-level error handler.
+
+    Inject by adding a parameter typed `NodeError` to a handler registered via
+    `StateGraph.add_node(..., error_handler=...)`:
+
+    ```python
+    def handler(state: State, error: NodeError) -> Command:
+        return Command(update={"status": f"recovered from {error.node}: {error.error}"})
+    ```
+    """
+
+    node: str
+    """Name of the node whose execution failed."""
+
+    error: BaseException
+    """Exception raised by the failed node."""
+
+
+class NodeTimeoutError(Exception):
+    """Raised when a node invocation exceeds one of its configured timeouts.
+
+    Does **not** inherit from the built-in `TimeoutError` (a subclass of
+    `OSError`) so that the default `RetryPolicy` treats it as retryable.
+
+    Both `idle_timeout` and `run_timeout` reflect the configured policy at the
+    time of the failure (each is `None` if not configured). `kind` and
+    `timeout` identify which one fired.
+    """
+
+    node: str
+    timeout: float
+    run_timeout: float | None
+    idle_timeout: float | None
+    elapsed: float
+    kind: Literal["idle", "run"]
+
+    def __init__(
+        self,
+        node: str,
+        elapsed: float,
+        *,
+        kind: Literal["idle", "run"],
+        idle_timeout: float | None = None,
+        run_timeout: float | None = None,
+    ) -> None:
+        if kind == "idle":
+            if idle_timeout is None:
+                raise ValueError("idle_timeout is required when kind='idle'")
+            message = (
+                f"Node '{node}' exceeded its idle timeout of "
+                f"{idle_timeout:.3f}s without making progress "
+                f"(elapsed: {elapsed:.3f}s)."
+            )
+            self.timeout = idle_timeout
+        elif kind == "run":
+            if run_timeout is None:
+                raise ValueError("run_timeout is required when kind='run'")
+            message = (
+                f"Node '{node}' exceeded its run timeout of "
+                f"{run_timeout:.3f}s (elapsed: {elapsed:.3f}s)."
+            )
+            self.timeout = run_timeout
+        else:
+            raise ValueError("kind must be 'idle' or 'run'")
+        super().__init__(message)
+        self.node = node
+        self.elapsed = elapsed
+        self.kind = kind
+        self.idle_timeout = idle_timeout
+        self.run_timeout = run_timeout

libs/langgraph/langgraph/func/__init__.py

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

libs/langgraph/langgraph/graph/_node.py

@@ -9,7 +9,7 @@ from langgraph.store.base import BaseStore
 
 from langgraph._internal._typing import EMPTY_SEQ
 from langgraph.runtime import Runtime
-from langgraph.types import CachePolicy, RetryPolicy, StreamWriter
+from langgraph.types import CachePolicy, RetryPolicy, StreamWriter, TimeoutPolicy
 from langgraph.typing import ContextT, NodeInputT, NodeInputT_contra
 
 
@@ -88,5 +88,8 @@ class StateNodeSpec(Generic[NodeInputT, ContextT]):
     input_schema: type[NodeInputT]
     retry_policy: RetryPolicy | Sequence[RetryPolicy] | None
     cache_policy: CachePolicy | None
+    is_error_handler: bool = False
+    error_handler_node: str | None = None
     ends: tuple[str, ...] | dict[str, str] | None = EMPTY_SEQ
     defer: bool = False
+    timeout: TimeoutPolicy | None = None

libs/langgraph/langgraph/graph/message.py

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

libs/langgraph/langgraph/graph/state.py

@@ -7,6 +7,7 @@ import warnings
 from collections import defaultdict
 from collections.abc import Awaitable, Callable, Hashable, Sequence
 from dataclasses import is_dataclass
+from datetime import timedelta
 from functools import partial
 from inspect import isclass, isfunction, ismethod, signature
 from types import FunctionType
@@ -45,9 +46,11 @@ from langgraph._internal._fields import (
 )
 from langgraph._internal._pydantic import create_model
 from langgraph._internal._runnable import coerce_to_runnable
+from langgraph._internal._timeout import coerce_timeout_policy
 from langgraph._internal._typing import EMPTY_SEQ, MISSING, DeprecatedKwargs
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.binop import BinaryOperatorAggregate
+from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue, LastValueAfterFinish
 from langgraph.channels.named_barrier_value import (
@@ -81,6 +84,7 @@ from langgraph.types import (
     Command,
     RetryPolicy,
     Send,
+    TimeoutPolicy,
     ensure_valid_checkpointer,
 )
 from langgraph.typing import ContextT, InputT, NodeInputT, OutputT, StateT
@@ -299,7 +303,9 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         input_schema: None = None,
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
+        error_handler: StateNode[Any, ContextT] | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
+        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
@@ -366,7 +372,9 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         input_schema: type[NodeInputT],
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
+        error_handler: StateNode[Any, ContextT] | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
+        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph` where input schema is specified.
@@ -438,7 +446,9 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         input_schema: None = None,
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
+        error_handler: StateNode[Any, ContextT] | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
+        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
@@ -505,7 +515,9 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         input_schema: type[NodeInputT],
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
+        error_handler: StateNode[Any, ContextT] | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
+        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is specified.
@@ -579,7 +591,9 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         input_schema: type[NodeInputT] | None = None,
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
+        error_handler: StateNode[Any, ContextT] | None = None,
         destinations: dict[str, str] | tuple[str, ...] | None = None,
+        timeout: float | timedelta | TimeoutPolicy | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`.
@@ -598,6 +612,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
 
                 If a sequence is provided, the first matching policy will be applied.
             cache_policy: The cache policy for the node.
+            error_handler: Optional node-level error handler callable for this node.
             destinations: Destinations that indicate where a node can route to.
 
                 Useful for edgeless graphs with nodes that return `Command` objects.
@@ -609,6 +624,14 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 !!! warning
 
                     This is only used for graph rendering and doesn't have any effect on the graph execution.
+            timeout: Timeout for each node attempt. A number or `timedelta` is
+                a hard wall-clock cap and is not refreshed. Use `TimeoutPolicy`
+                to configure both a wall-clock `run_timeout` and an
+                `idle_timeout` refreshed by progress signals. When exceeded, a
+                [`NodeTimeoutError`][langgraph.errors.NodeTimeoutError] is raised
+                and the retry policy (if any) decides whether to retry. Timeouts
+                are supported only for async nodes; sync nodes cannot be safely
+                cancelled in-process.
 
         Example:
             ```python
@@ -662,6 +685,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             )
             if input_schema is None:
                 input_schema = cast(type[NodeInputT] | None, input_)
+        timeout = coerce_timeout_policy(timeout)
 
         if not isinstance(node, str):
             action = node
@@ -748,6 +772,25 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         if destinations is not None:
             ends = destinations
 
+        resolved_input_schema: type[Any] = (
+            input_schema or inferred_input_schema or self.state_schema
+        )
+        handler_node_name: str | None = None
+        if error_handler is not None:
+            handler_node_name = f"__error_handler__{node}"
+            if handler_node_name in self.nodes:
+                raise ValueError(
+                    f"Auto-generated error handler node `{handler_node_name}` already exists."
+                )
+            self.nodes[handler_node_name] = StateNodeSpec[Any, ContextT](
+                coerce_to_runnable(error_handler, name=handler_node_name, trace=False),  # type: ignore[arg-type]
+                metadata=None,
+                input_schema=resolved_input_schema,
+                retry_policy=None,
+                cache_policy=None,
+                is_error_handler=True,
+            )
+
         if input_schema is not None:
             self.nodes[node] = StateNodeSpec[NodeInputT, ContextT](
                 coerce_to_runnable(action, name=node, trace=False),  # type: ignore[arg-type]
@@ -755,8 +798,10 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 input_schema=input_schema,
                 retry_policy=retry_policy,
                 cache_policy=cache_policy,
+                error_handler_node=handler_node_name,
                 ends=ends,
                 defer=defer,
+                timeout=timeout,
             )
         elif inferred_input_schema is not None:
             self.nodes[node] = StateNodeSpec(
@@ -765,8 +810,10 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 input_schema=inferred_input_schema,
                 retry_policy=retry_policy,
                 cache_policy=cache_policy,
+                error_handler_node=handler_node_name,
                 ends=ends,
                 defer=defer,
+                timeout=timeout,
             )
         else:
             self.nodes[node] = StateNodeSpec[StateT, ContextT](
@@ -775,8 +822,10 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 input_schema=self.state_schema,
                 retry_policy=retry_policy,
                 cache_policy=cache_policy,
+                error_handler_node=handler_node_name,
                 ends=ends,
                 defer=defer,
+                timeout=timeout,
             )
 
         input_schema = input_schema or inferred_input_schema
@@ -1031,7 +1080,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             for node in interrupt:
                 if node not in self.nodes:
                     raise ValueError(f"Interrupt node `{node}` not found")
-
         self.compiled = True
         return self
 
@@ -1045,6 +1093,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         interrupt_after: All | list[str] | None = None,
         debug: bool = False,
         name: str | None = None,
+        transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
     ) -> CompiledStateGraph[StateT, ContextT, InputT, OutputT]:
         """Compiles the `StateGraph` into a `CompiledStateGraph` object.
 
@@ -1077,11 +1126,19 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             interrupt_after: An optional list of node names to interrupt after.
             debug: A flag indicating whether to enable debug mode.
             name: The name to use for the compiled graph.
+            transformers: Optional sequence of `StreamTransformer` classes or
+                configured factories. Classes and factories are instantiated
+                per run whenever `stream_events(version="v3")` / `astream_events(version="v3")` is called and are
+                propagated to subgraph scopes. Custom factories should follow
+                the standard `StreamTransformer` constructor shape by
+                accepting `scope` as their first argument. Appended after the
+                built-in stream transformers.
 
         Returns:
             CompiledStateGraph: The compiled `StateGraph`.
         """
         checkpointer = ensure_valid_checkpointer(checkpointer)
+
         serde_allowlist: set[tuple[str, ...]] | None = None
         if _serde.STRICT_MSGPACK_ENABLED:
             schema_types: list[type[Any]] = [
@@ -1136,6 +1193,11 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 key for key, val in self.channels.items() if not is_managed_value(val)
             ]
         )
+        node_error_handler_map = {
+            node_name: spec.error_handler_node
+            for node_name, spec in self.nodes.items()
+            if spec.error_handler_node is not None
+        }
 
         compiled = CompiledStateGraph[StateT, ContextT, InputT, OutputT](
             builder=self,
@@ -1158,7 +1220,9 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             debug=debug,
             store=store,
             cache=cache,
+            node_error_handler_map=node_error_handler_map,
             name=name or "LangGraph",
+            stream_transformers=transformers,
         )
         compiled._serde_allowlist = serde_allowlist
 
@@ -1331,7 +1395,10 @@ class CompiledStateGraph(
                 metadata=node.metadata,
                 retry_policy=node.retry_policy,
                 cache_policy=node.cache_policy,
+                is_error_handler=node.is_error_handler,
+                error_handler_node=node.error_handler_node,
                 bound=node.runnable,  # type: ignore[arg-type]
+                timeout=node.timeout,
             )
         else:
             raise RuntimeError
@@ -1667,6 +1734,20 @@ def _is_field_channel(typ: type[Any]) -> BaseChannel | None:
         # Search through all annotated medata to find channel annotations
         for item in meta:
             if isinstance(item, BaseChannel):
+                if isinstance(item, DeltaChannel) and hasattr(typ, "__origin__"):
+                    origin = typ.__origin__
+                    # Unwrap parameterized Required[X]/NotRequired[X] to X
+                    # (e.g. Annotated[NotRequired[dict[...]], ...]).
+                    if hasattr(origin, "__origin__") and origin.__origin__ in (
+                        Required,
+                        NotRequired,
+                    ):
+                        origin = origin.__args__[0]
+                    item = item.__class__(
+                        item.reducer,
+                        origin,
+                        snapshot_frequency=item.snapshot_frequency,
+                    )
                 return item
             elif isclass(item) and issubclass(item, BaseChannel):
                 # ex, Annotated[int, EphemeralValue, SomeOtherAnnotation]

libs/langgraph/langgraph/pregel/_algo.py

@@ -39,6 +39,7 @@ from langgraph._internal._constants import (
     CONFIG_KEY_CHECKPOINT_MAP,
     CONFIG_KEY_CHECKPOINT_NS,
     CONFIG_KEY_CHECKPOINTER,
+    CONFIG_KEY_NODE_ERROR,
     CONFIG_KEY_READ,
     CONFIG_KEY_RESUME_MAP,
     CONFIG_KEY_RUNTIME,
@@ -47,6 +48,7 @@ from langgraph._internal._constants import (
     CONFIG_KEY_TASK_ID,
     CONFIG_KEY_THREAD_ID,
     ERROR,
+    ERROR_SOURCE_NODE,
     INTERRUPT,
     NO_WRITES,
     NS_END,
@@ -66,6 +68,7 @@ from langgraph.channels.base import BaseChannel
 from langgraph.channels.topic import Topic
 from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.constants import TAG_HIDDEN
+from langgraph.errors import NodeError
 from langgraph.managed.base import ManagedValueMapping
 from langgraph.pregel._call import get_runnable_for_task, identifier
 from langgraph.pregel._io import read_channels
@@ -80,6 +83,7 @@ from langgraph.types import (
     PregelTask,
     RetryPolicy,
     Send,
+    TimeoutPolicy,
 )
 
 GetNextVersion = Callable[[V | None, None], V]
@@ -114,13 +118,21 @@ class PregelTaskWrites(NamedTuple):
 
 
 class Call:
-    __slots__ = ("func", "input", "retry_policy", "cache_policy", "callbacks")
+    __slots__ = (
+        "func",
+        "input",
+        "retry_policy",
+        "cache_policy",
+        "callbacks",
+        "timeout",
+    )
 
     func: Callable
     input: tuple[tuple[Any, ...], dict[str, Any]]
     retry_policy: Sequence[RetryPolicy] | None
     cache_policy: CachePolicy | None
     callbacks: Callbacks
+    timeout: TimeoutPolicy | None
 
     def __init__(
         self,
@@ -130,12 +142,14 @@ class Call:
         retry_policy: Sequence[RetryPolicy] | None,
         cache_policy: CachePolicy | None,
         callbacks: Callbacks,
+        timeout: TimeoutPolicy | None = None,
     ) -> None:
         self.func = func
         self.input = input
         self.retry_policy = retry_policy
         self.cache_policy = cache_policy
         self.callbacks = callbacks
+        self.timeout = timeout
 
 
 def should_interrupt(
@@ -281,7 +295,15 @@ def apply_writes(
     pending_writes_by_channel: dict[str, list[Any]] = defaultdict(list)
     for task in tasks:
         for chan, val in task.writes:
-            if chan in (NO_WRITES, PUSH, RESUME, INTERRUPT, RETURN, ERROR):
+            if chan in (
+                NO_WRITES,
+                PUSH,
+                RESUME,
+                INTERRUPT,
+                RETURN,
+                ERROR,
+                ERROR_SOURCE_NODE,
+            ):
                 pass
             elif chan in channels:
                 pending_writes_by_channel[chan].append(val)
@@ -733,11 +755,48 @@ def prepare_single_task(
                         task_path[:3],
                         writers=proc.flat_writers,
                         subgraphs=proc.subgraphs,
+                        timeout=proc.timeout,
                     )
             else:
                 return PregelTask(task_id, name, task_path[:3])
 
 
+def _coerce_pending_error(value: Any) -> BaseException:
+    if isinstance(value, BaseException):
+        return value
+    return Exception(str(value))
+
+
+def _read_errors_from_pending_writes(
+    pending_writes: list[PendingWrite],
+) -> list[BaseException]:
+    errors: list[BaseException] = []
+    for _, channel, value in pending_writes:
+        if channel == ERROR:
+            errors.append(_coerce_pending_error(value))
+    return errors
+
+
+def _read_error_for_task_id_from_pending_writes(
+    pending_writes: list[PendingWrite], task_id: str
+) -> BaseException | None:
+    for pending_task_id, channel, value in reversed(pending_writes):
+        if pending_task_id == task_id and channel == ERROR:
+            return _coerce_pending_error(value)
+    return None
+
+
+def _read_error_source_node_from_pending_writes(
+    pending_writes: list[PendingWrite], task_id: str
+) -> str | None:
+    for pending_task_id, channel, value in reversed(pending_writes):
+        if pending_task_id == task_id and channel == ERROR_SOURCE_NODE:
+            if isinstance(value, str):
+                return value
+            return str(value)
+    return None
+
+
 def prepare_push_task_functional(
     task_path: tuple[str, tuple, int, str, Call],
     # (PUSH, parent task path, idx of PUSH write, id of parent task, Call)
@@ -870,6 +929,7 @@ def prepare_push_task_functional(
             cache_key,
             task_id,
             in_progress_task_path,
+            timeout=call.timeout,
         )
     else:
         return PregelTask(task_id, name, in_progress_task_path)
@@ -1041,11 +1101,153 @@ def prepare_push_task_send(
             translated_task_path,
             writers=proc.flat_writers,
             subgraphs=proc.subgraphs,
+            timeout=packet.timeout if packet.timeout is not None else proc.timeout,
         )
     else:
         return PregelTask(task_id, packet.node, translated_task_path)
 
 
+def prepare_node_error_handler_task(
+    failed_task: PregelExecutableTask,
+    *,
+    handler_node_name: str,
+    failed_error: BaseException,
+    checkpoint: Checkpoint,
+    pending_writes: list[PendingWrite],
+    processes: Mapping[str, PregelNode],
+    channels: Mapping[str, BaseChannel],
+    managed: ManagedValueMapping,
+    config: RunnableConfig,
+    step: int,
+    stop: int,
+    store: BaseStore | None = None,
+    checkpointer: BaseCheckpointSaver | None = None,
+    manager: None | ParentRunManager | AsyncParentRunManager = None,
+    cache_policy: CachePolicy | None = None,
+    retry_policy: Sequence[RetryPolicy] = (),
+) -> PregelExecutableTask | None:
+    """Prepare an immediate node-level error handler task for a failed task."""
+    if handler_node_name not in processes:
+        return None
+    proc = processes[handler_node_name]
+    proc_node = proc.node
+    if proc_node is None:
+        return None
+
+    checkpoint_id_bytes = binascii.unhexlify(checkpoint["id"].replace("-", ""))
+    task_id_func = _xxhash_str if checkpoint["v"] > 1 else _uuid5_str
+    configurable = config.get(CONF, {})
+    parent_ns = configurable.get(CONFIG_KEY_CHECKPOINT_NS, "")
+    checkpoint_ns = (
+        f"{parent_ns}{NS_SEP}{handler_node_name}" if parent_ns else handler_node_name
+    )
+    task_id = task_id_func(
+        checkpoint_id_bytes,
+        checkpoint_ns,
+        str(step),
+        handler_node_name,
+        PUSH,
+        "node_error_handler",
+        failed_task.id,
+    )
+    task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
+    translated_task_path = (*failed_task.path[:3], "node_error_handler", False)
+    metadata = {
+        "langgraph_step": step,
+        "langgraph_node": handler_node_name,
+        "langgraph_triggers": PUSH_TRIGGER,
+        "langgraph_path": translated_task_path,
+        "langgraph_checkpoint_ns": task_checkpoint_ns,
+    }
+    if proc.metadata:
+        metadata.update(proc.metadata)
+    writes: deque[tuple[str, Any]] = deque()
+
+    effective_retry_policy = proc.retry_policy or retry_policy
+    effective_cache_policy = proc.cache_policy or cache_policy
+    if effective_cache_policy:
+        args_key = effective_cache_policy.key_func(failed_task.input)
+        cache_key = CacheKey(
+            (
+                CACHE_NS_WRITES,
+                (identifier(proc) or "__dynamic__"),
+                handler_node_name,
+            ),
+            xxh3_128_hexdigest(
+                args_key.encode() if isinstance(args_key, str) else args_key
+            ),
+            effective_cache_policy.ttl,
+        )
+    else:
+        cache_key = None
+
+    scratchpad = _scratchpad(
+        config[CONF].get(CONFIG_KEY_SCRATCHPAD),
+        pending_writes,
+        task_id,
+        xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+        config[CONF].get(CONFIG_KEY_RESUME_MAP),
+        step,
+        stop,
+    )
+    runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
+    runtime = runtime.override(
+        store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
+    )
+    additional_config: RunnableConfig = {
+        "metadata": metadata,
+        "tags": proc.tags,
+    }
+    return PregelExecutableTask(
+        handler_node_name,
+        failed_task.input,
+        proc_node,
+        writes,
+        patch_config(
+            merge_configs(config, additional_config),
+            run_name=handler_node_name,
+            callbacks=manager.get_child(f"graph:step:{step}") if manager else None,
+            configurable={
+                CONFIG_KEY_TASK_ID: task_id,
+                CONFIG_KEY_SEND: writes.extend,
+                CONFIG_KEY_READ: partial(
+                    local_read,
+                    scratchpad,
+                    channels,
+                    managed,
+                    PregelTaskWrites(
+                        translated_task_path,
+                        handler_node_name,
+                        writes,
+                        PUSH_TRIGGER,
+                    ),
+                ),
+                CONFIG_KEY_CHECKPOINTER: (
+                    checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
+                ),
+                CONFIG_KEY_CHECKPOINT_MAP: {
+                    **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
+                    parent_ns: checkpoint["id"],
+                },
+                CONFIG_KEY_CHECKPOINT_ID: None,
+                CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
+                CONFIG_KEY_SCRATCHPAD: scratchpad,
+                CONFIG_KEY_RUNTIME: runtime,
+                CONFIG_KEY_NODE_ERROR: NodeError(
+                    node=failed_task.name, error=failed_error
+                ),
+            },
+        ),
+        PUSH_TRIGGER,
+        effective_retry_policy,
+        cache_key,
+        task_id,
+        translated_task_path,
+        writers=proc.flat_writers,
+        subgraphs=proc.subgraphs,
+    )
+
+
 def checkpoint_null_version(
     checkpoint: Checkpoint,
 ) -> V | None:
@@ -1255,4 +1457,4 @@ def sanitize_untracked_values_in_send(
         for k, v in packet.arg.items()
         if not isinstance(channels.get(k), UntrackedValue)
     }
-    return Send(node=packet.node, arg=sanitized_arg)
+    return Send(node=packet.node, arg=sanitized_arg, timeout=packet.timeout)

libs/langgraph/langgraph/pregel/_call.py

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

libs/langgraph/langgraph/pregel/_checkpoint.py

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

libs/langgraph/langgraph/pregel/_loop.py

@@ -45,11 +45,13 @@ from langgraph._internal._constants import (
     CONFIG_KEY_REPLAY_STATE,
     CONFIG_KEY_RESUME_MAP,
     CONFIG_KEY_RESUMING,
+    CONFIG_KEY_RUNTIME,
     CONFIG_KEY_SCRATCHPAD,
     CONFIG_KEY_STREAM,
     CONFIG_KEY_TASK_ID,
     CONFIG_KEY_THREAD_ID,
     ERROR,
+    ERROR_SOURCE_NODE,
     INPUT,
     INTERRUPT,
     NS_END,
@@ -62,7 +64,13 @@ from langgraph._internal._constants import (
 from langgraph._internal._replay import ReplayState
 from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
+from langgraph.callbacks import (
+    GraphInterruptEvent,
+    GraphLifecycleEvent,
+    GraphResumeEvent,
+)
 from langgraph.channels.base import BaseChannel
+from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.constants import TAG_HIDDEN
 from langgraph.errors import (
@@ -81,12 +89,14 @@ from langgraph.pregel._algo import (
     checkpoint_null_version,
     increment,
     prepare_next_tasks,
+    prepare_node_error_handler_task,
     prepare_single_task,
     sanitize_untracked_values_in_send,
     should_interrupt,
     task_path_str,
 )
 from langgraph.pregel._checkpoint import (
+    achannels_from_checkpoint,
     channels_from_checkpoint,
     copy_checkpoint,
     create_checkpoint,
@@ -112,11 +122,13 @@ from langgraph.pregel.debug import (
     map_debug_tasks,
 )
 from langgraph.pregel.protocol import StreamChunk, StreamProtocol
+from langgraph.runtime import RunControl, Runtime
 from langgraph.types import (
     All,
     CachePolicy,
     Command,
     Durability,
+    Interrupt,
     PregelExecutableTask,
     RetryPolicy,
     Send,
@@ -182,6 +194,8 @@ class PregelLoop:
     _migrate_checkpoint: Callable[[Checkpoint], None] | None
     submit: Submit
     channels: Mapping[str, BaseChannel]
+    # Only set on AsyncPregelLoop; sync loops keep this as None.
+    _delta_write_futs: list[Any] | None = None
     managed: ManagedValueMapping
     checkpoint: Checkpoint
     checkpoint_id_saved: str
@@ -196,13 +210,17 @@ class PregelLoop:
         "input",
         "pending",
         "done",
+        "draining",
         "interrupt_before",
         "interrupt_after",
         "out_of_steps",
     ]
+    control: RunControl | None
     tasks: dict[str, PregelExecutableTask]
     output: None | dict[str, Any] | Any = None
     updated_channels: set[str] | None = None
+    _graph_lifecycle_events: deque[GraphLifecycleEvent]
+    _has_graph_lifecycle_callbacks: bool
 
     # public
 
@@ -228,6 +246,7 @@ class PregelLoop:
         migrate_checkpoint: Callable[[Checkpoint], None] | None = None,
         retry_policy: Sequence[RetryPolicy] = (),
         cache_policy: CachePolicy | None = None,
+        has_graph_lifecycle_callbacks: bool = False,
     ) -> None:
         self.stream = stream
         self.config = config
@@ -252,6 +271,8 @@ class PregelLoop:
         self.retry_policy = retry_policy
         self.cache_policy = cache_policy
         self.durability = durability
+        self._has_graph_lifecycle_callbacks = has_graph_lifecycle_callbacks
+        self._graph_lifecycle_events = deque()
         if self.stream is not None and CONFIG_KEY_STREAM in config[CONF]:
             self.stream = DuplexStream(self.stream, config[CONF][CONFIG_KEY_STREAM])
         scratchpad: PregelScratchpad | None = config[CONF].get(CONFIG_KEY_SCRATCHPAD)
@@ -302,6 +323,47 @@ class PregelLoop:
             else ()
         )
         self.prev_checkpoint_config = None
+        runtime = self.config[CONF].get(CONFIG_KEY_RUNTIME)
+        self.control = runtime.control if isinstance(runtime, Runtime) else None
+
+    def _push_graph_lifecycle_event(
+        self,
+        kind: Literal["resume", "interrupt"],
+        *,
+        interrupts: tuple[Interrupt, ...] = (),
+    ) -> None:
+        # drain status never reaches lifecycle events: tick() returns False
+        # before pushing, and interrupts are raised through GraphInterrupt
+        if self.status == "draining":
+            raise RuntimeError("Draining status cannot emit lifecycle events")
+        status = self.status
+        if kind == "resume":
+            self._graph_lifecycle_events.append(
+                GraphResumeEvent(
+                    run_id=None,
+                    status=status,
+                    checkpoint_id=self.checkpoint["id"],
+                    checkpoint_ns=self.checkpoint_ns,
+                )
+            )
+        elif kind == "interrupt":
+            self._graph_lifecycle_events.append(
+                GraphInterruptEvent(
+                    run_id=None,
+                    status=status,
+                    checkpoint_id=self.checkpoint["id"],
+                    checkpoint_ns=self.checkpoint_ns,
+                    interrupts=interrupts,
+                )
+            )
+        else:
+            msg = f"Unknown graph lifecycle event type: {kind}"
+            raise AssertionError(msg)
+
+    def _pop_lifecycle_event(self) -> GraphLifecycleEvent | None:
+        if not self._graph_lifecycle_events:
+            return None
+        return self._graph_lifecycle_events.popleft()
 
     def put_writes(self, task_id: str, writes: WritesT) -> None:
         """Put writes for a task, to be read by the next tick."""
@@ -361,7 +423,7 @@ class PregelLoop:
                     task = self.tasks.get(task_id)
                 else:
                     task = None
-                self.submit(
+                fut = self.submit(
                     self.checkpointer_put_writes,
                     config,
                     writes_to_save,
@@ -369,12 +431,16 @@ class PregelLoop:
                     task_path_str(task.path) if task else "",
                 )
             else:
-                self.submit(
+                fut = self.submit(
                     self.checkpointer_put_writes,
                     config,
                     writes_to_save,
                     task_id,
                 )
+            if self._delta_write_futs is not None and any(
+                isinstance(self.specs.get(c), DeltaChannel) for c, _ in writes_to_save
+            ):
+                self._delta_write_futs.append(fut)
         # output writes
         if hasattr(self, "tasks"):
             self.output_writes(task_id, writes)
@@ -458,6 +524,16 @@ class PregelLoop:
             # return the new task, to be started if not run before
             return pushed
 
+    def schedule_error_handler(
+        self, failed_task: PregelExecutableTask, error: BaseException
+    ) -> PregelExecutableTask | None:
+        raise NotImplementedError
+
+    async def aschedule_error_handler(
+        self, failed_task: PregelExecutableTask, error: BaseException
+    ) -> PregelExecutableTask | None:
+        raise NotImplementedError
+
     def tick(self) -> bool:
         """Execute a single iteration of the Pregel loop.
 
@@ -516,6 +592,10 @@ class PregelLoop:
             self.status = "done"
             return False
 
+        if self.control is not None and self.control.drain_requested:
+            self.status = "draining"
+            return False
+
         # if there are pending writes from a previous loop, apply them
         if not self.is_replaying and self.checkpoint_pending_writes:
             self._match_writes(self.tasks)
@@ -582,7 +662,7 @@ class PregelLoop:
 
     def _match_writes(self, tasks: Mapping[str, PregelExecutableTask]) -> None:
         for tid, k, v in self.checkpoint_pending_writes:
-            if k in (ERROR, INTERRUPT, RESUME):
+            if k in (ERROR, ERROR_SOURCE_NODE, INTERRUPT, RESUME):
                 continue
             if task := tasks.get(tid):
                 task.writes.append((k, v))
@@ -647,7 +727,7 @@ class PregelLoop:
         # writes so that interrupt() calls re-fire instead of returning
         # stale values. But if we're actively resuming, keep them —
         # multi-interrupt scenarios need previously resolved values preserved.
-        if self.is_replaying and (
+        is_time_traveling = self.is_replaying and (
             # Time-travel to a subgraph checkpoint: the parent sets
             # RESUMING=True (it can't distinguish time-travel from resume),
             # so we check if this subgraph's own ns is in checkpoint_map.
@@ -665,7 +745,8 @@ class PregelLoop:
                 # (subgraph input is a Send arg, not a Command)
                 or configurable.get(CONFIG_KEY_RESUMING, False)
             )
-        ):
+        )
+        if is_time_traveling:
             self.checkpoint_pending_writes = [
                 w for w in self.checkpoint_pending_writes if w[1] != RESUME
             ]
@@ -720,6 +801,26 @@ class PregelLoop:
                 if k in self.checkpoint["channel_versions"]:
                     version = self.checkpoint["channel_versions"][k]
                     self.checkpoint["versions_seen"][INTERRUPT][k] = version
+            # When time-traveling (replaying from a specific checkpoint),
+            # save a fork checkpoint so the replayed execution creates a
+            # new branch. Without this, if the execution hits an interrupt
+            # before after_tick() runs, no new checkpoint is created —
+            # the parent's latest checkpoint remains the old one and
+            # subsequent resumes load the wrong state.
+            # Skip for update_state forks (source=update/fork) since they
+            # already have their own fork checkpoint.
+            if is_time_traveling and self.checkpoint_metadata.get("source") not in (
+                "update",
+                "fork",
+            ):
+                # Clear old INTERRUPT writes from the loaded checkpoint.
+                # The fork will have a new checkpoint_id which changes
+                # task IDs — stale interrupt writes would accumulate and
+                # confuse the multiple-interrupt check in future resumes.
+                self.checkpoint_pending_writes = [
+                    w for w in self.checkpoint_pending_writes if w[1] != INTERRUPT
+                ]
+                self._put_checkpoint({"source": "fork"})
             # produce values output
             self._emit(
                 "values", map_output_values, self.output_keys, True, self.channels
@@ -762,14 +863,28 @@ class PregelLoop:
         if not self.is_nested:
             # Pass the resolved before-bound checkpoint ID so subgraphs can
             # find their corresponding checkpoint without re-fetching the
-            # parent. For forks (source=update), use the fork's parent
+            # parent. For forks (source=update/fork), use the fork's parent
             # checkpoint ID since the fork was created after the subgraph's
             # checkpoints from the original execution.
+            #
+            # Only gate on is_time_traveling (not is_replaying). When the
+            # client resumes with an explicit checkpoint_id that happens to
+            # point at the current head (e.g. LangGraph Studio sending
+            # `checkpoint: {checkpoint_id}` alongside Command(resume=...)),
+            # is_replaying is True but is_time_traveling is False. In that
+            # case subgraphs should load their latest checkpoint normally,
+            # not go through ReplayState's before-bound lookup which would
+            # miss subgraph checkpoints created during processing of the
+            # current parent step.
             replay_state: ReplayState | None = None
-            if self.is_replaying:
+            if is_time_traveling:
                 replay_checkpoint_id = self.checkpoint["id"]
                 if (
-                    self.checkpoint_metadata.get("source") == "update"
+                    self.checkpoint_metadata.get("source")
+                    in (
+                        "update",
+                        "fork",
+                    )
                     and self.prev_checkpoint_config
                 ):
                     replay_checkpoint_id = self.prev_checkpoint_config[CONF].get(
@@ -785,6 +900,8 @@ class PregelLoop:
             )
         # set flag
         self.status = "pending"
+        if is_resuming:
+            self._push_graph_lifecycle_event("resume")
         return updated_channels
 
     def _put_checkpoint(self, metadata: CheckpointMetadata) -> None:
@@ -808,6 +925,10 @@ class PregelLoop:
             self.step,
             id=self.checkpoint["id"] if exiting else None,
             updated_channels=self.updated_channels,
+            get_next_version=self.checkpointer_get_next_version
+            if do_checkpoint
+            else None,
+            force_delta_snapshot=exiting and self.durability == "exit",
         )
         # sanitize TASK channel in the checkpoint before saving (durability=="exit")
         if TASKS in self.checkpoint["channel_values"] and any(
@@ -885,8 +1006,10 @@ class PregelLoop:
             self._put_checkpoint(self.checkpoint_metadata)
             self._put_pending_writes()
         # suppress interrupt
-        suppress = isinstance(exc_value, GraphInterrupt) and not self.is_nested
-        if suppress:
+        if isinstance(exc_value, GraphInterrupt) and not self.is_nested:
+            interrupt = exc_value
+            interrupts = tuple(interrupt.args[0]) if interrupt.args else ()
+            self._push_graph_lifecycle_event("interrupt", interrupts=interrupts)
             # emit one last "values" event, with pending writes applied
             if (
                 hasattr(self, "tasks")
@@ -913,12 +1036,11 @@ class PregelLoop:
                         self.channels,
                     )
             # emit INTERRUPT if exception is empty (otherwise emitted by put_writes)
-            if exc_value is not None and (not exc_value.args or not exc_value.args[0]):
+            if not interrupt.args or not interrupt.args[0]:
+                interrupt_payload = interrupt.args[0] if interrupt.args else ()
                 self._emit(
                     "updates",
-                    lambda: iter(
-                        [{INTERRUPT: cast(GraphInterrupt, exc_value).args[0]}]
-                    ),
+                    lambda: iter([{INTERRUPT: interrupt_payload}]),
                 )
             # save final output
             self.output = read_channels(self.channels, self.output_keys)
@@ -1040,6 +1162,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
         migrate_checkpoint: Callable[[Checkpoint], None] | None = None,
         retry_policy: Sequence[RetryPolicy] = (),
         cache_policy: CachePolicy | None = None,
+        has_graph_lifecycle_callbacks: bool = False,
     ) -> None:
         super().__init__(
             input,
@@ -1061,6 +1184,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
             retry_policy=retry_policy,
             cache_policy=cache_policy,
             durability=durability,
+            has_graph_lifecycle_callbacks=has_graph_lifecycle_callbacks,
         )
         self.stack = ExitStack()
         if checkpointer:
@@ -1115,6 +1239,45 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
                 self.output_writes(task.id, task.writes, cached=True)
         return pushed
 
+    def schedule_error_handler(
+        self, failed_task: PregelExecutableTask, error: BaseException
+    ) -> PregelExecutableTask | None:
+        handler_node = self.nodes[failed_task.name].error_handler_node
+        if not handler_node:
+            return None
+        writes = list(failed_task.writes)
+        writes.append((ERROR_SOURCE_NODE, failed_task.name))
+        self.put_writes(
+            failed_task.id,
+            writes,
+        )
+        handler_task = prepare_node_error_handler_task(
+            failed_task,
+            handler_node_name=handler_node,
+            failed_error=error,
+            checkpoint=self.checkpoint,
+            pending_writes=self.checkpoint_pending_writes,
+            processes=self.nodes,
+            channels=self.channels,
+            managed=self.managed,
+            config=failed_task.config,
+            step=self.step,
+            stop=self.stop,
+            store=self.store,
+            checkpointer=self.checkpointer,
+            manager=self.manager,
+            retry_policy=self.retry_policy,
+            cache_policy=self.cache_policy,
+        )
+        if handler_task is None:
+            return None
+        self.tasks[handler_task.id] = handler_task
+        if not self.is_replaying:
+            self._match_writes({handler_task.id: handler_task})
+        for task in self.match_cached_writes():
+            self.output_writes(task.id, task.writes, cached=True)
+        return handler_task
+
     def put_writes(self, task_id: str, writes: WritesT) -> None:
         """Put writes for a task, to be read by the next tick."""
         super().put_writes(task_id, writes)
@@ -1136,6 +1299,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
     # context manager
 
     def __enter__(self) -> Self:
+        self._graph_lifecycle_events = deque()
         if not self.checkpointer:
             saved = None
         elif self.checkpoint_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID):
@@ -1187,7 +1351,10 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
         )
         self.submit = self.stack.enter_context(BackgroundExecutor(self.config))
         self.channels, self.managed = channels_from_checkpoint(
-            self.specs, self.checkpoint
+            self.specs,
+            self.checkpoint,
+            saver=self.checkpointer,
+            config=self.checkpoint_config,
         )
         self.stack.push(self._suppress_interrupt)
         self.status = "input"
@@ -1236,6 +1403,7 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
         migrate_checkpoint: Callable[[Checkpoint], None] | None = None,
         retry_policy: Sequence[RetryPolicy] = (),
         cache_policy: CachePolicy | None = None,
+        has_graph_lifecycle_callbacks: bool = False,
     ) -> None:
         super().__init__(
             input,
@@ -1257,6 +1425,7 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
             retry_policy=retry_policy,
             cache_policy=cache_policy,
             durability=durability,
+            has_graph_lifecycle_callbacks=has_graph_lifecycle_callbacks,
         )
         self.stack = AsyncExitStack()
         if checkpointer:
@@ -1280,6 +1449,11 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
         metadata: CheckpointMetadata,
         new_versions: ChannelVersions,
     ) -> RunnableConfig:
+        # Drain DeltaChannel write futures before committing the checkpoint so
+        # DELTA_SENTINEL blobs are never saved ahead of their backing writes.
+        if self._delta_write_futs:
+            futs, self._delta_write_futs = self._delta_write_futs, []
+            await asyncio.gather(*futs)
         try:
             if prev is not None:
                 await prev
@@ -1311,6 +1485,45 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
                 self.output_writes(task.id, task.writes, cached=True)
         return pushed
 
+    async def aschedule_error_handler(
+        self, failed_task: PregelExecutableTask, error: BaseException
+    ) -> PregelExecutableTask | None:
+        handler_node = self.nodes[failed_task.name].error_handler_node
+        if not handler_node:
+            return None
+        writes = list(failed_task.writes)
+        writes.append((ERROR_SOURCE_NODE, failed_task.name))
+        self.put_writes(
+            failed_task.id,
+            writes,
+        )
+        handler_task = prepare_node_error_handler_task(
+            failed_task,
+            handler_node_name=handler_node,
+            failed_error=error,
+            checkpoint=self.checkpoint,
+            pending_writes=self.checkpoint_pending_writes,
+            processes=self.nodes,
+            channels=self.channels,
+            managed=self.managed,
+            config=failed_task.config,
+            step=self.step,
+            stop=self.stop,
+            store=self.store,
+            checkpointer=self.checkpointer,
+            manager=self.manager,
+            retry_policy=self.retry_policy,
+            cache_policy=self.cache_policy,
+        )
+        if handler_task is None:
+            return None
+        self.tasks[handler_task.id] = handler_task
+        if not self.is_replaying:
+            self._match_writes({handler_task.id: handler_task})
+        for task in await self.amatch_cached_writes():
+            self.output_writes(task.id, task.writes, cached=True)
+        return handler_task
+
     def put_writes(self, task_id: str, writes: WritesT) -> None:
         """Put writes for a task, to be read by the next tick."""
         super().put_writes(task_id, writes)
@@ -1335,6 +1548,7 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
     # context manager
 
     async def __aenter__(self) -> Self:
+        self._graph_lifecycle_events = deque()
         if not self.checkpointer:
             saved = None
         elif self.checkpoint_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID):
@@ -1384,11 +1598,15 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
             if saved.pending_writes is not None
             else []
         )
+        self._delta_write_futs = []
         self.submit = await self.stack.enter_async_context(
             AsyncBackgroundExecutor(self.config)
         )
-        self.channels, self.managed = channels_from_checkpoint(
-            self.specs, self.checkpoint
+        self.channels, self.managed = await achannels_from_checkpoint(
+            self.specs,
+            self.checkpoint,
+            saver=self.checkpointer,
+            config=self.checkpoint_config,
         )
         self.stack.push(self._suppress_interrupt)
         self.status = "input"

libs/langgraph/langgraph/pregel/_messages.py

@@ -24,6 +24,11 @@ try:
 except ImportError:
     _StreamingCallbackHandler = object  # type: ignore
 
+try:
+    from langchain_core.tracers._streaming import _V2StreamingCallbackHandler
+except ImportError:
+    _V2StreamingCallbackHandler = object  # type: ignore
+
 T = TypeVar("T")
 Meta = tuple[tuple[str, ...], dict[str, Any]]
 
@@ -248,3 +253,126 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
         **kwargs: Any,
     ) -> Any:
         self.metadata.pop(run_id, None)
+
+
+class StreamMessagesHandlerV2(StreamMessagesHandler, _V2StreamingCallbackHandler):
+    """v2 variant of `StreamMessagesHandler`.
+
+    Declaring `_V2StreamingCallbackHandler` as a base flips
+    `BaseChatModel.invoke` to route through `_stream_chat_model_events`
+    (firing `on_stream_event`) instead of `_stream` (firing
+    `on_llm_new_token`). Inherits `on_stream_event` from the parent,
+    which forwards protocol events onto the messages stream channel.
+
+    Pregel attaches this class instead of the v1 handler only when
+    `StreamingHandler` opts in via the internal
+    `CONFIG_KEY_STREAM_MESSAGES_V2` config key; direct
+    `graph.stream(stream_mode="messages")` callers keep the v1
+    AIMessageChunk shape.
+    """
+
+    def on_llm_new_token(
+        self,
+        token: str,
+        *,
+        chunk: ChatGenerationChunk | None = None,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        tags: list[str] | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        """Intentional no-op — v1 chunks are not used on v2-flagged runs.
+
+        The v2 marker already steers `invoke` to the event generator, so
+        `on_llm_new_token` should not fire under normal routing. This
+        override stays a pass-through (no call to `super()`) to make
+        the intent explicit and to guard against any caller (e.g. a
+        node that calls `model.stream()` directly, which still fires
+        the v1 callback) leaking AIMessageChunks onto a v2-flagged
+        messages stream.
+        """
+        # Intentionally empty: v2 handler does not forward v1 chunks.
+
+    def __init__(
+        self,
+        stream: Callable[[StreamChunk], None],
+        subgraphs: bool,
+        *,
+        parent_ns: tuple[str, ...] | None = None,
+    ) -> None:
+        super().__init__(stream, subgraphs, parent_ns=parent_ns)
+        self._streamed_run_ids: set[UUID] = set()
+
+    def on_llm_end(
+        self,
+        response: LLMResult,
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        if meta := self.metadata.get(run_id):
+            if response.generations and response.generations[0]:
+                gen = response.generations[0][0]
+                if isinstance(gen, ChatGeneration):
+                    if run_id in self._streamed_run_ids:
+                        if gen.message.id is None:
+                            gen.message.id = str(uuid4())
+                        self.seen.add(gen.message.id)
+                    else:
+                        self._emit(meta, gen.message, dedupe=True)
+        self._streamed_run_ids.discard(run_id)
+        self.metadata.pop(run_id, None)
+
+    def on_llm_error(
+        self,
+        error: BaseException,
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        self._streamed_run_ids.discard(run_id)
+        super().on_llm_error(
+            error,
+            run_id=run_id,
+            parent_run_id=parent_run_id,
+            **kwargs,
+        )
+
+    def on_stream_event(
+        self,
+        event: dict[str, Any],
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        tags: list[str] | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        """Forward a protocol event from `stream_events(version="v3")` as a messages stream part.
+
+        Fires once per `MessagesData` event (`message-start`, per-block
+        `content-block-*`, `message-finish`). The transformer layer
+        correlates events back to a single `ChatModelStream` via
+        `metadata["run_id"]` — attached here so the v1
+        `stream_mode="messages"` output (which emits
+        `(AIMessageChunk, metadata)` via `on_llm_new_token`) keeps its
+        original metadata shape.
+
+        Lives on the v2 handler rather than the v1 base: content-block
+        events are a v2-only concept, and forwarding them only when the
+        v2 handler is attached keeps the message channel's shape
+        predictable for v1 callers.
+        """
+        if meta := self.metadata.get(run_id):
+            # Record message_id on message-start so on_chain_end's
+            # dedupe skips the finalized AIMessage the node returns
+            # (otherwise the messages projection double-counts: once
+            # from streaming, once from the chain output).
+            if event.get("event") == "message-start":
+                self._streamed_run_ids.add(run_id)
+                msg_id = event.get("message_id")
+                if msg_id:
+                    self.seen.add(msg_id)
+            v2_meta = {**meta[1], "run_id": str(run_id)}
+            self.stream((meta[0], "messages", (event, v2_meta)))

libs/langgraph/langgraph/pregel/_read.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from collections.abc import AsyncIterator, Callable, Iterator, Mapping, Sequence
+from datetime import timedelta
 from functools import cached_property
 from typing import (
     Any,
@@ -11,10 +12,11 @@ from langchain_core.runnables import Runnable, RunnableConfig
 from langgraph._internal._config import merge_configs
 from langgraph._internal._constants import CONF, CONFIG_KEY_READ
 from langgraph._internal._runnable import RunnableCallable, RunnableSeq
+from langgraph._internal._timeout import coerce_timeout_policy
 from langgraph.pregel._utils import find_subgraph_pregel
 from langgraph.pregel._write import ChannelWrite
 from langgraph.pregel.protocol import PregelProtocol
-from langgraph.types import CachePolicy, RetryPolicy
+from langgraph.types import CachePolicy, RetryPolicy, TimeoutPolicy
 
 READ_TYPE = Callable[[str | Sequence[str], bool], Any | dict[str, Any]]
 INPUT_CACHE_KEY_TYPE = tuple[Callable[..., Any], tuple[str, ...]]
@@ -123,12 +125,25 @@ class PregelNode:
     cache_policy: CachePolicy | None
     """The cache policy to use when invoking the node."""
 
+    timeout: TimeoutPolicy | None
+    """Timeout policy for a single invocation.
+
+    If exceeded, `NodeTimeoutError` is raised and the retry policy (if any)
+    decides whether to retry. Supported only for async nodes.
+    """
+
     tags: Sequence[str] | None
     """Tags to attach to the node for tracing."""
 
     metadata: Mapping[str, Any] | None
     """Metadata to attach to the node for tracing."""
 
+    is_error_handler: bool
+    """Whether this node is registered as an error handler node."""
+
+    error_handler_node: str | None
+    """Optional handler node name for failures from this node."""
+
     subgraphs: Sequence[PregelProtocol]
     """Subgraphs used by the node."""
 
@@ -144,7 +159,10 @@ class PregelNode:
         bound: Runnable[Any, Any] | None = None,
         retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
         cache_policy: CachePolicy | None = None,
+        is_error_handler: bool = False,
+        error_handler_node: str | None = None,
         subgraphs: Sequence[PregelProtocol] | None = None,
+        timeout: float | timedelta | TimeoutPolicy | None = None,
     ) -> None:
         self.channels = channels
         self.triggers = list(triggers)
@@ -156,8 +174,11 @@ class PregelNode:
             self.retry_policy = (retry_policy,)
         else:
             self.retry_policy = retry_policy
+        self.timeout = coerce_timeout_policy(timeout)
         self.tags = tags
         self.metadata = metadata
+        self.is_error_handler = is_error_handler
+        self.error_handler_node = error_handler_node
         if subgraphs is not None:
             self.subgraphs = subgraphs
         elif self.bound is not DEFAULT_BOUND:

libs/langgraph/langgraph/pregel/_retry.py

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

libs/langgraph/langgraph/pregel/_runner.py

@@ -10,8 +10,10 @@ from collections.abc import (
     AsyncIterator,
     Awaitable,
     Callable,
+    Collection,
     Iterable,
     Iterator,
+    Mapping,
     Sequence,
 )
 from functools import partial
@@ -46,6 +48,7 @@ from langgraph.types import (
     CachePolicy,
     PregelExecutableTask,
     RetryPolicy,
+    TimeoutPolicy,
 )
 
 F = TypeVar("F", concurrent.futures.Future, asyncio.Future)
@@ -71,6 +74,10 @@ SKIP_RERAISE_SET: weakref.WeakSet[concurrent.futures.Future | asyncio.Future] =
 class FuturesDict(Generic[F, E], dict[F, PregelExecutableTask | None]):
     event: E
     callback: weakref.ref[Callable[[PregelExecutableTask, BaseException | None], None]]
+    # Stop condition is injected by PregelRunner instead of hard-coded here.
+    # This lets the runner treat graph-error-handled exceptions as non-fatal
+    # so `on_done` does not trigger an early stop for those futures.
+    should_stop: Callable[[set[F]], bool]
     counter: int
     done: set[F]
     lock: threading.Lock
@@ -81,6 +88,7 @@ class FuturesDict(Generic[F, E], dict[F, PregelExecutableTask | None]):
         callback: weakref.ref[
             Callable[[PregelExecutableTask, BaseException | None], None]
         ],
+        should_stop: Callable[[set[F]], bool],
         future_type: type[F],
         # used for generic typing, newer py supports FutureDict[...](...)
     ) -> None:
@@ -88,6 +96,7 @@ class FuturesDict(Generic[F, E], dict[F, PregelExecutableTask | None]):
         self.lock = threading.Lock()
         self.event = event
         self.callback = callback
+        self.should_stop = should_stop
         self.counter = 0
         self.done: set[F] = set()
 
@@ -108,6 +117,7 @@ class FuturesDict(Generic[F, E], dict[F, PregelExecutableTask | None]):
         task: PregelExecutableTask,
         fut: F,
     ) -> None:
+        # Called automatically by future.add_done_callback registered in __setitem__.
         try:
             if cb := self.callback():
                 cb(task, _exception(fut))
@@ -115,7 +125,9 @@ class FuturesDict(Generic[F, E], dict[F, PregelExecutableTask | None]):
             with self.lock:
                 self.done.add(fut)
                 self.counter -= 1
-                if self.counter == 0 or _should_stop_others(self.done):
+                # Wake waiter when all tracked futures are done, or when runner-level
+                # stop condition is met (for example, a non-handled fatal exception).
+                if self.counter == 0 or self.should_stop(self.done):
                     self.event.set()
 
 
@@ -131,11 +143,34 @@ class PregelRunner:
         put_writes: weakref.ref[Callable[[str, Sequence[tuple[str, Any]]], None]],
         use_astream: bool = False,
         node_finished: Callable[[str], None] | None = None,
+        node_error_handler_map: Mapping[str, str] | None = None,
+        schedule_error_handler: Callable[
+            [PregelExecutableTask, BaseException], PregelExecutableTask | None
+        ]
+        | None = None,
+        aschedule_error_handler: Callable[
+            [PregelExecutableTask, BaseException],
+            Awaitable[PregelExecutableTask | None],
+        ]
+        | None = None,
     ) -> None:
         self.submit = submit
         self.put_writes = put_writes
         self.use_astream = use_astream
         self.node_finished = node_finished
+        self.node_error_handler_map = dict(node_error_handler_map or {})
+        self.error_handler_nodes = set(self.node_error_handler_map.values())
+        self.schedule_error_handler = schedule_error_handler
+        self.aschedule_error_handler = aschedule_error_handler
+        # Exception object ids that are already routed to graph-level error handler.
+        # These ids are consulted by stop/panic checks to avoid re-raising handled
+        # exceptions via the normal fatal path in the same run.
+        self._handled_exception_ids: set[int] = set()
+
+    def _should_route_to_error_handler(self, task: PregelExecutableTask) -> bool:
+        if task.name in self.error_handler_nodes:
+            return False
+        return task.name in self.node_error_handler_map
 
     def tick(
         self,
@@ -154,6 +189,9 @@ class PregelRunner:
         futures = FuturesDict(
             callback=weakref.WeakMethod(self.commit),
             event=threading.Event(),
+            should_stop=partial(
+                _should_stop_others, handled_exception_ids=self._handled_exception_ids
+            ),
             future_type=concurrent.futures.Future,
         )
         # give control back to the caller
@@ -163,6 +201,7 @@ class PregelRunner:
             return
         elif len(tasks) == 1 and timeout is None and get_waiter is None:
             t = tasks[0]
+            scheduled_error_handler = False
             try:
                 run_with_retry(
                     t,
@@ -181,12 +220,23 @@ class PregelRunner:
                 self.commit(t, None)
             except Exception as exc:
                 self.commit(t, exc)
+                if (
+                    not isinstance(exc, GraphBubbleUp)
+                    and self._should_route_to_error_handler(t)
+                    and self.schedule_error_handler is not None
+                ):
+                    self._handled_exception_ids.add(id(exc))
+                    if handler_task := self.schedule_error_handler(t, exc):
+                        tasks = (handler_task,)
+                        scheduled_error_handler = True
+                        # Continue to the regular scheduling path for handler execution.
                 if reraise and futures:
-                    # will be re-raised after futures are done
-                    fut: concurrent.futures.Future = concurrent.futures.Future()
-                    fut.set_exception(exc)
-                    futures.done.add(fut)
-                elif reraise:
+                    if id(exc) not in self._handled_exception_ids:
+                        # will be re-raised after futures are done
+                        fut: concurrent.futures.Future = concurrent.futures.Future()
+                        fut.set_exception(exc)
+                        futures.done.add(fut)
+                elif reraise and id(exc) not in self._handled_exception_ids:
                     if tb := exc.__traceback__:
                         while tb.tb_next is not None and any(
                             tb.tb_frame.f_code.co_filename.endswith(name)
@@ -195,10 +245,12 @@ class PregelRunner:
                             tb = tb.tb_next
                         exc.__traceback__ = tb
                     raise
-            if not futures:  # maybe `t` scheduled another task
+            if not futures and not scheduled_error_handler:
+                # maybe `t` scheduled another task
                 return
             else:
-                tasks = ()  # don't reschedule this task
+                if not scheduled_error_handler:
+                    tasks = ()  # don't reschedule this task
         # add waiter task if requested
         if get_waiter is not None:
             futures[get_waiter()] = None
@@ -225,6 +277,7 @@ class PregelRunner:
         # each task is independent from all other concurrent tasks
         # yield updates/debug output as each task finishes
         end_time = timeout + time.monotonic() if timeout else None
+        handled_futures: set[concurrent.futures.Future[Any]] = set()
         while len(futures) > (1 if get_waiter is not None else 0):
             done, inflight = concurrent.futures.wait(
                 futures,
@@ -233,17 +286,49 @@ class PregelRunner:
             )
             if not done:
                 break  # timed out
+            done_for_stop: set[concurrent.futures.Future[Any]] = set()
             for fut in done:
                 task = futures.pop(fut)
                 if task is None:
                     # waiter task finished, schedule another
                     if inflight and get_waiter is not None:
                         futures[get_waiter()] = None
+                elif (
+                    (task_exc := _exception(fut))
+                    and self._should_route_to_error_handler(task)
+                    and not isinstance(task_exc, GraphBubbleUp)
+                ):
+                    self._handled_exception_ids.add(id(task_exc))
+                    SKIP_RERAISE_SET.add(fut)
+                    handled_futures.add(fut)
+                    if self.schedule_error_handler is not None:
+                        if handler_task := self.schedule_error_handler(task, task_exc):
+                            handler_fut = self.submit()(  # type: ignore[misc]
+                                run_with_retry,
+                                handler_task,
+                                retry_policy,
+                                configurable={
+                                    CONFIG_KEY_CALL: partial(
+                                        _call,
+                                        weakref.ref(handler_task),
+                                        retry_policy=retry_policy,
+                                        futures=weakref.ref(futures),
+                                        schedule_task=schedule_task,
+                                        submit=self.submit,
+                                    ),
+                                },
+                                __reraise_on_exit__=reraise,
+                            )
+                            futures[handler_fut] = handler_task
+                else:
+                    done_for_stop.add(fut)
             else:
                 # remove references to loop vars
                 del fut, task
             # maybe stop other tasks
-            if _should_stop_others(done):
+            if _should_stop_others(
+                done_for_stop, handled_exception_ids=self._handled_exception_ids
+            ):
                 break
             # give control back to the caller
             yield
@@ -258,6 +343,8 @@ class PregelRunner:
             _panic_or_proceed(
                 futures.done.union(f for f, t in futures.items() if t is not None),
                 panic=reraise,
+                handled_exception_ids=self._handled_exception_ids,
+                handled_futures=handled_futures,
             )
         except Exception as exc:
             if tb := exc.__traceback__:
@@ -291,6 +378,9 @@ class PregelRunner:
         futures = FuturesDict(
             callback=weakref.WeakMethod(self.commit),
             event=asyncio.Event(),
+            should_stop=partial(
+                _should_stop_others, handled_exception_ids=self._handled_exception_ids
+            ),
             future_type=asyncio.Future,
         )
         # give control back to the caller
@@ -300,6 +390,7 @@ class PregelRunner:
             return
         elif len(tasks) == 1 and get_waiter is None and timeout is None:
             t = tasks[0]
+            scheduled_error_handler = False
             try:
                 await arun_with_retry(
                     t,
@@ -321,12 +412,22 @@ class PregelRunner:
                 self.commit(t, None)
             except Exception as exc:
                 self.commit(t, exc)
+                if (
+                    not isinstance(exc, GraphBubbleUp)
+                    and self._should_route_to_error_handler(t)
+                    and self.aschedule_error_handler is not None
+                ):
+                    self._handled_exception_ids.add(id(exc))
+                    if handler_task := await self.aschedule_error_handler(t, exc):
+                        tasks = (handler_task,)
+                        scheduled_error_handler = True
                 if reraise and futures:
-                    # will be re-raised after futures are done
-                    fut: asyncio.Future = loop.create_future()
-                    fut.set_exception(exc)
-                    futures.done.add(fut)
-                elif reraise:
+                    if id(exc) not in self._handled_exception_ids:
+                        # will be re-raised after futures are done
+                        fut: asyncio.Future = loop.create_future()
+                        fut.set_exception(exc)
+                        futures.done.add(fut)
+                elif reraise and id(exc) not in self._handled_exception_ids:
                     if tb := exc.__traceback__:
                         while tb.tb_next is not None and any(
                             tb.tb_frame.f_code.co_filename.endswith(name)
@@ -335,10 +436,12 @@ class PregelRunner:
                             tb = tb.tb_next
                         exc.__traceback__ = tb
                     raise
-            if not futures:  # maybe `t` scheduled another task
+            if not futures and not scheduled_error_handler:
+                # maybe `t` scheduled another task
                 return
             else:
-                tasks = ()  # don't reschedule this task
+                if not scheduled_error_handler:
+                    tasks = ()  # don't reschedule this task
         # add waiter task if requested
         if get_waiter is not None:
             futures[get_waiter()] = None
@@ -373,6 +476,7 @@ class PregelRunner:
         # each task is independent from all other concurrent tasks
         # yield updates/debug output as each task finishes
         end_time = timeout + loop.time() if timeout else None
+        handled_futures: set[asyncio.Future[Any]] = set()
         while len(futures) > (1 if get_waiter is not None else 0):
             done, inflight = await asyncio.wait(
                 futures,
@@ -381,17 +485,59 @@ class PregelRunner:
             )
             if not done:
                 break  # timed out
+            done_for_stop: set[asyncio.Future[Any]] = set()
             for fut in done:
                 task = futures.pop(fut)
                 if task is None:
                     # waiter task finished, schedule another
                     if inflight and get_waiter is not None:
                         futures[get_waiter()] = None
+                elif (
+                    (task_exc := _exception(fut))
+                    and self._should_route_to_error_handler(task)
+                    and not isinstance(task_exc, GraphBubbleUp)
+                ):
+                    self._handled_exception_ids.add(id(task_exc))
+                    SKIP_RERAISE_SET.add(fut)
+                    handled_futures.add(fut)
+                    if self.aschedule_error_handler is not None:
+                        if handler_task := await self.aschedule_error_handler(
+                            task, task_exc
+                        ):
+                            handler_fut = cast(
+                                asyncio.Future,
+                                self.submit()(  # type: ignore[misc]
+                                    arun_with_retry,
+                                    handler_task,
+                                    retry_policy,
+                                    stream=self.use_astream,
+                                    configurable={
+                                        CONFIG_KEY_CALL: partial(
+                                            _acall,
+                                            weakref.ref(handler_task),
+                                            retry_policy=retry_policy,
+                                            stream=self.use_astream,
+                                            futures=weakref.ref(futures),
+                                            schedule_task=schedule_task,
+                                            submit=self.submit,
+                                            loop=loop,
+                                        ),
+                                    },
+                                    __name__=handler_task.name,
+                                    __cancel_on_exit__=True,
+                                    __reraise_on_exit__=reraise,
+                                ),
+                            )
+                            futures[handler_fut] = handler_task
+                else:
+                    done_for_stop.add(fut)
             else:
                 # remove references to loop vars
                 del fut, task
             # maybe stop other tasks
-            if _should_stop_others(done):
+            if _should_stop_others(
+                done_for_stop, handled_exception_ids=self._handled_exception_ids
+            ):
                 break
             # give control back to the caller
             yield
@@ -411,6 +557,8 @@ class PregelRunner:
                 futures.done.union(f for f, t in futures.items() if t is not None),
                 timeout_exc_cls=asyncio.TimeoutError,
                 panic=reraise,
+                handled_exception_ids=self._handled_exception_ids,
+                handled_futures=handled_futures,
             )
         except Exception as exc:
             if tb := exc.__traceback__:
@@ -446,6 +594,11 @@ class PregelRunner:
             else:
                 # save error to checkpointer
                 task.writes.append((ERROR, exception))
+                if self._should_route_to_error_handler(task) and not isinstance(
+                    exception, GraphBubbleUp
+                ):
+                    # Mark early in commit path; loop-side routing may happen later.
+                    self._handled_exception_ids.add(id(exception))
                 self.put_writes()(task.id, task.writes)  # type: ignore[misc]
         else:
             if self.node_finished and (
@@ -461,6 +614,8 @@ class PregelRunner:
 
 def _should_stop_others(
     done: set[F],
+    *,
+    handled_exception_ids: set[int] | None = None,
 ) -> bool:
     """Check if any task failed, if so, cancel all other tasks.
     GraphInterrupts are not considered failures."""
@@ -468,7 +623,11 @@ def _should_stop_others(
         if fut.cancelled():
             continue
         elif exc := fut.exception():
-            if not isinstance(exc, GraphBubbleUp) and fut not in SKIP_RERAISE_SET:
+            if (
+                id(exc) not in (handled_exception_ids or set())
+                and not isinstance(exc, GraphBubbleUp)
+                and fut not in SKIP_RERAISE_SET
+            ):
                 return True
 
     return False
@@ -492,6 +651,9 @@ def _panic_or_proceed(
     *,
     timeout_exc_cls: type[Exception] = TimeoutError,
     panic: bool = True,
+    handled_exception_ids: set[int] | None = None,
+    handled_futures: Collection[concurrent.futures.Future[Any] | asyncio.Future[Any]]
+    | None = None,
 ) -> None:
     """Cancel remaining tasks if any failed, re-raise exception if panic is True."""
     done: set[concurrent.futures.Future[Any] | asyncio.Future[Any]] = set()
@@ -508,6 +670,10 @@ def _panic_or_proceed(
         # if any task failed
         fut = done.pop()
         if exc := _exception(fut):
+            if fut in (handled_futures or set()):
+                continue
+            if id(exc) in (handled_exception_ids or set()):
+                continue
             # cancel all pending tasks
             while inflight:
                 inflight.pop().cancel()
@@ -537,6 +703,7 @@ def _call(
     *,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
+    timeout: TimeoutPolicy | None = None,
     callbacks: Callbacks = None,
     futures: weakref.ref[FuturesDict],
     schedule_task: Callable[
@@ -560,6 +727,7 @@ def _call(
             retry_policy=retry_policy,
             cache_policy=cache_policy,
             callbacks=callbacks,
+            timeout=timeout,
         ),
     ):
         if fut := next(
@@ -624,6 +792,7 @@ def _acall(
     *,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
+    timeout: TimeoutPolicy | None = None,
     callbacks: Callbacks = None,
     # injected dependencies
     futures: weakref.ref[FuturesDict],
@@ -657,6 +826,7 @@ def _acall(
             input,
             retry_policy=retry_policy,
             cache_policy=cache_policy,
+            timeout=timeout,
             callbacks=callbacks,
             futures=futures,
             schedule_task=schedule_task,
@@ -678,6 +848,7 @@ async def _acall_impl(
     *,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,
+    timeout: TimeoutPolicy | None = None,
     callbacks: Callbacks = None,
     # injected dependencies
     futures: weakref.ref[FuturesDict[asyncio.Future, asyncio.Event]],
@@ -703,6 +874,7 @@ async def _acall_impl(
                 retry_policy=retry_policy,
                 cache_policy=cache_policy,
                 callbacks=callbacks,
+                timeout=timeout,
             ),
         ):
             if fut := next(

libs/langgraph/langgraph/pregel/_tools.py

@@ -0,0 +1,268 @@
+from __future__ import annotations
+
+from collections.abc import AsyncIterator, Callable, Iterator
+from contextvars import ContextVar, Token
+from typing import Any, TypeVar, cast
+from uuid import UUID
+
+from langchain_core.callbacks import BaseCallbackHandler
+
+from langgraph._internal._constants import NS_SEP
+from langgraph.constants import TAG_NOSTREAM
+from langgraph.pregel.protocol import StreamChunk
+
+try:
+    from langchain_core.tracers._streaming import _StreamingCallbackHandler
+except ImportError:
+    _StreamingCallbackHandler = object  # type: ignore[assignment,misc]
+
+
+T = TypeVar("T")
+
+ToolCallWriter = Callable[[Any], None]
+"""A closure bound to a single tool call that emits `tool-output-delta` events."""
+
+_tool_call_writer: ContextVar[ToolCallWriter | None] = ContextVar(
+    "langgraph_tool_call_writer", default=None
+)
+"""ContextVar holding the writer for the currently-executing tool call.
+
+Set by `StreamToolCallHandler.on_tool_start` and reset on end/error.
+Read by `ToolRuntime.emit_output_delta` (in `langgraph.prebuilt`).
+"""
+
+
+class StreamToolCallHandler(BaseCallbackHandler, _StreamingCallbackHandler):
+    """Callback handler that emits tool-call lifecycle events on the stream.
+
+    Fires on LangChain's `on_tool_*` callbacks and pushes to the `tools`
+    stream mode. Emits `tool-started` / `tool-output-delta` /
+    `tool-finished` / `tool-error` payloads keyed by `tool_call_id`.
+
+    While a tool is executing, this handler sets `_tool_call_writer` to a
+    closure bound to that call's namespace and `tool_call_id`.
+    `ToolRuntime.emit_output_delta` reads that ContextVar so tool bodies
+    can stream partial output without threading the writer through their
+    own signature.
+
+    Attached by `Pregel.stream` / `astream` when `"tools"` is in
+    `stream_modes`. `run_inline = True` keeps event ordering
+    deterministic.
+    """
+
+    run_inline = True
+
+    def __init__(
+        self,
+        stream: Callable[[StreamChunk], None],
+        subgraphs: bool,
+        *,
+        parent_ns: tuple[str, ...] | None = None,
+    ) -> None:
+        """Configure the handler to stream tool-call events.
+
+        Args:
+            stream: Callable that accepts a `StreamChunk` tuple
+                `(namespace, mode, payload)` and enqueues it.
+            subgraphs: Whether to emit events from tools called inside
+                nested subgraphs. When False, only tools at the
+                handler's own scope (`parent_ns`) emit.
+            parent_ns: Namespace where the handler was attached.
+                Mirrors the `StreamMessagesHandler` escape hatch:
+                tools whose containing namespace equals `parent_ns`
+                still emit even with `subgraphs=False`, so a node that
+                explicitly streams a subgraph with `stream_mode="tools"`
+                sees its own tools.
+        """
+        self.stream = stream
+        self.subgraphs = subgraphs
+        self.parent_ns = parent_ns
+        # run_id → (namespace, tool_call_id, ContextVar token)
+        # `on_tool_end` does not receive `tool_call_id` in kwargs, so
+        # we correlate by `run_id` which is present on every callback.
+        self._run_to_call: dict[
+            UUID, tuple[tuple[str, ...], str, Token[ToolCallWriter | None]]
+        ] = {}
+
+    def _ns_for_emit(
+        self,
+        metadata: dict[str, Any] | None,
+        tags: list[str] | None,
+    ) -> tuple[str, ...] | None:
+        """Resolve the namespace this tool call should emit at, or `None` to skip.
+
+        Mirrors `StreamMessagesHandler.on_chat_model_start`'s namespace
+        derivation: parses `langgraph_checkpoint_ns` (which ends with
+        the `node_name:task_id` of the calling node), drops that
+        trailing segment, and returns the containing subgraph's own
+        namespace. Returns `None` when the call should be silently
+        suppressed:
+
+        - `metadata` is missing — handler is attached to a context
+          without Pregel routing info.
+        - `TAG_NOSTREAM` is in `tags` — caller explicitly opted out.
+        - Tool runs in a subgraph (`len(ns) > 0`) and the handler was
+          attached with `subgraphs=False` and a different `parent_ns`
+          than the call's containing subgraph.
+        """
+        if not metadata:
+            return None
+        if tags and TAG_NOSTREAM in tags:
+            return None
+        nskey = metadata.get("langgraph_checkpoint_ns")
+        if not nskey:
+            ns: tuple[str, ...] = ()
+        else:
+            ns = tuple(cast(str, nskey).split(NS_SEP))[:-1]
+        if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
+            return None
+        return ns
+
+    def _start(
+        self,
+        serialized: dict[str, Any] | None,
+        input_str: str,
+        *,
+        run_id: UUID,
+        metadata: dict[str, Any] | None,
+        tags: list[str] | None,
+        inputs: dict[str, Any] | None,
+        kwargs: dict[str, Any],
+    ) -> None:
+        ns = self._ns_for_emit(metadata, tags)
+        if ns is None:
+            return
+        tool_call_id = cast("str | None", kwargs.get("tool_call_id")) or str(run_id)
+        tool_name = (
+            (serialized or {}).get("name")
+            or cast("str | None", kwargs.get("name"))
+            or ""
+        )
+
+        def writer(delta: Any) -> None:
+            self.stream(
+                (
+                    ns,
+                    "tools",
+                    {
+                        "event": "tool-output-delta",
+                        "tool_call_id": tool_call_id,
+                        "delta": delta,
+                    },
+                )
+            )
+
+        token = _tool_call_writer.set(writer)
+        self._run_to_call[run_id] = (ns, tool_call_id, token)
+
+        payload: dict[str, Any] = {
+            "event": "tool-started",
+            "tool_call_id": tool_call_id,
+            "tool_name": tool_name,
+        }
+        if inputs is not None:
+            payload["input"] = inputs
+        self.stream((ns, "tools", payload))
+
+    def _end(self, output: Any, *, run_id: UUID) -> None:
+        info = self._run_to_call.pop(run_id, None)
+        if info is None:
+            return
+        ns, tool_call_id, token = info
+        self._reset_writer(token)
+        self.stream(
+            (
+                ns,
+                "tools",
+                {
+                    "event": "tool-finished",
+                    "tool_call_id": tool_call_id,
+                    "output": output,
+                },
+            )
+        )
+
+    def _error(self, error: BaseException, *, run_id: UUID) -> None:
+        info = self._run_to_call.pop(run_id, None)
+        if info is None:
+            return
+        ns, tool_call_id, token = info
+        self._reset_writer(token)
+        self.stream(
+            (
+                ns,
+                "tools",
+                {
+                    "event": "tool-error",
+                    "tool_call_id": tool_call_id,
+                    "message": str(error),
+                },
+            )
+        )
+
+    def tap_output_aiter(
+        self, run_id: UUID, output: AsyncIterator[T]
+    ) -> AsyncIterator[T]:
+        """Pass-through — required by the `_StreamingCallbackHandler` protocol."""
+        return output
+
+    def tap_output_iter(self, run_id: UUID, output: Iterator[T]) -> Iterator[T]:
+        """Pass-through — sync counterpart to `tap_output_aiter`."""
+        return output
+
+    @staticmethod
+    def _reset_writer(token: Token[ToolCallWriter | None]) -> None:
+        # Token is invalid if `on_tool_end` runs in a different context
+        # than `on_tool_start` (e.g. langchain may hand off to a thread
+        # worker without copying the context). Swallow that case; the
+        # ContextVar lifetime is bounded by the enclosing task anyway.
+        try:
+            _tool_call_writer.reset(token)
+        except ValueError:
+            pass
+
+    # ------------------------------------------------------------------
+    # Sync callbacks
+    # ------------------------------------------------------------------
+
+    def on_tool_start(
+        self,
+        serialized: dict[str, Any],
+        input_str: str,
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        tags: list[str] | None = None,
+        metadata: dict[str, Any] | None = None,
+        inputs: dict[str, Any] | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        self._start(
+            serialized,
+            input_str,
+            run_id=run_id,
+            metadata=metadata,
+            tags=tags,
+            inputs=inputs,
+            kwargs=kwargs,
+        )
+
+    def on_tool_end(
+        self,
+        output: Any,
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        self._end(output, run_id=run_id)
+
+    def on_tool_error(
+        self,
+        error: BaseException,
+        *,
+        run_id: UUID,
+        parent_run_id: UUID | None = None,
+        **kwargs: Any,
+    ) -> Any:
+        self._error(error, run_id=run_id)

libs/langgraph/langgraph/pregel/_utils.py

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

libs/langgraph/langgraph/runtime.py

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

libs/langgraph/langgraph/stream/__init__.py

@@ -0,0 +1,45 @@
+"""Streaming infrastructure for LangGraph.
+
+Compile a graph with `transformers=[...]` and call `graph.stream_events(version="v3")` /
+`graph.astream_events(version="v3")` to drive a transformer pipeline that projects the
+graph's raw events into ergonomic per-channel streams.
+"""
+
+from langgraph.stream._types import ProtocolEvent, StreamTransformer
+from langgraph.stream.run_stream import (
+    AsyncGraphRunStream,
+    AsyncSubgraphRunStream,
+    GraphRunStream,
+    SubgraphRunStream,
+)
+from langgraph.stream.stream_channel import StreamChannel
+from langgraph.stream.transformers import (
+    CheckpointsTransformer,
+    CustomTransformer,
+    DebugTransformer,
+    LifecyclePayload,
+    LifecycleTransformer,
+    SubgraphStatus,
+    SubgraphTransformer,
+    TasksTransformer,
+    UpdatesTransformer,
+)
+
+__all__ = [
+    "AsyncGraphRunStream",
+    "AsyncSubgraphRunStream",
+    "CheckpointsTransformer",
+    "CustomTransformer",
+    "DebugTransformer",
+    "GraphRunStream",
+    "LifecyclePayload",
+    "LifecycleTransformer",
+    "ProtocolEvent",
+    "StreamChannel",
+    "StreamTransformer",
+    "SubgraphRunStream",
+    "SubgraphStatus",
+    "SubgraphTransformer",
+    "TasksTransformer",
+    "UpdatesTransformer",
+]

libs/langgraph/langgraph/stream/_convert.py

@@ -0,0 +1,32 @@
+from __future__ import annotations
+
+import time
+from typing import Any, cast
+
+from langgraph.stream._types import ProtocolEvent, _ProtocolEventParams
+from langgraph.types import StreamPart
+
+
+def convert_to_protocol_event(part: StreamPart) -> ProtocolEvent:
+    """Convert a v2 StreamPart to a ProtocolEvent.
+
+    Args:
+        part: A stream part with keys `type`, `ns`, `data`, and
+            optionally `interrupts` (present on values events).
+
+    Returns:
+        The equivalent ProtocolEvent.
+    """
+    part_dict = cast(dict[str, Any], part)
+    params: _ProtocolEventParams = {
+        "namespace": list(part_dict["ns"]),
+        "timestamp": int(time.time() * 1000),
+        "data": part_dict["data"],
+    }
+    if "interrupts" in part_dict:
+        params["interrupts"] = part_dict["interrupts"]
+    return {
+        "type": "event",
+        "method": part_dict["type"],
+        "params": params,
+    }

libs/langgraph/langgraph/stream/_mux.py

@@ -0,0 +1,498 @@
+from __future__ import annotations
+
+import asyncio
+import time
+from collections.abc import Awaitable, Callable
+from typing import Any
+
+from langgraph.stream._types import (
+    ProtocolEvent,
+    StreamTransformer,
+    transformer_requires_async,
+)
+from langgraph.stream.stream_channel import StreamChannel
+
+TransformerFactory = Callable[["tuple[str, ...]"], StreamTransformer]
+"""Factory that builds a scoped transformer for a mux.
+
+Called once per `StreamMux` with the mux's scope (typically `()` for
+the root). Standard transformer classes accept a single positional
+scope argument, so the class itself is a valid factory. User
+transformers can close over their config:
+`lambda scope: MyTransformer(scope, foo=...)`.
+"""
+
+
+class StreamMux:
+    """Central event dispatcher for the streaming infrastructure.
+
+    Owns the main event log and routes events through a transformer
+    pipeline. StreamChannels with a name discovered in transformer
+    projections are auto-wired so that every `push()` also injects a
+    `ProtocolEvent` into the main log. StreamChannels without a name
+    are local-only.
+
+    Pass `is_async=True` when the mux will be consumed via async
+    iteration (`handler.astream()`). All StreamChannel instances
+    discovered during registration are automatically bound to the
+    matching mode.
+
+    Attributes:
+        extensions: Merged projection dict across all registered
+            transformers. Treat as read-only — mutations won't be
+            reflected back in individual transformers' state.
+        native_keys: Projection keys contributed by transformers with
+            `_native = True`.
+    """
+
+    def __init__(
+        self,
+        transformers: list[StreamTransformer] | None = None,
+        *,
+        is_async: bool = False,
+        factories: list[TransformerFactory] | None = None,
+        scope: tuple[str, ...] = (),
+        _assign_seq: bool = True,
+    ) -> None:
+        """Initialize the mux and register transformers in order.
+
+        Callers pass either `transformers` (pre-built instances) or
+        `factories` (callables producing fresh instances per mux). Each
+        transformer's `init()` is called, projections are merged into
+        `extensions`, `_native` keys are recorded in `native_keys`, and
+        any StreamChannel instances are bound and (if named) wired.
+
+        Args:
+            transformers: Already-built transformer instances. Registered
+                only on this mux — they are NOT cloned into child
+                mini-muxes built by `_make_child`. Use `factories` for
+                transformers that should propagate to nested scopes.
+            is_async: True for async dispatch (`apush` / `aclose` /
+                `afail`), False for the sync path.
+            factories: One-argument callables `(scope) -> StreamTransformer`.
+                Called once with this mux's `scope` here, and cloned
+                again per child scope by `_make_child` so each
+                sub-mux gets fresh instances.
+            scope: The namespace the mux operates within. The root mux
+                is `()`.
+            _assign_seq: Internal flag for child muxes. Root muxes assign
+                monotonic `seq` numbers when appending to their main event
+                log; child muxes share forwarded event objects and must not
+                mutate their envelopes.
+
+        Raises:
+            RuntimeError: If any transformer requires an async run but
+                the mux is in sync mode.
+            TypeError: If a transformer's `init()` doesn't return a dict.
+            ValueError: If transformers' projection keys collide.
+        """
+        self.is_async = is_async
+        self.scope: tuple[str, ...] = scope
+        self._assign_seq = _assign_seq
+        self._events: StreamChannel[ProtocolEvent] = StreamChannel()
+        self._events._bind(is_async=is_async)
+        self._events._bind_mux(self)
+        self._transformers: list[StreamTransformer] = []
+        self._channels: list[StreamChannel[Any]] = []
+        self._seq = 0
+        self._push_seq = 0
+
+        self.extensions: dict[str, Any] = {}
+        self.native_keys: set[str] = set()
+        self._projection_owners: dict[str, str] = {}
+        self._transformer_by_key: dict[str, StreamTransformer] = {}
+
+        # Stored only when constructed from factories — used by
+        # `_make_child` to clone the transformer pipeline at a deeper
+        # scope. Pre-built transformers can't be cloned, so a mux
+        # built with `transformers=` rejects child construction.
+        self._factories: list[TransformerFactory] | None = (
+            list(factories) if factories is not None else None
+        )
+        self._pump_fn: Callable[[], bool] | None = None
+        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
+
+        # Factories run first (they propagate to child mini-muxes
+        # via `_make_child`), then any pre-built `transformers=`
+        # instances are registered as root-only — they aren't cloned
+        # for child scopes.
+        if factories is not None:
+            for factory in factories:
+                self._register(factory(scope))
+        for transformer in transformers or ():
+            self._register(transformer)
+
+    def transformer_by_key(self, key: str) -> StreamTransformer | None:
+        """Return the transformer that contributed `key` to the projection."""
+        return self._transformer_by_key.get(key)
+
+    def _next_push_seq(self) -> int:
+        self._push_seq += 1
+        return self._push_seq
+
+    # ------------------------------------------------------------------
+    # Pump wiring + mini-mux nesting
+    # ------------------------------------------------------------------
+
+    def bind_pump(self, fn: Callable[[], bool]) -> None:
+        """Wire the sync pull callback onto every projection in this mux.
+
+        Records the pump on the mux so child mini-muxes built by
+        `_make_child` can inherit it. Propagates to:
+        - the main event log (`self._events`)
+        - every projection StreamChannel in `extensions`
+        - any registered transformer that exposes `_bind_pump` (e.g.
+          `MessagesTransformer` so `ChatModelStream` instances drive the
+          shared pump from their cursors)
+        """
+        self._pump_fn = fn
+        self._events._request_more = fn
+        for ch in self._channels:
+            ch._request_more = fn
+        for transformer in self._transformers:
+            bind = getattr(transformer, "_bind_pump", None)
+            if bind is not None:
+                bind(fn)
+
+    def bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
+        """Async counterpart to `bind_pump`."""
+        self._apump_fn = fn
+        self._events._arequest_more = fn
+        for ch in self._channels:
+            ch._arequest_more = fn
+        for transformer in self._transformers:
+            abind = getattr(transformer, "_bind_apump", None)
+            if abind is not None:
+                abind(fn)
+
+    def _make_child(self, scope: tuple[str, ...]) -> StreamMux:
+        """Build a mini-mux with the same factories scoped to `scope`.
+
+        Used by `SubgraphTransformer` to attach a fresh transformer
+        pipeline to each discovered subgraph handle. The child mux
+        inherits the current pump bindings (so cursors on its
+        projection logs drive the root pump), carries the same factory
+        list forward to any grandchild subgraphs, and does not assign
+        `seq` numbers so forwarded events can be shared without
+        mutating their envelope.
+
+        Raises:
+            RuntimeError: If the mux was not constructed with
+                `factories=`. Mini-muxes require factories so each scope
+                gets its own fresh transformer instances.
+        """
+        if self._factories is None:
+            raise RuntimeError(
+                "StreamMux._make_child requires the mux to be constructed "
+                "with `factories=`; pre-built transformers can't be "
+                "cloned to a new scope."
+            )
+        child = StreamMux(
+            factories=self._factories,
+            is_async=self.is_async,
+            scope=scope,
+            _assign_seq=False,
+        )
+        if self._pump_fn is not None:
+            child.bind_pump(self._pump_fn)
+        if self._apump_fn is not None:
+            child.bind_apump(self._apump_fn)
+        return child
+
+    def _register(self, transformer: StreamTransformer) -> None:
+        """Register a single transformer.
+
+        Calls `transformer.init()`, stores the transformer for event
+        processing, binds any StreamChannel instances in the projection,
+        and merges the projection into `extensions`.
+        """
+        if transformer_requires_async(transformer) and not self.is_async:
+            raise RuntimeError(
+                f"{type(transformer).__name__} requires an async run — "
+                "it overrides aprocess/afinalize/afail or sets "
+                "requires_async=True. Use astream(), not stream()."
+            )
+        projection = transformer.init()
+        if not isinstance(projection, dict):
+            raise TypeError(
+                f"StreamTransformer.init() must return a dict, "
+                f"got {type(projection).__name__}"
+            )
+        conflicts = set(projection) & set(self.extensions)
+        if conflicts:
+            attributions = ", ".join(
+                f"{key!r} (owned by {self._projection_owners[key]})"
+                for key in sorted(conflicts)
+            )
+            raise ValueError(
+                f"Transformer {type(transformer).__name__} returned "
+                f"projection keys that conflict with already-registered "
+                f"keys: {attributions}"
+            )
+        is_native = bool(getattr(transformer, "_native", False))
+        self._transformers.append(transformer)
+        self._bind_and_wire(projection, native=is_native)
+        self.extensions.update(projection)
+        owner_name = type(transformer).__name__
+        for key in projection:
+            self._projection_owners[key] = owner_name
+            self._transformer_by_key[key] = transformer
+        if is_native:
+            self.native_keys.update(projection.keys())
+        transformer._on_register(self)
+
+    def push(self, event: ProtocolEvent) -> None:
+        """Route an event through all transformers, then append to the main log.
+
+        Each transformer's `process()` is called in registration order.
+        If any transformer returns False, the event is suppressed from
+        the main log, but transformers that already saw it keep their
+        side effects.
+
+        On the root mux, `seq` is assigned right before an event enters
+        the main log, not before the transformer pipeline runs. This
+        ensures that events auto-forwarded from StreamChannels during
+        `process()` get earlier seq numbers than the original event,
+        preserving monotonic ordering in the root log. Child muxes do
+        not assign `seq`, so subgraph forwarding can share event objects
+        without mutating their envelopes.
+
+        Args:
+            event: The protocol event to dispatch.
+        """
+        keep = True
+        for transformer in self._transformers:
+            if not transformer.process(event):
+                keep = False
+        if keep:
+            if self._assign_seq:
+                self._seq += 1
+                event["seq"] = self._seq
+            self._events.push(event)
+
+    def close(self) -> None:
+        """Finalize all transformers, close all projections and the main log.
+
+        StreamChannels discovered in transformer projections are
+        auto-closed after `finalize()` runs — transformers don't need
+        to close them manually. If any transformer's `finalize()` raises,
+        the remaining transformers, projections, and the main log are
+        still closed; the first error is re-raised after cleanup
+        completes.
+
+        Raises:
+            BaseException: The first error raised by a transformer's
+                `finalize()`, re-raised after cleanup finishes.
+        """
+        first_error: BaseException | None = None
+        for transformer in self._transformers:
+            try:
+                transformer.finalize()
+            except BaseException as e:
+                if first_error is None:
+                    first_error = e
+        for ch in self._channels:
+            if not ch._closed:
+                ch.close()
+        self._events.close()
+        if first_error is not None:
+            raise first_error
+
+    def fail(self, err: BaseException) -> None:
+        """Fail all transformers, projections, and the main log.
+
+        StreamChannels discovered in transformer projections are
+        auto-failed — transformers don't need to fail them manually.
+        If any transformer's `fail()` raises, the remaining
+        transformers, projections, and the main log are still failed.
+
+        Args:
+            err: The exception that ended the run.
+        """
+        for transformer in self._transformers:
+            try:
+                transformer.fail(err)
+            except BaseException:
+                pass
+        for ch in self._channels:
+            if not ch._closed:
+                ch.fail(err)
+        self._events.fail(err)
+
+    # ------------------------------------------------------------------
+    # Async dispatch
+    # ------------------------------------------------------------------
+
+    async def apush(self, event: ProtocolEvent) -> None:
+        """Dispatch an event on the async lane.
+
+        Awaits each transformer's `aprocess` in registration order
+        before appending to the main log. A slow `aprocess` serializes
+        the pipeline by design — that's the guarantee that lets a later
+        transformer (or a synchronous consumer) see the result of the
+        async work. For decoupled work, use `schedule()` from inside
+        `process` / `aprocess` instead.
+
+        The main log append is a non-blocking `push` — matching v1's
+        `put_nowait` shape. The root mux assigns `seq`; child muxes do
+        not, so forwarded subgraph events can be shared without copying.
+        Memory is bounded by caller pace via the caller-driven pump; see
+        `StreamChannel` for the full tradeoff story.
+
+        Args:
+            event: The protocol event to dispatch.
+        """
+        keep = True
+        for transformer in self._transformers:
+            if not await transformer.aprocess(event):
+                keep = False
+        if keep:
+            if self._assign_seq:
+                self._seq += 1
+                event["seq"] = self._seq
+            self._events.push(event)
+
+    async def aclose(self) -> None:
+        """Finalize on the async lane.
+
+        Awaits every task started via `StreamTransformer.schedule()`
+        across all transformers, then calls `afinalize()` on each,
+        then auto-closes channels and the main event log.
+
+        If any scheduled task raised under `on_error="raise"`, or any
+        transformer's `afinalize` raises, the exception propagates.
+        The caller (the pump) handles it by routing into `afail`.
+
+        Raises:
+            BaseException: The first scheduled-task or `afinalize`
+                error, re-raised after cleanup.
+        """
+        pending = self._collect_scheduled_tasks()
+        if pending:
+            results = await asyncio.gather(*pending, return_exceptions=True)
+            first_err = next(
+                (
+                    r
+                    for r in results
+                    if isinstance(r, BaseException)
+                    and not isinstance(r, asyncio.CancelledError)
+                ),
+                None,
+            )
+            if first_err is not None:
+                raise first_err
+
+        first_error: BaseException | None = None
+        for transformer in self._transformers:
+            try:
+                await transformer.afinalize()
+            except BaseException as e:
+                if first_error is None:
+                    first_error = e
+        for ch in self._channels:
+            if not ch._closed:
+                ch.close()
+        self._events.close()
+        if first_error is not None:
+            raise first_error
+
+    async def afail(self, err: BaseException) -> None:
+        """Fail on the async lane.
+
+        Cancels every scheduled task across all transformers, awaits
+        them to completion, then runs each transformer's `afail` hook
+        and auto-fails channels and the main event log.
+
+        Args:
+            err: The exception that ended the run.
+        """
+        pending = self._collect_scheduled_tasks()
+        for task in pending:
+            task.cancel()
+        if pending:
+            await asyncio.gather(*pending, return_exceptions=True)
+
+        for transformer in self._transformers:
+            try:
+                await transformer.afail(err)
+            except BaseException:
+                pass
+        for ch in self._channels:
+            if not ch._closed:
+                ch.fail(err)
+        if not self._events._closed:
+            self._events.fail(err)
+
+    def _collect_scheduled_tasks(self) -> list[asyncio.Task[Any]]:
+        """Return a snapshot of in-flight tasks scheduled via transformers."""
+        return [
+            task
+            for transformer in self._transformers
+            for task in getattr(transformer, "_stream_scheduled_tasks", ())
+            if not task.done()
+        ]
+
+    # ------------------------------------------------------------------
+    # Binding and StreamChannel auto-wiring
+    # ------------------------------------------------------------------
+
+    def _bind_and_wire(
+        self, projection: dict[str, Any], *, native: bool = False
+    ) -> None:
+        """Bind and optionally wire StreamChannel instances in a projection.
+
+        All StreamChannels are bound and tracked. Channels with a name
+        are additionally wired for protocol auto-forwarding.
+
+        Args:
+            projection: The projection dict returned by a transformer's
+                `init()`.
+            native: True when the owning transformer is `_native`.
+                Named channels owned by a native transformer use the
+                channel name directly as the protocol method;
+                user-defined channels are prefixed with `custom:`.
+        """
+        for value in projection.values():
+            if isinstance(value, StreamChannel):
+                value._bind(is_async=self.is_async)
+                value._bind_mux(self)
+                self._channels.append(value)
+                if value.name is not None:
+                    method = value.name if native else f"custom:{value.name}"
+
+                    def _make_forward(method_name: str) -> Callable[[Any], None]:
+                        def _forward(item: Any) -> None:
+                            self._forward(method_name, item)
+
+                        return _forward
+
+                    value._wire(_make_forward(method))
+
+    def _forward(self, method: str, item: Any) -> None:
+        """Inject a ProtocolEvent for a StreamChannel push.
+
+        Forwarded events bypass the transformer pipeline to avoid
+        infinite recursion (a transformer that pushes to a channel
+        during `process()` would re-trigger itself). These events are
+        visible in this mux's main event log but are not passed through
+        transformers' `process()` methods. Only the root mux assigns
+        `seq` to forwarded channel events.
+
+        Args:
+            method: The full protocol method (already with or without
+                the `custom:` prefix; resolved by `_bind_and_wire`).
+            item: The payload pushed onto the channel.
+        """
+        event: ProtocolEvent = {
+            "type": "event",
+            "method": method,
+            "params": {
+                "namespace": [],
+                "timestamp": int(time.time() * 1000),
+                "data": item,
+            },
+        }
+        if self._assign_seq:
+            self._seq += 1
+            event["seq"] = self._seq
+        self._events.push(event)

libs/langgraph/langgraph/stream/_types.py

@@ -0,0 +1,313 @@
+from __future__ import annotations
+
+import asyncio
+import logging
+from abc import ABC, abstractmethod
+from collections.abc import Coroutine
+from typing import Any, ClassVar, Literal
+
+from typing_extensions import NotRequired, TypedDict
+
+_logger = logging.getLogger(__name__)
+
+
+class _ProtocolEventParams(TypedDict):
+    """Parameters for a protocol event.
+
+    `timestamp` is wall-clock milliseconds since the epoch and can go
+    backwards across NTP adjustments — use `ProtocolEvent.seq` for
+    ordering.
+    """
+
+    namespace: list[str]
+    timestamp: int
+    data: Any
+    interrupts: NotRequired[tuple[Any, ...]]
+
+
+class ProtocolEvent(TypedDict):
+    """A protocol event emitted by the streaming infrastructure.
+
+    Wraps a raw stream part (values, messages, custom, etc.) in a uniform
+    envelope with a monotonic sequence number assigned by the root StreamMux.
+    Consumers that need a total order across root events should use `seq`, not
+    `params.timestamp` (which is wall-clock and not monotonic).
+    """
+
+    type: Literal["event"]
+    eventId: NotRequired[str]
+    seq: NotRequired[int]
+    method: str  # StreamMode value: "values", "messages", "custom", etc.
+    params: _ProtocolEventParams
+
+
+class StreamTransformer(ABC):
+    """Extension point for custom stream projections.
+
+    Transformers observe protocol events flowing through the StreamMux and
+    build typed derived projections (StreamChannels, promises, etc.).
+
+    Set `_native = True` on a transformer to have its projection keys
+    exposed as direct attributes on the run stream (in addition to
+    appearing in `run.extensions`).
+
+    Subclasses must implement `init` and override at least one of
+    `process` / `aprocess`. The `finalize` / `afinalize` and `fail` /
+    `afail` hooks are optional — the default implementations are no-ops.
+    StreamChannel instances in the projection dict are auto-closed /
+    auto-failed by the mux, so most transformers don't need `finalize`
+    or `fail` at all.
+
+    Transformers that need async work pick the async lane by:
+
+    1. Overriding `aprocess` (and optionally `afinalize` / `afail`), or
+    2. Calling `self.schedule(coro)` from inside a sync `process`, or
+    3. Setting `requires_async = True` explicitly.
+
+    The mux detects these cases at registration and raises if they're
+    used under sync `stream()` — they only work under `astream()`.
+
+    Use `aprocess` when the pump must wait for async work before the
+    next transformer sees the event (e.g. PII redaction that mutates
+    `event` in place). Use `schedule()` for decoupled async work whose
+    result lands on an independent projection (e.g. async moderation
+    scoring, cost lookup, external tracing).
+
+    Attributes:
+        scope: Namespace the transformer operates within — `()` for the
+            root mux. Set at construction from the mux's scope (each
+            factory is called as `factory(scope)`).
+        requires_async: Explicit opt-in for transformers that need a
+            running event loop but don't override any async method (for
+            example, transformers that call `schedule()` from a sync
+            `process`). The mux also auto-detects the async lane when
+            `aprocess`, `afinalize`, or `afail` is overridden.
+        supports_sync: Set True only for transformers that override
+            async-lane hooks while still fully supporting the sync lane.
+            Such transformers may be registered under `stream()`.
+        required_stream_modes: Stream modes the graph must emit for
+            this transformer to have anything to process. Computed as
+            the union across all registered transformers to determine
+            which modes a `stream_events(version="v3")` run requests from the graph.
+            Empty tuple means the transformer consumes only synthetic
+            events (or is purely passive).
+    """
+
+    requires_async: ClassVar[bool] = False
+    supports_sync: ClassVar[bool] = False
+    required_stream_modes: ClassVar[tuple[str, ...]] = ()
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        """Initialize the transformer with its mux's scope.
+
+        Args:
+            scope: The namespace tuple the owning mux is scoped to.
+                `()` for the root. Factories receive this at
+                construction time (`factory(scope)` in `StreamMux`).
+        """
+        self.scope: tuple[str, ...] = scope
+
+    @abstractmethod
+    def init(self) -> dict[str, Any]:
+        """Return the projection dict.
+
+        Keys become entries in `run.extensions`. If the transformer has
+        `_native = True`, keys are also set as direct attributes on the
+        run stream.
+
+        StreamChannel instances in the return value are automatically
+        wired by the StreamMux for protocol event auto-forwarding.
+        """
+        ...
+
+    def _on_register(self, mux: Any) -> None:
+        """Called by `StreamMux._register` after this transformer is wired in.
+
+        Default is a no-op. Override to capture a reference to the
+        owning mux — needed for transformers that build mini-muxes
+        via `mux._make_child(...)` (e.g. `SubgraphTransformer`).
+        """
+
+    def process(self, event: ProtocolEvent) -> bool:
+        """Handle an event on the sync lane.
+
+        Called for every event before it is appended to the main event
+        log. Subclasses must override either `process` or `aprocess`.
+        The default raises so a missing override fails loudly rather
+        than silently passing every event through.
+
+        Args:
+            event: The protocol event to observe.
+
+        Returns:
+            True to keep the event in the main log, False to suppress it.
+        """
+        raise NotImplementedError(
+            f"{type(self).__name__} must override process() or aprocess()"
+        )
+
+    async def aprocess(self, event: ProtocolEvent) -> bool:
+        """Handle an event on the async lane.
+
+        The mux awaits this before dispatching to the next transformer,
+        so a slow `aprocess` serializes the pipeline. Use it only when
+        a later transformer — or a consumer reading the event
+        synchronously — must see the result of the async work (e.g.
+        PII redaction that mutates `event` in place).
+
+        The default delegates to `process`, so purely-sync transformers
+        run unchanged under `astream()`.
+
+        Args:
+            event: The protocol event to observe.
+
+        Returns:
+            True to keep the event in the main log, False to suppress it.
+        """
+        return self.process(event)
+
+    def finalize(self) -> None:
+        """Called when the run ends normally (sync lane).
+
+        Override to close StreamChannels, resolve promises, or perform
+        other teardown. StreamChannel instances in the projection dict
+        are auto-closed by the mux.
+        """
+
+    async def afinalize(self) -> None:
+        """Called when the run ends normally (async lane).
+
+        By the time this runs, the mux has already awaited every task
+        started via `schedule()`, so StreamChannels can be closed here
+        without a last-task-wins race.
+
+        The default delegates to `finalize`.
+        """
+        self.finalize()
+
+    def fail(self, err: BaseException) -> None:
+        """Called when the run ends with an error (sync lane).
+
+        Override to fail StreamChannels, reject promises, or perform
+        other teardown. StreamChannel instances in the projection dict
+        are auto-failed by the mux.
+
+        Args:
+            err: The exception that ended the run.
+        """
+
+    async def afail(self, err: BaseException) -> None:
+        """Called when the run ends with an error (async lane).
+
+        The mux cancels and awaits every task started via `schedule()`
+        before calling this, so cleanup doesn't race with in-flight work.
+
+        The default delegates to `fail`.
+
+        Args:
+            err: The exception that ended the run.
+        """
+        self.fail(err)
+
+    # ------------------------------------------------------------------
+    # Scheduled async work
+    # ------------------------------------------------------------------
+
+    def schedule(
+        self,
+        coro: Coroutine[Any, Any, Any],
+        *,
+        on_error: Literal["log", "raise"] = "log",
+    ) -> asyncio.Task[Any]:
+        """Schedule a coroutine tied to this transformer's lifecycle.
+
+        The mux holds the task reference, awaits all scheduled tasks
+        during `aclose()` before calling `afinalize()`, and cancels
+        them on `afail()`. Authors don't need to track tasks or
+        implement the last-task-closes-the-log dance.
+
+        Requires a running event loop — call only under `astream()`.
+        Set `requires_async = True` on the class so registration under
+        sync `stream()` fails fast with a clear message.
+
+        Args:
+            coro: The coroutine to run. Its lifecycle is owned by the
+                mux from this point on.
+            on_error: `"log"` (default) catches and logs any exception
+                the coroutine raises, so a single failure doesn't tear
+                down the run. `"raise"` lets the exception propagate
+                when the mux joins pendings, converting the close path
+                into the fail path.
+
+        Returns:
+            The asyncio Task. Authors rarely need to await it directly
+            — consumers read results from whatever projection the
+            coroutine pushes into.
+
+        Raises:
+            RuntimeError: If called without a running event loop (i.e.
+                under sync `stream()` rather than `astream()`).
+        """
+        try:
+            asyncio.get_running_loop()
+        except RuntimeError:
+            raise RuntimeError(
+                f"{type(self).__name__}.schedule() requires a running "
+                "event loop; this transformer must run under astream(), "
+                "not stream(). Set requires_async=True on the class so "
+                "this fails at registration rather than at first event."
+            ) from None
+
+        wrapped = self._wrap_scheduled(coro) if on_error == "log" else coro
+        task = asyncio.create_task(wrapped)
+        tasks = self._scheduled_task_set()
+        tasks.add(task)
+        task.add_done_callback(tasks.discard)
+        return task
+
+    @staticmethod
+    async def _wrap_scheduled(coro: Coroutine[Any, Any, Any]) -> Any:
+        try:
+            return await coro
+        except asyncio.CancelledError:
+            raise
+        except BaseException:
+            _logger.exception("Scheduled StreamTransformer task failed")
+
+    def _scheduled_task_set(self) -> set[asyncio.Task[Any]]:
+        """Return the lazily-allocated task set.
+
+        Avoids requiring subclasses to call `super().__init__()`.
+        """
+        tasks: set[asyncio.Task[Any]] | None = getattr(
+            self, "_stream_scheduled_tasks", None
+        )
+        if tasks is None:
+            tasks = set()
+            self._stream_scheduled_tasks = tasks
+        return tasks
+
+
+def transformer_requires_async(transformer: StreamTransformer) -> bool:
+    """Return True if the transformer needs a running event loop.
+
+    A transformer requires async if it explicitly opts in
+    (`requires_async = True`) or overrides any of the async-lane methods
+    (`aprocess`, `afinalize`, `afail`) without also declaring that it
+    supports the sync lane.
+
+    Args:
+        transformer: The transformer to inspect.
+
+    Returns:
+        True if the transformer cannot run under sync `stream()`.
+    """
+    if transformer.requires_async:
+        return True
+    if transformer.supports_sync:
+        return False
+    cls = type(transformer)
+    for name in ("aprocess", "afinalize", "afail"):
+        if getattr(cls, name) is not getattr(StreamTransformer, name):
+            return True
+    return False

libs/langgraph/langgraph/stream/run_stream.py

@@ -0,0 +1,608 @@
+from __future__ import annotations
+
+import asyncio
+from collections.abc import AsyncIterator, Awaitable, Callable, Iterator, Mapping
+from types import MappingProxyType, TracebackType
+from typing import TYPE_CHECKING, Any
+
+from langchain_core._api import beta
+
+from langgraph.stream._convert import convert_to_protocol_event
+from langgraph.stream._mux import StreamMux
+from langgraph.stream._types import ProtocolEvent
+
+if TYPE_CHECKING:
+    from langgraph.stream.transformers import SubgraphStatus
+
+
+def _drive_until_done(pump: Callable[[], bool]) -> None:
+    """Call the sync pump until it returns False."""
+    while pump():
+        pass
+
+
+async def _adrive_until_done(pump: Callable[[], Awaitable[bool]]) -> None:
+    """Call the async pump until it returns False."""
+    while await pump():
+        pass
+
+
+@beta(message="The v3 streaming protocol on Pregel is experimental.")
+class GraphRunStream:
+    """Sync run stream with caller-driven pumping.
+
+    The caller's iteration on any projection (`values`, `messages`,
+    raw events, or `output`) drives the graph forward. No background
+    thread is used — the caller's `for` loop is the pump.
+
+    Projections are single-consumer — iterating `run.values` twice
+    raises. Use `projection.tee(n)` if you genuinely need fan-out.
+
+    All transformer projections live in `extensions`. Native transformer
+    projections (those with `_native = True`) are also set as direct
+    attributes on this instance (e.g. `run.values`, `run.messages`).
+
+    !!! warning
+
+        Returned by `Pregel.stream_events(version="v3")`, which is
+        experimental and may change.
+    """
+
+    def __init__(
+        self,
+        graph_iter: Iterator[Any] | None,
+        mux: StreamMux,
+        *,
+        wire_pump: bool = True,
+    ) -> None:
+        """Initialize the run stream.
+
+        Args:
+            graph_iter: Pull-based iterator over the graph's stream,
+                or `None` for nested run streams whose pump is driven
+                by an outer run (e.g. `SubgraphRunStream`).
+            mux: The StreamMux owning projections and the main log.
+            wire_pump: When True (default), bind `_pump_next` as the
+                mux's pump callable. Subclasses that inherit a parent
+                pump via `StreamMux._make_child` should pass False to
+                preserve the parent binding.
+        """
+        self._graph_iter = graph_iter
+        self._mux = mux
+        self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
+        self._exhausted = False
+        self._latest: dict[str, Any] | None = None
+        self._interrupted = False
+        self._interrupts: list[Any] = []
+        self._scope_list: list[str] = list(mux.scope)
+        for key in mux.native_keys:
+            setattr(self, key, mux.extensions[key])
+        if wire_pump:
+            self._wire_request_more(mux)
+
+    def _wire_request_more(self, mux: StreamMux) -> None:
+        """Wire the sync pull callback through the mux.
+
+        Routing through `mux.bind_pump` (rather than walking
+        projections directly here) lets child mini-muxes built by
+        `mux._make_child(...)` inherit the same pump callable, so
+        cursors on a subgraph handle's projections drive the root
+        pump just like cursors on `run.values` do.
+        """
+        mux.bind_pump(self._pump_next)
+
+    def _observe_event(self, event: ProtocolEvent) -> None:
+        """Track values-event state for output/interrupted/interrupts."""
+        if event["method"] != "values":
+            return
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return
+        self._latest = params["data"]
+        interrupts = params.get("interrupts", ())
+        if interrupts:
+            self._interrupted = True
+            self._interrupts.extend(interrupts)
+
+    def _pump_next(self) -> bool:
+        """Pull one event from the graph and push it through the mux.
+
+        Returns:
+            True if an event was pulled, False if the graph is exhausted
+            or has raised. Always False when constructed with
+            `graph_iter=None` (the run is driven by an outer pump).
+        """
+        if self._exhausted or self._graph_iter is None:
+            return False
+        try:
+            part = next(self._graph_iter)
+            event = convert_to_protocol_event(part)
+            self._observe_event(event)
+            self._mux.push(event)
+            return True
+        except StopIteration:
+            self._mux.close()
+            self._exhausted = True
+            return False
+        except Exception as e:
+            self._mux.fail(e)
+            self._exhausted = True
+            return False
+
+    def abort(self) -> None:
+        """Stop the run early.
+
+        Closes the mux and marks the stream exhausted. The graph
+        iterator is dropped; any in-flight nodes see the closure on
+        their next yield point. Idempotent.
+        """
+        if self._exhausted:
+            return
+        self._exhausted = True
+        try:
+            self._mux.close()
+        except Exception:
+            pass
+
+    def __enter__(self) -> GraphRunStream:
+        return self
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc: BaseException | None,
+        tb: TracebackType | None,
+    ) -> None:
+        self.abort()
+
+    @property
+    def output(self) -> dict[str, Any] | None:
+        """Drive the run to completion and return the final state."""
+        _drive_until_done(self._pump_next)
+        if (err := self._mux._events._error) is not None:
+            raise err
+        return self._latest
+
+    @property
+    def interrupted(self) -> bool:
+        """Drive the run to completion, then return whether it was
+        interrupted.
+
+        Raises:
+            BaseException: If the run ended with an error.
+        """
+        _drive_until_done(self._pump_next)
+        if (err := self._mux._events._error) is not None:
+            raise err
+        return self._interrupted
+
+    @property
+    def interrupts(self) -> list[Any]:
+        """Drive the run to completion, then return interrupt payloads.
+
+        Raises:
+            BaseException: If the run ended with an error.
+        """
+        _drive_until_done(self._pump_next)
+        if (err := self._mux._events._error) is not None:
+            raise err
+        return self._interrupts
+
+    def __iter__(self) -> Iterator[ProtocolEvent]:
+        """Subscribe to the main event log and iterate protocol events."""
+        return iter(self._mux._events)
+
+    def interleave(self, *names: str) -> Iterator[tuple[str, Any]]:
+        """Iterate multiple projections in arrival order, yielding ``(name, item)``.
+
+        Items are ordered by a monotonic push stamp assigned when each
+        transformer pushes into its `StreamChannel`. This gives strict
+        arrival ordering across projections, unlike round-robin.
+
+        Args:
+            *names: Projection keys to interleave. Must match keys in
+                ``extensions``.
+
+        Yields:
+            ``(name, item)`` tuples in arrival order across the named
+            projections.
+
+        Each named channel is locked for the duration of iteration and
+        released when the generator completes, is closed, or raises.
+        Channels cannot be subscribed concurrently — use `.tee(n)` if
+        you need fan-out.
+
+        Raises:
+            KeyError: If a name doesn't match a registered projection.
+
+        Example:
+            ```python
+            for name, item in run.interleave("messages", "values"):
+                if name == "messages":
+                    print("msg:", item)
+                else:
+                    print("val:", item)
+            ```
+        """
+        from langgraph.stream.stream_channel import StreamChannel
+
+        channels: dict[str, StreamChannel[Any]] = {}
+        try:
+            for name in names:
+                ch = self.extensions[name]
+                if not isinstance(ch, StreamChannel):
+                    raise TypeError(
+                        f"interleave() requires StreamChannel projections, "
+                        f"got {type(ch).__name__} for {name!r}"
+                    )
+                if ch._is_async is None:
+                    raise TypeError(
+                        f"StreamChannel {name!r} has not been bound yet. "
+                        "Register the transformer with a StreamMux first."
+                    )
+                if ch._is_async:
+                    raise TypeError(
+                        f"StreamChannel {name!r} is bound to async mode — "
+                        "sync interleave() cannot consume async channels."
+                    )
+                if ch._subscribed:
+                    raise RuntimeError(
+                        f"StreamChannel {name!r} already has a subscriber; "
+                        "use .tee(n) for fan-out."
+                    )
+                ch._subscribed = True
+                channels[name] = ch
+
+            done: set[str] = set()
+
+            while len(done) < len(channels):
+                best: tuple[int, str] | None = None
+                for name, ch in channels.items():
+                    if name in done:
+                        continue
+                    if ch._closed and not ch._items:
+                        if ch._error is not None:
+                            raise ch._error
+                        done.add(name)
+                        continue
+                    if ch._items:
+                        stamp = ch._items[0][0]
+                        if best is None or stamp < best[0]:
+                            best = (stamp, name)
+
+                if best is not None:
+                    _stamp, item = channels[best[1]]._items.popleft()
+                    yield (best[1], item)
+                else:
+                    pump = self._mux._pump_fn
+                    if pump is None or not pump():
+                        before = len(done)
+                        for name, ch in channels.items():
+                            if name not in done and not ch._items:
+                                if ch._closed:
+                                    if ch._error is not None:
+                                        raise ch._error
+                                    done.add(name)
+                        if len(done) == before:
+                            break
+        finally:
+            for ch in channels.values():
+                ch._subscribed = False
+
+
+@beta(message="The v3 streaming protocol on Pregel is experimental.")
+class AsyncGraphRunStream:
+    """Async run stream with caller-driven pumping.
+
+    Async iteration on any projection drives the graph forward — there
+    is no background task. Concurrent consumers share a single-flight
+    pump via an `asyncio.Lock`, so each awaiting cursor contributes one
+    event per acquisition. Backpressure comes from the logs: when a
+    subscribed log's buffer reaches `maxlen`, `apush` awaits the
+    subscriber to drain, which holds back the pump and paces the graph.
+
+    Projections are single-consumer — a second `aiter(run.values)`
+    raises. Use `projection.tee(n)` for fan-out.
+
+    Use as an async context manager to guarantee clean shutdown on
+    early exit:
+
+    ```python
+    async with await handler.astream(input) as run:
+        async for msg in run.messages:
+            ...
+    ```
+
+    !!! warning
+
+        Awaited from `Pregel.astream_events(version="v3")`, which is
+        experimental and may change.
+    """
+
+    def __init__(
+        self,
+        graph_aiter: AsyncIterator[Any] | None,
+        mux: StreamMux,
+        *,
+        wire_pump: bool = True,
+    ) -> None:
+        """Initialize the async run stream.
+
+        Args:
+            graph_aiter: Async iterator over the graph's stream, or
+                `None` for nested run streams whose pump is driven by
+                an outer run (e.g. `AsyncSubgraphRunStream`).
+            mux: The StreamMux owning projections and the main log.
+            wire_pump: When True (default), bind `_apump_next` as the
+                mux's async pump callable. Subclasses that inherit a
+                parent pump via `StreamMux._make_child` should pass
+                False to preserve the parent binding.
+        """
+        self._graph_aiter = graph_aiter
+        self._mux = mux
+        self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
+        self._exhausted = False
+        self._latest: dict[str, Any] | None = None
+        self._interrupted = False
+        self._interrupts: list[Any] = []
+        self._scope_list: list[str] = list(mux.scope)
+        self._pump_cond = asyncio.Condition()
+        self._pumping = False
+        for key in mux.native_keys:
+            setattr(self, key, mux.extensions[key])
+        if wire_pump:
+            self._wire_arequest_more(mux)
+
+    def _observe_event(self, event: ProtocolEvent) -> None:
+        """Track values-event state for output/interrupted/interrupts."""
+        if event["method"] != "values":
+            return
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return
+        self._latest = params["data"]
+        interrupts = params.get("interrupts", ())
+        if interrupts:
+            self._interrupted = True
+            self._interrupts.extend(interrupts)
+
+    def _wire_arequest_more(self, mux: StreamMux) -> None:
+        """Wire the async pull callback through the mux.
+
+        Mirrors `_wire_request_more`: routing through
+        `mux.bind_apump` lets child mini-muxes inherit the pump
+        callable so cursors on subgraph handles drive the root
+        pump.
+        """
+        mux.bind_apump(self._apump_next)
+
+    async def _apump_next(self) -> bool:
+        """Drive one pump step, or wait for the active pumper to drive one.
+
+        "Take-a-number" semantics: at most one task at a time calls
+        `graph_aiter.__anext__()` (asyncio iterators can't be advanced
+        concurrently). Other callers wait on a Condition that the
+        active pumper notifies after each step. This lets a "passive"
+        consumer — one whose projection's buffer is being filled by the
+        active pumper's push — wake up as soon as its data lands,
+        instead of queueing on the pump and only observing its data one
+        graph event late.
+
+        `except Exception` is intentional — `CancelledError` and other
+        `BaseException` subclasses propagate, matching asyncio's
+        cancellation contract.
+
+        Returns:
+            True if a pump step completed (by this task or another),
+            False if the graph is exhausted.
+        """
+        async with self._pump_cond:
+            if self._exhausted or self._graph_aiter is None:
+                return False
+            if self._pumping:
+                # Another task is pumping; wait for its progress signal.
+                await self._pump_cond.wait()
+                return not self._exhausted
+            self._pumping = True
+
+        try:
+            try:
+                part = await self._graph_aiter.__anext__()
+                event = convert_to_protocol_event(part)
+                self._observe_event(event)
+                await self._mux.apush(event)
+                return True
+            except StopAsyncIteration:
+                self._exhausted = True
+                await self._mux.aclose()
+                return False
+            except Exception as e:
+                self._exhausted = True
+                await self._mux.afail(e)
+                return False
+        finally:
+            async with self._pump_cond:
+                self._pumping = False
+                self._pump_cond.notify_all()
+
+    async def abort(self) -> None:
+        """Stop the run early.
+
+        Marks the stream exhausted, wakes any pump-waiters, and closes
+        the mux. Any `apush` blocked on backpressure wakes and returns
+        without appending. Idempotent.
+        """
+        async with self._pump_cond:
+            if self._exhausted:
+                return
+            self._exhausted = True
+            self._pump_cond.notify_all()
+        try:
+            await self._mux.aclose()
+        except Exception:
+            pass
+
+    async def __aenter__(self) -> AsyncGraphRunStream:
+        return self
+
+    async def __aexit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc: BaseException | None,
+        tb: TracebackType | None,
+    ) -> None:
+        await self.abort()
+
+    async def output(self) -> dict[str, Any] | None:
+        """Drive the run to completion and return the final state.
+
+        Methods (not properties) on the async lane so `run.output`
+        without `await` raises at type-check time instead of silently
+        yielding a coroutine object.
+
+        Example:
+            ```python
+            output = await run.output()
+            ```
+
+        Raises:
+            BaseException: If the run ended with an error.
+        """
+        await _adrive_until_done(self._apump_next)
+        if (err := self._mux._events._error) is not None:
+            raise err
+        return self._latest
+
+    async def interrupted(self) -> bool:
+        """Drive the run to completion and return whether it was
+        interrupted.
+
+        Raises:
+            BaseException: If the run ended with an error.
+        """
+        await _adrive_until_done(self._apump_next)
+        if (err := self._mux._events._error) is not None:
+            raise err
+        return self._interrupted
+
+    async def interrupts(self) -> list[Any]:
+        """Drive the run to completion and return interrupt payloads.
+
+        Raises:
+            BaseException: If the run ended with an error.
+        """
+        await _adrive_until_done(self._apump_next)
+        if (err := self._mux._events._error) is not None:
+            raise err
+        return self._interrupts
+
+    def __aiter__(self) -> AsyncIterator[ProtocolEvent]:
+        """Subscribe to the main event log and iterate protocol events."""
+        return self._mux._events.__aiter__()
+
+
+class _SubgraphRunStreamMixin:
+    """Subgraph metadata + parent-pump delegation shared by both lanes.
+
+    Inherits from `GraphRunStream` (or `AsyncGraphRunStream`) with
+    `graph_iter=None` + `wire_pump=False` — the mini-mux is driven
+    by the parent's pump (inherited via `StreamMux._make_child`), and
+    the handle never pulls upstream itself. Pump-driving methods
+    delegate to the parent pump so `handle.output` and friends drive
+    the root run.
+
+    Subclasses set the parent pump function captured at construction
+    (`_parent_pump_fn` / `_parent_apump_fn`) and override
+    `_pump_next` / `_apump_next` to delegate to it.
+
+    Status is updated in place by `SubgraphTransformer`. Iterate
+    `run.subgraphs` to receive handles as subgraphs spawn, then
+    drill into projections inside the loop body **before** the next
+    pump cycle — same lazy-subscribe constraint as root projections.
+    """
+
+    path: tuple[str, ...]
+    graph_name: str | None
+    trigger_call_id: str | None
+    status: SubgraphStatus
+    error: str | None
+    _seen_terminal: bool
+
+
+class SubgraphRunStream(GraphRunStream, _SubgraphRunStreamMixin):
+    """Sync handle for a discovered subgraph (extends `GraphRunStream`)."""
+
+    def __init__(
+        self,
+        mux: StreamMux,
+        *,
+        path: tuple[str, ...],
+        graph_name: str | None = None,
+        trigger_call_id: str | None = None,
+    ) -> None:
+        # Capture the parent-inherited pump before super().__init__
+        # touches anything; we delegate to it from `_pump_next`.
+        self._parent_pump_fn: Callable[[], bool] | None = mux._pump_fn
+        super().__init__(
+            graph_iter=None,
+            mux=mux,
+            wire_pump=False,
+        )
+        self.path = path
+        self.graph_name = graph_name
+        self.trigger_call_id = trigger_call_id
+        self.status = "started"
+        self.error = None
+        self._seen_terminal = False
+
+    def _pump_next(self) -> bool:
+        """Delegate to the parent's pump.
+
+        Cursors on this handle's projections call here when their
+        buffers empty. Driving the parent fans events into our
+        mini-mux, transparently advancing the whole run.
+        """
+        if (
+            self._exhausted
+            or self._seen_terminal
+            or self._mux._events._closed
+            or self._parent_pump_fn is None
+        ):
+            return False
+        return self._parent_pump_fn()
+
+
+class AsyncSubgraphRunStream(AsyncGraphRunStream, _SubgraphRunStreamMixin):
+    """Async handle for a discovered subgraph (extends `AsyncGraphRunStream`)."""
+
+    def __init__(
+        self,
+        mux: StreamMux,
+        *,
+        path: tuple[str, ...],
+        graph_name: str | None = None,
+        trigger_call_id: str | None = None,
+    ) -> None:
+        self._parent_apump_fn: Callable[[], Awaitable[bool]] | None = mux._apump_fn
+        super().__init__(
+            graph_aiter=None,
+            mux=mux,
+            wire_pump=False,
+        )
+        self.path = path
+        self.graph_name = graph_name
+        self.trigger_call_id = trigger_call_id
+        self.status = "started"
+        self.error = None
+        self._seen_terminal = False
+
+    async def _apump_next(self) -> bool:
+        """Delegate to the parent's async pump."""
+        if (
+            self._exhausted
+            or self._seen_terminal
+            or self._mux._events._closed
+            or self._parent_apump_fn is None
+        ):
+            return False
+        return await self._parent_apump_fn()

libs/langgraph/langgraph/stream/stream_channel.py

@@ -0,0 +1,341 @@
+from __future__ import annotations
+
+import asyncio
+from collections import deque
+from collections.abc import AsyncIterator, Awaitable, Callable, Iterator
+from typing import TYPE_CHECKING, Generic, TypeVar
+
+if TYPE_CHECKING:
+    from langgraph.stream._mux import StreamMux
+
+T = TypeVar("T")
+
+
+class StreamChannel(Generic[T]):
+    """Single-consumer drainable queue for streaming events, with optional
+    protocol auto-forwarding.
+
+    When constructed with a `name`, the StreamMux auto-wires every
+    `push()` to also inject a `ProtocolEvent` into the main event stream
+    using the channel's name as the method. When constructed without a
+    name, the channel is local-only — items are only visible to
+    in-process consumers that iterate the channel directly.
+
+    Items are popped off the front as the consumer advances — there is
+    no retention beyond what's currently queued. A channel accepts
+    exactly one subscriber; a second `__iter__` / `__aiter__` call
+    raises. Use `tee(n)` / `atee(n)` for fan-out.
+
+    Starts unbound — neither `__iter__` nor `__aiter__` is available
+    until the StreamMux calls `_bind(is_async)`. After binding, only
+    the matching iteration protocol works; the other raises `TypeError`.
+
+    Pump wiring (set by the run stream, not by `_bind`):
+        - `_request_more`: sync pump callable, returns True if a new
+          event was produced.
+        - `_arequest_more`: async pump coroutine factory, same contract.
+
+    Memory is bounded by caller pace: both sync and async use caller-
+    driven pumps, so each cursor advance produces at most one event.
+
+    Lazy-subscribe: `push` appends to the local buffer only when a
+    subscriber has registered. Auto-forward via `_wire_fn` always fires
+    regardless of subscription state.
+
+    Lifecycle (`close` / `fail`) is managed by the mux — transformers
+    don't need to close their channels manually.
+    """
+
+    def __init__(self, name: str | None = None, *, maxlen: int | None = None) -> None:
+        """Initialize the channel.
+
+        Args:
+            name: Optional protocol channel name. When set, the
+                StreamMux wires every `push()` to also inject a
+                `ProtocolEvent` into the main event stream. Surfaced
+                on the wire as `custom:<name>` for user-defined
+                transformers, or as `<name>` for channels owned by a
+                native transformer (`_native = True`). When `None`,
+                the channel is local-only.
+            maxlen: Accepted for forward compatibility; currently
+                unused. The caller-driven pump bounds memory naturally
+                for single-consumer use.
+
+        Raises:
+            ValueError: If `maxlen` is not a positive integer or `None`.
+        """
+        if maxlen is not None and maxlen <= 0:
+            raise ValueError("StreamChannel maxlen must be a positive int or None")
+        self.name = name
+        self._items: deque[tuple[int, T]] = deque()
+        self._maxlen: int | None = maxlen
+        self._closed = False
+        self._error: BaseException | None = None
+
+        self._is_async: bool | None = None
+
+        self._subscribed = False
+
+        self._request_more: Callable[[], bool] | None = None
+        self._arequest_more: Callable[[], Awaitable[bool]] | None = None
+
+        self._wire_fn: Callable[[T], None] | None = None
+        self._mux: StreamMux | None = None
+
+    # ------------------------------------------------------------------
+    # Binding
+    # ------------------------------------------------------------------
+
+    def _bind_mux(self, mux: StreamMux) -> None:
+        self._mux = mux
+
+    def _bind(self, *, is_async: bool) -> None:
+        """Bind this channel to sync or async mode.
+
+        Called by the StreamMux after transformer registration. Must be
+        called exactly once before any iteration.
+
+        Args:
+            is_async: True to enable async iteration, False for sync.
+
+        Raises:
+            RuntimeError: If the channel has already been bound.
+        """
+        if self._is_async is not None:
+            raise RuntimeError("StreamChannel is already bound")
+        self._is_async = is_async
+
+    # ------------------------------------------------------------------
+    # Mux wiring (not called by transformers directly)
+    # ------------------------------------------------------------------
+
+    def _wire(self, fn: Callable[[T], None]) -> None:
+        """Install the auto-forward callback (called by StreamMux)."""
+        self._wire_fn = fn
+
+    # ------------------------------------------------------------------
+    # Producer API
+    # ------------------------------------------------------------------
+
+    def push(self, item: T) -> None:
+        """Append an item. Auto-forwards if wired.
+
+        The local buffer append is a no-op when no subscriber is
+        registered, but auto-forwarding always fires so wired events
+        reach the main event log regardless of subscription state.
+
+        Items are stored as `(stamp, item)` tuples where stamp is a
+        monotonic counter from the owning mux. Stamps are stripped by
+        the default cursors; raw stamped tuples are visible on `_items`.
+
+        Raises:
+            RuntimeError: If the channel is closed (and subscribed).
+        """
+        if self._subscribed:
+            if self._closed:
+                raise RuntimeError("Cannot push to a closed StreamChannel")
+            stamp = self._mux._next_push_seq() if self._mux is not None else 0
+            self._items.append((stamp, item))
+        if self._wire_fn is not None:
+            self._wire_fn(item)
+
+    def close(self) -> None:
+        """Mark the channel as complete."""
+        self._closed = True
+
+    def fail(self, err: BaseException) -> None:
+        """Mark the channel as errored.
+
+        Args:
+            err: The exception to surface to the subscriber.
+        """
+        self._error = err
+        self._closed = True
+
+    # ------------------------------------------------------------------
+    # Sync iteration (caller-driven pump)
+    # ------------------------------------------------------------------
+
+    def __iter__(self) -> Iterator[T]:
+        """Subscribe and return a sync cursor. Can be called only once.
+
+        Raises:
+            TypeError: If the channel is unbound or bound to async mode.
+            RuntimeError: If the channel already has a subscriber.
+        """
+        if self._is_async is None:
+            raise TypeError(
+                "StreamChannel has not been bound yet. "
+                "Register the transformer with a StreamMux first."
+            )
+        if self._is_async:
+            raise TypeError(
+                "This StreamChannel is bound to async mode — use 'async for' instead."
+            )
+        if self._subscribed:
+            raise RuntimeError(
+                "StreamChannel already has a subscriber; use .tee(n) for fan-out."
+            )
+        self._subscribed = True
+        return self._sync_cursor()
+
+    def _sync_cursor(self) -> Iterator[T]:
+        while True:
+            if self._items:
+                _stamp, item = self._items.popleft()
+                yield item
+            elif self._closed:
+                if self._error is not None:
+                    raise self._error
+                return
+            elif self._request_more is not None:
+                if not self._request_more():
+                    if not self._items and not self._closed:
+                        return
+            else:
+                return
+
+    # ------------------------------------------------------------------
+    # Async iteration (caller-driven pump)
+    # ------------------------------------------------------------------
+
+    def __aiter__(self) -> AsyncIterator[T]:
+        """Subscribe and return an async cursor. Can be called only once.
+
+        Raises:
+            TypeError: If the channel is unbound or bound to sync mode.
+            RuntimeError: If the channel already has a subscriber.
+        """
+        if self._is_async is None:
+            raise TypeError(
+                "StreamChannel has not been bound yet. "
+                "Register the transformer with a StreamMux first."
+            )
+        if not self._is_async:
+            raise TypeError(
+                "This StreamChannel is bound to sync mode — use 'for' instead."
+            )
+        if self._subscribed:
+            raise RuntimeError(
+                "StreamChannel already has a subscriber; use .atee(n) for fan-out."
+            )
+        self._subscribed = True
+        return self._async_cursor()
+
+    async def _async_cursor(self) -> AsyncIterator[T]:
+        while True:
+            if self._items:
+                _stamp, item = self._items.popleft()
+                yield item
+            elif self._closed:
+                if self._error is not None:
+                    raise self._error
+                return
+            elif self._arequest_more is not None:
+                if not await self._arequest_more():
+                    if not self._items and not self._closed:
+                        return
+            else:
+                return
+
+    # ------------------------------------------------------------------
+    # Fan-out via tee
+    # ------------------------------------------------------------------
+
+    def tee(self, n: int = 2) -> tuple[Iterator[T], ...]:
+        """Subscribe and return `n` independent sync iterators.
+
+        Each branch has its own buffer; items pulled from the
+        underlying cursor are copied into every branch. Branches are
+        naturally bounded by caller pace since the sync pump is
+        caller-driven.
+
+        Args:
+            n: Number of branches to create. Must be >= 1.
+
+        Returns:
+            A tuple of `n` iterators over the same underlying stream.
+
+        Raises:
+            TypeError: If the channel is unbound or bound to async mode.
+            RuntimeError: If the channel already has a subscriber.
+            ValueError: If `n` < 1.
+        """
+        if n < 1:
+            raise ValueError("tee() requires n >= 1")
+        source = self.__iter__()
+        buffers: list[deque[T]] = [deque() for _ in range(n)]
+        exhausted = [False]
+
+        def branch(i: int) -> Iterator[T]:
+            buf = buffers[i]
+            while True:
+                if buf:
+                    yield buf.popleft()
+                elif exhausted[0]:
+                    return
+                else:
+                    try:
+                        item = next(source)
+                    except StopIteration:
+                        exhausted[0] = True
+                        return
+                    for b in buffers:
+                        b.append(item)
+
+        return tuple(branch(i) for i in range(n))
+
+    def atee(self, n: int = 2) -> tuple[AsyncIterator[T], ...]:
+        """Subscribe and return `n` independent async iterators.
+
+        Caller-driven fan-out: each branch's `__anext__` either pops
+        from its own buffer or, under a shared `asyncio.Lock`, pulls
+        one item from the underlying cursor and distributes it to
+        every branch's buffer.
+
+        Args:
+            n: Number of branches to create. Must be >= 1.
+
+        Returns:
+            A tuple of `n` async iterators over the same underlying
+            stream.
+
+        Raises:
+            TypeError: If the channel is unbound or bound to sync mode.
+            RuntimeError: If the channel already has a subscriber.
+            ValueError: If `n` < 1.
+        """
+        if n < 1:
+            raise ValueError("atee() requires n >= 1")
+        source = self.__aiter__()
+        buffers: list[deque[T]] = [deque() for _ in range(n)]
+        exhausted = [False]
+        error: list[BaseException | None] = [None]
+        lock = asyncio.Lock()
+
+        async def branch(i: int) -> AsyncIterator[T]:
+            buf = buffers[i]
+            while True:
+                if buf:
+                    yield buf.popleft()
+                    continue
+                if exhausted[0]:
+                    if error[0] is not None:
+                        raise error[0]
+                    return
+                async with lock:
+                    if buf or exhausted[0]:
+                        continue
+                    try:
+                        item = await source.__anext__()
+                    except StopAsyncIteration:
+                        exhausted[0] = True
+                        continue
+                    except Exception as e:
+                        error[0] = e
+                        exhausted[0] = True
+                        continue
+                    for b in buffers:
+                        b.append(item)
+
+        return tuple(branch(i) for i in range(n))

libs/langgraph/langgraph/stream/transformers.py

@@ -0,0 +1,928 @@
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING, Any, Literal, cast
+
+from langchain_core.language_models._compat_bridge import message_to_events
+from langchain_core.language_models.chat_model_stream import (
+    AsyncChatModelStream,
+    ChatModelStream,
+)
+from langchain_core.messages import AIMessageChunk, BaseMessage
+from langchain_protocol.protocol import MessagesData
+from typing_extensions import NotRequired, TypedDict
+
+from langgraph.errors import GraphDrained, GraphInterrupt
+from langgraph.stream._types import ProtocolEvent, StreamTransformer
+from langgraph.stream.run_stream import AsyncSubgraphRunStream, SubgraphRunStream
+from langgraph.stream.stream_channel import StreamChannel
+
+if TYPE_CHECKING:
+    from collections.abc import Awaitable, Callable
+
+    from langgraph.stream._mux import StreamMux
+
+_logger = logging.getLogger(__name__)
+
+
+class ValuesTransformer(StreamTransformer):
+    """Capture values events as a drainable stream of state snapshots.
+
+    Provides the `run.values` projection. `run.output`,
+    `run.interrupted` and `run.interrupts` are tracked directly
+    by the run stream and do not depend on this transformer.
+
+    Native transformer — projection keys are exposed as direct
+    attributes on the run stream (e.g. `run.values`).
+
+    Only values events at the run's own level are captured; snapshots
+    from deeper subgraphs are left in the main event log but excluded
+    from the projection. "Own level" is defined by `scope`, which
+    `stream_events(version="v3")` / `astream_events(version="v3")` populate from the caller's
+    checkpoint namespace so that a nested `stream_events(version="v3")` call still
+    sees its own root snapshots.
+    """
+
+    _native = True
+    required_stream_modes = ("values",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
+        self._latest: dict[str, Any] | None = None
+        self._interrupted = False
+        self._interrupts: list[Any] = []
+        # Cached as a list once for cheap equality with the protocol
+        # event's `namespace` field, which is `list[str]`.
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"values": self._log}
+
+    @property
+    def error(self) -> BaseException | None:
+        """The error that ended the run, or `None` if it succeeded.
+
+        Set by the mux when it auto-fails the projection log.
+        """
+        return self._log._error
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "values":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+        self._latest = params["data"]
+        interrupts = params.get("interrupts", ())
+        if interrupts:
+            self._interrupted = True
+            self._interrupts.extend(interrupts)
+        self._log.push(params["data"])
+        return True
+
+
+class CustomTransformer(StreamTransformer):
+    """Capture custom events as a drainable stream of arbitrary payloads.
+
+    Nodes emit custom data via `get_stream_writer()`. This transformer
+    surfaces those events on `run.custom` as a `StreamChannel[Any]`,
+    preserving payloads in arrival order.
+
+    Only events at the run's own scope are captured; custom data from
+    deeper subgraphs is available on the respective subgraph handle's
+    `.custom` projection.
+
+    Native transformer — `run.custom` is a direct attribute.
+    """
+
+    _native = True
+    required_stream_modes = ("custom",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[Any] = StreamChannel()
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"custom": self._log}
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "custom":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+        self._log.push(params["data"])
+        return True
+
+
+class UpdatesTransformer(StreamTransformer):
+    """Capture updates events as a drainable stream of node outputs.
+
+    Surfaces `stream_mode="updates"` data on `run.updates` as a
+    `StreamChannel[dict[str, Any]]`. Each item is a dict mapping a node
+    (or task) name to the update it returned after a step.
+
+    Only events at the run's own scope are captured; updates from deeper
+    subgraphs are available on the respective subgraph handle's
+    `.updates` projection.
+
+    Native transformer — `run.updates` is a direct attribute.
+    """
+
+    _native = True
+    required_stream_modes = ("updates",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"updates": self._log}
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "updates":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+        self._log.push(params["data"])
+        return True
+
+
+class MessagesTransformer(StreamTransformer):
+    """Capture messages events as ChatModelStream objects.
+
+    The messages projection yields one `ChatModelStream` (or
+    `AsyncChatModelStream`) per LLM call. Consumers iterate
+    `run.messages` to get stream handles, then use each handle's typed
+    projections (`.text`, `.reasoning`, `.tool_calls`, `.usage`,
+    `.output`) for per-message content.
+
+    Two input shapes are handled (via `params["data"] = (payload,
+    metadata)` from `StreamMessagesHandler`):
+
+    1. Protocol event (dict with `"event"` key) — emitted by
+       `stream_events(version="v3")` / `astream_events(version="v3")` via the `on_stream_event`
+       callback. Routed to an existing `ChatModelStream` by
+       `metadata["run_id"]`. A `message-start` event creates a new
+       stream; `message-finish` closes it.
+    2. Whole `AIMessage` — emitted from `on_chain_end` when a node
+       returns a finalized message. Replayed as a synthetic protocol
+       event lifecycle via `message_to_events`, then the
+       already-complete stream is pushed to the log.
+
+    V1 `AIMessageChunk` tuples (from `on_llm_new_token`) are not
+    streamed into this projection: chat models that want to populate
+    `run.messages` with content-block streaming must use
+    `stream_events(version="v3")` / `astream_events(version="v3")`. Models called via the legacy
+    `stream()` method still surface their final `AIMessage` via
+    `on_chain_end` when a node returns it as state.
+
+    Only events at the run's own level are projected; tokens from
+    deeper subgraphs are left in the main event log but excluded from
+    `.messages`. "Own level" is defined by `scope`, which
+    `stream_events(version="v3")` / `astream_events(version="v3")` populate from the caller's checkpoint
+    namespace so that a `stream_events(version="v3")` call inside a node still sees its
+    own root chat model streams on `.messages`. Consumers that need
+    subgraph tokens should iterate the raw event stream or register a
+    custom transformer.
+
+    Native transformer — the `messages` projection is exposed as a
+    direct attribute on the run stream.
+    """
+
+    _native = True
+    required_stream_modes = ("messages",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[ChatModelStream] = StreamChannel()
+        # Correlate protocol events back to a ChatModelStream by run_id
+        # (attached to the event's metadata by StreamMessagesHandler).
+        self._by_run: dict[str, ChatModelStream] = {}
+        self._pump_fn: Callable[[], bool] | None = None
+        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
+        # Cached as a list once for cheap equality with the protocol
+        # event's `namespace` field, which is `list[str]`.
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"messages": self._log}
+
+    def _bind_pump(self, fn: Callable[[], bool]) -> None:
+        """Wire the sync pull callback. Called by GraphRunStream._wire_request_more."""
+        self._pump_fn = fn
+
+    def _bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
+        """Wire the async pull callback.
+
+        Called by `AsyncGraphRunStream._wire_arequest_more` so each
+        `AsyncChatModelStream` this transformer creates can drive the
+        shared graph pump from its projection cursors.
+        """
+        self._apump_fn = fn
+
+    def _make_stream(
+        self,
+        *,
+        namespace: list[str],
+        node: str | None,
+        message_id: str | None,
+    ) -> ChatModelStream:
+        """Create a ChatModelStream (sync) or AsyncChatModelStream (async).
+
+        Wires whichever pump is bound. Prefers the async pump so nested
+        iteration under `AsyncGraphRunStream` drives the graph forward
+        without a background task. The unwired fallback (no pump bound)
+        is used by unit tests that dispatch events manually.
+        """
+        if self._apump_fn is not None:
+            astream = AsyncChatModelStream(
+                namespace=namespace,
+                node=node,
+                message_id=message_id,
+            )
+            astream.set_arequest_more(self._apump_fn)
+            return astream
+        if self._pump_fn is not None:
+            stream: ChatModelStream = ChatModelStream(
+                namespace=namespace,
+                node=node,
+                message_id=message_id,
+            )
+            stream.set_request_more(self._pump_fn)
+            return stream
+        return AsyncChatModelStream(
+            namespace=namespace,
+            node=node,
+            message_id=message_id,
+        )
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "messages":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+
+        payload, metadata = params["data"]
+        node: str | None = metadata.get("langgraph_node")
+        run_id = str(metadata.get("run_id", "")) if metadata else ""
+
+        if isinstance(payload, dict) and "event" in payload:
+            self._route_protocol_event(
+                cast("MessagesData", payload), run_id=run_id, node=node
+            )
+        elif isinstance(payload, BaseMessage) and not isinstance(
+            payload, AIMessageChunk
+        ):
+            self._route_whole_message(payload, node=node)
+        # Legacy AIMessageChunk tuples (from on_llm_new_token) are ignored;
+        # v1 streaming callers must switch to stream_events(version="v3") to populate this
+        # projection.
+
+        return True
+
+    def _route_protocol_event(
+        self,
+        event: MessagesData,
+        *,
+        run_id: str,
+        node: str | None,
+    ) -> None:
+        event_type = event.get("event")
+        if event_type == "message-start":
+            message_id = event.get("message_id")
+            stream = self._make_stream(
+                namespace=[],
+                node=node,
+                message_id=str(message_id) if message_id is not None else None,
+            )
+            self._by_run[run_id] = stream
+            self._log.push(stream)
+            stream.dispatch(event)
+        elif run_id in self._by_run:
+            stream = self._by_run[run_id]
+            stream.dispatch(event)
+            if event_type == "message-finish":
+                del self._by_run[run_id]
+
+    def _route_whole_message(self, message: BaseMessage, *, node: str | None) -> None:
+        stream = self._make_stream(namespace=[], node=node, message_id=message.id)
+        for evt in message_to_events(message, message_id=message.id):
+            stream.dispatch(evt)
+        self._log.push(stream)
+
+    def finalize(self) -> None:
+        """Clear any routing state — streams close themselves via `message-finish`."""
+        self._by_run.clear()
+
+    def fail(self, err: BaseException) -> None:
+        """Propagate run error to any streams still open when the graph fails."""
+        for stream in list(self._by_run.values()):
+            stream.fail(err)
+        self._by_run.clear()
+
+
+SubgraphStatus = Literal["started", "completed", "failed", "interrupted", "drained"]
+
+
+def _parse_ns_segment(segment: str) -> tuple[str, str | None]:
+    """Split a namespace segment into `(graph_name, trigger_call_id)`.
+
+    Segments are formatted `node_name:task_id` by `prepare_next_tasks`.
+    Returns `(segment, None)` if no `:` is present.
+    """
+    name, sep, task_id = segment.partition(":")
+    return name, task_id if sep else None
+
+
+class LifecyclePayload(TypedDict, total=False):
+    """Payload of a lifecycle event surfaced on the `lifecycle` channel.
+
+    Auto-forwarded as `lifecycle` protocol events (no `custom:` prefix
+    because `LifecycleTransformer` is a native transformer) so remote
+    SDK clients receive the same data in-process consumers see via
+    `run.lifecycle`.
+    """
+
+    event: SubgraphStatus
+    namespace: list[str]
+    graph_name: NotRequired[str]
+    trigger_call_id: NotRequired[str]
+    error: NotRequired[str]
+
+
+class _TasksLifecycleBase(StreamTransformer):
+    """Shared bookkeeping for `tasks`-event-driven lifecycle inference.
+
+    Both `LifecycleTransformer` (wire-serializable channel) and
+    `SubgraphTransformer` (in-process navigation handles) discover
+    subgraphs by watching the same `tasks` stream — `started` on the
+    first event at a tracked namespace, terminal status when the
+    parent's `TaskResultPayload` arrives. Centralizing the dispatch
+    + open-set bookkeeping here keeps the inference rules from
+    drifting between the two surfaces.
+
+    Subclasses provide three template-method hooks:
+
+    - `_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.
+
+    Tasks events are suppressed from the main event log (`process`
+    returns False) — they're folded into whichever projection the
+    subclass populates; consumers iterating the raw protocol stream
+    see the higher-level view.
+    """
+
+    required_stream_modes = ("tasks",)
+
+    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
+        # `TaskResultPayload` will close it.
+        self._open: dict[tuple[str, ...], str] = {}
+
+    # --- Template-method hooks (subclass overrides) ---
+
+    def _should_track(self, ns: tuple[str, ...]) -> bool:
+        """Scope filter — return True iff `ns` is in this transformer's region."""
+        raise NotImplementedError
+
+    def _on_started(
+        self,
+        ns: tuple[str, ...],
+        graph_name: str | None,
+        trigger_call_id: str | None,
+    ) -> None:
+        """Fired once per discovered namespace (first observed task event)."""
+        raise NotImplementedError
+
+    def _on_terminal(
+        self,
+        ns: tuple[str, ...],
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> None:
+        """Fired once per tracked namespace when its parent's result arrives,
+        or via finalize/fail safety-net sweeps.
+        """
+        raise NotImplementedError
+
+    # --- Dispatch + bookkeeping (shared) ---
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "tasks":
+            return True
+        ns = tuple(event["params"]["namespace"])
+        data = event["params"]["data"]
+        if "result" in data:
+            self._handle_task_result(ns, data)
+        else:
+            self._handle_task_start(ns)
+        # 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:
+        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
+
+    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."""
+        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:
+                continue
+            status, error = _terminal_from_result(data)
+            transitions.append((child_ns, status, error))
+            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)
+
+    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)
+        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)
+        self._open.clear()
+
+
+def _status_from_exception(err: BaseException) -> tuple[SubgraphStatus, str | None]:
+    """Map a run exception to a subgraph terminal status and error string."""
+    if isinstance(err, GraphDrained):
+        return "drained", None
+    if isinstance(err, GraphInterrupt):
+        return "interrupted", None
+    return "failed", str(err)
+
+
+def _terminal_from_result(
+    payload: dict[str, Any],
+) -> tuple[SubgraphStatus, str | None]:
+    """Map a `TaskResultPayload` to a `(status, error)` pair.
+
+    Order matters: a result with both `error` and `interrupts` prefers
+    the interrupt classification, since `GraphInterrupt` manifests as
+    a populated `interrupts` list, not as `error`.
+    """
+    if payload.get("interrupts"):
+        return "interrupted", None
+    error = payload.get("error")
+    if error:
+        return "failed", str(error)
+    return "completed", None
+
+
+class LifecycleTransformer(_TasksLifecycleBase):
+    """Surface subgraph lifecycle as `lifecycle` protocol events.
+
+    Pushes `LifecyclePayload` to a `StreamChannel` named `lifecycle`.
+    The channel is auto-forwarded by the mux so payloads land in the
+    main event log under `method = "lifecycle"` (native transformer —
+    no `custom:` prefix) — visible to remote SDK clients over the
+    wire and to in-process consumers via `run.lifecycle`.
+
+    Tracks subgraphs at every depth strictly below the transformer's
+    scope, so a graph → subgraph → subgraph chain produces lifecycle
+    events for both nested levels in a flat stream.
+
+    Native transformer — projection key `lifecycle` is exposed as
+    `run.lifecycle`.
+    """
+
+    _native = True
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._channel: StreamChannel[LifecyclePayload] = StreamChannel("lifecycle")
+
+    def init(self) -> dict[str, Any]:
+        return {"lifecycle": self._channel}
+
+    def _should_track(self, ns: tuple[str, ...]) -> bool:
+        depth = len(self.scope)
+        return len(ns) > depth and ns[:depth] == self.scope
+
+    def _on_started(
+        self,
+        ns: tuple[str, ...],
+        graph_name: str | None,
+        trigger_call_id: str | None,
+    ) -> None:
+        if trigger_call_id is None:
+            # Without a task id we can't correlate a parent-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)}
+        if graph_name:
+            payload["graph_name"] = graph_name
+        payload["trigger_call_id"] = trigger_call_id
+        self._channel.push(payload)
+
+    def _on_terminal(
+        self,
+        ns: tuple[str, ...],
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> None:
+        payload: LifecyclePayload = {"event": status, "namespace": list(ns)}
+        if error is not None:
+            payload["error"] = error
+        self._channel.push(payload)
+
+
+class SubgraphTransformer(_TasksLifecycleBase):
+    """Discover subgraph invocations as in-process navigation handles.
+
+    Per discovered direct-child subgraph, builds a `SubgraphRunStream`
+    (or `AsyncSubgraphRunStream`) wrapping a child mini-mux scoped to
+    the subgraph's namespace. Consumers iterate `run.subgraphs` to
+    receive handles, then drill into `handle.values` / `handle.messages`
+    / `handle.subgraphs` (recursive grandchildren) / `handle.lifecycle`.
+
+    Each mini-mux owns its own scope and uses its own
+    `SubgraphTransformer` to discover its direct children, so
+    grandchildren live on the child handle — never on the root's
+    `subgraphs` log. Forwarding events into the matching child mini-mux
+    is what keeps the child's projections populated.
+
+    Native transformer — `subgraphs` is exposed as `run.subgraphs`.
+    """
+
+    _native = True
+    supports_sync = True
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[SubgraphRunStream | AsyncSubgraphRunStream] = (
+            StreamChannel()
+        )
+        self._handles: dict[
+            tuple[str, ...], SubgraphRunStream | AsyncSubgraphRunStream
+        ] = {}
+        self._mux: StreamMux | None = None
+
+    def init(self) -> dict[str, Any]:
+        return {"subgraphs": self._log}
+
+    def _on_register(self, mux: Any) -> None:
+        self._mux = mux
+
+    def _should_track(self, ns: tuple[str, ...]) -> bool:
+        # Direct children only — grandchildren are picked up by the
+        # child mini-mux's own SubgraphTransformer.
+        depth = len(self.scope)
+        return len(ns) == depth + 1 and ns[:depth] == self.scope
+
+    def _on_started(
+        self,
+        ns: tuple[str, ...],
+        graph_name: str | None,
+        trigger_call_id: str | None,
+    ) -> None:
+        if self._mux is None:
+            return
+        try:
+            child_mux = self._mux._make_child(ns)
+        except RuntimeError:
+            return
+        handle_cls = AsyncSubgraphRunStream if child_mux.is_async else SubgraphRunStream
+        handle = handle_cls(
+            mux=child_mux,
+            path=ns,
+            graph_name=graph_name,
+            trigger_call_id=trigger_call_id,
+        )
+        self._handles[ns] = handle
+        self._log.push(handle)
+
+    def _on_terminal(
+        self,
+        ns: tuple[str, ...],
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> None:
+        handle = self._handles.get(ns)
+        if handle is None or not self._mark_terminal(handle, status, error):
+            return
+        self._close_or_fail_handle(handle, status, error)
+
+    async def _aon_terminal(
+        self,
+        ns: tuple[str, ...],
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> None:
+        handle = self._handles.get(ns)
+        if handle is None or not self._mark_terminal(handle, status, error):
+            return
+        await self._aclose_or_fail_handle(handle, status, error)
+
+    def _mark_terminal(
+        self,
+        handle: SubgraphRunStream | AsyncSubgraphRunStream,
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> bool:
+        """Mark a handle terminal once. Returns True on first transition."""
+        if handle._seen_terminal:
+            return False
+        handle.status = status
+        if error is not None and handle.error is None:
+            handle.error = error
+        handle._seen_terminal = True
+        return True
+
+    def _close_or_fail_handle(
+        self,
+        handle: SubgraphRunStream | AsyncSubgraphRunStream,
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> None:
+        if handle._mux is None or handle._mux._events._closed:
+            return
+        if status == "failed":
+            handle._mux.fail(RuntimeError(error or "Subgraph failed"))
+        else:
+            handle._mux.close()
+
+    async def _aclose_or_fail_handle(
+        self,
+        handle: SubgraphRunStream | AsyncSubgraphRunStream,
+        status: SubgraphStatus,
+        error: str | None,
+    ) -> None:
+        if handle._mux is None or handle._mux._events._closed:
+            return
+        if status == "failed":
+            await handle._mux.afail(RuntimeError(error or "Subgraph failed"))
+        else:
+            await handle._mux.aclose()
+
+    def _handle_for_event(
+        self, event: ProtocolEvent
+    ) -> SubgraphRunStream | AsyncSubgraphRunStream | None:
+        ns = tuple(event["params"]["namespace"])
+        depth = len(self.scope)
+        if len(ns) < depth + 1:
+            return None
+        handle = self._handles.get(ns[: depth + 1])
+        if handle is None or handle._mux is None or handle._mux._events._closed:
+            return None
+        return handle
+
+    def process(self, event: ProtocolEvent) -> bool:
+        # Run tasks bookkeeping first so a `started` handle exists
+        # by the time we forward the event to the child mini-mux.
+        keep = super().process(event)
+        handle = self._handle_for_event(event)
+        if handle is not None:
+            handle._observe_event(event)
+            handle._mux.push(event)
+        return keep
+
+    async def aprocess(self, event: ProtocolEvent) -> bool:
+        # Async counterpart: repeats the tasks bookkeeping here so
+        # child mini-muxes receive events through their async lane.
+        if event["method"] == "tasks":
+            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)
+            else:
+                self._handle_task_start(ns)
+            keep = False
+        else:
+            keep = True
+        handle = self._handle_for_event(event)
+        if handle is not None:
+            handle._observe_event(event)
+            await handle._mux.apush(event)
+        return keep
+
+    def _complete_open_handles(self) -> BaseException | None:
+        first_error: BaseException | None = None
+        for ns in list(self._open):
+            try:
+                self._on_terminal(ns, "completed", None)
+            except BaseException as e:
+                if first_error is None:
+                    first_error = e
+        self._open.clear()
+        for handle in self._handles.values():
+            if self._mark_terminal(handle, "completed", None):
+                try:
+                    self._close_or_fail_handle(handle, "completed", None)
+                except BaseException as e:
+                    if first_error is None:
+                        first_error = e
+        return first_error
+
+    async def _acomplete_open_handles(self) -> BaseException | None:
+        first_error: BaseException | None = None
+        for ns in list(self._open):
+            try:
+                await self._aon_terminal(ns, "completed", None)
+            except BaseException as e:
+                if first_error is None:
+                    first_error = e
+        self._open.clear()
+        for handle in self._handles.values():
+            if self._mark_terminal(handle, "completed", None):
+                try:
+                    await self._aclose_or_fail_handle(handle, "completed", None)
+                except BaseException as e:
+                    if first_error is None:
+                        first_error = e
+        return first_error
+
+    def finalize(self) -> None:
+        first_error = self._complete_open_handles()
+        if first_error is not None:
+            raise first_error
+
+    async def afinalize(self) -> None:
+        first_error = await self._acomplete_open_handles()
+        if first_error is not None:
+            raise first_error
+
+    def fail(self, err: BaseException) -> None:
+        status, error_str = _status_from_exception(err)
+        self._open.clear()
+        for handle in self._handles.values():
+            self._mark_terminal(handle, status, error_str)
+            if handle._mux is not None and not handle._mux._events._closed:
+                try:
+                    handle._mux.fail(err)
+                except Exception:
+                    _logger.warning(
+                        "Error failing subgraph mini-mux at %s; "
+                        "subscribers may not see the terminal error.",
+                        handle.path,
+                        exc_info=True,
+                    )
+
+    async def afail(self, err: BaseException) -> None:
+        status, error_str = _status_from_exception(err)
+        self._open.clear()
+        for handle in self._handles.values():
+            self._mark_terminal(handle, status, error_str)
+            if handle._mux is not None and not handle._mux._events._closed:
+                try:
+                    await handle._mux.afail(err)
+                except Exception:
+                    _logger.warning(
+                        "Error failing subgraph mini-mux at %s; "
+                        "subscribers may not see the terminal error.",
+                        handle.path,
+                        exc_info=True,
+                    )
+
+
+class CheckpointsTransformer(StreamTransformer):
+    """Capture checkpoint events as a drainable stream.
+
+    Surfaces `stream_mode="checkpoints"` data on `run.checkpoints` as
+    a `StreamChannel[dict[str, Any]]`. Each item is in the same format
+    as returned by `get_state()`.
+
+    Checkpoint events are only emitted when a checkpointer is configured
+    on the graph. When no checkpointer is present, the projection exists
+    but receives no events.
+
+    Only events at the run's own scope are captured; checkpoint data from
+    deeper subgraphs is available on the respective subgraph handle's
+    `.checkpoints` projection.
+
+    Native transformer — `run.checkpoints` is a direct attribute.
+    """
+
+    _native = True
+    required_stream_modes = ("checkpoints",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"checkpoints": self._log}
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "checkpoints":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+        self._log.push(params["data"])
+        return True
+
+
+class DebugTransformer(StreamTransformer):
+    """Capture debug events as a drainable stream.
+
+    Surfaces `stream_mode="debug"` data on `run.debug` as a
+    `StreamChannel[dict[str, Any]]`. Each item is a debug event with
+    step-level detail (checkpoint snapshots, task payloads, and
+    task results wrapped with step number and timestamp).
+
+    Only events at the run's own scope are captured; debug data from
+    deeper subgraphs is available on the respective subgraph handle's
+    `.debug` projection.
+
+    Native transformer — `run.debug` is a direct attribute.
+    """
+
+    _native = True
+    required_stream_modes = ("debug",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"debug": self._log}
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "debug":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+        self._log.push(params["data"])
+        return True
+
+
+class TasksTransformer(StreamTransformer):
+    """Capture raw task events as a drainable stream.
+
+    Surfaces `stream_mode="tasks"` data on `run.tasks` as a
+    `StreamChannel[dict[str, Any]]`. Each item is a task payload
+    (start or result).
+
+    `LifecycleTransformer` and `SubgraphTransformer` also consume
+    `tasks` events for subgraph discovery and lifecycle tracking.
+    This transformer captures the raw payloads independently for
+    consumers who need task-level detail.
+
+    Only events at the run's own scope are captured; task data from
+    deeper subgraphs is available on the respective subgraph handle's
+    `.tasks` projection.
+
+    Native transformer — `run.tasks` is a direct attribute.
+    """
+
+    _native = True
+    required_stream_modes = ("tasks",)
+
+    def __init__(self, scope: tuple[str, ...] = ()) -> None:
+        super().__init__(scope)
+        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
+        self._scope_list: list[str] = list(scope)
+
+    def init(self) -> dict[str, Any]:
+        return {"tasks": self._log}
+
+    def process(self, event: ProtocolEvent) -> bool:
+        if event["method"] != "tasks":
+            return True
+        params = event["params"]
+        if params["namespace"] != self._scope_list:
+            return True
+        self._log.push(params["data"])
+        return True

libs/langgraph/langgraph/types.py

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

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.1.6"
+version = "1.2.0a3"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -24,10 +24,10 @@ classifiers = [
     'Programming Language :: Python :: 3.13',
 ]
 dependencies = [
-    "langchain-core>=0.1",
-    "langgraph-checkpoint>=2.1.0,<5.0.0",
+    "langchain-core>=1.4.0a2,<2",
+    "langgraph-checkpoint>=4.1.0a3,<5.0.0",
     "langgraph-sdk>=0.3.0,<0.4.0",
-    "langgraph-prebuilt>=1.0.9,<1.1.0",
+    "langgraph-prebuilt>=1.0.12,<1.1.0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",
 ]
@@ -38,7 +38,7 @@ Homepage = "https://docs.langchain.com/oss/python/langgraph/overview"
 Documentation = "https://reference.langchain.com/python/langgraph/"
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/langgraph"
 Changelog = "https://github.com/langchain-ai/langgraph/releases"
-Twitter = "https://x.com/LangChain"
+Twitter = "https://x.com/langchain_oss"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/langgraph/tests/test_channels.py

@@ -1,18 +1,34 @@
 import operator
 from collections.abc import Sequence
+from typing import Annotated
 
 import pytest
+from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
+from langgraph.checkpoint.base import DELTA_SENTINEL
+from langgraph.checkpoint.memory import InMemorySaver
+from langgraph.checkpoint.serde.types import _DeltaSnapshot
+from typing_extensions import NotRequired, TypedDict
 
 from langgraph._internal._typing import MISSING
 from langgraph.channels.binop import BinaryOperatorAggregate
+from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
 from langgraph.channels.topic import Topic
 from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.errors import EmptyChannelError, InvalidUpdateError
+from langgraph.graph import START, StateGraph
+from langgraph.graph.message import _messages_delta_reducer
+from langgraph.graph.state import _get_channel
+from langgraph.types import Overwrite
 
 pytestmark = pytest.mark.anyio
 
 
+# ---------------------------------------------------------------------------
+# Core channel primitives
+# ---------------------------------------------------------------------------
+
+
 def test_last_value() -> None:
     channel = LastValue(int).from_checkpoint(MISSING)
     assert channel.ValueType is int
@@ -95,25 +111,542 @@ def test_untracked_value() -> None:
     assert channel.ValueType is dict
     assert channel.UpdateType is dict
 
-    # UntrackedValue should start empty
     with pytest.raises(EmptyChannelError):
         channel.get()
 
-    # Should be able to update with a value
     test_data = {"session": "test", "temp": "dir"}
     channel.update([test_data])
     assert channel.get() == test_data
 
-    # Update with new value
     new_data = {"session": "updated", "temp": "newdir"}
     channel.update([new_data])
     assert channel.get() == new_data
 
-    # On checkpoint, UntrackedValue should return MISSING
     checkpoint = channel.checkpoint()
     assert checkpoint is MISSING
 
-    # Creating from checkpoint with MISSING should start empty
     new_channel = UntrackedValue(dict).from_checkpoint(checkpoint)
     with pytest.raises(EmptyChannelError):
         new_channel.get()
+
+
+# ---------------------------------------------------------------------------
+# DeltaChannel — message reducer
+# ---------------------------------------------------------------------------
+
+
+def test_delta_channel_basic_two_steps() -> None:
+    ch = DeltaChannel(_messages_delta_reducer, list).from_checkpoint(MISSING)
+
+    ch.update([HumanMessage(content="hi", id="h1")])
+    d1 = ch.checkpoint()
+    assert d1 is DELTA_SENTINEL
+
+    ch.update([AIMessage(content="hello", id="a1")])
+    d2 = ch.checkpoint()
+    assert d2 is DELTA_SENTINEL
+
+    assert len(ch.get()) == 2
+    assert ch.get()[0].content == "hi"
+    assert ch.get()[1].content == "hello"
+
+
+def test_delta_channel_from_checkpoint_writes_list() -> None:
+    """replay_writes on a fresh channel replays through the operator."""
+    spec = DeltaChannel(_messages_delta_reducer, list)
+    ch = spec.from_checkpoint(DELTA_SENTINEL)
+    ch.replay_writes(
+        [
+            ("t0", "messages", HumanMessage(content="hi", id="h1")),
+            ("t1", "messages", AIMessage(content="hello", id="a1")),
+            ("t2", "messages", HumanMessage(content="bye", id="h2")),
+        ]
+    )
+    msgs = ch.get()
+    assert len(msgs) == 3
+    assert msgs[0].content == "hi"
+    assert msgs[1].content == "hello"
+    assert msgs[2].content == "bye"
+
+
+def test_delta_channel_from_checkpoint_backwards_compat() -> None:
+    spec = DeltaChannel(_messages_delta_reducer, list)
+    old_value = [HumanMessage(content="old", id="h1")]
+    ch = spec.from_checkpoint(old_value)
+    assert ch.get() == old_value
+
+
+def test_delta_channel_overwrite() -> None:
+    ch = DeltaChannel(_messages_delta_reducer, list).from_checkpoint(MISSING)
+    ch.update([HumanMessage(content="old", id="h1")])
+
+    ch.update([Overwrite([HumanMessage(content="new", id="h2")])])
+    d = ch.checkpoint()
+    assert d is DELTA_SENTINEL
+    assert len(ch.get()) == 1
+    assert ch.get()[0].content == "new"
+
+
+def test_delta_channel_remove_message_and_replay() -> None:
+    """RemoveMessage must round-trip correctly when writes are replayed."""
+    spec = DeltaChannel(_messages_delta_reducer, list)
+    ch = spec.from_checkpoint(MISSING)
+
+    ch.update([HumanMessage(content="hi", id="h1")])
+    ch.update([AIMessage(content="hello", id="a1")])
+    assert ch.get() == [
+        HumanMessage(content="hi", id="h1"),
+        AIMessage(content="hello", id="a1"),
+    ]
+
+    ch.update([RemoveMessage(id="a1")])
+    assert ch.get() == [HumanMessage(content="hi", id="h1")]
+
+    ch2 = spec.from_checkpoint(DELTA_SENTINEL)
+    ch2.replay_writes(
+        [
+            ("t0", "messages", HumanMessage(content="hi", id="h1")),
+            ("t1", "messages", AIMessage(content="hello", id="a1")),
+            ("t2", "messages", RemoveMessage(id="a1")),
+        ]
+    )
+    assert ch2.get() == [HumanMessage(content="hi", id="h1")]
+
+
+def test_delta_channel_update_by_id_and_replay() -> None:
+    """Updating a message by ID must round-trip correctly through writes replay."""
+    spec = DeltaChannel(_messages_delta_reducer, list)
+    ch = spec.from_checkpoint(MISSING)
+
+    ch.update([HumanMessage(content="original", id="h1")])
+    ch.update([HumanMessage(content="updated", id="h1")])
+    assert ch.get() == [HumanMessage(content="updated", id="h1")]
+
+    ch2 = spec.from_checkpoint(DELTA_SENTINEL)
+    ch2.replay_writes(
+        [
+            ("t0", "messages", HumanMessage(content="original", id="h1")),
+            ("t1", "messages", HumanMessage(content="updated", id="h1")),
+        ]
+    )
+    assert len(ch2.get()) == 1
+    assert ch2.get()[0].content == "updated"
+
+
+def test_delta_channel_checkpoint_returns_sentinel() -> None:
+    """checkpoint() always returns DELTA_SENTINEL regardless of state."""
+    ch = DeltaChannel(_messages_delta_reducer, list).from_checkpoint(MISSING)
+    assert ch.checkpoint() is DELTA_SENTINEL
+
+    ch.update([HumanMessage(content="hi", id="h1")])
+    assert ch.checkpoint() is DELTA_SENTINEL
+
+
+# ---------------------------------------------------------------------------
+# DeltaChannel — snapshot frequency
+# ---------------------------------------------------------------------------
+
+
+def test_delta_channel_snapshot_step_based() -> None:
+    """Snapshots fire on every Nth step regardless of whether the channel was written.
+
+    With snapshot_frequency=N, every Nth pregel step produces a _DeltaSnapshot
+    blob — even if the channel had no write that step (eager snapshot). This
+    bounds the ancestor walk to at most N steps on any read.
+    """
+
+    class State(TypedDict):
+        messages: Annotated[
+            list, DeltaChannel(_messages_delta_reducer, snapshot_frequency=5)
+        ]
+        other: str
+
+    def node_a(state: State) -> dict:
+        i = len(state["messages"]) // 2
+        return {"messages": [AIMessage(content=f"a{i}", id=f"a{i}")]}
+
+    def node_b(state: State) -> dict:
+        return {"other": "y"}
+
+    g = StateGraph(State)
+    g.add_node("a", node_a)
+    g.add_node("b", node_b)
+    g.add_edge(START, "a")
+    g.add_edge("a", "b")
+    saver = InMemorySaver()
+    graph = g.compile(checkpointer=saver)
+
+    config = {"configurable": {"thread_id": "t1"}}
+    for i in range(6):
+        graph.invoke(
+            {"messages": [HumanMessage(content=f"h{i}", id=f"h{i}")], "other": ""},
+            config,
+        )
+
+    msg_blob_values = [
+        saver.serde.loads_typed((type_tag, blob))
+        for k, (type_tag, blob) in saver.blobs.items()
+        if k[2] == "messages" and type_tag == "msgpack" and blob
+    ]
+    snapshots = [v for v in msg_blob_values if isinstance(v, _DeltaSnapshot)]
+    assert snapshots, "expected at least one _DeltaSnapshot blob for messages"
+
+    state = graph.get_state(config)
+    assert len(state.values["messages"]) == 12  # 6 human + 6 AI
+
+
+def test_delta_channel_snapshot_fires_even_when_not_written() -> None:
+    """Eager snapshot: _DeltaSnapshot stored at snapshot step even when the
+    channel had no write that step (node_b doesn't touch messages).
+    """
+
+    class State(TypedDict):
+        messages: Annotated[
+            list, DeltaChannel(_messages_delta_reducer, snapshot_frequency=3)
+        ]
+        tick: int
+
+    def writer(state: State) -> dict:
+        i = len(state["messages"]) // 2
+        return {"messages": [AIMessage(content=f"a{i}", id=f"a{i}")]}
+
+    def ticker(state: State) -> dict:
+        return {"tick": state["tick"] + 1}
+
+    g = StateGraph(State)
+    g.add_node("writer", writer)
+    g.add_node("ticker", ticker)
+    g.add_edge(START, "writer")
+    g.add_edge("writer", "ticker")
+    saver = InMemorySaver()
+    graph = g.compile(checkpointer=saver)
+
+    config = {"configurable": {"thread_id": "t1"}}
+    for i in range(5):
+        graph.invoke(
+            {"messages": [HumanMessage(content=f"h{i}", id=f"h{i}")], "tick": 0},
+            config,
+        )
+
+    msg_blobs = {
+        k: saver.serde.loads_typed((t, b))
+        for k, (t, b) in saver.blobs.items()
+        if k[2] == "messages" and t == "msgpack" and b
+    }
+    snapshots = {k: v for k, v in msg_blobs.items() if isinstance(v, _DeltaSnapshot)}
+    assert snapshots, (
+        "eager snapshots must fire even on steps where messages wasn't written"
+    )
+
+    state = graph.get_state(config)
+    assert len(state.values["messages"]) == 10  # 5 human + 5 AI
+
+
+# ---------------------------------------------------------------------------
+# DeltaChannel — end-to-end (InMemorySaver)
+# ---------------------------------------------------------------------------
+
+
+def test_delta_channel_inmemory_saver_assembles_writes() -> None:
+    """InMemorySaver assembles writes from checkpoint_writes inside get_tuple."""
+
+    class State(TypedDict):
+        messages: Annotated[list, DeltaChannel(_messages_delta_reducer, list)]
+
+    n = {"v": 0}
+
+    def respond(state: State) -> dict:
+        n["v"] += 1
+        return {"messages": [AIMessage(content=f"ok{n['v']}", id=f"ai{n['v']}")]}
+
+    builder = StateGraph(State)
+    builder.add_node("respond", respond)
+    builder.add_edge(START, "respond")
+    saver = InMemorySaver()
+    graph = builder.compile(checkpointer=saver)
+    config = {"configurable": {"thread_id": "t1"}}
+
+    graph.invoke({"messages": [HumanMessage(content="hi", id="h1")]}, config)
+    graph.invoke({"messages": [HumanMessage(content="bye", id="h2")]}, config)
+
+    saved = saver.get_tuple(config)
+    assert saved is not None
+    assert "messages" not in saved.checkpoint["channel_values"]
+
+    state = graph.get_state(config)
+    assert len(state.values["messages"]) == 4  # 2 human + 2 AI
+
+
+# ---------------------------------------------------------------------------
+# DeltaChannel — dict reducer
+# ---------------------------------------------------------------------------
+
+
+def _delta_channel_with_type(op, typ):
+    """Build a DeltaChannel with an explicit type via the Annotated injection path."""
+    return _get_channel("_test", Annotated[typ, DeltaChannel(op)])
+
+
+def test_delta_channel_dict_reducer_fresh_channel() -> None:
+    """DeltaChannel with a dict reducer starts as empty dict on MISSING checkpoint."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
+    assert ch.is_available()
+    assert ch.get() == {}
+
+
+def test_delta_channel_dict_reducer_basic_updates() -> None:
+    """DeltaChannel with a dict reducer accumulates key/value pairs across steps."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
+
+    ch.update([{"a": 1}])
+    d1 = ch.checkpoint()
+    assert d1 is DELTA_SENTINEL
+
+    ch.update([{"b": 2}])
+    d2 = ch.checkpoint()
+    assert d2 is DELTA_SENTINEL
+
+    assert ch.get() == {"a": 1, "b": 2}
+
+
+def test_delta_channel_dict_reducer_writes_reconstruction() -> None:
+    """replay_writes on a fresh channel replays through a dict merge reducer."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    spec = _delta_channel_with_type(merge_dicts, dict)
+    ch = spec.from_checkpoint(DELTA_SENTINEL)
+    ch.replay_writes(
+        [
+            ("t0", "files", {"a": 1}),
+            ("t1", "files", {"b": 2}),
+            ("t2", "files", {"c": 3}),
+        ]
+    )
+    assert ch.get() == {"a": 1, "b": 2, "c": 3}
+
+
+def test_delta_channel_dict_reducer_with_deletions() -> None:
+    """Dict reducer that treats None values as deletions works end-to-end."""
+
+    def merge_files(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            for k, v in w.items():
+                if v is None:
+                    result.pop(k, None)
+                else:
+                    result[k] = v
+        return result
+
+    ch = _delta_channel_with_type(merge_files, dict).from_checkpoint(MISSING)
+    ch.update([{"file1.py": "content1", "file2.py": "content2"}])
+    ch.update([{"file1.py": None, "file3.py": "content3"}])
+    assert ch.get() == {"file2.py": "content2", "file3.py": "content3"}
+
+    spec = _delta_channel_with_type(merge_files, dict)
+    ch2 = spec.from_checkpoint(DELTA_SENTINEL)
+    ch2.replay_writes(
+        [
+            ("t0", "files", {"file1.py": "content1", "file2.py": "content2"}),
+            ("t1", "files", {"file1.py": None, "file3.py": "content3"}),
+        ]
+    )
+    assert ch2.get() == {"file2.py": "content2", "file3.py": "content3"}
+
+
+def test_delta_channel_dict_reducer_overwrite_in_update() -> None:
+    """Overwrite(dict) in update() must preserve dict shape, not coerce to list."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    ch = _delta_channel_with_type(merge_dicts, dict).from_checkpoint(MISSING)
+    ch.update([{"a": 1}])
+    ch.update([Overwrite({"b": 2, "c": 3})])
+    assert ch.get() == {"b": 2, "c": 3}
+
+
+def test_delta_channel_dict_reducer_overwrite_in_writes_replay() -> None:
+    """Overwrite(dict) embedded in replayed writes must reconstruct as dict."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    spec = _delta_channel_with_type(merge_dicts, dict)
+    ch = spec.from_checkpoint(DELTA_SENTINEL)
+    ch.replay_writes(
+        [
+            ("t0", "files", {"a": 1}),
+            ("t1", "files", Overwrite({"x": 10, "y": 20})),
+            ("t2", "files", {"z": 30}),
+        ]
+    )
+    assert ch.get() == {"x": 10, "y": 20, "z": 30}
+
+
+def test_delta_channel_dict_reducer_with_notrequired_annotation() -> None:
+    """DeltaChannel infers dict type through `Annotated[NotRequired[dict[...]], ch]`."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    annotation = Annotated[NotRequired[dict[str, int]], DeltaChannel(merge_dicts)]
+    ch = _get_channel("files", annotation).from_checkpoint(MISSING)
+    assert ch.get() == {}
+    ch.update([{"a": 1}])
+    ch.update([{"b": 2}])
+    assert ch.get() == {"a": 1, "b": 2}
+
+
+def test_delta_channel_dict_reducer_end_to_end_filesystem() -> None:
+    """End-to-end: graph with dict-reducer (filesystem-style) channel wrapped in DeltaChannel."""
+
+    def merge_files(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            for k, v in w.items():
+                if v is None:
+                    result.pop(k, None)
+                else:
+                    result[k] = v
+        return result
+
+    class State(TypedDict):
+        files: Annotated[dict[str, str], DeltaChannel(merge_files)]
+
+    turn = {"v": 0}
+
+    def write_file(state: State) -> dict:
+        turn["v"] += 1
+        n = turn["v"]
+        return {"files": {f"/doc_{n}.txt": f"content for turn {n}"}}
+
+    builder = StateGraph(State)
+    builder.add_node("write_file", write_file)
+    builder.add_edge(START, "write_file")
+    saver = InMemorySaver()
+    graph = builder.compile(checkpointer=saver)
+    config = {"configurable": {"thread_id": "fs"}}
+
+    for _ in range(3):
+        graph.invoke({"files": {}}, config)
+
+    saved = saver.get_tuple(config)
+    assert saved is not None
+    assert "files" not in saved.checkpoint["channel_values"]
+    state = graph.get_state(config)
+    assert state.values["files"] == {
+        "/doc_1.txt": "content for turn 1",
+        "/doc_2.txt": "content for turn 2",
+        "/doc_3.txt": "content for turn 3",
+    }
+
+    def delete_file(state: State) -> dict:
+        return {"files": {"/doc_1.txt": None}}
+
+    builder2 = StateGraph(State)
+    builder2.add_node("write_file", write_file)
+    builder2.add_node("delete_file", delete_file)
+    builder2.add_edge(START, "write_file")
+    builder2.add_edge("write_file", "delete_file")
+    turn["v"] = 0
+    saver2 = InMemorySaver()
+    graph2 = builder2.compile(checkpointer=saver2)
+    config2 = {"configurable": {"thread_id": "fs2"}}
+    graph2.invoke({"files": {}}, config2)
+    state2 = graph2.get_state(config2)
+    assert state2.values["files"] == {}
+
+
+def test_delta_channel_dict_reducer_backwards_compat() -> None:
+    """A pre-DeltaChannel dict checkpoint must load as a dict, not be listified."""
+
+    def merge_dicts(state: dict, writes: list) -> dict:
+        result = dict(state)
+        for w in writes:
+            result.update(w)
+        return result
+
+    spec = _delta_channel_with_type(merge_dicts, dict)
+    old_value = {"a": 1, "b": 2}
+    ch = spec.from_checkpoint(old_value)
+    assert ch.get() == {"a": 1, "b": 2}
+
+
+# ---------------------------------------------------------------------------
+# DeltaChannel — seed / pre-delta migration
+# ---------------------------------------------------------------------------
+
+
+def test_delta_channel_from_checkpoint_honors_seed() -> None:
+    """A non-sentinel value to from_checkpoint is used as the pre-delta seed.
+
+    Guards the pre-delta migration path: when the saver's ancestor walk hits
+    a pre-DeltaChannel blob it passes it as `seed` so replay reconstructs
+    the post-migration state correctly rather than replaying from empty.
+    """
+    spec = DeltaChannel(_messages_delta_reducer, list)
+    seed = [HumanMessage(content="pre-delta", id="p1")]
+    ch = spec.from_checkpoint(seed)
+    ch.replay_writes(
+        [
+            ("t0", "messages", AIMessage(content="delta-1", id="d1")),
+            ("t1", "messages", HumanMessage(content="delta-2", id="d2")),
+        ]
+    )
+    msgs = ch.get()
+    assert [m.content for m in msgs] == ["pre-delta", "delta-1", "delta-2"]
+
+
+def test_delta_channel_from_checkpoint_seed_without_writes() -> None:
+    """Reconstruction at a pre-delta ancestor with no newer deltas returns
+    just the seed — the saver's terminator fired immediately."""
+    spec = DeltaChannel(_messages_delta_reducer, list)
+    seed = [HumanMessage(content="only-snap", id="s1")]
+    ch = spec.from_checkpoint(seed)
+    ch.replay_writes([])
+    assert ch.get() == seed
+
+
+def test_delta_channel_from_checkpoint_seed_none_is_distinct_from_sentinel() -> None:
+    """`seed=None` must start replay from None, not from an empty channel.
+
+    The DELTA_SENTINEL / MISSING sentinels mean 'no seed'; passing `None`
+    explicitly should feed None to the reducer as the left operand.
+    """
+
+    def replace(state, writes):
+        return writes[-1] if writes else state
+
+    spec = DeltaChannel(replace, list)
+    ch = spec.from_checkpoint(None)
+    ch.replay_writes([("t0", "x", "after")])
+    assert ch.get() == "after"