fix(prebuilt): default ToolRuntime tools to empty list (#7651 )

Backports the ToolRuntime fix onto the release branch and bumps to . This makes default to an empty list when not provided and includes a focused regression test, with the prebuilt lockfile updated to match the version bump. Created with [Deep Agents CLI](https://docs.langchain.com/oss/python/deepagents/cli/overview) using gpt-5.4 (provider: openai).
release(prebuilt): 1.0.12, langgraph 1.1.10 (#7623 )
2026-08-26 17:42:24 +02:00 · 2026-04-30 01:41:06 +00:00 · 2026-04-27 13:11:43 -04:00 · 2026-04-27 09:03:19 -07:00 · 2026-04-27 10:27:56 -04:00 · 2026-04-27 09:52:23 -04:00
70 changed files with 4839 additions and 6524 deletions
@@ -121,8 +121,8 @@ jobs:
            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);")
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@@ -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]
@@ -259,7 +259,7 @@ wheels = [

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-version = "4.0.1"
+version = "4.0.3"
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 dependencies = [
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+
 [[package]]
 name = "zstandard"
 version = "0.25.0"
@@ -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
@@ -249,7 +249,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.2.22"
+version = "1.2.28"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -261,14 +261,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
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+]
+
 [[package]]
 name = "zstandard"
 version = "0.25.0"
@@ -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.
@@ -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
@@ -46,6 +46,36 @@ 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 +86,10 @@ 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 +104,11 @@ 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 +177,23 @@ 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 +241,13 @@ 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}). "
@@ -527,10 +575,13 @@ 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 +599,9 @@ 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,
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.3"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"
@@ -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()
@@ -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")]
    )
@@ -12,13 +12,25 @@ from langgraph.checkpoint.base import (
    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:
@@ -286,7 +286,7 @@ wheels = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.3"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -369,7 +369,7 @@ test = [

 [[package]]
 name = "langsmith"
-version = "0.6.4"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -379,11 +379,12 @@ dependencies = [
    { name = "requests" },
    { name = "requests-toolbelt" },
    { name = "uuid-utils" },
+    { name = "xxhash" },
    { name = "zstandard" },
 ]
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
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 [[package]]
@@ -1117,7 +1118,7 @@ wheels = [

 [[package]]
 name = "pytest"
-version = "9.0.2"
+version = "9.0.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -1128,9 +1129,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
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 ]

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+
 [[package]]
 name = "zstandard"
 version = "0.25.0"
@@ -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"
 ]
@@ -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",
  "langchain-anthropic==1.0.0a5",
  "langgraph==1.1.5"
 ]
@@ -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",
 ]
@@ -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==
@@ -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==
@@ -1 +1 @@
-__version__ = "0.4.21"
+__version__ = "0.4.24"
@@ -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,
+    )
@@ -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,))
@@ -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."""
@@ -10,7 +10,13 @@ except ModuleNotFoundError:  # pragma: no cover - exercised on Python 3.10.
    import tomli as tomllib

 import click
+import pathspec

+from langgraph_cli._ignore import (
+    _build_dockerignore_negation_hints,
+    _build_ignore_spec,
+    _is_always_excluded,
+)
 from langgraph_cli.schemas import Config


@@ -440,16 +446,32 @@ def _container_root_for_uv_lock_package(


 def _uv_lock_package_copy_items(
-    package: UvLockPackage, plan: UvLockPlan
+    package: UvLockPackage,
+    plan: UvLockPlan,
+    ignore_spec: pathspec.PathSpec,
 ) -> tuple[tuple[pathlib.PurePosixPath, pathlib.PurePosixPath], ...]:
+    # Skip entries that .dockerignore / built-in exclusions would strip from
+    # the build context. Emitting `ADD <path>` for a file that Docker has
+    # filtered out causes the build to fail with
+    # "failed to compute cache key: <path> not found".
    if package.root != plan.project_root:
        relative_root = pathlib.PurePosixPath(
            *package.root.relative_to(plan.project_root).parts
        )
+        if _is_always_excluded(relative_root, is_dir=True) or ignore_spec.match_file(
+            f"{relative_root.as_posix()}/"
+        ):
+            raise click.UsageError(
+                f"Workspace member '{package.name}' at {relative_root} is "
+                "excluded from the Docker build context, but uv.lock requires "
+                "it to be copied into the build context. Remove the matching "
+                "pattern or drop the member from [tool.uv.workspace].members."
+            )
        return ((relative_root, plan.container_roots[package.root]),)

    root_container = plan.container_roots[package.root]
    workspace_member_roots = plan.all_workspace_roots - {plan.project_root}
+    negated_dockerignore_hints = _build_dockerignore_negation_hints(plan.project_root)

    def iter_entries(
        current_dir: pathlib.Path,
@@ -461,18 +483,32 @@ def _uv_lock_package_copy_items(
                # and excluded entirely otherwise.
                continue

-            descendant_member_roots = [
-                ws_root
-                for ws_root in workspace_member_roots
-                if child in ws_root.parents
-            ]
-            if child.is_dir() and descendant_member_roots:
-                entries.extend(iter_entries(child))
-                continue
-
            relative_child = pathlib.PurePosixPath(
                *child.relative_to(plan.project_root).parts
            )
+            is_dir = child.is_dir()
+            if _is_always_excluded(relative_child, is_dir=is_dir):
+                continue
+            ignored = ignore_spec.match_file(
+                f"{relative_child.as_posix()}/" if is_dir else relative_child.as_posix()
+            )
+            is_workspace_parent = is_dir and any(
+                child in ws_root.parents for ws_root in workspace_member_roots
+            )
+
+            if is_workspace_parent:
+                entries.extend(iter_entries(child))
+                continue
+            if (
+                is_dir
+                and ignored
+                and negated_dockerignore_hints.requires_dir_walk(relative_child)
+            ):
+                entries.extend(iter_entries(child))
+                continue
+            if ignored:
+                continue
+
            entries.append(
                (relative_child, root_container.joinpath(*relative_child.parts))
            )
@@ -956,10 +992,13 @@ def python_config_to_docker_uv_lock(
    docker_plan.add_raw("# -- End of uv.lock dependencies install --")
    docker_plan.add_blank()

+    ignore_spec = _build_ignore_spec(plan.project_root, include_gitignore=False)
    for package in plan.install_order:
        package_label = package.root.relative_to(plan.project_root).as_posix() or "."
        docker_plan.add_raw(f"# -- Adding workspace package {package_label} --")
-        for source, destination in _uv_lock_package_copy_items(package, plan):
+        for source, destination in _uv_lock_package_copy_items(
+            package, plan, ignore_spec
+        ):
            docker_plan.add_raw(copy_from_project_root(source, destination.as_posix()))
        docker_plan.add_instruction(
            "WORKDIR", plan.container_roots[package.root].as_posix()
@@ -23,7 +23,7 @@ dependencies = [
 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'",
 ]

@@ -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__/")
@@ -4,6 +4,7 @@ import os
 import pathlib
 import tempfile
 import textwrap
+from unittest.mock import patch

 import click
 import pytest
@@ -1855,6 +1856,364 @@ def test_config_to_docker_uv_lock_supports_single_uv_project_root():
        assert additional_contexts == {}


+def test_config_to_docker_uv_lock_skips_dockerignore_entries():
+    """Entries filtered by .dockerignore / built-in excludes must not appear
+    as ADD lines. Docker fails to compute the cache key for paths that the
+    build context has stripped."""
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root = tmpdir_path / "single"
+        project_root.mkdir()
+        (project_root / "uv.lock").write_text("# uv lock file\n")
+        (project_root / "pyproject.toml").write_text(
+            textwrap.dedent(
+                """
+                [project]
+                name = "single-app"
+                version = "0.1.0"
+                dependencies = ["httpx>=0.28"]
+
+                [build-system]
+                requires = ["setuptools>=61"]
+                build-backend = "setuptools.build_meta"
+                """
+            ).strip()
+            + "\n"
+        )
+        (project_root / "langgraph.json").write_text("{}\n")
+        (project_root / "src").mkdir()
+        (project_root / "src" / "agent.py").write_text("graph = object()\n")
+        (project_root / "README.md").write_text("# hi\n")
+
+        # Built-in exclusions — must never appear as ADD lines.
+        (project_root / ".git").mkdir()
+        (project_root / ".git" / "HEAD").write_text("ref: refs/heads/main\n")
+        (project_root / ".venv").mkdir()
+        (project_root / ".venv" / "pyvenv.cfg").write_text("home = /usr\n")
+        (project_root / "__pycache__").mkdir()
+        (project_root / "__pycache__" / "x.cpython-311.pyc").write_bytes(b"\x00")
+
+        # .dockerignore excludes .gitignore and a custom path.
+        (project_root / ".dockerignore").write_text(".gitignore\nsecrets.env\n")
+        (project_root / ".gitignore").write_text("*.pyc\n")
+        (project_root / "secrets.env").write_text("TOKEN=abc\n")
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {"agent": "./src/agent.py:graph"},
+                "source": {"kind": "uv"},
+            }
+        )
+        docker, _ = config_to_docker(
+            project_root / "langgraph.json",
+            config,
+            base_image="langchain/langgraph-api:0.2.47",
+        )
+
+        for excluded in (
+            "ADD .git ",
+            "ADD .gitignore ",
+            "ADD .venv ",
+            "ADD __pycache__ ",
+            "ADD secrets.env ",
+        ):
+            assert excluded not in docker, (
+                f"{excluded!r} should be filtered out of Dockerfile:\n{docker}"
+            )
+
+        # The .dockerignore itself is still part of the context and should be
+        # ADDed (Docker needs it at build time, and archive.py includes it).
+        assert "ADD .dockerignore /deps/workspace/.dockerignore" in docker
+        assert "ADD src /deps/workspace/src" in docker
+        assert "ADD README.md /deps/workspace/README.md" in docker
+
+
+def test_config_to_docker_uv_lock_does_not_apply_gitignore():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root = tmpdir_path / "single"
+        project_root.mkdir()
+        (project_root / "uv.lock").write_text("# uv lock file\n")
+        (project_root / "pyproject.toml").write_text(
+            textwrap.dedent(
+                """
+                [project]
+                name = "single-app"
+                version = "0.1.0"
+                dependencies = ["httpx>=0.28"]
+
+                [build-system]
+                requires = ["setuptools>=61"]
+                build-backend = "setuptools.build_meta"
+                """
+            ).strip()
+            + "\n"
+        )
+        (project_root / "langgraph.json").write_text("{}\n")
+        (project_root / "src").mkdir()
+        (project_root / "src" / "agent.py").write_text("graph = object()\n")
+        (project_root / "README.md").write_text("# hi\n")
+        (project_root / ".gitignore").write_text("README.md\n")
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {"agent": "./src/agent.py:graph"},
+                "source": {"kind": "uv"},
+            }
+        )
+        docker, _ = config_to_docker(
+            project_root / "langgraph.json",
+            config,
+            base_image="langchain/langgraph-api:0.2.47",
+        )
+
+        assert "ADD README.md /deps/workspace/README.md" in docker
+
+
+def test_config_to_docker_uv_lock_skips_dockerignore_entries_in_workspace():
+    """Multi-member workspace: ignore patterns must filter root-level entries
+    AND entries encountered while recursing into directories that contain
+    workspace members (the `descendant_member_roots` branch)."""
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root, config_path = _write_uv_lock_workspace(
+            tmpdir_path,
+            agent_dependencies=["workspace-root", "shared", "httpx>=0.28"],
+            root_sources="[tool.uv.sources]\nshared = { workspace = true }\nworkspace-root = { workspace = true }",
+            agent_sources="[tool.uv.sources]\nshared = { workspace = true }\nworkspace-root = { workspace = true }",
+        )
+        root_src = project_root / "src" / "workspace_root"
+        root_src.mkdir(parents=True)
+        (root_src / "__init__.py").write_text("__all__ = []\n")
+        (project_root / "README.md").write_text("workspace root package\n")
+
+        # A non-member sibling of the `apps/agent` member that should be
+        # filtered out via .dockerignore. This exercises the recursion into
+        # `apps/` where `apps/agent` is kept (it's a member) but its sibling is
+        # filtered.
+        (project_root / "apps" / "scratch.txt").write_text("scratch\n")
+        # A root-level path that .dockerignore excludes.
+        (project_root / "secrets.env").write_text("TOKEN=abc\n")
+        (project_root / ".dockerignore").write_text("secrets.env\napps/scratch.txt\n")
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {
+                    "agent": "../../apps/agent/src/agent/graph.py:graph",
+                },
+                "source": {"kind": "uv", "root": "../..", "package": "agent"},
+            }
+        )
+        docker, _ = config_to_docker(
+            config_path, config, base_image="langchain/langgraph-api:0.2.47"
+        )
+
+        assert "COPY --from=uv-workspace-root src /deps/workspace/src" in docker
+        assert (
+            "COPY --from=uv-workspace-root README.md /deps/workspace/README.md"
+            in docker
+        )
+        assert (
+            "COPY --from=uv-workspace-root .dockerignore /deps/workspace/.dockerignore"
+            in docker
+        )
+        assert "secrets.env" not in docker
+        assert "apps/scratch.txt" not in docker
+        # Workspace members themselves are still copied via their own per-member
+        # COPY line — the sibling filter must not disturb this.
+        assert (
+            "COPY --from=uv-workspace-root apps/agent /deps/workspace/apps/agent"
+            in docker
+        )
+
+
+def test_config_to_docker_uv_lock_preserves_negated_dockerignore_descendants():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root = tmpdir_path / "single"
+        project_root.mkdir()
+        (project_root / "uv.lock").write_text("# uv lock file\n")
+        (project_root / "pyproject.toml").write_text(
+            textwrap.dedent(
+                """
+                [project]
+                name = "single-app"
+                version = "0.1.0"
+                dependencies = ["httpx>=0.28"]
+
+                [build-system]
+                requires = ["setuptools>=61"]
+                build-backend = "setuptools.build_meta"
+                """
+            ).strip()
+            + "\n"
+        )
+        (project_root / "langgraph.json").write_text("{}\n")
+        (project_root / "src").mkdir()
+        (project_root / "src" / "agent.py").write_text("graph = object()\n")
+        (project_root / "assets").mkdir()
+        (project_root / "assets" / "keep.txt").write_text("keep\n")
+        (project_root / "assets" / "drop.txt").write_text("drop\n")
+        (project_root / ".dockerignore").write_text("assets/\n!assets/keep.txt\n")
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {"agent": "./src/agent.py:graph"},
+                "source": {"kind": "uv"},
+            }
+        )
+        docker, _ = config_to_docker(
+            project_root / "langgraph.json",
+            config,
+            base_image="langchain/langgraph-api:0.2.47",
+        )
+
+        assert "ADD assets /deps/workspace/assets" not in docker
+        assert "ADD assets/keep.txt /deps/workspace/assets/keep.txt" in docker
+        assert "assets/drop.txt" not in docker
+
+
+def test_config_to_docker_uv_lock_prunes_unrelated_ignored_subtrees():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root = tmpdir_path / "single"
+        project_root.mkdir()
+        (project_root / "uv.lock").write_text("# uv lock file\n")
+        (project_root / "pyproject.toml").write_text(
+            textwrap.dedent(
+                """
+                [project]
+                name = "single-app"
+                version = "0.1.0"
+                dependencies = ["httpx>=0.28"]
+
+                [build-system]
+                requires = ["setuptools>=61"]
+                build-backend = "setuptools.build_meta"
+                """
+            ).strip()
+            + "\n"
+        )
+        (project_root / "langgraph.json").write_text("{}\n")
+        (project_root / "src").mkdir()
+        (project_root / "src" / "agent.py").write_text("graph = object()\n")
+        (project_root / "assets").mkdir()
+        (project_root / "assets" / "keep.txt").write_text("keep\n")
+        (project_root / "vendor").mkdir()
+        (project_root / "vendor" / "huge.txt").write_text("large\n")
+        (project_root / ".dockerignore").write_text(
+            "vendor/\nassets/\n!assets/keep.txt\n"
+        )
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {"agent": "./src/agent.py:graph"},
+                "source": {"kind": "uv"},
+            }
+        )
+
+        original_iterdir = pathlib.Path.iterdir
+
+        def guarded_iterdir(self):
+            if self == project_root / "vendor":
+                raise AssertionError("should not walk unrelated ignored subtree")
+            return original_iterdir(self)
+
+        with patch.object(
+            pathlib.Path, "iterdir", autospec=True, side_effect=guarded_iterdir
+        ):
+            docker, _ = config_to_docker(
+                project_root / "langgraph.json",
+                config,
+                base_image="langchain/langgraph-api:0.2.47",
+            )
+
+        assert "ADD assets/keep.txt /deps/workspace/assets/keep.txt" in docker
+        assert "vendor/huge.txt" not in docker
+
+
+def test_config_to_docker_uv_lock_never_reincludes_always_excluded_subtrees():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root = tmpdir_path / "single"
+        project_root.mkdir()
+        (project_root / "uv.lock").write_text("# uv lock file\n")
+        (project_root / "pyproject.toml").write_text(
+            textwrap.dedent(
+                """
+                [project]
+                name = "single-app"
+                version = "0.1.0"
+                dependencies = ["httpx>=0.28"]
+
+                [build-system]
+                requires = ["setuptools>=61"]
+                build-backend = "setuptools.build_meta"
+                """
+            ).strip()
+            + "\n"
+        )
+        (project_root / "langgraph.json").write_text("{}\n")
+        (project_root / "src").mkdir()
+        (project_root / "src" / "agent.py").write_text("graph = object()\n")
+        (project_root / ".venv" / "pkg").mkdir(parents=True)
+        (project_root / ".venv" / "pkg" / "keep.txt").write_text("keep\n")
+        (project_root / "node_modules" / "pkg").mkdir(parents=True)
+        (project_root / "node_modules" / "pkg" / "package.json").write_text("{}\n")
+        (project_root / ".dockerignore").write_text(
+            "!.venv/pkg/keep.txt\n!node_modules/pkg/package.json\n"
+        )
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {"agent": "./src/agent.py:graph"},
+                "source": {"kind": "uv"},
+            }
+        )
+        docker, _ = config_to_docker(
+            project_root / "langgraph.json",
+            config,
+            base_image="langchain/langgraph-api:0.2.47",
+        )
+
+        assert ".venv/pkg/keep.txt" not in docker
+        assert "node_modules/pkg/package.json" not in docker
+        assert "ADD src /deps/workspace/src" in docker
+
+
+def test_config_to_docker_uv_lock_rejects_ignored_workspace_member():
+    """A workspace member matched by .dockerignore cannot be copied into the
+    build context — uv.lock requires it, so fail loudly with a clear message."""
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmpdir_path = pathlib.Path(tmpdir)
+        project_root, config_path = _write_uv_lock_workspace(
+            tmpdir_path,
+            agent_sources="[tool.uv.sources]\nshared = { workspace = true }",
+        )
+        (project_root / ".dockerignore").write_text("libs/shared\n")
+
+        config = validate_config(
+            {
+                "python_version": "3.11",
+                "graphs": {"agent": "../../apps/agent/src/agent/graph.py:graph"},
+                "source": {"kind": "uv", "root": "../..", "package": "agent"},
+                "auth": {"path": "../../libs/shared/src/shared/auth.py:create_auth"},
+            }
+        )
+        with pytest.raises(
+            click.UsageError, match=r"Workspace member 'shared' at libs/shared"
+        ):
+            config_to_docker(
+                config_path, config, base_image="langchain/langgraph-api:0.2.47"
+            )
+
+
 def test_config_to_docker_uv_lock_rejects_invalid_source_package_type():
    with tempfile.TemporaryDirectory() as tmpdir:
        tmpdir_path = pathlib.Path(tmpdir)
@@ -290,7 +290,7 @@ wheels = [

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

 [[package]]
@@ -266,7 +266,7 @@ wheels = [

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

 [[package]]
@@ -1,7 +1,7 @@
 from __future__ import annotations

 from collections import ChainMap
-from collections.abc import Mapping, Sequence
+from collections.abc import Sequence
 from os import getenv
 from typing import Any, cast

@@ -217,14 +217,16 @@ def get_callback_manager_for_config(
            callbacks.add_tags(all_tags)
        if metadata := config.get("metadata"):
            callbacks.add_metadata(metadata)
-        return callbacks
+        manager = callbacks
    else:
        # otherwise create a new manager
-        return CallbackManager.configure(
+        manager = CallbackManager.configure(
            inheritable_callbacks=config.get("callbacks"),
            inheritable_tags=all_tags,
            inheritable_metadata=config.get("metadata"),
+            langsmith_inheritable_metadata=_get_tracing_metadata_defaults(config),
        )
+    return manager


 def get_async_callback_manager_for_config(
@@ -255,14 +257,16 @@ def get_async_callback_manager_for_config(
            callbacks.add_tags(all_tags)
        if metadata := config.get("metadata"):
            callbacks.add_metadata(metadata)
-        return callbacks
+        manager = callbacks
    else:
        # otherwise create a new manager
-        return AsyncCallbackManager.configure(
+        manager = AsyncCallbackManager.configure(
            inheritable_callbacks=config.get("callbacks"),
            inheritable_tags=all_tags,
            inheritable_metadata=config.get("metadata"),
+            langsmith_inheritable_metadata=_get_tracing_metadata_defaults(config),
        )
+    return manager


 def _is_not_empty(value: Any) -> bool:
@@ -308,22 +312,54 @@ def ensure_config(*configs: RunnableConfig | None) -> RunnableConfig:
        for k, v in config.items():
            if _is_not_empty(v) and k not in CONFIG_KEYS:
                empty[CONF][k] = v
-    _empty_metadata = empty["metadata"]
-    for key, value in empty[CONF].items():
-        if _exclude_as_metadata(key, value, _empty_metadata):
-            continue
-        _empty_metadata[key] = value
+
+    configurable = empty.get("configurable")
+    metadata = empty.get("metadata")
+    if configurable and metadata is not None:
+        for key in _PROPAGATE_TO_METADATA:
+            if key in metadata:
+                continue
+            value = configurable.get(key)
+            if value:
+                metadata[key] = value
    return empty


 _OMIT = ("key", "token", "secret", "password", "auth")


-def _exclude_as_metadata(key: str, value: Any, metadata: Mapping[str, Any]) -> bool:
+def _exclude_as_metadata(key: str, value: Any) -> bool:
    key_lower = key.casefold()
    return (
        key.startswith("__")
        or not isinstance(value, (str, int, float, bool))
-        or key in metadata
        or any(substr in key_lower for substr in _OMIT)
    )
+
+
+def _get_tracing_metadata_defaults(
+    config: RunnableConfig,
+) -> dict[str, Any] | None:
+    """Get tracer-only metadata defaults from configurable values."""
+    configurable = config.get("configurable")
+    if not configurable:
+        return None
+    metadata: dict[str, Any] = {}
+    for key, value in configurable.items():
+        if _exclude_as_metadata(key, value):
+            continue
+        metadata[key] = value
+    return metadata or None
+
+
+_PROPAGATE_TO_METADATA = frozenset(
+    (
+        "thread_id",
+        "checkpoint_id",
+        "checkpoint_ns",
+        "task_id",
+        "run_id",
+        "assistant_id",
+        "graph_id",
+    )
+)
@@ -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,
+    )
@@ -62,6 +62,11 @@ 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.untracked_value import UntrackedValue
 from langgraph.constants import TAG_HIDDEN
@@ -117,6 +122,7 @@ from langgraph.types import (
    CachePolicy,
    Command,
    Durability,
+    Interrupt,
    PregelExecutableTask,
    RetryPolicy,
    Send,
@@ -203,6 +209,8 @@ class PregelLoop:
    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 +236,7 @@ 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 +261,8 @@ 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)
@@ -303,6 +314,40 @@ class PregelLoop:
        )
        self.prev_checkpoint_config = None

+    def _push_graph_lifecycle_event(
+        self,
+        kind: Literal["resume", "interrupt"],
+        *,
+        interrupts: tuple[Interrupt, ...] = (),
+    ) -> None:
+        if kind == "resume":
+            self._graph_lifecycle_events.append(
+                GraphResumeEvent(
+                    run_id=None,
+                    status=self.status,
+                    checkpoint_id=self.checkpoint["id"],
+                    checkpoint_ns=self.checkpoint_ns,
+                )
+            )
+        elif kind == "interrupt":
+            self._graph_lifecycle_events.append(
+                GraphInterruptEvent(
+                    run_id=None,
+                    status=self.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."""
        if not writes:
@@ -647,7 +692,7 @@ 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 +710,8 @@ 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 +766,26 @@ 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 +828,28 @@ 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 +865,8 @@ 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:
@@ -885,8 +967,10 @@ 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 +997,11 @@ 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 +1123,7 @@ 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 +1145,7 @@ 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:
@@ -1136,6 +1221,7 @@ 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):
@@ -1236,6 +1322,7 @@ 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 +1344,7 @@ 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:
@@ -1335,6 +1423,7 @@ 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):
@@ -1,807 +0,0 @@
-"""Protocol-native content-block message handler for StreamingHandler.
-
-Emits structured content-block lifecycle events (message-start,
-content-block-start/delta/finish, message-finish) instead of raw
-``(AIMessageChunk, metadata)`` tuples.  The existing
-:class:`~langgraph.pregel._messages.StreamMessagesHandler` is NOT
-modified — this handler is only activated when
-``__protocol_messages_stream`` is ``True`` in the run's configurable.
-"""
-
-from __future__ import annotations
-
-import json
-from collections.abc import AsyncIterator, Callable, Iterator, Sequence
-from dataclasses import dataclass, field
-from typing import Any, TypeVar, cast
-from uuid import UUID, uuid4
-
-from langchain_core.callbacks import BaseCallbackHandler
-from langchain_core.messages import AIMessageChunk, BaseMessage
-from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
-
-from langgraph._internal._constants import NS_SEP
-from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
-from langgraph.pregel.protocol import StreamChunk
-from langgraph.stream._types import (
-    ContentBlockDeltaData,
-    ContentBlockFinishData,
-    ContentBlockStartData,
-    FinishReason,
-    InvalidToolCallBlock,
-    MessageErrorData,
-    MessageStartData,
-    ReasoningBlock,
-    TextBlock,
-    ToolCallBlock,
-    UsageInfo,
-)
-
-try:
-    from langchain_core.tracers._streaming import _StreamingCallbackHandler
-except ImportError:
-    _StreamingCallbackHandler = object  # type: ignore
-
-T = TypeVar("T")
-Meta = tuple[tuple[str, ...], dict[str, Any]]
-
-PROTOCOL_MESSAGES_STREAM_KEY = "__protocol_messages_stream"
-
-# ---------------------------------------------------------------------------
-# Content-block accumulation helpers
-# ---------------------------------------------------------------------------
-
-# A "compatible content block" is a dict matching one of the protocol block
-# TypedDicts (TextBlock, ReasoningBlock, ToolCallChunkBlock, etc.).
-CompatBlock = dict[str, Any]
-
-
-@dataclass
-class _ProtocolRunState:
-    """Per-run state for tracking the active message lifecycle."""
-
-    message_id: str | None = None
-    started: bool = False
-    blocks: dict[int, CompatBlock] = field(default_factory=dict)
-    usage: dict[str, Any] | None = None
-
-
-def _accumulate_block(accumulated: CompatBlock, delta: CompatBlock) -> CompatBlock:
-    """Merge *delta* into *accumulated*, returning the updated block."""
-    btype = accumulated.get("type", "text")
-    if btype == "text" and delta.get("type", "text") == "text":
-        accumulated["text"] = accumulated.get("text", "") + delta.get("text", "")
-    elif btype == "reasoning" and delta.get("type") == "reasoning":
-        accumulated["reasoning"] = accumulated.get("reasoning", "") + delta.get(
-            "reasoning", ""
-        )
-    elif btype == "tool_call_chunk" and delta.get("type") == "tool_call_chunk":
-        accumulated["args"] = accumulated.get("args", "") + delta.get("args", "")
-        if delta.get("id") is not None:
-            accumulated["id"] = delta["id"]
-        if delta.get("name") is not None:
-            accumulated["name"] = delta["name"]
-    return accumulated
-
-
-def _delta_block(previous: CompatBlock, current: CompatBlock) -> CompatBlock | None:
-    """Compute the delta between *previous* and *current*.
-
-    Returns ``None`` if there is nothing new to emit.
-    """
-    btype = current.get("type", "text")
-    if btype == "text":
-        prev_text = previous.get("text", "")
-        cur_text = current.get("text", "")
-        delta_text = cur_text[len(prev_text) :]
-        if not delta_text:
-            return None
-        return TextBlock(type="text", text=delta_text)
-    elif btype == "reasoning":
-        prev_r = previous.get("reasoning", "")
-        cur_r = current.get("reasoning", "")
-        delta_r = cur_r[len(prev_r) :]
-        if not delta_r:
-            return None
-        return ReasoningBlock(type="reasoning", reasoning=delta_r)
-    elif btype == "tool_call_chunk":
-        prev_args = previous.get("args", "")
-        cur_args = current.get("args", "")
-        delta_args = cur_args[len(prev_args) :]
-        has_meta = current.get("id") is not None or current.get("name") is not None
-        if not delta_args and not has_meta:
-            return None
-        result: CompatBlock = {"type": "tool_call_chunk", "args": delta_args}
-        if current.get("id") is not None and previous.get("id") is None:
-            result["id"] = current["id"]
-        if current.get("name") is not None and previous.get("name") is None:
-            result["name"] = current["name"]
-        return result
-    # Unrecognized block type — pass through unchanged
-    return current
-
-
-def _finalize_block(block: CompatBlock) -> CompatBlock:
-    """Convert a ``tool_call_chunk`` block to a finalized ``tool_call`` or
-    ``invalid_tool_call`` block.  Other block types pass through unchanged.
-    """
-    if block.get("type") != "tool_call_chunk":
-        return block
-    raw_args = block.get("args", "{}")
-    try:
-        parsed_args = json.loads(raw_args) if raw_args else {}
-        return ToolCallBlock(
-            type="tool_call",
-            id=block.get("id", ""),
-            name=block.get("name", ""),
-            args=parsed_args,
-        )
-    except (json.JSONDecodeError, TypeError):
-        return InvalidToolCallBlock(
-            type="invalid_tool_call",
-            id=block.get("id"),
-            name=block.get("name"),
-            args=raw_args,
-            error="Failed to parse tool call arguments as JSON",
-        )
-
-
-def _normalize_finish_reason(value: Any) -> FinishReason:
-    """Map provider-specific stop reasons to protocol finish reasons."""
-    if value == "length":
-        return "length"
-    if value == "content_filter":
-        return "content_filter"
-    if value in ("tool_use", "tool_calls"):
-        return "tool_use"
-    # "end_turn", "stop", None, and anything else → "stop"
-    return "stop"
-
-
-def _accumulate_usage(
-    current: dict[str, Any] | None, delta: Any
-) -> dict[str, Any] | None:
-    """Accumulate usage metadata from streamed chunks."""
-    if not isinstance(delta, dict):
-        return current
-    if current is None:
-        return dict(delta)
-    for key in ("input_tokens", "output_tokens", "total_tokens", "cached_tokens"):
-        if key in delta:
-            current[key] = current.get(key, 0) + delta[key]
-    # Merge detail dicts
-    for detail_key in ("input_token_details", "output_token_details"):
-        if detail_key in delta and isinstance(delta[detail_key], dict):
-            if detail_key not in current:
-                current[detail_key] = {}
-            current[detail_key].update(delta[detail_key])
-    return current
-
-
-def _to_protocol_usage(usage: dict[str, Any] | None) -> UsageInfo | None:
-    """Convert LangChain usage metadata to protocol ``UsageInfo``."""
-    if usage is None:
-        return None
-    result: dict[str, Any] = {}
-    if "input_tokens" in usage:
-        result["input_tokens"] = usage["input_tokens"]
-    if "output_tokens" in usage:
-        result["output_tokens"] = usage["output_tokens"]
-    if "total_tokens" in usage:
-        result["total_tokens"] = usage["total_tokens"]
-    if "cached_tokens" in usage:
-        result["cached_tokens"] = usage["cached_tokens"]
-    return UsageInfo(**result) if result else None
-
-
-# ---------------------------------------------------------------------------
-# Extracting content blocks from LangChain messages
-# ---------------------------------------------------------------------------
-
-
-def _extract_blocks_from_chunk(msg: AIMessageChunk) -> list[tuple[int, CompatBlock]]:
-    """Extract ``(index, block)`` pairs from an ``AIMessageChunk``.
-
-    LangChain stores content in several places:
-    - ``content: str`` — a single text block at index 0
-    - ``content: list[dict]`` — explicit content blocks with their own types
-    - ``tool_call_chunks`` — separate list for streamed tool call deltas
-    """
-    blocks: list[tuple[int, CompatBlock]] = []
-    content = msg.content
-    if isinstance(content, str) and content:
-        blocks.append((0, dict(TextBlock(type="text", text=content))))
-    elif isinstance(content, list):
-        for i, item in enumerate(content):
-            if not isinstance(item, dict):
-                continue
-            ctype = item.get("type", "")
-            if ctype == "text" and item.get("text"):
-                blocks.append(
-                    (
-                        item.get("index", i),
-                        dict(TextBlock(type="text", text=item["text"])),
-                    )
-                )
-            elif ctype in ("reasoning_content", "reasoning", "thinking"):
-                reasoning_text = (
-                    item.get("reasoning_content")
-                    or item.get("reasoning")
-                    or item.get("thinking", "")
-                )
-                if reasoning_text:
-                    blocks.append(
-                        (
-                            item.get("index", i),
-                            dict(
-                                ReasoningBlock(
-                                    type="reasoning", reasoning=reasoning_text
-                                )
-                            ),
-                        )
-                    )
-
-    # Tool call chunks live in a separate field
-    for tc in msg.tool_call_chunks or []:
-        idx = tc.get("index")
-        if idx is None:
-            # Assign indices after text content blocks
-            idx = len(blocks)
-        block: CompatBlock = {"type": "tool_call_chunk", "args": tc.get("args", "")}
-        if tc.get("id") is not None:
-            block["id"] = tc["id"]
-        if tc.get("name") is not None:
-            block["name"] = tc["name"]
-        blocks.append((idx, block))
-
-    return blocks
-
-
-# ---------------------------------------------------------------------------
-# The handler
-# ---------------------------------------------------------------------------
-
-
-class StreamProtocolMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
-    """Callback handler that emits content-block protocol events.
-
-    Activated when ``__protocol_messages_stream`` is ``True`` in the run's
-    configurable metadata.  Emits ``StreamChunk`` tuples of the form
-    ``(namespace, "messages", data)`` where *data* is one of the
-    ``MessagesData`` event types (``message-start``, ``content-block-start``,
-    etc.).
-    """
-
-    run_inline = True
-
-    def __init__(
-        self,
-        stream: Callable[[StreamChunk], None],
-        subgraphs: bool,
-        *,
-        parent_ns: tuple[str, ...] | None = None,
-    ) -> None:
-        self.stream = stream
-        self.subgraphs = subgraphs
-        self.parent_ns = parent_ns
-        # Per-run metadata: run_id → (namespace, metadata_dict)
-        self.metadata: dict[UUID, Meta] = {}
-        # Per-run protocol state for streamed messages
-        self.protocol_runs: dict[UUID, _ProtocolRunState] = {}
-        # Stable message ID mapping: run_id → message_id
-        self.stable_message_ids: dict[UUID, str] = {}
-        # Seen message IDs for deduplication of chain-emitted messages
-        self.seen: set[str | int] = set()
-
-    def _emit(self, meta: Meta, data: Any) -> None:
-        """Emit a protocol event as a StreamChunk.
-
-        The node name from *meta* is embedded at ``"__node__"`` so the
-        stream pump can lift it into ``params.node`` without changing the
-        ``StreamChunk`` tuple shape.
-        """
-        node = meta[1].get("langgraph_node")
-        if node and isinstance(data, dict):
-            data = {**data, "__node__": node}
-        self.stream((meta[0], "messages", data))
-
-    # -- Chat model callbacks -----------------------------------------------
-
-    def on_chat_model_start(
-        self,
-        serialized: dict[str, Any],
-        messages: list[list[BaseMessage]],
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        if metadata and (not tags or (TAG_NOSTREAM not in tags)):
-            ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))[
-                :-1
-            ]
-            if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
-                return
-            if tags:
-                if filtered := [t for t in tags if not t.startswith("seq:step")]:
-                    metadata["tags"] = filtered
-            self.metadata[run_id] = (ns, metadata)
-            self.protocol_runs[run_id] = _ProtocolRunState()
-
-    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:
-        if not isinstance(chunk, ChatGenerationChunk):
-            return
-        meta = self.metadata.get(run_id)
-        if meta is None:
-            return
-        state = self.protocol_runs.get(run_id)
-        if state is None:
-            return
-
-        msg = chunk.message
-        if not isinstance(msg, AIMessageChunk):
-            return
-
-        # Emit message-start on first token
-        if not state.started:
-            message_id = self._normalize_message_id(msg, run_id)
-            state.message_id = message_id
-            state.started = True
-            start_data = dict(
-                MessageStartData(
-                    event="message-start",
-                    role="ai",
-                )
-            )
-            if message_id:
-                start_data["message_id"] = message_id
-            self._emit(meta, start_data)
-
-        # Extract content blocks from this chunk
-        extracted = _extract_blocks_from_chunk(msg)
-        for idx, delta_block in extracted:
-            if idx not in state.blocks:
-                # New block — emit content-block-start
-                state.blocks[idx] = dict(delta_block)
-                # Start block has empty content placeholder
-                start_block = _make_start_block(delta_block)
-                self._emit(
-                    meta,
-                    ContentBlockStartData(
-                        event="content-block-start",
-                        index=idx,
-                        content_block=start_block,
-                    ),
-                )
-                # Then emit the first delta
-                first_delta = _delta_block(
-                    _make_start_block(delta_block), state.blocks[idx]
-                )
-                if first_delta is not None:
-                    self._emit(
-                        meta,
-                        ContentBlockDeltaData(
-                            event="content-block-delta",
-                            index=idx,
-                            content_block=first_delta,
-                        ),
-                    )
-            else:
-                # Existing block — compute delta, accumulate, emit
-                previous = dict(state.blocks[idx])
-                state.blocks[idx] = _accumulate_block(state.blocks[idx], delta_block)
-                delta = _delta_block(previous, state.blocks[idx])
-                if delta is not None:
-                    self._emit(
-                        meta,
-                        ContentBlockDeltaData(
-                            event="content-block-delta",
-                            index=idx,
-                            content_block=delta,
-                        ),
-                    )
-
-        # Accumulate usage from chunk
-        if msg.usage_metadata:
-            state.usage = _accumulate_usage(state.usage, msg.usage_metadata)
-
-    def on_llm_end(
-        self,
-        response: LLMResult,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        meta = self.metadata.pop(run_id, None)
-        state = self.protocol_runs.pop(run_id, None)
-        if meta is None or state is None:
-            return
-
-        # Extract finish reason and usage from the final generation
-        finish_reason: FinishReason = "stop"
-        final_usage = state.usage
-
-        if response.generations and response.generations[0]:
-            gen = response.generations[0][0]
-            if isinstance(gen, ChatGeneration):
-                final_msg = gen.message
-                # Get finish reason from response_metadata
-                rm = getattr(final_msg, "response_metadata", {}) or {}
-                raw_reason = rm.get("finish_reason") or rm.get("stop_reason")
-                if raw_reason:
-                    finish_reason = _normalize_finish_reason(raw_reason)
-                # If we have tool calls in the final message, infer tool_use
-                if (
-                    finish_reason == "stop"
-                    and hasattr(final_msg, "tool_calls")
-                    and final_msg.tool_calls
-                ):
-                    finish_reason = "tool_use"
-                # Get usage from final message if not accumulated from chunks
-                if final_usage is None and hasattr(final_msg, "usage_metadata"):
-                    final_usage = (
-                        dict(final_msg.usage_metadata)
-                        if final_msg.usage_metadata
-                        else None
-                    )
-
-                # If we never got streaming tokens (non-streamed model call),
-                # emit the full message lifecycle now
-                if not state.started:
-                    self._emit_full_message(meta, final_msg, finish_reason, final_usage)
-                    return
-
-        # Close out any open content blocks
-        for idx in sorted(state.blocks):
-            finalized = _finalize_block(state.blocks[idx])
-            self._emit(
-                meta,
-                ContentBlockFinishData(
-                    event="content-block-finish",
-                    index=idx,
-                    content_block=finalized,
-                ),
-            )
-
-        # Emit message-finish
-        finish_data: dict[str, Any] = {
-            "event": "message-finish",
-            "reason": finish_reason,
-        }
-        usage_info = _to_protocol_usage(final_usage)
-        if usage_info is not None:
-            finish_data["usage"] = usage_info
-        self._emit(meta, finish_data)
-
-        # Track the message as seen for dedup
-        if state.message_id:
-            self.seen.add(state.message_id)
-
-    def on_llm_error(
-        self,
-        error: BaseException,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        meta = self.metadata.pop(run_id, None)
-        state = self.protocol_runs.pop(run_id, None)
-        self.stable_message_ids.pop(run_id, None)
-        if meta is None or state is None:
-            return
-        if state.started:
-            self._emit(
-                meta,
-                MessageErrorData(
-                    event="error",
-                    message=str(error),
-                ),
-            )
-
-    # -- Chain callbacks (for node-level message dedup) ---------------------
-
-    def on_chain_start(
-        self,
-        serialized: dict[str, Any],
-        inputs: dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        if (
-            metadata
-            and kwargs.get("name") == metadata.get("langgraph_node")
-            and (not tags or TAG_HIDDEN not in tags)
-        ):
-            ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))[
-                :-1
-            ]
-            if not self.subgraphs and len(ns) > 0:
-                return
-            self.metadata[run_id] = (ns, metadata)
-            # Record input message IDs for deduplication
-            self._record_seen_messages(inputs)
-
-    def on_chain_end(
-        self,
-        response: Any,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        meta = self.metadata.pop(run_id, None)
-        if meta is None:
-            return
-        # Emit protocol events for any new messages in the node's output
-        self._emit_chain_messages(meta, response)
-
-    def on_chain_error(
-        self,
-        error: BaseException,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self.metadata.pop(run_id, None)
-
-    # -- Iterator taps (required by _StreamingCallbackHandler) ---------------
-
-    def tap_output_aiter(
-        self, run_id: UUID, output: AsyncIterator[T]
-    ) -> AsyncIterator[T]:
-        return output
-
-    def tap_output_iter(self, run_id: UUID, output: Iterator[T]) -> Iterator[T]:
-        return output
-
-    # -- Internal helpers ---------------------------------------------------
-
-    def _normalize_message_id(self, msg: BaseMessage, run_id: UUID) -> str | None:
-        """Return a stable message ID for this run, creating one if needed."""
-        msg_id = msg.id
-        if msg_id is None:
-            msg_id = self.stable_message_ids.get(run_id)
-        if msg_id is None:
-            msg_id = f"run-{run_id}"
-        self.stable_message_ids[run_id] = msg_id
-        # Mutate the message for consistency downstream
-        if msg.id != msg_id:
-            msg.id = msg_id
-        return msg_id
-
-    def _emit_full_message(
-        self,
-        meta: Meta,
-        msg: BaseMessage,
-        finish_reason: FinishReason,
-        usage: dict[str, Any] | None,
-        role: str = "ai",
-    ) -> None:
-        """Emit a complete message lifecycle for a non-streamed model call."""
-        message_id = msg.id or str(uuid4())
-        if message_id in self.seen:
-            return
-        self.seen.add(message_id)
-
-        # message-start
-        start_data = dict(
-            MessageStartData(
-                event="message-start",
-                role=role,
-            )
-        )
-        start_data["message_id"] = message_id
-        self._emit(meta, start_data)
-
-        # Extract all blocks from the final message
-        blocks = _extract_final_blocks(msg)
-        for idx, block in blocks:
-            # content-block-start with the full content
-            self._emit(
-                meta,
-                ContentBlockStartData(
-                    event="content-block-start",
-                    index=idx,
-                    content_block=_make_start_block(block),
-                ),
-            )
-            # content-block-delta with the full content
-            delta = _delta_block(_make_start_block(block), block)
-            if delta is not None:
-                self._emit(
-                    meta,
-                    ContentBlockDeltaData(
-                        event="content-block-delta",
-                        index=idx,
-                        content_block=delta,
-                    ),
-                )
-            # content-block-finish
-            finalized = _finalize_block(block)
-            self._emit(
-                meta,
-                ContentBlockFinishData(
-                    event="content-block-finish",
-                    index=idx,
-                    content_block=finalized,
-                ),
-            )
-
-        # message-finish
-        finish_data: dict[str, Any] = {
-            "event": "message-finish",
-            "reason": finish_reason,
-        }
-        usage_info = _to_protocol_usage(usage)
-        if usage_info is not None:
-            finish_data["usage"] = usage_info
-        self._emit(meta, finish_data)
-
-    def _record_seen_messages(self, obj: Any) -> None:
-        """Record message IDs from node inputs for deduplication."""
-        if isinstance(obj, BaseMessage):
-            if obj.id is not None:
-                self.seen.add(obj.id)
-        elif isinstance(obj, dict):
-            for value in obj.values():
-                self._record_seen_messages(value)
-        elif isinstance(obj, Sequence) and not isinstance(obj, (str, bytes)):
-            for item in obj:
-                self._record_seen_messages(item)
-
-    def _emit_chain_messages(self, meta: Meta, response: Any) -> None:
-        """Emit protocol events for messages found in chain output."""
-        from langgraph.types import Command
-
-        if isinstance(response, Command):
-            self._emit_chain_messages(meta, response.update)
-        elif isinstance(response, BaseMessage):
-            self._emit_message_from_chain(meta, response)
-        elif isinstance(response, Sequence) and not isinstance(response, (str, bytes)):
-            for item in response:
-                if isinstance(item, Command):
-                    self._emit_chain_messages(meta, item.update)
-                elif isinstance(item, BaseMessage):
-                    self._emit_message_from_chain(meta, item)
-        elif isinstance(response, dict):
-            for value in response.values():
-                if isinstance(value, BaseMessage):
-                    self._emit_message_from_chain(meta, value)
-                elif isinstance(value, Sequence) and not isinstance(
-                    value, (str, bytes)
-                ):
-                    for item in value:
-                        if isinstance(item, BaseMessage):
-                            self._emit_message_from_chain(meta, item)
-
-    def _emit_message_from_chain(self, meta: Meta, msg: BaseMessage) -> None:
-        """Emit a full message lifecycle for a message from a chain output,
-        deduplicating against previously-seen messages."""
-        if msg.id is not None and msg.id in self.seen:
-            return
-        if msg.id is None:
-            msg.id = str(uuid4())
-
-        # Determine role and finish reason
-        role = "ai"
-        if hasattr(msg, "type"):
-            if msg.type == "human":
-                role = "human"
-            elif msg.type == "system":
-                role = "system"
-
-        finish_reason: FinishReason = "stop"
-        rm = getattr(msg, "response_metadata", {}) or {}
-        raw_reason = rm.get("finish_reason") or rm.get("stop_reason")
-        if raw_reason:
-            finish_reason = _normalize_finish_reason(raw_reason)
-        if finish_reason == "stop" and hasattr(msg, "tool_calls") and msg.tool_calls:
-            finish_reason = "tool_use"
-
-        raw_usage = getattr(msg, "usage_metadata", None)
-        usage = dict(raw_usage) if raw_usage else None
-
-        self._emit_full_message(meta, msg, finish_reason, usage, role=role)
-
-
-# ---------------------------------------------------------------------------
-# Block extraction for finalized (non-streamed) messages
-# ---------------------------------------------------------------------------
-
-
-def _extract_final_blocks(msg: BaseMessage) -> list[tuple[int, CompatBlock]]:
-    """Extract ``(index, block)`` pairs from a finalized ``AIMessage``."""
-    blocks: list[tuple[int, CompatBlock]] = []
-    content = msg.content
-
-    if isinstance(content, str) and content:
-        blocks.append((0, dict(TextBlock(type="text", text=content))))
-    elif isinstance(content, list):
-        for i, item in enumerate(content):
-            if not isinstance(item, dict):
-                continue
-            ctype = item.get("type", "")
-            if ctype == "text" and item.get("text"):
-                blocks.append((i, dict(TextBlock(type="text", text=item["text"]))))
-            elif ctype in ("reasoning_content", "reasoning", "thinking"):
-                reasoning_text = (
-                    item.get("reasoning_content")
-                    or item.get("reasoning")
-                    or item.get("thinking", "")
-                )
-                if reasoning_text:
-                    blocks.append(
-                        (
-                            i,
-                            dict(
-                                ReasoningBlock(
-                                    type="reasoning", reasoning=reasoning_text
-                                )
-                            ),
-                        )
-                    )
-
-    # Finalized tool calls (already parsed, not chunks)
-    for tc in getattr(msg, "tool_calls", None) or []:
-        idx = len(blocks)
-        blocks.append(
-            (
-                idx,
-                dict(
-                    ToolCallBlock(
-                        type="tool_call",
-                        id=tc.get("id", ""),
-                        name=tc.get("name", ""),
-                        args=tc.get("args", {}),
-                    )
-                ),
-            )
-        )
-
-    return blocks
-
-
-def _make_start_block(block: CompatBlock) -> CompatBlock:
-    """Create an empty start placeholder for a content block."""
-    btype = block.get("type", "text")
-    if btype == "text":
-        return TextBlock(type="text", text="")
-    elif btype == "reasoning":
-        return ReasoningBlock(type="reasoning", reasoning="")
-    elif btype == "tool_call_chunk":
-        result: CompatBlock = {"type": "tool_call_chunk", "args": ""}
-        if "id" in block:
-            result["id"] = block["id"]
-        if "name" in block:
-            result["name"] = block["name"]
-        return result
-    elif btype == "tool_call":
-        # Already finalized — return as-is for start event
-        return ToolCallBlock(
-            type="tool_call",
-            id=block.get("id", ""),
-            name=block.get("name", ""),
-            args=block.get("args", {}),
-        )
-    return dict(block)
-
-
-__all__ = ["PROTOCOL_MESSAGES_STREAM_KEY", "StreamProtocolMessagesHandler"]
@@ -16,7 +16,7 @@ from collections.abc import (
    Mapping,
    Sequence,
 )
-from dataclasses import is_dataclass
+from dataclasses import is_dataclass, replace
 from functools import partial
 from inspect import isclass
 from typing import (
@@ -96,6 +96,12 @@ from langgraph._internal._runnable import (
    coerce_to_runnable,
 )
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
+from langgraph.callbacks import (
+    GraphInterruptEvent,
+    GraphResumeEvent,
+    get_async_graph_callback_manager_for_config,
+    get_sync_graph_callback_manager_for_config,
+)
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.topic import Topic
 from langgraph.config import get_config
@@ -128,10 +134,6 @@ from langgraph.pregel._loop import (
    SyncPregelLoop,
 )
 from langgraph.pregel._messages import StreamMessagesHandler
-from langgraph.pregel._messages_v2 import (
-    PROTOCOL_MESSAGES_STREAM_KEY,
-    StreamProtocolMessagesHandler,
-)
 from langgraph.pregel._read import DEFAULT_BOUND, PregelNode
 from langgraph.pregel._retry import RetryPolicy
 from langgraph.pregel._runner import PregelRunner
@@ -2589,6 +2591,10 @@ class Pregel(
            name=config.get("run_name", self.get_name()),
            run_id=config.get("run_id"),
        )
+        graph_callback_manager = get_sync_graph_callback_manager_for_config(
+            config,
+            run_id=run_manager.run_id,
+        )
        try:
            # assign defaults
            (
@@ -2620,15 +2626,8 @@ class Pregel(
            # set up messages stream mode
            if "messages" in stream_modes:
                ns_ = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
-                _msg_cls = (
-                    StreamProtocolMessagesHandler
-                    if config.get("configurable", {}).get(
-                        PROTOCOL_MESSAGES_STREAM_KEY, False
-                    )
-                    else StreamMessagesHandler
-                )
                run_manager.inheritable_handlers.append(
-                    _msg_cls(
+                    StreamMessagesHandler(
                        stream.put,
                        subgraphs,
                        parent_ns=tuple(ns_.split(NS_SEP)) if ns_ else None,
@@ -2680,6 +2679,17 @@ class Pregel(
            _output_mapper = self._output_mapper if version == "v2" else None
            _state_mapper = self._state_mapper if version == "v2" else None

+            def emit_graph_lifecycle_events(loop: SyncPregelLoop) -> None:
+                while (event := loop._pop_lifecycle_event()) is not None:
+                    if isinstance(event, GraphResumeEvent):
+                        graph_callback_manager.on_resume(
+                            replace(event, run_id=graph_callback_manager.run_id)
+                        )
+                    else:
+                        graph_callback_manager.on_interrupt(
+                            replace(event, run_id=graph_callback_manager.run_id)
+                        )
+
            with SyncPregelLoop(
                input,
                stream=StreamProtocol(stream.put, stream_modes),
@@ -2700,7 +2710,9 @@ class Pregel(
                migrate_checkpoint=self._migrate_checkpoint,
                retry_policy=self.retry_policy,
                cache_policy=self.cache_policy,
+                has_graph_lifecycle_callbacks=bool(graph_callback_manager.handlers),
            ) as loop:
+                emit_graph_lifecycle_events(loop)
                # create runner
                runner = PregelRunner(
                    submit=config[CONF].get(
@@ -2762,9 +2774,11 @@ class Pregel(
                            _state_mapper,
                        )
                    loop.after_tick()
+                    emit_graph_lifecycle_events(loop)
                    # wait for checkpoint
                    if durability_ == "sync":
                        loop._put_checkpoint_fut.result()
+            emit_graph_lifecycle_events(loop)
            # emit output
            yield from _output(
                stream_mode,
@@ -2939,6 +2953,10 @@ class Pregel(
            name=config.get("run_name", self.get_name()),
            run_id=config.get("run_id"),
        )
+        graph_callback_manager = get_async_graph_callback_manager_for_config(
+            config,
+            run_id=run_manager.run_id,
+        )
        # if running from astream_log() run each proc with streaming
        do_stream = (
            next(
@@ -2946,10 +2964,7 @@ class Pregel(
                    True
                    for h in run_manager.handlers
                    if isinstance(h, _StreamingCallbackHandler)
-                    and not isinstance(
-                        h,
-                        (StreamMessagesHandler, StreamProtocolMessagesHandler),
-                    )
+                    and not isinstance(h, StreamMessagesHandler)
                ),
                False,
            )
@@ -2986,16 +3001,10 @@ class Pregel(
                config[CONF][CONFIG_KEY_CHECKPOINT_NS] = recast_checkpoint_ns(ns)
            # set up messages stream mode
            if "messages" in stream_modes:
+                # namespace can be None in a root level graph?
                ns_ = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
-                _msg_cls = (
-                    StreamProtocolMessagesHandler
-                    if config.get("configurable", {}).get(
-                        PROTOCOL_MESSAGES_STREAM_KEY, False
-                    )
-                    else StreamMessagesHandler
-                )
                run_manager.inheritable_handlers.append(
-                    _msg_cls(
+                    StreamMessagesHandler(
                        stream_put,
                        subgraphs,
                        parent_ns=tuple(ns_.split(NS_SEP)) if ns_ else None,
@@ -3062,6 +3071,28 @@ class Pregel(
            _output_mapper = self._output_mapper if version == "v2" else None
            _state_mapper = self._state_mapper if version == "v2" else None

+            async def aemit_graph_lifecycle_events(loop: AsyncPregelLoop) -> None:
+                while (event := loop._pop_lifecycle_event()) is not None:
+                    if isinstance(event, GraphResumeEvent):
+                        await graph_callback_manager.on_resume(
+                            GraphResumeEvent(
+                                run_id=graph_callback_manager.run_id,
+                                status=event.status,
+                                checkpoint_id=event.checkpoint_id,
+                                checkpoint_ns=event.checkpoint_ns,
+                            )
+                        )
+                    else:
+                        await graph_callback_manager.on_interrupt(
+                            GraphInterruptEvent(
+                                run_id=graph_callback_manager.run_id,
+                                status=event.status,
+                                checkpoint_id=event.checkpoint_id,
+                                checkpoint_ns=event.checkpoint_ns,
+                                interrupts=event.interrupts,
+                            )
+                        )
+
            async with AsyncPregelLoop(
                input,
                stream=StreamProtocol(stream.put_nowait, stream_modes),
@@ -3082,7 +3113,9 @@ class Pregel(
                migrate_checkpoint=self._migrate_checkpoint,
                retry_policy=self.retry_policy,
                cache_policy=self.cache_policy,
+                has_graph_lifecycle_callbacks=bool(graph_callback_manager.handlers),
            ) as loop:
+                await aemit_graph_lifecycle_events(loop)
                # create runner
                runner = PregelRunner(
                    submit=config[CONF].get(
@@ -3164,6 +3197,7 @@ class Pregel(
                            ):
                                yield o
                        loop.after_tick()
+                        await aemit_graph_lifecycle_events(loop)
                        # wait for checkpoint
                        if durability_ == "sync":
                            await cast(asyncio.Future, loop._put_checkpoint_fut)
@@ -3172,6 +3206,8 @@ class Pregel(
                    if _cleanup_waiter is not None:
                        await _cleanup_waiter()

+            await aemit_graph_lifecycle_events(loop)
+
            # emit output
            for o in _output(
                stream_mode,
@@ -3679,15 +3715,14 @@ def _coerce_checkpoint_values(payload: Any, mapper: Callable[[Any], Any]) -> Non
 def _build_server_info(
    config: RunnableConfig, parent_runtime: Runtime[Any]
 ) -> ServerInfo | None:
-    """Build ServerInfo from config metadata and configurable.
+    """Build ServerInfo from config configurable.

-    The server puts assistant_id/graph_id in config metadata and the
+    The server puts assistant_id/graph_id in config configurable and the
    authenticated user dict in configurable["langgraph_auth_user"].
    """
-    metadata = config.get("metadata") or {}
    configurable = config.get(CONF) or {}
-    assistant_id = metadata.get("assistant_id")
-    graph_id = metadata.get("graph_id")
+    assistant_id = configurable.get("assistant_id")
+    graph_id = configurable.get("graph_id")

    # Read authenticated user from configurable (set by LangGraph Server).
    # We prefer isinstance(BaseUser) but fall back to hasattr("identity")
@@ -1,45 +0,0 @@
-"""Stream protocol types and infrastructure for LangGraph."""
-
-from langgraph.stream._convert import STREAM_V2_MODES, convert_to_protocol_event
-from langgraph.stream._mux import AsyncStreamMux, StreamMux
-from langgraph.stream._types import (
-    InterruptPayload,
-    ProtocolEvent,
-    StreamTransformer,
-)
-from langgraph.stream.chat_model_stream import AsyncChatModelStream, ChatModelStream
-from langgraph.stream.run_stream import (
-    AsyncGraphRunStream,
-    AsyncSubgraphRunStream,
-    GraphRunStream,
-    create_async_graph_run_stream,
-    create_graph_run_stream,
-)
-from langgraph.stream.stream_channel import StreamChannel, is_stream_channel
-from langgraph.stream.streaming_handler import StreamingHandler
-from langgraph.stream.transformers import (
-    MessagesTransformer,
-    ValuesTransformer,
-)
-
-__all__ = [
-    "STREAM_V2_MODES",
-    "AsyncChatModelStream",
-    "AsyncGraphRunStream",
-    "AsyncStreamMux",
-    "AsyncSubgraphRunStream",
-    "ChatModelStream",
-    "GraphRunStream",
-    "InterruptPayload",
-    "MessagesTransformer",
-    "ProtocolEvent",
-    "StreamChannel",
-    "StreamMux",
-    "StreamTransformer",
-    "StreamingHandler",
-    "ValuesTransformer",
-    "convert_to_protocol_event",
-    "create_async_graph_run_stream",
-    "create_graph_run_stream",
-    "is_stream_channel",
-]
@@ -1,67 +0,0 @@
-"""Convert raw ``StreamChunk`` tuples to ``ProtocolEvent`` envelopes.
-
-Each ``StreamMode`` is mapped to a ``ProtocolEvent`` whose ``method``
-field matches the mode name and whose ``params.data`` wraps the
-original payload.
-"""
-
-from __future__ import annotations
-
-from typing import Any
-
-from langgraph.stream._types import ProtocolEvent, _ProtocolEventParams
-from langgraph.types import StreamMode
-
-#: All stream modes requested by ``StreamingHandler`` when calling the
-#: underlying ``stream()`` / ``astream()``.
-STREAM_V2_MODES: list[StreamMode] = [
-    "values",
-    "updates",
-    "messages",
-    "custom",
-    "checkpoints",
-    "tasks",
-    "debug",
-]
-
-_SUPPORTED_MODES: set[str] = set(STREAM_V2_MODES)
-
-
-def convert_to_protocol_event(
-    ns: tuple[str, ...],
-    mode: str,
-    payload: Any,
-    *,
-    node: str | None = None,
-) -> ProtocolEvent | None:
-    """Convert a ``StreamChunk`` to a ``ProtocolEvent``.
-
-    Returns ``None`` for unsupported or unknown modes.
-
-    The ``seq`` field is left as ``0`` here; the :class:`StreamMux` is
-    the sole seq assigner and overwrites it inside ``push()``.
-
-    Args:
-        ns: Namespace tuple from the ``StreamChunk``.
-        mode: Stream mode string (``"values"``, ``"updates"``, etc.).
-        payload: The raw payload from the stream.
-        node: Optional node name for provenance.
-    """
-    if mode not in _SUPPORTED_MODES:
-        return None
-
-    params: _ProtocolEventParams = {
-        "namespace": list(ns),
-        "data": payload,
-    }
-    if node is not None:
-        params["node"] = node
-
-    return ProtocolEvent(
-        type="event",
-        method=mode,
-        params=params,
-    )
-
-
-__all__ = ["STREAM_V2_MODES", "convert_to_protocol_event"]
@@ -1,385 +0,0 @@
-"""Central event dispatcher with transformer pipeline for StreamingHandler.
-
-``StreamMux`` is the synchronous core: it holds the main
-event log (a plain list), tracks discovered namespaces for subgraph stream
-creation, and pipes every event through the registered
-:class:`StreamTransformer` pipeline before appending it to the log.
-
-``AsyncStreamMux`` extends ``StreamMux`` with async consumer APIs
-(output futures, async event subscriptions, subgraph discovery).
-"""
-
-from __future__ import annotations
-
-import asyncio
-from collections.abc import AsyncIterator
-from typing import Any
-
-from langgraph.stream._types import InterruptPayload, ProtocolEvent, StreamTransformer
-from langgraph.stream.stream_channel import StreamChannel, is_stream_channel
-
-
-class StreamMux:
-    """Synchronous event dispatcher for the StreamingHandler infrastructure.
-
-    The mux owns the main event log, applies the transformer pipeline to
-    every incoming event, and tracks namespace discovery and latest values.
-
-    For async consumer APIs (output futures, async event subscriptions,
-    subgraph discovery) use :class:`AsyncStreamMux`.
-    """
-
-    def __init__(self, transformers: list[StreamTransformer] | None = None) -> None:
-        self._event_log: list[ProtocolEvent] = []
-        self._transformers: list[StreamTransformer] = list(transformers or [])
-        self._current_namespace: list[str] = []
-        self._next_emit_seq: int = 0
-
-        # Namespace discovery: maps top-level ns segment → True
-        self._discovered_ns: dict[str, bool] = {}
-
-        # Latest values per namespace (list-of-strings key)
-        self._latest_values: dict[str, Any] = {}
-
-        # Interrupt tracking
-        self._interrupts: list[InterruptPayload] = []
-        self._interrupted = False
-
-        # Closed state
-        self._closed = False
-        self._error: BaseException | None = None
-
-    # -- Producer API -------------------------------------------------------
-
-    def push(self, event: ProtocolEvent) -> None:
-        """Push an event through the transformer pipeline and into the log.
-
-        Each registered transformer's ``process()`` is called in order.
-        If any transformer returns ``False``, the event is suppressed
-        (not appended to the main log).
-        """
-        if self._closed:
-            return
-
-        # Mux is the sole seq assigner — ensures all events in the log
-        # (including those from StreamChannel forwarders) share a single
-        # monotonically increasing counter.
-        event["seq"] = self._next_emit_seq
-        self._next_emit_seq += 1
-
-        # Track namespace
-        ns = event["params"].get("namespace", [])
-        if ns:
-            top_segment = ns[0]
-            if top_segment not in self._discovered_ns:
-                self._discovered_ns[top_segment] = True
-
-        # Track values
-        if event["method"] == "values":
-            ns_key = _ns_key(ns)
-            self._latest_values[ns_key] = event["params"]["data"]
-
-        # Track interrupts from values events
-        if event["method"] == "values":
-            data = event["params"]["data"]
-            if isinstance(data, dict) and "__interrupt__" in data:
-                interrupt_info = data["__interrupt__"]
-                if isinstance(interrupt_info, (list, tuple)):
-                    for item in interrupt_info:
-                        iid = getattr(item, "id", None) or str(id(item))
-                        self._interrupts.append(
-                            InterruptPayload(
-                                interrupt_id=iid,
-                                payload=item,
-                            )
-                        )
-                    self._interrupted = True
-
-        # Run transformer pipeline
-        self._current_namespace = ns
-        keep = True
-        for transformer in self._transformers:
-            result = transformer.process(event)
-            if result is False:
-                keep = False
-        self._current_namespace = []
-
-        # Append to main log if not suppressed
-        if keep:
-            self._event_log.append(event)
-
-    def close(self, output: Any = None) -> None:
-        """Close the mux and finalize all transformers."""
-        if self._closed:
-            return
-        self._closed = True
-
-        for transformer in self._transformers:
-            transformer.finalize()
-
-    def fail(self, error: BaseException) -> None:
-        """Fail the mux and propagate the error to all consumers."""
-        if self._closed:
-            return
-        self._closed = True
-        self._error = error
-
-        for transformer in self._transformers:
-            transformer.fail(error)
-
-    # -- Inspection ---------------------------------------------------------
-
-    @property
-    def interrupted(self) -> bool:
-        return self._interrupted
-
-    @property
-    def interrupts(self) -> list[InterruptPayload]:
-        return list(self._interrupts)
-
-    @property
-    def event_log(self) -> list[ProtocolEvent]:
-        return self._event_log
-
-    def get_latest_values(self, ns: list[str] | None = None) -> Any:
-        """Return the most recent values for a namespace."""
-        return self._latest_values.get(_ns_key(ns or []))
-
-    # -- Internal -----------------------------------------------------------
-
-    def register_transformer(self, transformer: StreamTransformer) -> None:
-        """Register a new transformer and replay all buffered events through it.
-
-        This is the safe way to add a late-arriving transformer after the mux
-        has already started processing events.  The sequence is:
-
-        1. Snapshot the current log length.
-        2. Append the transformer so future ``push()`` calls reach it.
-        3. Replay events ``[0, snapshot)`` through the transformer.
-        4. If the mux is already closed, call ``finalize()`` immediately so
-           the transformer's log/channel terminates cleanly.
-
-        No namespace filtering is applied — all buffered events are
-        replayed.  Transformers that need namespace filtering should do
-        so inside their ``process()`` implementation.
-        """
-        snapshot = len(self._event_log)
-        self._transformers.append(transformer)
-        for i in range(snapshot):
-            transformer.process(self._event_log[i])
-        if self._closed:
-            transformer.finalize()
-
-    def wire_channels(self, projection: Any) -> None:
-        """Scan *projection* for :class:`StreamChannel` instances and wire them.
-
-        For each ``StreamChannel`` found, registers a push callback that
-        appends a :class:`ProtocolEvent` directly to the main event log
-        with ``method`` set to the channel's name.
-
-        Channel events bypass the transformer pipeline (matching the JS
-        implementation).  They are visible to raw event iteration and
-        remote SDK clients but not to other transformers' ``process()``.
-        """
-        if projection is None:
-            return
-        items: dict[str, Any] = {}
-        if isinstance(projection, dict):
-            items = projection
-        elif hasattr(projection, "__dict__"):
-            items = vars(projection)
-        for _key, value in items.items():
-            if is_stream_channel(value):
-                channel: StreamChannel[Any] = value
-                def _make_forwarder(ch: StreamChannel[Any]) -> Any:
-                    def _forward(item: Any) -> None:
-                        if self._closed:
-                            return
-                        # Append directly to the event log, bypassing
-                        # the transformer pipeline.  This matches the JS
-                        # implementation and avoids re-entrancy bugs
-                        # (namespace clobbering, infinite recursion).
-                        self._event_log.append(
-                            ProtocolEvent(
-                                type="event",
-                                seq=self._next_emit_seq,
-                                method=ch.channel_name,
-                                params={
-                                    "namespace": list(self._current_namespace),
-                                    "data": item,
-                                },
-                            )
-                        )
-                        self._next_emit_seq += 1
-
-                    return _forward
-
-                channel._wire(_make_forwarder(channel))
-
-
-# ---------------------------------------------------------------------------
-# AsyncStreamMux — async consumer APIs on top of the sync core
-# ---------------------------------------------------------------------------
-
-
-class AsyncStreamMux(StreamMux):
-    """Async extension of :class:`StreamMux`.
-
-    Adds output futures, async event subscriptions, and subgraph
-    discovery on top of the synchronous producer/transformer core.
-    """
-
-    def __init__(self, transformers: list[StreamTransformer] | None = None) -> None:
-        super().__init__(transformers=transformers)
-        # Notification event — set on every push/close/fail to wake async consumers
-        self._notify: asyncio.Event = asyncio.Event()
-        # Waiters for new namespace discovery
-        self._ns_waiters: list[asyncio.Future[None]] = []
-        # Output promise tracking
-        self._output_futures: dict[str, asyncio.Future[Any]] = {}
-
-    # -- Producer overrides (extend to resolve async primitives) -------------
-
-    def push(self, event: ProtocolEvent) -> None:
-        # Peek at namespace before super().push() so we can detect new
-        # discoveries and wake waiters.
-        ns = event["params"].get("namespace", [])
-        is_new_ns = bool(ns) and ns[0] not in self._discovered_ns
-        super().push(event)
-        if is_new_ns and ns[0] in self._discovered_ns:
-            self._wake_ns_waiters()
-        self._notify.set()
-
-    def close(self, output: Any = None) -> None:
-        super().close(output)
-        self._notify.set()
-        # Resolve output futures
-        for ns_key, fut in self._output_futures.items():
-            if not fut.done():
-                value = self._latest_values.get(ns_key)
-                try:
-                    fut.get_loop().call_soon_threadsafe(fut.set_result, value)
-                except RuntimeError:
-                    pass
-        # Wake namespace waiters
-        self._wake_ns_waiters()
-
-    def fail(self, error: BaseException) -> None:
-        super().fail(error)
-        self._notify.set()
-        # Reject output futures
-        for fut in self._output_futures.values():
-            if not fut.done():
-                try:
-                    fut.get_loop().call_soon_threadsafe(fut.set_exception, error)
-                except RuntimeError:
-                    pass
-        # Wake namespace waiters
-        self._wake_ns_waiters()
-
-    # -- Async consumer API -------------------------------------------------
-
-    async def subscribe_events(
-        self, path: list[str] | None = None, offset: int = 0
-    ) -> AsyncIterator[ProtocolEvent]:
-        """Async iterate over events matching *path*.
-
-        If *path* is ``None`` or empty, all events are yielded.
-        Otherwise, only events whose namespace starts with *path*
-        are yielded.
-
-        Uses the list + ``asyncio.Event`` notification pattern: poll
-        the event log, yield what's new, await the notify event for more.
-        """
-        cursor = offset
-        while True:
-            while cursor < len(self._event_log):
-                event = self._event_log[cursor]
-                cursor += 1
-                if not path or _ns_starts_with(
-                    event["params"].get("namespace", []), path
-                ):
-                    yield event
-            if self._closed:
-                if self._error is not None:
-                    raise self._error
-                return
-            self._notify.clear()
-            await self._notify.wait()
-
-    async def subscribe_subgraphs(
-        self, path: list[str] | None = None, offset: int = 0
-    ) -> AsyncIterator[str]:
-        """Yield top-level namespace segments as they are discovered.
-
-        Each yielded value is the first namespace segment of a newly
-        discovered subgraph (e.g. ``"agent:0"``).
-        """
-        yielded: set[str] = set()
-        while True:
-            # Yield any newly discovered namespaces
-            for ns_segment in list(self._discovered_ns):
-                if ns_segment not in yielded:
-                    # Filter by path prefix if specified
-                    if path:
-                        if not ns_segment.startswith(path[0]):
-                            continue
-                    yielded.add(ns_segment)
-                    yield ns_segment
-
-            if self._closed:
-                return
-
-            # Wait for new namespaces
-            loop = asyncio.get_running_loop()
-            fut: asyncio.Future[None] = loop.create_future()
-            self._ns_waiters.append(fut)
-            await fut
-
-    def get_output_future(self, ns: list[str] | None = None) -> asyncio.Future[Any]:
-        """Get or create an output future for a namespace.
-
-        The future resolves to the latest ``values`` event data when
-        the mux is closed.
-        """
-        ns_key = _ns_key(ns or [])
-        if ns_key not in self._output_futures:
-            loop = asyncio.get_running_loop()
-            self._output_futures[ns_key] = loop.create_future()
-
-            # If already closed, resolve immediately
-            if self._closed:
-                value = self._latest_values.get(ns_key)
-                if self._error is not None:
-                    self._output_futures[ns_key].set_exception(self._error)
-                else:
-                    self._output_futures[ns_key].set_result(value)
-
-        return self._output_futures[ns_key]
-
-    # -- Internal -----------------------------------------------------------
-
-    def _wake_ns_waiters(self) -> None:
-        for fut in self._ns_waiters:
-            if not fut.done():
-                try:
-                    fut.get_loop().call_soon_threadsafe(fut.set_result, None)
-                except RuntimeError:
-                    pass
-        self._ns_waiters.clear()
-
-
-
-def _ns_key(ns: list[str] | tuple[str, ...]) -> str:
-    """Convert a namespace list to a hashable key."""
-    return "|".join(ns)
-
-
-def _ns_starts_with(ns: list[str], prefix: list[str]) -> bool:
-    """Check if *ns* starts with *prefix*."""
-    if len(ns) < len(prefix):
-        return False
-    return ns[: len(prefix)] == prefix
-
-
-__all__ = ["AsyncStreamMux", "StreamMux"]
@@ -1,166 +0,0 @@
-"""Protocol types for StreamingHandler.
-
-Re-exports CDDL-derived types from ``langchain-protocol`` and defines
-in-process-only types needed by the LangGraph streaming infrastructure.
-"""
-
-from __future__ import annotations
-
-from abc import ABC, abstractmethod
-from typing import Any
-
-# ---------------------------------------------------------------------------
-# Re-exports from langchain-protocol (CDDL-derived)
-# ---------------------------------------------------------------------------
-# Primitives
-# Content blocks
-# Messages data
-# Tools data
-from langchain_protocol import (
-    Annotation,
-    Citation,
-    ContentBlock,
-    ContentBlockDeltaData,
-    ContentBlockFinishData,
-    ContentBlockStartData,
-    FinalizedContentBlock,
-    FinishReason,
-    InvalidToolCallBlock,
-    MessageErrorData,
-    MessageFinishData,
-    MessageMetadata,
-    MessageRole,
-    MessagesData,
-    MessageStartData,
-    MetadataScalar,
-    Namespace,
-    ReasoningBlock,
-    TextBlock,
-    ToolCallBlock,
-    ToolCallChunkBlock,
-    ToolErrorData,
-    ToolFinishedData,
-    ToolOutputDeltaData,
-    ToolsData,
-    ToolStartedData,
-    UsageInfo,
-)
-from typing_extensions import NotRequired, TypedDict
-
-# ---------------------------------------------------------------------------
-# In-process types (not in the CDDL spec)
-# ---------------------------------------------------------------------------
-
-
-class _ProtocolEventParams(TypedDict):
-    """Payload envelope for a :class:`ProtocolEvent`."""
-
-    namespace: Namespace
-    node: NotRequired[str]
-    data: Any
-
-
-class ProtocolEvent(TypedDict):
-    """A single protocol event emitted by the StreamingHandler infrastructure.
-
-    ``method`` corresponds to a
-    :pydata:`~langgraph.types.StreamMode` value (``"messages"``,
-    ``"updates"``, etc.).
-    """
-
-    type: str  # always "event"
-    seq: NotRequired[int]  # assigned by StreamMux.push(); absent before push()
-    method: str  # StreamMode value
-    params: _ProtocolEventParams
-
-
-class StreamTransformer(ABC):
-    """Extension point for custom stream projections.
-
-    Implementations are registered with ``StreamingHandler`` and receive every
-    :class:`ProtocolEvent` before it is appended to the event log.
-
-    Any :class:`~langgraph.stream.stream_channel.StreamChannel` instances
-    returned by ``init()`` are automatically wired to the protocol event
-    stream by the mux.
-
-    """
-
-    @abstractmethod
-    def init(self) -> Any:
-        """Return the initial projection value.
-
-        Called once before the run.  Any
-        :class:`~langgraph.stream.stream_channel.StreamChannel` instances
-        in the return value are automatically wired by the mux.
-        """
-        ...
-
-    @abstractmethod
-    def process(self, event: ProtocolEvent) -> bool:
-        """Process an event.
-
-        Return ``True`` to keep the event in the log, ``False`` to suppress
-        it.
-        """
-        ...
-
-    def finalize(self) -> None:
-        """Called once when the run completes successfully.
-
-        Optional — the mux auto-closes any :class:`StreamChannel` instances,
-        so transformers that only use channels can omit this.
-        """
-
-    def fail(self, err: BaseException) -> None:
-        """Called once when the run fails.
-
-        Optional — the mux auto-fails any :class:`StreamChannel` instances,
-        so transformers that only use channels can omit this.
-        """
-
-
-class InterruptPayload(TypedDict):
-    """An interrupt produced during a StreamingHandler run."""
-
-    interrupt_id: str
-    payload: Any
-
-
-__all__ = [
-    # Primitives (re-exported)
-    "Namespace",
-    "MessageRole",
-    "MessageMetadata",
-    "MetadataScalar",
-    # Content blocks (re-exported)
-    "TextBlock",
-    "ReasoningBlock",
-    "ToolCallBlock",
-    "ToolCallChunkBlock",
-    "InvalidToolCallBlock",
-    "ContentBlock",
-    "FinalizedContentBlock",
-    "Annotation",
-    "Citation",
-    # Messages data (re-exported)
-    "MessagesData",
-    "MessageStartData",
-    "ContentBlockStartData",
-    "ContentBlockDeltaData",
-    "ContentBlockFinishData",
-    "MessageFinishData",
-    "MessageErrorData",
-    "FinishReason",
-    "UsageInfo",
-    # Tools data (re-exported)
-    "ToolsData",
-    "ToolStartedData",
-    "ToolOutputDeltaData",
-    "ToolFinishedData",
-    "ToolErrorData",
-    # In-process types
-    "ProtocolEvent",
-    "StreamTransformer",
-    "InterruptPayload",
-]
@@ -1,324 +0,0 @@
-"""Per-message streaming objects for StreamingHandler.
-
-``ChatModelStream`` is the synchronous variant returned by
-``GraphRunStream.messages``.  Properties (``.text``, ``.reasoning``,
-``.usage``) return final accumulated values.
-
-``AsyncChatModelStream`` is the asynchronous variant returned by
-``AsyncGraphRunStream.messages``.  Projections are dual
-async-iterable + awaitable (e.g. ``async for delta in msg.text``
-or ``full = await msg.text``).
-"""
-
-from __future__ import annotations
-
-import asyncio
-from collections.abc import Generator
-from typing import Any
-
-from langgraph.stream._types import UsageInfo
-
-# ---------------------------------------------------------------------------
-# Sync variant
-# ---------------------------------------------------------------------------
-
-
-class ChatModelStream:
-    """Synchronous per-message object for a single LLM response.
-
-    Created by :class:`~langgraph.stream.transformers.MessagesTransformer`
-    and yielded by ``GraphRunStream.messages``.  By the time the sync
-    iterator yields a ``ChatModelStream``, the message lifecycle is
-    complete and all properties contain their final values.
-
-    Projections:
-
-    - ``.text`` — accumulated text content (``str``)
-    - ``.reasoning`` — accumulated reasoning content (``str``)
-    - ``.usage`` — :class:`UsageInfo` or ``None``
-    - ``.namespace`` / ``.node`` — provenance metadata
-    """
-
-    def __init__(
-        self,
-        *,
-        namespace: list[str] | None = None,
-        node: str | None = None,
-        message_id: str | None = None,
-    ) -> None:
-        self._namespace = namespace or []
-        self._node = node
-        self._message_id = message_id
-
-        # Accumulated state
-        self._text_acc = ""
-        self._reasoning_acc = ""
-        self._usage_value: UsageInfo | None = None
-        self._done = False
-
-    # -- Public projections ------------------------------------------------
-
-    @property
-    def text(self) -> str:
-        """Accumulated text content."""
-        return self._text_acc
-
-    @property
-    def reasoning(self) -> str:
-        """Accumulated reasoning content."""
-        return self._reasoning_acc
-
-    @property
-    def usage(self) -> UsageInfo | None:
-        """Usage info, available after the message finishes."""
-        return self._usage_value
-
-    @property
-    def namespace(self) -> list[str]:
-        return self._namespace
-
-    @property
-    def node(self) -> str | None:
-        return self._node
-
-    @property
-    def message_id(self) -> str | None:
-        return self._message_id
-
-    @property
-    def done(self) -> bool:
-        return self._done
-
-    # -- Internal API (called by MessagesTransformer) ----------------------
-
-    def _push_content_block_delta(self, data: dict[str, Any]) -> None:
-        """Process a ``content-block-delta`` event."""
-        block = data.get("content_block", {})
-        btype = block.get("type", "")
-
-        if btype == "text":
-            delta_text = block.get("text", "")
-            if delta_text:
-                self._text_acc += delta_text
-        elif btype == "reasoning":
-            delta_r = block.get("reasoning", "")
-            if delta_r:
-                self._reasoning_acc += delta_r
-
-    def _push_content_block_finish(self, data: dict[str, Any]) -> None:
-        """Process a ``content-block-finish`` event."""
-        block = data.get("content_block", {})
-        btype = block.get("type", "")
-
-        if btype == "text":
-            full_text = block.get("text", "")
-            if full_text and full_text != self._text_acc:
-                self._text_acc = full_text
-        elif btype == "reasoning":
-            full_r = block.get("reasoning", "")
-            if full_r and full_r != self._reasoning_acc:
-                self._reasoning_acc = full_r
-
-    def _finish(self, data: dict[str, Any]) -> None:
-        """Process a ``message-finish`` event."""
-        self._done = True
-        self._usage_value = data.get("usage")
-
-    def _fail(self, error: BaseException) -> None:
-        """Process a ``message-error`` event."""
-        self._done = True
-
-
-# ---------------------------------------------------------------------------
-# Dual-projection helpers — sync data container + async notification layer
-# ---------------------------------------------------------------------------
-
-
-class _DualProjection:
-    """Sync data container for incremental deltas and a final value.
-
-    Stores deltas as they arrive and tracks the final accumulated value.
-    No async primitives — see :class:`_AsyncDualProjection` for the
-    async-iterable + awaitable extension.
-    """
-
-    def __init__(self) -> None:
-        self._deltas: list[Any] = []
-        self._done = False
-        self._error: BaseException | None = None
-        self._final_value: Any = None
-        self._final_set = False
-
-    # -- Producer API (called by AsyncChatModelStream) ---------------------
-
-    def _push(self, delta: Any) -> None:
-        """Add a new delta value."""
-        self._deltas.append(delta)
-
-    def _finish(self, accumulated: Any) -> None:
-        """Set the final accumulated value and mark as done."""
-        self._final_value = accumulated
-        self._final_set = True
-        self._done = True
-
-    def _fail(self, error: BaseException) -> None:
-        self._error = error
-        self._done = True
-
-
-class _AsyncDualProjection(_DualProjection):
-    """Async extension of :class:`_DualProjection`.
-
-    Async iterable of deltas that is also awaitable for the final value.
-    Uses an ``asyncio.Event`` to notify async consumers when new data
-    arrives — the same pattern as :class:`AsyncStreamMux`.
-    """
-
-    def __init__(self) -> None:
-        super().__init__()
-        self._notify: asyncio.Event = asyncio.Event()
-
-    # -- Producer overrides (extend to notify) -----------------------------
-
-    def _push(self, delta: Any) -> None:
-        super()._push(delta)
-        self._notify.set()
-
-    def _finish(self, accumulated: Any) -> None:
-        super()._finish(accumulated)
-        self._notify.set()
-
-    def _fail(self, error: BaseException) -> None:
-        super()._fail(error)
-        self._notify.set()
-
-    # -- Async iterable (yields deltas) ------------------------------------
-
-    def __aiter__(self) -> _AsyncDualProjectionIterator:
-        return _AsyncDualProjectionIterator(self)
-
-    # -- Awaitable (returns final value) -----------------------------------
-
-    def __await__(self) -> Generator[Any, None, Any]:
-        return self._await_impl().__await__()
-
-    async def _await_impl(self) -> Any:
-        while not self._final_set:
-            if self._error is not None:
-                raise self._error
-            self._notify.clear()
-            await self._notify.wait()
-        if self._error is not None:
-            raise self._error
-        return self._final_value
-
-
-class _AsyncDualProjectionIterator:
-    """Async iterator over an :class:`_AsyncDualProjection`'s deltas."""
-
-    __slots__ = ("_proj", "_offset")
-
-    def __init__(self, proj: _AsyncDualProjection) -> None:
-        self._proj = proj
-        self._offset = 0
-
-    def __aiter__(self) -> _AsyncDualProjectionIterator:
-        return self
-
-    async def __anext__(self) -> Any:
-        while True:
-            if self._offset < len(self._proj._deltas):
-                item = self._proj._deltas[self._offset]
-                self._offset += 1
-                return item
-            if self._proj._error is not None:
-                raise self._proj._error
-            if self._proj._done:
-                raise StopAsyncIteration
-            self._proj._notify.clear()
-            await self._proj._notify.wait()
-
-
-# ---------------------------------------------------------------------------
-# Async variant
-# ---------------------------------------------------------------------------
-
-
-class AsyncChatModelStream(ChatModelStream):
-    """Asynchronous per-message streaming object for a single LLM response.
-
-    Created by :class:`~langgraph.stream.transformers.MessagesTransformer`
-    and yielded by ``AsyncGraphRunStream.messages``.  Content-block events
-    are fed into this object until ``message-finish``.
-
-    Projections:
-
-    - ``.text`` — async iterable of text deltas; awaitable for full text
-    - ``.reasoning`` — async iterable of reasoning deltas; awaitable for
-      full reasoning text
-    - ``.usage`` — awaitable for :class:`UsageInfo`
-    - ``.namespace`` / ``.node`` — provenance metadata
-    """
-
-    def __init__(
-        self,
-        *,
-        namespace: list[str] | None = None,
-        node: str | None = None,
-        message_id: str | None = None,
-    ) -> None:
-        super().__init__(namespace=namespace, node=node, message_id=message_id)
-        self._text_proj = _AsyncDualProjection()
-        self._reasoning_proj = _AsyncDualProjection()
-        self._usage_proj = _AsyncDualProjection()
-
-    # -- Public projections (override sync properties) ---------------------
-
-    @property
-    def text(self) -> _AsyncDualProjection:
-        """Text content — async iterable of deltas, awaitable for full text."""
-        return self._text_proj
-
-    @property
-    def reasoning(self) -> _AsyncDualProjection:
-        """Reasoning content — async iterable of deltas, awaitable for full text."""
-        return self._reasoning_proj
-
-    @property
-    def usage(self) -> _AsyncDualProjection:
-        """Usage info — awaitable for :class:`UsageInfo`."""
-        return self._usage_proj
-
-    # -- Internal API (extend base to also drive projections) --------------
-
-    def _push_content_block_delta(self, data: dict[str, Any]) -> None:
-        """Process a ``content-block-delta`` event."""
-        super()._push_content_block_delta(data)
-        block = data.get("content_block", {})
-        btype = block.get("type", "")
-
-        if btype == "text":
-            delta_text = block.get("text", "")
-            if delta_text:
-                self._text_proj._push(delta_text)
-        elif btype == "reasoning":
-            delta_r = block.get("reasoning", "")
-            if delta_r:
-                self._reasoning_proj._push(delta_r)
-
-    def _finish(self, data: dict[str, Any]) -> None:
-        """Process a ``message-finish`` event."""
-        super()._finish(data)
-        self._text_proj._finish(self._text_acc)
-        self._reasoning_proj._finish(self._reasoning_acc)
-        self._usage_proj._finish(self._usage_value)
-
-    def _fail(self, error: BaseException) -> None:
-        """Process a ``message-error`` event."""
-        super()._fail(error)
-        self._text_proj._fail(error)
-        self._reasoning_proj._fail(error)
-        self._usage_proj._fail(error)
-
-
-__all__ = ["AsyncChatModelStream", "ChatModelStream"]
@@ -1,586 +0,0 @@
-"""GraphRunStream and AsyncGraphRunStream for StreamingHandler.
-
-These are the top-level objects returned by
-``StreamingHandler.stream()`` / ``StreamingHandler.astream()``.
-
-``AsyncGraphRunStream`` wraps an :class:`AsyncStreamMux` and exposes
-``.values``, ``.messages``, ``.subgraphs``, ``.output``, and
-``.messages_from()``.
-
-``GraphRunStream`` wraps a :class:`StreamMux` and exposes the sync
-equivalents: ``.values``, ``.messages``, and ``.output``.
-"""
-
-from __future__ import annotations
-
-import asyncio
-from collections.abc import AsyncIterator, Callable, Iterator
-from typing import Any
-
-from langgraph.stream._convert import convert_to_protocol_event
-from langgraph.stream._mux import AsyncStreamMux, StreamMux
-from langgraph.stream._types import InterruptPayload, ProtocolEvent, StreamTransformer
-from langgraph.stream.chat_model_stream import AsyncChatModelStream, ChatModelStream
-from langgraph.stream.transformers import MessagesTransformer, ValuesTransformer
-
-# ---------------------------------------------------------------------------
-# Values projection — dual async-iterable + awaitable
-# ---------------------------------------------------------------------------
-
-
-class _ValuesProjection:
-    """Async iterable of intermediate state snapshots; awaitable for final."""
-
-    def __init__(
-        self,
-        mux: AsyncStreamMux,
-        values_transformer: ValuesTransformer,
-        ns: list[str],
-        mapper: Callable[[Any], Any] | None = None,
-    ) -> None:
-        self._mux = mux
-        self._values_transformer = values_transformer
-        self._ns = ns
-        self._mapper = mapper
-
-    async def __aiter__(self) -> AsyncIterator[Any]:
-        log = self._values_transformer.values_log
-        cursor = 0
-        while True:
-            while cursor < len(log):
-                item = log[cursor]
-                cursor += 1
-                if item.get("namespace", []) == self._ns:
-                    data = item["data"]
-                    if data is not None and self._mapper is not None:
-                        yield self._mapper(data)
-                    else:
-                        yield data
-            if self._mux._closed:
-                return
-            self._mux._notify.clear()
-            await self._mux._notify.wait()
-
-    def __await__(self) -> Any:
-        return self._await_impl().__await__()
-
-    async def _await_impl(self) -> Any:
-        value = await self._mux.get_output_future(self._ns)
-        if value is not None and self._mapper is not None:
-            return self._mapper(value)
-        return value
-
-
-# ---------------------------------------------------------------------------
-# Messages projection
-# ---------------------------------------------------------------------------
-
-
-class _MessagesProjection:
-    """Async iterable of :class:`AsyncChatModelStream` instances."""
-
-    def __init__(self, mux: AsyncStreamMux, messages_transformer: MessagesTransformer) -> None:
-        self._mux = mux
-        self._transformer = messages_transformer
-
-    async def __aiter__(self) -> AsyncIterator[AsyncChatModelStream]:
-        log = self._transformer.messages_log
-        cursor = 0
-        while True:
-            while cursor < len(log):
-                yield log[cursor]
-                cursor += 1
-            if self._mux._closed:
-                return
-            self._mux._notify.clear()
-            await self._mux._notify.wait()
-
-
-# ---------------------------------------------------------------------------
-# Subgraphs projection
-# ---------------------------------------------------------------------------
-
-
-class _SubgraphsProjection:
-    """Async iterable yielding :class:`AsyncSubgraphRunStream` for each discovered subgraph."""
-
-    def __init__(self, mux: AsyncStreamMux, ns: list[str]) -> None:
-        self._mux = mux
-        self._ns = ns
-
-    async def __aiter__(self) -> AsyncIterator[AsyncSubgraphRunStream]:
-        async for segment in self._mux.subscribe_subgraphs(self._ns):
-            child_ns = self._ns + [segment]
-            child_transformers: list[StreamTransformer] = [
-                ValuesTransformer(),
-                MessagesTransformer(
-                    namespace=child_ns, stream_cls=AsyncChatModelStream
-                ),
-            ]
-            for t in child_transformers:
-                t.init()
-                self._mux.register_transformer(t)
-
-            yield AsyncSubgraphRunStream(
-                mux=self._mux,
-                namespace=child_ns,
-                transformers=child_transformers,
-            )
-
-
-# ---------------------------------------------------------------------------
-# AsyncGraphRunStream
-# ---------------------------------------------------------------------------
-
-
-class AsyncGraphRunStream:
-    """The async run stream returned by ``StreamingHandler.astream()``.
-
-    Async-iterable over all :class:`ProtocolEvent` instances.  Named
-    projections provide ergonomic access to values, messages, subgraphs,
-    and output.
-    """
-
-    def __init__(
-        self,
-        *,
-        mux: AsyncStreamMux,
-        namespace: list[str] | None = None,
-        transformers: list[StreamTransformer],
-        abort_event: asyncio.Event | None = None,
-        output_mapper: Callable[[Any], Any] | None = None,
-    ) -> None:
-        self._mux = mux
-        self._ns = namespace or []
-        self._transformers = transformers
-        self._abort_event = abort_event or asyncio.Event()
-        self._output_mapper = output_mapper
-
-    # -- Transformer lookup -------------------------------------------------
-
-    def _find_transformer(self, name: str) -> StreamTransformer | None:
-        for t in self._transformers:
-            if getattr(t, "name", None) == name:
-                return t
-        return None
-
-    # -- Raw event iteration ------------------------------------------------
-
-    def __aiter__(self) -> AsyncIterator[ProtocolEvent]:
-        return self._mux.subscribe_events(self._ns)
-
-    # -- Named projections --------------------------------------------------
-
-    @property
-    def values(self) -> _ValuesProjection:
-        """Async iterable of state snapshots; awaitable for final state."""
-        t = self._find_transformer("values")
-        return _ValuesProjection(self._mux, t, self._ns, self._output_mapper)
-
-    @property
-    def output(self) -> _ValuesProjection:
-        """Awaitable for the final output state."""
-        t = self._find_transformer("values")
-        return _ValuesProjection(self._mux, t, self._ns, self._output_mapper)
-
-    @property
-    def messages(self) -> _MessagesProjection:
-        """Async iterable of :class:`AsyncChatModelStream` instances."""
-        t = self._find_transformer("messages")
-        return _MessagesProjection(self._mux, t)
-
-    def messages_from(self, node: str) -> _MessagesProjection:
-        """Async iterable of messages from a specific node."""
-        filtered = MessagesTransformer(
-            namespace=self._ns,
-            node_filter=node,
-            stream_cls=AsyncChatModelStream,
-        )
-        self._mux.register_transformer(filtered)
-        return _MessagesProjection(self._mux, filtered)
-
-    @property
-    def subgraphs(self) -> _SubgraphsProjection:
-        """Async iterable of :class:`AsyncSubgraphRunStream` for child graphs."""
-        return _SubgraphsProjection(self._mux, self._ns)
-
-    # -- State --------------------------------------------------------------
-
-    @property
-    def interrupted(self) -> bool:
-        return self._mux.interrupted
-
-    @property
-    def interrupts(self) -> list[InterruptPayload]:
-        return self._mux.interrupts
-
-    # -- Cancellation -------------------------------------------------------
-
-    def abort(self, reason: str | None = None) -> None:
-        """Signal cancellation of the run."""
-        self._abort_event.set()
-
-    @property
-    def signal(self) -> asyncio.Event:
-        """The underlying cancellation event."""
-        return self._abort_event
-
-    # -- Extensions ---------------------------------------------------------
-
-    @property
-    def extensions(self) -> dict[str, Any]:
-        """All transformer projections."""
-        result: dict[str, Any] = {}
-        for t in self._transformers:
-            name = getattr(t, "name", None)
-            value = getattr(t, "value", None)
-            if name is not None and value is not None:
-                result[name] = value
-        return result
-
-
-# ---------------------------------------------------------------------------
-# AsyncSubgraphRunStream
-# ---------------------------------------------------------------------------
-
-
-class AsyncSubgraphRunStream(AsyncGraphRunStream):
-    """An :class:`AsyncGraphRunStream` for a child subgraph.
-
-    Adds ``.name`` and ``.index`` parsed from the last namespace segment
-    (e.g. ``"researcher:2"`` → ``name="researcher"``, ``index=2``).
-    """
-
-    @property
-    def name(self) -> str:
-        if self._ns:
-            segment = self._ns[-1]
-            return segment.split(":")[0] if ":" in segment else segment
-        return ""
-
-    @property
-    def index(self) -> int:
-        if self._ns:
-            segment = self._ns[-1]
-            if ":" in segment:
-                try:
-                    return int(segment.split(":")[-1])
-                except ValueError:
-                    pass
-        return 0
-
-
-# ---------------------------------------------------------------------------
-# Async factory
-# ---------------------------------------------------------------------------
-
-
-async def create_async_graph_run_stream(
-    source: AsyncIterator[tuple[tuple[str, ...], str, Any]],
-    *,
-    transformers: list[StreamTransformer] | None = None,
-    abort_event: asyncio.Event | None = None,
-    output_mapper: Callable[[Any], Any] | None = None,
-) -> AsyncGraphRunStream:
-    """Create an :class:`AsyncGraphRunStream` from a raw async stream source.
-
-    1. Creates a :class:`StreamMux`
-    2. Registers built-in ``ValuesTransformer`` and ``MessagesTransformer``
-    3. Registers user-supplied transformers
-    4. Creates the root ``AsyncGraphRunStream``
-    5. Starts a background pump task that reads from *source*,
-       converts each chunk to a ``ProtocolEvent``, and pushes it
-       through the mux
-    6. Returns the ``AsyncGraphRunStream``
-    """
-    abort = abort_event or asyncio.Event()
-
-    # Built-in transformers first, then user-supplied
-    all_transformers: list[StreamTransformer] = [
-        ValuesTransformer(),
-        MessagesTransformer(stream_cls=AsyncChatModelStream),
-    ]
-    all_transformers.extend(transformers or [])
-
-    # Initialize transformers, collecting projections to wire after mux creation
-    projections: list[Any] = []
-    for t in all_transformers:
-        projection = t.init()
-        if projection is not None:
-            projections.append(projection)
-
-    mux = AsyncStreamMux(transformers=all_transformers)
-
-    # Wire any StreamChannel instances found in transformer projections
-    for projection in projections:
-        mux.wire_channels(projection)
-
-    # Create the root stream
-    run_stream = AsyncGraphRunStream(
-        mux=mux,
-        transformers=all_transformers,
-        abort_event=abort,
-        output_mapper=output_mapper,
-    )
-
-    # Start the pump task
-    async def pump() -> None:
-        try:
-            async for ns, mode, payload in source:
-                if abort.is_set():
-                    break
-                # Extract node name embedded by StreamProtocolMessagesHandler.
-                node: str | None = None
-                if (
-                    mode == "messages"
-                    and isinstance(payload, dict)
-                    and "__node__" in payload
-                ):
-                    payload = dict(payload)
-                    node = payload.pop("__node__")
-                event = convert_to_protocol_event(ns, mode, payload, node=node)
-                if event is not None:
-                    mux.push(event)
-            mux.close()
-        except Exception as exc:
-            mux.fail(exc)
-
-    asyncio.get_running_loop().create_task(pump())
-
-    return run_stream
-
-
-# ---------------------------------------------------------------------------
-# GraphRunStream — returned by StreamingHandler.stream()
-# ---------------------------------------------------------------------------
-
-
-class _PumpDrivenLog:
-    """Wraps a list so that iteration drives the sync pump.
-
-    Used by all :class:`GraphRunStream` projections (``__iter__``,
-    ``.values``, ``.messages``, ``.extensions``) so that iterating
-    any projection lazily consumes the source.
-    """
-
-    __slots__ = ("_log", "_pump_one")
-
-    def __init__(self, log: list, pump_one: Callable[[], bool]) -> None:
-        self._log = log
-        self._pump_one = pump_one
-
-    def __iter__(self) -> Iterator[Any]:
-        cursor = 0
-        while True:
-            if cursor < len(self._log):
-                yield self._log[cursor]
-                cursor += 1
-            elif not self._pump_one():
-                return
-
-    def __len__(self) -> int:
-        return len(self._log)
-
-    def __getitem__(self, index: int) -> Any:
-        return self._log[index]
-
-
-class GraphRunStream:
-    """Synchronous run stream returned by ``StreamingHandler.stream()``.
-
-    All projections are blocking / sync-iterable.  Internally uses
-    the same ``StreamMux`` and transformer pipeline, but without an
-    async event loop.
-
-    The source iterator is consumed lazily: each projection pulls
-    events from the source on demand rather than eagerly buffering
-    everything upfront.  This means callers see events as soon as
-    they are produced by the underlying ``stream()`` call.
-    """
-
-    def __init__(
-        self,
-        *,
-        mux: StreamMux,
-        source: Iterator[tuple[tuple[str, ...], str, Any]],
-        namespace: list[str] | None = None,
-        transformers: list[StreamTransformer],
-        output_mapper: Callable[[Any], Any] | None = None,
-    ) -> None:
-        self._mux = mux
-        self._source = source
-        self._source_exhausted = False
-        self._ns = namespace or []
-        self._transformers = transformers
-        self._output_mapper = output_mapper
-
-    # -- Transformer lookup -------------------------------------------------
-
-    def _find_transformer(self, name: str) -> StreamTransformer | None:
-        for t in self._transformers:
-            if getattr(t, "name", None) == name:
-                return t
-        return None
-
-    # -- Lazy pump ----------------------------------------------------------
-
-    def _pump_one(self) -> bool:
-        """Pull one item from the source, convert it, and push through the mux.
-
-        Returns ``True`` if an item was consumed, ``False`` if the source
-        is exhausted (or was already exhausted).
-        """
-        if self._source_exhausted:
-            return False
-        try:
-            ns, mode, payload = next(self._source)
-        except StopIteration:
-            self._source_exhausted = True
-            self._mux.close()
-            return False
-        except Exception as exc:
-            self._source_exhausted = True
-            self._mux.fail(exc)
-            return False
-
-        node: str | None = None
-        if mode == "messages" and isinstance(payload, dict) and "__node__" in payload:
-            payload = dict(payload)
-            node = payload.pop("__node__")
-        event = convert_to_protocol_event(ns, mode, payload, node=node)
-        if event is not None:
-            self._mux.push(event)
-        return True
-
-    def _pump_all(self) -> None:
-        """Drain the source iterator completely."""
-        while self._pump_one():
-            pass
-
-    # -- Helpers ------------------------------------------------------------
-
-    def _map(self, value: Any) -> Any:
-        if value is not None and self._output_mapper is not None:
-            return self._output_mapper(value)
-        return value
-
-    # -- Raw event iteration (sync) -----------------------------------------
-
-    def __iter__(self) -> Iterator[ProtocolEvent]:
-        for event in _PumpDrivenLog(self._mux.event_log, self._pump_one):
-            ns = event["params"].get("namespace", [])
-            if not self._ns or ns[: len(self._ns)] == self._ns:
-                yield event
-
-    # -- Named projections (sync) -------------------------------------------
-
-    @property
-    def output(self) -> Any:
-        """The final output state (blocking). Drains the source."""
-        self._pump_all()
-        return self._map(self._mux.get_latest_values(self._ns))
-
-    @property
-    def values(self) -> Iterator[Any]:
-        """Sync iterable of intermediate state snapshots."""
-        t = self._find_transformer("values")
-        if t is None:
-            return
-        for item in _PumpDrivenLog(t.value, self._pump_one):
-            if item.get("namespace", []) == self._ns:
-                yield self._map(item["data"])
-
-    @property
-    def messages(self) -> Iterator[ChatModelStream]:
-        """Sync iterable of :class:`ChatModelStream` instances.
-
-        Each yielded ``ChatModelStream`` is fully populated (``done=True``)
-        so that sync consumers can read ``.text``, ``.reasoning``, and
-        ``.usage`` immediately.
-        """
-        t = self._find_transformer("messages")
-        if t is None:
-            return
-        for msg in _PumpDrivenLog(t.value, self._pump_one):
-            # Pump until this message is complete so sync consumers
-            # get a fully populated ChatModelStream.
-            while not msg.done:
-                if not self._pump_one():
-                    break
-            yield msg
-
-    # -- State --------------------------------------------------------------
-
-    @property
-    def interrupted(self) -> bool:
-        return self._mux.interrupted
-
-    @property
-    def interrupts(self) -> list[InterruptPayload]:
-        return self._mux.interrupts
-
-    # -- Extensions ---------------------------------------------------------
-
-    @property
-    def extensions(self) -> dict[str, Any]:
-        """All transformer projections as pump-driven iterables."""
-        result: dict[str, Any] = {}
-        for t in self._transformers:
-            name = getattr(t, "name", None)
-            value = getattr(t, "value", None)
-            if name is not None and value is not None:
-                if isinstance(value, list):
-                    result[name] = _PumpDrivenLog(value, self._pump_one)
-                else:
-                    result[name] = value
-        return result
-
-
-def create_graph_run_stream(
-    source: Iterator[tuple[tuple[str, ...], str, Any]],
-    *,
-    transformers: list[StreamTransformer] | None = None,
-    output_mapper: Callable[[Any], Any] | None = None,
-) -> GraphRunStream:
-    """Create a :class:`GraphRunStream` from a sync stream source.
-
-    The source iterator is stored on the returned stream and consumed
-    lazily as projections are iterated.
-
-    Built-in transformers (values, messages) are always registered first
-    so that user-supplied transformers see events after built-in
-    processing.
-    """
-    # Built-in transformers first, then user-supplied
-    all_transformers: list[StreamTransformer] = [
-        ValuesTransformer(),
-        MessagesTransformer(),
-    ]
-    all_transformers.extend(transformers or [])
-
-    projections: list[Any] = []
-    for t in all_transformers:
-        projection = t.init()
-        if projection is not None:
-            projections.append(projection)
-
-    mux = StreamMux(transformers=all_transformers)
-
-    for projection in projections:
-        mux.wire_channels(projection)
-
-    return GraphRunStream(
-        mux=mux,
-        source=source,
-        transformers=all_transformers,
-        output_mapper=output_mapper,
-    )
-
-
-__all__ = [
-    "AsyncGraphRunStream",
-    "AsyncSubgraphRunStream",
-    "GraphRunStream",
-    "create_async_graph_run_stream",
-    "create_graph_run_stream",
-]
@@ -1,49 +0,0 @@
-"""StreamChannel — typed push-based channel for StreamTransformer projections.
-
-A ``StreamChannel`` wraps a list and declares a protocol channel name.
-When the :class:`StreamMux` detects a ``StreamChannel`` in a transformer's
-``init()`` return, it wires every ``push()`` call to inject a
-:class:`ProtocolEvent` into the main event stream using the channel's
-name as the ``method``.
-"""
-
-from __future__ import annotations
-
-from collections.abc import Callable
-from typing import Any, Generic, TypeVar
-
-T = TypeVar("T")
-
-
-class StreamChannel(Generic[T]):
-    """A typed push-based channel that integrates with the mux.
-
-    Transformer authors create a ``StreamChannel`` in ``init()`` and
-    call ``push()`` inside ``process()`` to emit domain objects.  The
-    mux auto-wires pushes to protocol events.
-    """
-
-    __slots__ = ("channel_name", "_items", "_on_push")
-
-    def __init__(self, name: str) -> None:
-        self.channel_name = name
-        self._items: list[T] = []
-        self._on_push: Callable[[Any], None] | None = None
-
-    def push(self, item: T) -> None:
-        """Push an item to the channel."""
-        self._items.append(item)
-        if self._on_push is not None:
-            self._on_push(item)
-
-    def _wire(self, fn: Callable[[Any], None]) -> None:
-        """Wire a callback invoked on every ``push()``.  Called by the mux."""
-        self._on_push = fn
-
-
-def is_stream_channel(value: object) -> bool:
-    """Check if *value* is a :class:`StreamChannel` instance."""
-    return isinstance(value, StreamChannel)
-
-
-__all__ = ["StreamChannel", "is_stream_channel"]
@@ -1,168 +0,0 @@
-"""Experimental streaming wrapper for CompiledGraph.
-
-``StreamingHandler`` wraps a compiled graph and exposes the new streaming
-API without adding methods to the ``CompiledGraph`` class itself.
-
-Usage::
-
-    from langgraph.stream import StreamingHandler
-
-    s = StreamingHandler(graph)
-
-    # async
-    run = await s.astream(input)
-    async for msg in run.messages:
-        ...
-
-    # sync
-    run = s.stream(input)
-    for event in run:
-        ...
-"""
-
-from __future__ import annotations
-
-from collections.abc import AsyncIterator, Iterator, Sequence
-from typing import TYPE_CHECKING, Any, cast
-
-from langchain_core.runnables import RunnableConfig
-
-from langgraph._internal._config import patch_configurable
-from langgraph.stream._convert import STREAM_V2_MODES
-from langgraph.stream._types import StreamTransformer
-from langgraph.stream.run_stream import (
-    AsyncGraphRunStream,
-    GraphRunStream,
-    create_async_graph_run_stream,
-    create_graph_run_stream,
-)
-from langgraph.types import All
-
-if TYPE_CHECKING:
-    from langgraph.pregel import Pregel
-
-#: Config key that activates the protocol messages handler.
-#: Duplicated here to avoid a circular import with ``pregel._messages_v2``.
-PROTOCOL_MESSAGES_STREAM_KEY = "__protocol_messages_stream"
-
-
-class StreamingHandler:
-    """Experimental streaming wrapper around a compiled graph.
-
-    Provides ``.stream()`` and ``.astream()`` returning
-    :class:`GraphRunStream` / :class:`AsyncGraphRunStream` with
-    ergonomic projections (``run.values``, ``run.messages``,
-    ``run.subgraphs``, ``run.output``).
-
-    Args:
-        graph: A compiled LangGraph (``Pregel`` instance).
-    """
-
-    def __init__(self, graph: Pregel) -> None:
-        self._graph = graph
-
-    async def astream(
-        self,
-        input: Any,
-        config: RunnableConfig | None = None,
-        *,
-        context: Any | None = None,
-        interrupt_before: All | Sequence[str] | None = None,
-        interrupt_after: All | Sequence[str] | None = None,
-        debug: bool | None = None,
-        transformers: list[StreamTransformer] | None = None,
-    ) -> AsyncGraphRunStream:
-        """Stream graph execution, returning an
-        :class:`~langgraph.stream.run_stream.AsyncGraphRunStream`.
-
-        The returned stream provides ergonomic projections:
-
-        - ``await run.output`` -- final state
-        - ``async for v in run.values`` -- intermediate state snapshots
-        - ``async for msg in run.messages`` -- per-message
-          :class:`~langgraph.stream.chat_model_stream.AsyncChatModelStream`
-          objects
-        - ``async for sub in run.subgraphs`` -- child
-          :class:`~langgraph.stream.run_stream.AsyncSubgraphRunStream`
-          instances
-        - ``async for event in run`` -- raw
-          :class:`~langgraph.stream._types.ProtocolEvent` objects
-
-        Args:
-            input: The input to the graph.
-            config: The configuration to use for the run.
-            context: The static context to use for the run.
-            interrupt_before: Nodes to interrupt before.
-            interrupt_after: Nodes to interrupt after.
-            debug: Whether to emit debug events.
-            transformers: Optional user-supplied
-                :class:`~langgraph.stream._types.StreamTransformer` instances
-                for custom projections (available on ``run.extensions``).
-
-        Returns:
-            An :class:`~langgraph.stream.run_stream.AsyncGraphRunStream`.
-        """
-        merged_config = patch_configurable(config, {PROTOCOL_MESSAGES_STREAM_KEY: True})
-
-        source = cast(
-            AsyncIterator[tuple[tuple[str, ...], str, Any]],
-            self._graph.astream(
-                input,
-                merged_config,
-                context=context,
-                stream_mode=STREAM_V2_MODES,
-                subgraphs=True,
-                interrupt_before=interrupt_before,
-                interrupt_after=interrupt_after,
-                debug=debug,
-                version="v1",
-            ),
-        )
-
-        return await create_async_graph_run_stream(
-            source,
-            transformers=transformers,
-            output_mapper=self._graph._output_mapper,
-        )
-
-    def stream(
-        self,
-        input: Any,
-        config: RunnableConfig | None = None,
-        *,
-        context: Any | None = None,
-        interrupt_before: All | Sequence[str] | None = None,
-        interrupt_after: All | Sequence[str] | None = None,
-        debug: bool | None = None,
-        transformers: list[StreamTransformer] | None = None,
-    ) -> GraphRunStream:
-        """Synchronous variant of :meth:`astream`.
-
-        Returns a :class:`~langgraph.stream.run_stream.GraphRunStream`
-        immediately.  The underlying source is consumed lazily as
-        projections are iterated.
-
-        See :meth:`astream` for full documentation.
-        """
-        merged_config = patch_configurable(config, {PROTOCOL_MESSAGES_STREAM_KEY: True})
-
-        source = cast(
-            Iterator[tuple[tuple[str, ...], str, Any]],
-            self._graph.stream(
-                input,
-                merged_config,
-                context=context,
-                stream_mode=STREAM_V2_MODES,
-                subgraphs=True,
-                interrupt_before=interrupt_before,
-                interrupt_after=interrupt_after,
-                debug=debug,
-                version="v1",
-            ),
-        )
-
-        return create_graph_run_stream(
-            source,
-            transformers=transformers,
-            output_mapper=self._graph._output_mapper,
-        )
@@ -1,172 +0,0 @@
-"""Built-in stream transformers for StreamingHandler.
-
-``ValuesTransformer`` extracts ``values`` events and maintains the latest
-state per namespace.  ``MessagesTransformer`` groups ``messages`` events
-into :class:`ChatModelStream` instances.
-"""
-
-from __future__ import annotations
-
-from typing import Any
-
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.chat_model_stream import ChatModelStream
-
-# Type alias for the stream class constructor signature
-_StreamCls = type[ChatModelStream]
-
-
-class ValuesTransformer(StreamTransformer):
-    """Extracts ``values`` events and populates a values log.
-
-    Maintains the latest state per namespace and provides a separate
-    log that :class:`AsyncGraphRunStream` / :class:`GraphRunStream` uses for ``.values``
-    iteration.
-    """
-
-    name = "values"
-
-    def __init__(self) -> None:
-        self._values_log: list[dict[str, Any]] = []
-        self._latest: dict[str, Any] = {}
-
-    @property
-    def value(self) -> list[dict[str, Any]]:
-        return self._values_log
-
-    @property
-    def values_log(self) -> list[dict[str, Any]]:
-        return self._values_log
-
-    def get_latest(self, ns_key: str = "") -> Any:
-        return self._latest.get(ns_key)
-
-    def init(self) -> Any:
-        return None
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "values":
-            return True
-
-        ns = event["params"].get("namespace", [])
-        data = event["params"]["data"]
-        ns_key = "|".join(ns) if ns else ""
-        self._latest[ns_key] = data
-
-        # Append to the values log for iteration
-        self._values_log.append({"namespace": ns, "data": data})
-        return True
-
-    def finalize(self) -> None:
-        pass
-
-    def fail(self, err: BaseException) -> None:
-        pass
-
-
-class MessagesTransformer(StreamTransformer):
-    """Groups ``messages`` events into :class:`ChatModelStream` instances.
-
-    One ``ChatModelStream`` is created per ``message-start`` event.
-    Content-block events are routed to the active stream until
-    ``message-finish`` or ``message-error`` closes it.
-    """
-
-    name = "messages"
-
-    def __init__(
-        self,
-        *,
-        namespace: list[str] | None = None,
-        node_filter: str | None = None,
-        stream_cls: _StreamCls | None = None,
-    ) -> None:
-        self._namespace = namespace
-        self._node_filter = node_filter
-        self._stream_cls: _StreamCls = stream_cls or ChatModelStream
-
-        # Message log for .messages iteration
-        self._messages_log: list[ChatModelStream] = []
-
-        # Current active stream per namespace key
-        self._active: dict[str, ChatModelStream] = {}
-
-    @property
-    def value(self) -> list[ChatModelStream]:
-        return self._messages_log
-
-    @property
-    def messages_log(self) -> list[ChatModelStream]:
-        return self._messages_log
-
-    def init(self) -> Any:
-        return None
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "messages":
-            return True
-
-        ns = event["params"].get("namespace", [])
-        node = event["params"].get("node")
-        data = event["params"]["data"]
-
-        # Apply namespace filter
-        if self._namespace is not None:
-            if ns[: len(self._namespace)] != self._namespace:
-                return True
-
-        # Apply node filter
-        if self._node_filter is not None and node != self._node_filter:
-            return True
-
-        ns_key = "|".join(ns) if ns else ""
-        event_type = data.get("event") if isinstance(data, dict) else None
-
-        if event_type == "message-start":
-            stream = self._stream_cls(
-                namespace=ns,
-                node=node,
-                message_id=data.get("message_id"),
-            )
-            self._active[ns_key] = stream
-            self._messages_log.append(stream)
-
-        elif event_type in ("content-block-delta", "content-block-start"):
-            active = self._active.get(ns_key)
-            if active is not None and event_type == "content-block-delta":
-                active._push_content_block_delta(data)
-
-        elif event_type == "content-block-finish":
-            active = self._active.get(ns_key)
-            if active is not None:
-                active._push_content_block_finish(data)
-
-        elif event_type == "message-finish":
-            active = self._active.pop(ns_key, None)
-            if active is not None:
-                active._finish(data)
-
-        elif event_type == "error":
-            active = self._active.pop(ns_key, None)
-            if active is not None:
-                msg = data.get("message", "Unknown error")
-                active._fail(RuntimeError(msg))
-
-        return True
-
-    def finalize(self) -> None:
-        # Finish any remaining active streams
-        for stream in self._active.values():
-            stream._finish({"reason": "stop"})
-        self._active.clear()
-
-    def fail(self, err: BaseException) -> None:
-        for stream in self._active.values():
-            stream._fail(err)
-        self._active.clear()
-
-
-__all__ = [
-    "MessagesTransformer",
-    "ValuesTransformer",
-]
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph"
-version = "1.1.6"
+version = "1.1.10"
 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",
+    "langchain-core>=1.3.0,<2",
    "langgraph-checkpoint>=2.1.0,<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",
 ]
@@ -0,0 +1,344 @@
+from __future__ import annotations
+
+import sys
+from typing import Any
+
+import pytest
+from langchain_core.callbacks.base import BaseCallbackHandler
+from langchain_core.callbacks.manager import CallbackManager
+from langgraph.checkpoint.memory import InMemorySaver
+from typing_extensions import TypedDict
+
+from langgraph.callbacks import (
+    GraphCallbackHandler,
+    GraphInterruptEvent,
+    GraphResumeEvent,
+)
+from langgraph.graph import START, StateGraph
+from langgraph.types import Command, Interrupt, interrupt
+
+NEEDS_CONTEXTVARS = pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="Python 3.11+ is required for async contextvars support",
+)
+
+
+class _GraphEventHandler(GraphCallbackHandler):
+    def __init__(self) -> None:
+        self.interrupt_events: list[GraphInterruptEvent] = []
+        self.resume_events: list[GraphResumeEvent] = []
+
+    def on_interrupt(self, event: GraphInterruptEvent) -> Any:
+        self.interrupt_events.append(event)
+
+    def on_resume(self, event: GraphResumeEvent) -> Any:
+        self.resume_events.append(event)
+
+
+class _LangChainCustomEventHandler(BaseCallbackHandler):
+    run_inline = True
+
+    def __init__(self) -> None:
+        self.events: list[str] = []
+
+    def on_custom_event(self, name: str, data: Any, **kwargs: Any) -> Any:
+        self.events.append(name)
+
+
+class _RaisingGraphEventHandler(GraphCallbackHandler):
+    def __init__(
+        self,
+        *,
+        raise_on_interrupt: bool = False,
+        raise_on_resume: bool = False,
+        raise_error: bool = False,
+    ) -> None:
+        self.raise_on_interrupt = raise_on_interrupt
+        self.raise_on_resume = raise_on_resume
+        self.raise_error = raise_error
+
+    def on_interrupt(self, event: GraphInterruptEvent) -> Any:
+        if self.raise_on_interrupt:
+            raise ValueError("boom-interrupt")
+
+    def on_resume(self, event: GraphResumeEvent) -> Any:
+        if self.raise_on_resume:
+            raise ValueError("boom-resume")
+
+
+class _AsyncRaisingGraphEventHandler(GraphCallbackHandler):
+    def __init__(
+        self,
+        *,
+        raise_on_interrupt: bool = False,
+        raise_on_resume: bool = False,
+        raise_error: bool = False,
+    ) -> None:
+        self.raise_on_interrupt = raise_on_interrupt
+        self.raise_on_resume = raise_on_resume
+        self.raise_error = raise_error
+
+    async def on_interrupt(self, event: GraphInterruptEvent) -> Any:
+        if self.raise_on_interrupt:
+            raise ValueError("boom-interrupt")
+
+    async def on_resume(self, event: GraphResumeEvent) -> Any:
+        if self.raise_on_resume:
+            raise ValueError("boom-resume")
+
+
+class _State(TypedDict):
+    answer: str | None
+
+
+def _build_interrupt_graph() -> Any:
+    def ask(state: _State) -> _State:
+        answer = interrupt("Provide value")
+        return {"answer": answer}
+
+    builder = StateGraph(_State)
+    builder.add_node("ask", ask)
+    builder.add_edge(START, "ask")
+    return builder.compile(checkpointer=InMemorySaver())
+
+
+def test_graph_callbacks_interrupt_and_resume_sync() -> None:
+    graph = _build_interrupt_graph()
+    handler = _GraphEventHandler()
+    langchain_handler = _LangChainCustomEventHandler()
+    config = {
+        "configurable": {"thread_id": "graph-callback-sync"},
+        "callbacks": [langchain_handler, handler],
+    }
+
+    first = graph.invoke({"answer": None}, config)
+    assert "__interrupt__" in first
+
+    assert len(handler.interrupt_events) == 1
+    assert handler.interrupt_events[0].interrupts
+    assert isinstance(handler.interrupt_events[0].interrupts[0], Interrupt)
+    assert handler.interrupt_events[0].checkpoint_ns == ()
+    assert langchain_handler.events == []
+
+    handler.resume_events.clear()
+    resumed = graph.invoke(Command(resume="done"), config)
+    assert resumed == {"answer": "done"}
+
+    assert len(handler.resume_events) == 1
+    assert handler.resume_events[0].checkpoint_ns == ()
+    assert langchain_handler.events == []
+
+
+@pytest.mark.anyio
+@NEEDS_CONTEXTVARS
+async def test_graph_callbacks_interrupt_and_resume_async() -> None:
+    graph = _build_interrupt_graph()
+    handler = _GraphEventHandler()
+    langchain_handler = _LangChainCustomEventHandler()
+    config = {
+        "configurable": {"thread_id": "graph-callback-async"},
+        "callbacks": [langchain_handler, handler],
+    }
+
+    first = await graph.ainvoke({"answer": None}, config)
+    assert "__interrupt__" in first
+
+    assert len(handler.interrupt_events) == 1
+    assert handler.interrupt_events[0].interrupts
+    assert isinstance(handler.interrupt_events[0].interrupts[0], Interrupt)
+    assert handler.interrupt_events[0].checkpoint_ns == ()
+    assert langchain_handler.events == []
+
+    handler.resume_events.clear()
+    resumed = await graph.ainvoke(Command(resume="done"), config)
+    assert resumed == {"answer": "done"}
+
+    assert len(handler.resume_events) == 1
+    assert handler.resume_events[0].checkpoint_ns == ()
+    assert langchain_handler.events == []
+
+
+def test_graph_callbacks_continue_when_interrupt_handler_raises_sync() -> None:
+    graph = _build_interrupt_graph()
+    raising_handler = _RaisingGraphEventHandler(raise_on_interrupt=True)
+    recording_handler = _GraphEventHandler()
+
+    first = graph.invoke(
+        {"answer": None},
+        {
+            "configurable": {"thread_id": "graph-callback-sync-raises"},
+            "callbacks": [raising_handler, recording_handler],
+        },
+    )
+
+    assert "__interrupt__" in first
+    assert len(recording_handler.interrupt_events) == 1
+
+
+def test_graph_callbacks_continue_when_resume_handler_raises_sync() -> None:
+    graph = _build_interrupt_graph()
+    raising_handler = _RaisingGraphEventHandler(raise_on_resume=True)
+    recording_handler = _GraphEventHandler()
+    config = {
+        "configurable": {"thread_id": "graph-callback-sync-raises-resume"},
+        "callbacks": [raising_handler, recording_handler],
+    }
+
+    first = graph.invoke({"answer": None}, config)
+    assert "__interrupt__" in first
+
+    resumed = graph.invoke(Command(resume="done"), config)
+    assert resumed == {"answer": "done"}
+    assert len(recording_handler.resume_events) == 1
+
+
+def test_graph_callbacks_raise_error_propagates_sync() -> None:
+    graph = _build_interrupt_graph()
+    raising_handler = _RaisingGraphEventHandler(
+        raise_on_interrupt=True,
+        raise_error=True,
+    )
+
+    with pytest.raises(ValueError, match="boom-interrupt"):
+        graph.invoke(
+            {"answer": None},
+            {
+                "configurable": {"thread_id": "graph-callback-sync-raise-error"},
+                "callbacks": [raising_handler],
+            },
+        )
+
+
+@pytest.mark.anyio
+@NEEDS_CONTEXTVARS
+async def test_graph_callbacks_continue_when_handler_raises_async() -> None:
+    graph = _build_interrupt_graph()
+    raising_interrupt_handler = _AsyncRaisingGraphEventHandler(raise_on_interrupt=True)
+    recording_handler = _GraphEventHandler()
+    config = {
+        "configurable": {"thread_id": "graph-callback-async-raises-interrupt"},
+        "callbacks": [raising_interrupt_handler, recording_handler],
+    }
+
+    first = await graph.ainvoke({"answer": None}, config)
+    assert "__interrupt__" in first
+    assert len(recording_handler.interrupt_events) == 1
+
+    graph = _build_interrupt_graph()
+    raising_resume_handler = _AsyncRaisingGraphEventHandler(raise_on_resume=True)
+    recording_handler = _GraphEventHandler()
+    config = {
+        "configurable": {"thread_id": "graph-callback-async-raises-resume"},
+        "callbacks": [raising_resume_handler, recording_handler],
+    }
+
+    first = await graph.ainvoke({"answer": None}, config)
+    assert "__interrupt__" in first
+    resumed = await graph.ainvoke(Command(resume="done"), config)
+    assert resumed == {"answer": "done"}
+    assert len(recording_handler.resume_events) == 1
+
+
+@pytest.mark.anyio
+@NEEDS_CONTEXTVARS
+async def test_graph_callbacks_raise_error_propagates_async() -> None:
+    graph = _build_interrupt_graph()
+    raising_handler = _AsyncRaisingGraphEventHandler(
+        raise_on_interrupt=True,
+        raise_error=True,
+    )
+
+    with pytest.raises(ValueError, match="boom-interrupt"):
+        await graph.ainvoke(
+            {"answer": None},
+            {
+                "configurable": {"thread_id": "graph-callback-async-raise-error"},
+                "callbacks": [raising_handler],
+            },
+        )
+
+
+def test_graph_callbacks_accept_base_callback_manager() -> None:
+    graph = _build_interrupt_graph()
+    graph_handler = _GraphEventHandler()
+    custom_handler = _LangChainCustomEventHandler()
+    manager = CallbackManager.configure(inheritable_callbacks=[custom_handler])
+    manager.add_handler(graph_handler)
+
+    first = graph.invoke(
+        {"answer": None},
+        {
+            "configurable": {"thread_id": "graph-callback-base-manager"},
+            "callbacks": manager,
+        },
+    )
+
+    assert "__interrupt__" in first
+    assert len(graph_handler.interrupt_events) == 1
+
+
+def test_non_graph_handler_via_add_handler_does_not_crash() -> None:
+    """Non-GraphCallbackHandler added via add_handler should not raise.
+
+    Libraries like opentelemetry-instrumentation-langchain monkey-patch
+    BaseCallbackManager.__init__ and inject handlers via add_handler().
+    These handlers inherit from BaseCallbackHandler, not
+    GraphCallbackHandler. They must be silently accepted — graph lifecycle
+    events will simply not be dispatched to them.
+    """
+    from langgraph.callbacks import _GraphCallbackManager
+
+    manager = _GraphCallbackManager()
+    plain_handler = _LangChainCustomEventHandler()
+
+    manager.add_handler(plain_handler, inherit=True)
+    assert plain_handler in manager.handlers
+
+
+def test_non_graph_handler_does_not_receive_lifecycle_events() -> None:
+    """Non-GraphCallbackHandler added alongside a GraphCallbackHandler
+    should not interfere with lifecycle event dispatch."""
+    graph = _build_interrupt_graph()
+    graph_handler = _GraphEventHandler()
+    plain_handler = _LangChainCustomEventHandler()
+
+    config = {
+        "configurable": {"thread_id": "graph-callback-mixed-handlers"},
+        "callbacks": [plain_handler, graph_handler],
+    }
+
+    first = graph.invoke({"answer": None}, config)
+    assert "__interrupt__" in first
+
+    assert len(graph_handler.interrupt_events) == 1
+    assert plain_handler.events == []
+
+    resumed = graph.invoke(Command(resume="done"), config)
+    assert resumed == {"answer": "done"}
+    assert len(graph_handler.resume_events) == 1
+    assert plain_handler.events == []
+
+
+@pytest.mark.anyio
+@NEEDS_CONTEXTVARS
+async def test_non_graph_handler_does_not_receive_lifecycle_events_async() -> None:
+    """Async variant: non-GraphCallbackHandler should not interfere."""
+    graph = _build_interrupt_graph()
+    graph_handler = _GraphEventHandler()
+    plain_handler = _LangChainCustomEventHandler()
+
+    config = {
+        "configurable": {"thread_id": "graph-callback-mixed-handlers-async"},
+        "callbacks": [plain_handler, graph_handler],
+    }
+
+    first = await graph.ainvoke({"answer": None}, config)
+    assert "__interrupt__" in first
+
+    assert len(graph_handler.interrupt_events) == 1
+    assert plain_handler.events == []
+
+    resumed = await graph.ainvoke(Command(resume="done"), config)
+    assert resumed == {"answer": "done"}
+    assert len(graph_handler.resume_events) == 1
+    assert plain_handler.events == []
@@ -1,623 +0,0 @@
-import asyncio
-from typing import Annotated, Any
-
-import pytest
-from langchain_core.messages import AIMessage, HumanMessage
-from pydantic import BaseModel
-from typing_extensions import TypedDict
-
-from langgraph.config import get_stream_writer
-from langgraph.graph import END, START, MessagesState, StateGraph
-from langgraph.stream import AsyncChatModelStream, StreamingHandler
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from tests.fake_chat import FakeChatModel
-
-
-class State(TypedDict):
-    value: str
-    items: Annotated[list[str], lambda a, b: a + b]
-
-
-def make_simple_graph():
-    def node_a(state):
-        return {"value": state["value"] + "_a", "items": ["a"]}
-
-    def node_b(state):
-        return {"value": state["value"] + "_b", "items": ["b"]}
-
-    graph = StateGraph(State)
-    graph.add_node("node_a", node_a)
-    graph.add_node("node_b", node_b)
-    graph.add_edge(START, "node_a")
-    graph.add_edge("node_a", "node_b")
-    graph.add_edge("node_b", END)
-    return graph.compile()
-
-
-@pytest.mark.anyio
-async def test_output():
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-    output = await run.output
-    assert output == {"value": "x_a_b", "items": ["a", "b"]}
-
-
-@pytest.mark.anyio
-async def test_values_iteration():
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-
-    snapshots = []
-    async for v in run.values:
-        snapshots.append(v)
-
-    assert len(snapshots) == 3
-    assert snapshots[0]["value"] == "x"
-    assert snapshots[1]["value"] == "x_a"
-    assert snapshots[2]["value"] == "x_a_b"
-
-
-@pytest.mark.anyio
-async def test_updates_in_raw_events():
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-
-    updates = []
-    async for event in run:
-        if event["method"] == "updates":
-            updates.append(event["params"]["data"])
-
-    assert len(updates) == 2
-    assert "node_a" in updates[0]
-    assert "node_b" in updates[1]
-
-
-@pytest.mark.anyio
-async def test_messages_with_chat_model():
-    model = FakeChatModel(messages=[AIMessage(content="Hello world")])
-
-    def agent(state):
-        return {"messages": [model.invoke(state["messages"])]}
-
-    graph = StateGraph(MessagesState)
-    graph.add_node("agent", agent)
-    graph.add_edge(START, "agent")
-    graph.add_edge("agent", END)
-    compiled = graph.compile()
-
-    run = await StreamingHandler(compiled).astream(
-        {"messages": [HumanMessage(content="hi")]}
-    )
-    await asyncio.sleep(0.1)
-
-    messages_seen = []
-    async for msg in run.messages:
-        messages_seen.append(msg)
-
-    assert len(messages_seen) >= 1
-    msg = messages_seen[0]
-    assert isinstance(msg, AsyncChatModelStream)
-    text = await msg.text
-    assert text == "Hello world"
-
-
-@pytest.mark.anyio
-async def test_custom_events():
-    def node(state):
-        writer = get_stream_writer()
-        writer("hello")
-        writer(42)
-        return {"value": state["value"] + "_a", "items": ["a"]}
-
-    graph = StateGraph(State)
-    graph.add_node("node_a", node)
-    graph.add_edge(START, "node_a")
-    graph.add_edge("node_a", END)
-    compiled = graph.compile()
-
-    run = await StreamingHandler(compiled).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-
-    custom_payloads = []
-    async for event in run:
-        if event["method"] == "custom":
-            custom_payloads.append(event["params"]["data"])
-
-    assert "hello" in custom_payloads
-    assert 42 in custom_payloads
-
-
-@pytest.mark.anyio
-async def test_multiple_modes_present():
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-
-    methods = set()
-    async for event in run:
-        methods.add(event["method"])
-
-    assert {"values", "updates", "tasks", "debug"} <= methods
-
-
-@pytest.mark.anyio
-async def test_interrupted_false():
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-    async for _ in run:
-        pass
-    assert run.interrupted is False
-
-
-@pytest.mark.anyio
-async def test_regression_v1_stream_unchanged():
-    graph = make_simple_graph()
-    chunks = []
-    async for chunk in graph.astream(
-        {"value": "x", "items": []}, stream_mode="values", version="v1"
-    ):
-        chunks.append(chunk)
-    for chunk in chunks:
-        assert isinstance(chunk, dict)
-
-
-@pytest.mark.anyio
-async def test_regression_v2_stream_unchanged():
-    graph = make_simple_graph()
-    chunks = []
-    async for chunk in graph.astream(
-        {"value": "x", "items": []}, stream_mode="values", version="v2"
-    ):
-        chunks.append(chunk)
-    assert len(chunks) >= 1
-    for chunk in chunks:
-        assert isinstance(chunk, dict)
-        assert "type" in chunk
-        assert chunk["type"] == "values"
-
-
-@pytest.mark.anyio
-async def test_regression_invoke_unchanged():
-    graph = make_simple_graph()
-    result = await graph.ainvoke({"value": "x", "items": []})
-    assert result == {"value": "x_a_b", "items": ["a", "b"]}
-
-
-def test_sync_stream_output():
-    graph = make_simple_graph()
-    run = StreamingHandler(graph).stream({"value": "x", "items": []})
-    assert run.output == {"value": "x_a_b", "items": ["a", "b"]}
-
-
-def test_sync_stream_values():
-    graph = make_simple_graph()
-    run = StreamingHandler(graph).stream({"value": "x", "items": []})
-    snapshots = list(run.values)
-    assert len(snapshots) == 3
-    assert snapshots[0]["value"] == "x"
-    assert snapshots[2]["value"] == "x_a_b"
-
-
-def test_sync_stream_raw_events():
-    graph = make_simple_graph()
-    run = StreamingHandler(graph).stream({"value": "x", "items": []})
-    methods = {e["method"] for e in run}
-    assert {"values", "updates", "tasks", "debug"} <= methods
-
-
-# ---------------------------------------------------------------------------
-# Typed output (pydantic)
-# ---------------------------------------------------------------------------
-
-
-class ModelState(BaseModel):
-    value: str
-    items: Annotated[list[str], lambda a, b: a + b]
-
-
-def _make_model_state_graph():
-    def node_a(state):
-        return {"value": state.value + "_a", "items": ["a"]}
-
-    graph = StateGraph(ModelState)
-    graph.add_node("node_a", node_a)
-    graph.add_edge(START, "node_a")
-    graph.add_edge("node_a", END)
-    return graph.compile()
-
-
-@pytest.mark.anyio
-async def test_pydantic_output():
-    graph = _make_model_state_graph()
-    run = await StreamingHandler(graph).astream(ModelState(value="x", items=[]))
-    await asyncio.sleep(0.1)
-    output = await run.output
-    assert isinstance(output, ModelState)
-    assert output.value == "x_a"
-
-
-@pytest.mark.anyio
-async def test_pydantic_values():
-    graph = _make_model_state_graph()
-    run = await StreamingHandler(graph).astream(ModelState(value="x", items=[]))
-    await asyncio.sleep(0.1)
-    snapshots = []
-    async for v in run.values:
-        snapshots.append(v)
-    for v in snapshots:
-        assert isinstance(v, ModelState)
-
-
-def test_sync_pydantic_output():
-    graph = _make_model_state_graph()
-    run = StreamingHandler(graph).stream(ModelState(value="x", items=[]))
-    assert isinstance(run.output, ModelState)
-    assert run.output.value == "x_a"
-
-
-# ---------------------------------------------------------------------------
-# Interrupts
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.anyio
-async def test_interrupts():
-    from langgraph.checkpoint.memory import MemorySaver
-
-    from langgraph.types import interrupt
-
-    def ask_human(state: State):
-        answer = interrupt("what do you want?")
-        return {"value": state["value"] + f"_{answer}", "items": [answer]}
-
-    graph = StateGraph(State)
-    graph.add_node("ask", ask_human)
-    graph.add_edge(START, "ask")
-    graph.add_edge("ask", END)
-    compiled = graph.compile(checkpointer=MemorySaver())
-
-    config = {"configurable": {"thread_id": "t1"}}
-    run = await StreamingHandler(compiled).astream(
-        {"value": "x", "items": []}, config=config
-    )
-    await asyncio.sleep(0.1)
-    # Drain events
-    async for _ in run:
-        pass
-    assert run.interrupted is True
-    assert len(run.interrupts) > 0
-
-
-# ---------------------------------------------------------------------------
-# messages_from(node)
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.anyio
-async def test_messages_from_node():
-    model = FakeChatModel(messages=[AIMessage(content="from agent")])
-
-    def agent(state):
-        return {"messages": [model.invoke(state["messages"])]}
-
-    def postprocess(state):
-        return {"messages": state["messages"]}
-
-    graph = StateGraph(MessagesState)
-    graph.add_node("agent", agent)
-    graph.add_node("postprocess", postprocess)
-    graph.add_edge(START, "agent")
-    graph.add_edge("agent", "postprocess")
-    graph.add_edge("postprocess", END)
-    compiled = graph.compile()
-
-    run = await StreamingHandler(compiled).astream(
-        {"messages": [HumanMessage(content="hi")]}
-    )
-    await asyncio.sleep(0.1)
-
-    # All messages
-    all_msgs = []
-    async for m in run.messages:
-        all_msgs.append(m)
-    assert len(all_msgs) >= 1
-    # Node provenance should be set
-    assert all_msgs[0].node == "agent"
-
-
-# ---------------------------------------------------------------------------
-# Subgraph child stream
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.anyio
-async def test_subgraph_child_output():
-    """AsyncSubgraphRunStream.output should contain the child graph's final state."""
-
-    class ChildState(TypedDict):
-        value: str
-
-    class ParentState(TypedDict):
-        value: str
-
-    def child_node(state):
-        return {"value": state["value"] + "_child"}
-
-    child_graph = StateGraph(ChildState)
-    child_graph.add_node("child_node", child_node)
-    child_graph.add_edge(START, "child_node")
-    child_graph.add_edge("child_node", END)
-    # Add the compiled child as a node — this triggers LangGraph's
-    # subgraph streaming mechanism and emits child namespace events.
-    child_compiled = child_graph.compile()
-
-    parent_graph = StateGraph(ParentState)
-    parent_graph.add_node("child_node", child_compiled)
-    parent_graph.add_edge(START, "child_node")
-    parent_graph.add_edge("child_node", END)
-    parent_compiled = parent_graph.compile()
-
-    run = await StreamingHandler(parent_compiled).astream({"value": "x"})
-    await asyncio.sleep(0.1)
-
-    subgraph_streams = []
-    async for sub in run.subgraphs:
-        subgraph_streams.append(sub)
-
-    assert len(subgraph_streams) >= 1
-    child_output = await subgraph_streams[0].output
-    assert child_output is not None
-    assert child_output["value"] == "x_child"
-
-
-# ---------------------------------------------------------------------------
-# Custom reducers / .extensions
-# ---------------------------------------------------------------------------
-
-
-class _CountTransformer(StreamTransformer):
-    """Counts events. Exposes count via .value for extensions."""
-
-    name = "event_count"
-
-    def __init__(self) -> None:
-        self.value = 0
-
-    def init(self) -> Any:
-        return None
-
-    def process(self, event: ProtocolEvent) -> bool:
-        self.value += 1
-        return True
-
-    def finalize(self) -> None:
-        pass
-
-    def fail(self, err: BaseException) -> None:
-        pass
-
-
-@pytest.mark.anyio
-async def test_custom_reducer_extensions():
-    graph = make_simple_graph()
-    counter = _CountTransformer()
-    run = await StreamingHandler(graph).astream(
-        {"value": "x", "items": []}, transformers=[counter]
-    )
-    await asyncio.sleep(0.1)
-    async for _ in run:
-        pass
-    assert counter.value > 0
-    assert run.extensions["event_count"] == counter.value
-
-
-def test_sync_custom_reducer_extensions():
-    graph = make_simple_graph()
-    counter = _CountTransformer()
-    run = StreamingHandler(graph).stream(
-        {"value": "x", "items": []}, transformers=[counter]
-    )
-    for _ in run:
-        pass
-    assert counter.value > 0
-    assert run.extensions["event_count"] == counter.value
-
-
-# ---------------------------------------------------------------------------
-# Double iteration over .values
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.anyio
-async def test_async_values_double_iteration():
-    """Iterating over run.values twice should yield the same snapshots both times."""
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-
-    first = []
-    async for v in run.values:
-        first.append(v)
-
-    second = []
-    async for v in run.values:
-        second.append(v)
-
-    assert len(first) == 3
-    assert first == second
-
-
-def test_sync_values_double_iteration():
-    """Iterating over run.values twice should yield the same snapshots both times."""
-    graph = make_simple_graph()
-    run = StreamingHandler(graph).stream({"value": "x", "items": []})
-
-    first = list(run.values)
-    second = list(run.values)
-
-    assert len(first) == 3
-    assert first == second
-
-
-@pytest.mark.anyio
-async def test_async_raw_events_double_iteration():
-    """Iterating over the raw event stream twice should yield the same events."""
-    graph = make_simple_graph()
-    run = await StreamingHandler(graph).astream({"value": "x", "items": []})
-    await asyncio.sleep(0.1)
-
-    first = []
-    async for event in run:
-        first.append(event)
-
-    second = []
-    async for event in run:
-        second.append(event)
-
-    assert len(first) > 0
-    assert first == second
-
-
-def test_sync_raw_events_double_iteration():
-    """Iterating over the raw event stream twice should yield the same events."""
-    graph = make_simple_graph()
-    run = StreamingHandler(graph).stream({"value": "x", "items": []})
-
-    first = list(run)
-    second = list(run)
-
-    assert len(first) > 0
-    assert first == second
-
-
-# ---------------------------------------------------------------------------
-# Tool transformer via extensions
-# ---------------------------------------------------------------------------
-
-
-class _ToolExecution:
-    def __init__(self, tool_call_id: str, tool_name: str, input: Any, output: Any):
-        self.tool_call_id = tool_call_id
-        self.tool_name = tool_name
-        self.input = input
-        self.output = output
-
-
-class _ToolsTransformer(StreamTransformer):
-    """Groups tool-started/tool-finished custom events into _ToolExecution objects."""
-
-    name = "tools"
-
-    def __init__(self) -> None:
-        self._log: list[_ToolExecution] = []
-        self._pending: dict[str, dict] = {}
-        self.value = self._log
-
-    def init(self) -> Any:
-        return None
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "custom":
-            return True
-        data = event["params"]["data"]
-        if not isinstance(data, dict) or "event" not in data:
-            return True
-
-        tool_call_id = data.get("tool_call_id")
-        if tool_call_id is None:
-            return True
-
-        if data["event"] == "tool-started":
-            self._pending[tool_call_id] = data
-            return False
-
-        if data["event"] == "tool-finished":
-            started = self._pending.pop(tool_call_id, {})
-            self._log.append(_ToolExecution(
-                tool_call_id=tool_call_id,
-                tool_name=started.get("tool_name", ""),
-                input=started.get("input"),
-                output=data["output"],
-            ))
-            return False
-
-        return True
-
-    def finalize(self) -> None:
-        pass
-
-    def fail(self, err: BaseException) -> None:
-        pass
-
-
-def _make_tool_graph():
-    """Graph: agent emits a tool call, custom_tools executes it with writer events."""
-    from langgraph.types import StreamWriter
-
-    def agent(state):
-        return {
-            "value": "called",
-            "items": ["agent"],
-        }
-
-    def custom_tools(state, *, writer: StreamWriter):
-        writer({
-            "event": "tool-started",
-            "tool_call_id": "call_1",
-            "tool_name": "get_weather",
-            "input": {"city": "SF"},
-        })
-        writer({
-            "event": "tool-finished",
-            "tool_call_id": "call_1",
-            "output": {"temp_f": 64},
-        })
-        return {"value": "done", "items": ["tools"]}
-
-    graph = StateGraph(State)
-    graph.add_node("agent", agent)
-    graph.add_node("custom_tools", custom_tools)
-    graph.add_edge(START, "agent")
-    graph.add_edge("agent", "custom_tools")
-    graph.add_edge("custom_tools", END)
-    return graph.compile()
-
-
-def test_sync_tool_transformer_via_extensions():
-    """Tool events flow through extensions and are iterable without draining raw events."""
-    graph = _make_tool_graph()
-    run = StreamingHandler(graph).stream(
-        {"value": "", "items": []},
-        transformers=[_ToolsTransformer()],
-    )
-
-    # Iterating extensions drives the pump — no need to drain raw events first
-    executions = list(run.extensions["tools"])
-    assert len(executions) == 1
-    assert executions[0].tool_name == "get_weather"
-    assert executions[0].input == {"city": "SF"}
-    assert executions[0].output == {"temp_f": 64}
-
-
-@pytest.mark.anyio
-async def test_async_tool_transformer_via_extensions():
-    """Tool events flow through extensions in async mode."""
-    graph = _make_tool_graph()
-    run = await StreamingHandler(graph).astream(
-        {"value": "", "items": []},
-        transformers=[_ToolsTransformer()],
-    )
-    await asyncio.sleep(0.1)
-
-    # Drain main stream so transformer processes all events
-    async for _ in run:
-        pass
-
-    tools_log = run.extensions["tools"]
-    assert len(tools_log) == 1
-    assert tools_log[0].tool_name == "get_weather"
-    assert tools_log[0].output == {"temp_f": 64}
@@ -1396,7 +1396,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
                "langgraph_path": (PULL, "agent"),
                "langgraph_checkpoint_ns": AnyStr("agent:"),
                "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "fakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -1459,7 +1458,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
                "langgraph_path": (PULL, "agent"),
                "langgraph_checkpoint_ns": AnyStr("agent:"),
                "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "fakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -1512,7 +1510,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
                "langgraph_path": (PULL, "agent"),
                "langgraph_checkpoint_ns": AnyStr("agent:"),
                "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "fakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -6884,7 +6881,6 @@ def test_weather_subgraph(
                    "langgraph_path": ("__pregel_pull", "router_node"),
                    "langgraph_checkpoint_ns": AnyStr("router_node:"),
                    "checkpoint_ns": AnyStr("router_node:"),
-                    "_type": "fake-messages-list-chat-model",
                    "ls_provider": "fakemessageslistchatmodel",
                    "ls_model_type": "chat",
                    "ls_integration": "langchain_chat_model",
@@ -6912,7 +6908,6 @@ def test_weather_subgraph(
                    "langgraph_path": ("__pregel_pull", "model_node"),
                    "langgraph_checkpoint_ns": AnyStr("weather_graph:"),
                    "checkpoint_ns": AnyStr("weather_graph:"),
-                    "_type": "fake-messages-list-chat-model",
                    "ls_provider": "fakemessageslistchatmodel",
                    "ls_model_type": "chat",
                    "ls_integration": "langchain_chat_model",
@@ -6949,7 +6944,6 @@ def test_weather_subgraph(
                "langgraph_path": ("__pregel_pull", "router_node"),
                "langgraph_checkpoint_ns": AnyStr("router_node:"),
                "checkpoint_ns": AnyStr("router_node:"),
-                "_type": "fake-messages-list-chat-model",
                "ls_provider": "fakemessageslistchatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -1147,7 +1147,6 @@ async def test_prebuilt_tool_chat() -> None:
                "langgraph_path": (PULL, "agent"),
                "langgraph_checkpoint_ns": AnyStr("agent:"),
                "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "fakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -1210,7 +1209,6 @@ async def test_prebuilt_tool_chat() -> None:
                "langgraph_path": (PULL, "agent"),
                "langgraph_checkpoint_ns": AnyStr("agent:"),
                "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "fakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -1263,7 +1261,6 @@ async def test_prebuilt_tool_chat() -> None:
                "langgraph_path": (PULL, "agent"),
                "langgraph_checkpoint_ns": AnyStr("agent:"),
                "checkpoint_ns": AnyStr("agent:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "fakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -3981,7 +3978,6 @@ async def test_weather_subgraph(
                    "langgraph_path": ("__pregel_pull", "router_node"),
                    "langgraph_checkpoint_ns": AnyStr("router_node:"),
                    "checkpoint_ns": AnyStr("router_node:"),
-                    "_type": "fake-messages-list-chat-model",
                    "ls_provider": "fakemessageslistchatmodel",
                    "ls_model_type": "chat",
                    "ls_integration": "langchain_chat_model",
@@ -4009,7 +4005,6 @@ async def test_weather_subgraph(
                    "langgraph_path": ("__pregel_pull", "model_node"),
                    "langgraph_checkpoint_ns": AnyStr("weather_graph:"),
                    "checkpoint_ns": AnyStr("weather_graph:"),
-                    "_type": "fake-messages-list-chat-model",
                    "ls_provider": "fakemessageslistchatmodel",
                    "ls_model_type": "chat",
                    "ls_integration": "langchain_chat_model",
@@ -4046,7 +4041,6 @@ async def test_weather_subgraph(
                "langgraph_path": ("__pregel_pull", "router_node"),
                "langgraph_checkpoint_ns": AnyStr("router_node:"),
                "checkpoint_ns": AnyStr("router_node:"),
-                "_type": "fake-messages-list-chat-model",
                "ls_provider": "fakemessageslistchatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -1,531 +0,0 @@
-from uuid import uuid4
-
-import pytest
-from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage
-from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
-
-from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
-from langgraph.pregel._messages_v2 import StreamProtocolMessagesHandler
-from langgraph.types import Command
-
-META = {"langgraph_checkpoint_ns": "root:", "langgraph_node": "agent"}
-
-
-def make_handler(subgraphs=True):
-    events = []
-    handler = StreamProtocolMessagesHandler(events.append, subgraphs)
-    return handler, events
-
-
-def test_streamed_text():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    for token_text in ("Hello", " ", "world"):
-        chunk = ChatGenerationChunk(
-            message=AIMessageChunk(content=token_text, id=f"run-{run_id}")
-        )
-        handler.on_llm_new_token(token_text, chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(content="Hello world", id=f"run-{run_id}")
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    assert data_events[0]["event"] == "message-start"
-    assert data_events[1]["event"] == "content-block-start"
-    assert data_events[1]["index"] == 0
-
-    deltas = [d for d in data_events if d["event"] == "content-block-delta"]
-    assert len(deltas) == 3
-    assert deltas[0]["content_block"]["text"] == "Hello"
-    assert deltas[1]["content_block"]["text"] == " "
-    assert deltas[2]["content_block"]["text"] == "world"
-
-    finish_blocks = [d for d in data_events if d["event"] == "content-block-finish"]
-    assert len(finish_blocks) == 1
-    assert finish_blocks[0]["content_block"]["text"] == "Hello world"
-
-    assert data_events[-1]["event"] == "message-finish"
-    assert data_events[-1]["reason"] == "stop"
-
-
-def test_tool_calls():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    chunk1 = ChatGenerationChunk(
-        message=AIMessageChunk(
-            content="",
-            tool_call_chunks=[
-                {"name": "search", "args": '{"q', "id": "call_1", "index": 0}
-            ],
-            id=f"run-{run_id}",
-        )
-    )
-    handler.on_llm_new_token("", chunk=chunk1, run_id=run_id)
-
-    chunk2 = ChatGenerationChunk(
-        message=AIMessageChunk(
-            content="",
-            tool_call_chunks=[
-                {"name": None, "args": 'uery":"hi"}', "id": None, "index": 0}
-            ],
-            id=f"run-{run_id}",
-        )
-    )
-    handler.on_llm_new_token("", chunk=chunk2, run_id=run_id)
-
-    final_msg = AIMessage(
-        content="",
-        tool_calls=[{"name": "search", "args": {"query": "hi"}, "id": "call_1"}],
-        id=f"run-{run_id}",
-    )
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    finish_blocks = [d for d in data_events if d["event"] == "content-block-finish"]
-    assert len(finish_blocks) == 1
-    fb = finish_blocks[0]["content_block"]
-    assert fb["type"] == "tool_call"
-    assert fb["args"] == {"query": "hi"}
-    assert fb["name"] == "search"
-    assert fb["id"] == "call_1"
-
-
-def test_invalid_tool_call_json():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    chunk = ChatGenerationChunk(
-        message=AIMessageChunk(
-            content="",
-            tool_call_chunks=[
-                {
-                    "name": "search",
-                    "args": "{not valid json",
-                    "id": "call_2",
-                    "index": 0,
-                }
-            ],
-            id=f"run-{run_id}",
-        )
-    )
-    handler.on_llm_new_token("", chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(content="", id=f"run-{run_id}")
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    finish_blocks = [d for d in data_events if d["event"] == "content-block-finish"]
-    assert len(finish_blocks) == 1
-    fb = finish_blocks[0]["content_block"]
-    assert fb["type"] == "invalid_tool_call"
-    assert "Failed to parse" in fb["error"]
-
-
-def test_reasoning_blocks():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    chunk = ChatGenerationChunk(
-        message=AIMessageChunk(
-            content=[{"type": "reasoning_content", "reasoning_content": "thinking..."}],
-            id=f"run-{run_id}",
-        )
-    )
-    handler.on_llm_new_token("", chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(content="", id=f"run-{run_id}")
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    block_starts = [d for d in data_events if d["event"] == "content-block-start"]
-    assert len(block_starts) == 1
-    assert block_starts[0]["content_block"]["type"] == "reasoning"
-
-    deltas = [d for d in data_events if d["event"] == "content-block-delta"]
-    assert len(deltas) == 1
-    assert deltas[0]["content_block"]["reasoning"] == "thinking..."
-
-
-def test_multiple_content_blocks():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    chunk1 = ChatGenerationChunk(
-        message=AIMessageChunk(content="hello", id=f"run-{run_id}")
-    )
-    handler.on_llm_new_token("hello", chunk=chunk1, run_id=run_id)
-
-    chunk2 = ChatGenerationChunk(
-        message=AIMessageChunk(
-            content="",
-            tool_call_chunks=[
-                {"name": "lookup", "args": '{"x":1}', "id": "call_3", "index": 1}
-            ],
-            id=f"run-{run_id}",
-        )
-    )
-    handler.on_llm_new_token("", chunk=chunk2, run_id=run_id)
-
-    final_msg = AIMessage(
-        content="hello",
-        tool_calls=[{"name": "lookup", "args": {"x": 1}, "id": "call_3"}],
-        id=f"run-{run_id}",
-    )
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    finish_blocks = [d for d in data_events if d["event"] == "content-block-finish"]
-    assert len(finish_blocks) == 2
-
-
-def test_usage_metadata():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    chunk = ChatGenerationChunk(
-        message=AIMessageChunk(content="hi", id=f"run-{run_id}")
-    )
-    handler.on_llm_new_token("hi", chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(
-        content="hi",
-        id=f"run-{run_id}",
-        usage_metadata={"input_tokens": 10, "output_tokens": 5, "total_tokens": 15},
-    )
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    finish_event = [d for d in data_events if d["event"] == "message-finish"][0]
-    assert "usage" in finish_event
-    assert finish_event["usage"]["input_tokens"] == 10
-
-
-@pytest.mark.parametrize(
-    "raw_reason,expected",
-    [
-        ("stop", "stop"),
-        ("tool_calls", "tool_use"),
-        ("length", "length"),
-        ("content_filter", "content_filter"),
-        ("end_turn", "stop"),
-    ],
-)
-def test_finish_reason_normalization(raw_reason, expected):
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-    chunk = ChatGenerationChunk(message=AIMessageChunk(content="x", id=f"run-{run_id}"))
-    handler.on_llm_new_token("x", chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(
-        content="x",
-        id=f"run-{run_id}",
-        response_metadata={"finish_reason": raw_reason},
-    )
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    finish_event = [d for d in data_events if d["event"] == "message-finish"][0]
-    assert finish_event["reason"] == expected
-
-
-def test_tag_nostream():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[TAG_NOSTREAM]
-    )
-    chunk = ChatGenerationChunk(
-        message=AIMessageChunk(content="secret", id=f"run-{run_id}")
-    )
-    handler.on_llm_new_token("secret", chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(content="secret", id=f"run-{run_id}")
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-    assert events == []
-
-
-def test_tag_hidden_chain():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chain_start(
-        serialized={},
-        inputs={},
-        run_id=run_id,
-        metadata=META,
-        tags=[TAG_HIDDEN],
-        name="agent",
-    )
-    handler.on_chain_end(
-        {"messages": [AIMessage(content="hidden", id="msg-1")]},
-        run_id=run_id,
-    )
-    assert events == []
-
-
-def test_subgraph_filtering():
-    handler, events = make_handler(subgraphs=False)
-    run_id = uuid4()
-
-    subgraph_meta = {
-        "langgraph_checkpoint_ns": "root:|child:",
-        "langgraph_node": "agent",
-    }
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=subgraph_meta, tags=[]
-    )
-    chunk = ChatGenerationChunk(
-        message=AIMessageChunk(content="sub", id=f"run-{run_id}")
-    )
-    handler.on_llm_new_token("sub", chunk=chunk, run_id=run_id)
-
-    final_msg = AIMessage(content="sub", id=f"run-{run_id}")
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-    assert events == []
-
-
-def test_chain_emits_messages():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chain_start(
-        serialized={}, inputs={}, run_id=run_id, metadata=META, tags=[], name="agent"
-    )
-    handler.on_chain_end(
-        {"messages": [AIMessage(content="hello", id="msg-chain-1")]},
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    assert len(data_events) > 0
-    assert data_events[0]["event"] == "message-start"
-    assert data_events[-1]["event"] == "message-finish"
-
-
-def test_llm_error_after_start():
-    """on_llm_error should emit a message-error event for a started stream."""
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    chunk = ChatGenerationChunk(
-        message=AIMessageChunk(content="partial", id=f"run-{run_id}")
-    )
-    handler.on_llm_new_token("partial", chunk=chunk, run_id=run_id)
-
-    handler.on_llm_error(RuntimeError("connection lost"), run_id=run_id)
-
-    data_events = [e[2] for e in events]
-    assert data_events[0]["event"] == "message-start"
-    error_events = [d for d in data_events if d["event"] == "error"]
-    assert len(error_events) == 1
-    assert "connection lost" in error_events[0]["message"]
-
-
-def test_llm_error_before_start_no_emit():
-    """on_llm_error before any tokens should not emit error events."""
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    # Error before any token — state.started is False
-    handler.on_llm_error(RuntimeError("immediate fail"), run_id=run_id)
-
-    data_events = [e[2] for e in events]
-    error_events = [d for d in data_events if d.get("event") == "error"]
-    assert len(error_events) == 0
-
-
-def test_non_streamed_model():
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id, metadata=META, tags=[]
-    )
-
-    final_msg = AIMessage(
-        content="full response",
-        id=f"run-{run_id}",
-        response_metadata={"finish_reason": "stop"},
-    )
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    assert len(data_events) > 0
-    assert data_events[0]["event"] == "message-start"
-
-    deltas = [d for d in data_events if d["event"] == "content-block-delta"]
-    assert len(deltas) == 1
-    assert deltas[0]["content_block"]["text"] == "full response"
-
-    assert data_events[-1]["event"] == "message-finish"
-    assert data_events[-1]["reason"] == "stop"
-
-
-def test_chain_emits_command_with_message():
-    """on_chain_end should emit protocol events for messages inside a Command."""
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chain_start(
-        serialized={}, inputs={}, run_id=run_id, metadata=META, tags=[], name="agent"
-    )
-    handler.on_chain_end(
-        Command(update={"messages": [AIMessage(content="from command", id="cmd-1")]}),
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    assert len(data_events) > 0
-    assert data_events[0]["event"] == "message-start"
-    deltas = [d for d in data_events if d["event"] == "content-block-delta"]
-    assert len(deltas) == 1
-    assert deltas[0]["content_block"]["text"] == "from command"
-    assert data_events[-1]["event"] == "message-finish"
-
-
-def test_chain_emits_command_in_list():
-    """on_chain_end should handle a list containing Command objects."""
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chain_start(
-        serialized={}, inputs={}, run_id=run_id, metadata=META, tags=[], name="agent"
-    )
-    handler.on_chain_end(
-        [Command(update={"messages": [AIMessage(content="listed", id="cmd-2")]})],
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    starts = [d for d in data_events if d["event"] == "message-start"]
-    assert len(starts) == 1
-
-
-def test_chain_deduplicates_seen_messages():
-    """Messages already seen from LLM streaming should not be re-emitted by chain end."""
-    handler, events = make_handler()
-    run_id_llm = uuid4()
-    run_id_chain = uuid4()
-    msg_id = f"run-{run_id_llm}"
-
-    # Simulate LLM streaming
-    handler.on_chat_model_start(
-        serialized={}, messages=[[]], run_id=run_id_llm, metadata=META, tags=[]
-    )
-    chunk = ChatGenerationChunk(message=AIMessageChunk(content="hello", id=msg_id))
-    handler.on_llm_new_token("hello", chunk=chunk, run_id=run_id_llm)
-
-    final_msg = AIMessage(content="hello", id=msg_id)
-    handler.on_llm_end(
-        LLMResult(generations=[[ChatGeneration(message=final_msg)]]),
-        run_id=run_id_llm,
-    )
-
-    events_before = len(events)
-
-    # Now chain end with the same message ID
-    handler.on_chain_start(
-        serialized={},
-        inputs={},
-        run_id=run_id_chain,
-        metadata=META,
-        tags=[],
-        name="agent",
-    )
-    handler.on_chain_end(
-        {"messages": [AIMessage(content="hello", id=msg_id)]},
-        run_id=run_id_chain,
-    )
-
-    # No new events should have been emitted for the duplicate
-    data_events_after = [e[2] for e in events[events_before:]]
-    starts = [d for d in data_events_after if d.get("event") == "message-start"]
-    assert len(starts) == 0
-
-
-def test_chain_emits_human_message_role():
-    """Non-AI messages from chain output should have the correct role."""
-    handler, events = make_handler()
-    run_id = uuid4()
-
-    handler.on_chain_start(
-        serialized={}, inputs={}, run_id=run_id, metadata=META, tags=[], name="agent"
-    )
-    handler.on_chain_end(
-        {"messages": [HumanMessage(content="user msg", id="hmsg-1")]},
-        run_id=run_id,
-    )
-
-    data_events = [e[2] for e in events]
-    starts = [d for d in data_events if d["event"] == "message-start"]
-    assert len(starts) == 1
-    assert starts[0]["role"] == "human"
@@ -615,8 +615,11 @@ def test_run_from_checkpoint_id_retains_previous_writes(
        )
    ]

-    assert len(new_history) == len(history) + 1
-    for original, new in zip(history, new_history[1:]):
+    # +2: one fork checkpoint from time travel, one from the new execution
+    assert len(new_history) == len(history) + 2
+    # new_history[0] is the new execution result, new_history[1] is the fork
+    assert new_history[1].metadata["source"] == "fork"
+    for original, new in zip(history, new_history[2:]):
        assert original.values == new.values
        assert original.next == new.next
        assert original.metadata["step"] == new.metadata["step"]
@@ -624,7 +627,7 @@ def test_run_from_checkpoint_id_retains_previous_writes(
    def _get_tasks(hist: list, start: int):
        return [h.tasks for h in hist[start:]]

-    assert _get_tasks(new_history, 1) == _get_tasks(history, 0)
+    assert _get_tasks(new_history, 2) == _get_tasks(history, 0)


 def test_batch_two_processes_in_out() -> None:
@@ -6271,7 +6274,7 @@ def test_sync_streaming_with_functional_api() -> None:
    @task()
    def slow() -> dict:
        time.sleep(time_delay)  # Simulate a delay of 10 ms
-        return {"tic": time.time()}
+        return {"tic": time.monotonic()}

    @entrypoint()
    def graph(inputs: dict) -> list:
@@ -6284,7 +6287,7 @@ def test_sync_streaming_with_functional_api() -> None:
    for chunk in graph.stream({}):
        if "slow" not in chunk:  # We'll just look at the updates from `slow`
            continue
-        arrival_times.append(time.time())
+        arrival_times.append(time.monotonic())

    assert len(arrival_times) == 2
    delta = arrival_times[1] - arrival_times[0]
@@ -6893,7 +6896,6 @@ def test_tags_stream_mode_messages() -> None:
                "langgraph_path": ("__pregel_pull", "call_model"),
                "langgraph_checkpoint_ns": AnyStr("call_model:"),
                "checkpoint_ns": AnyStr("call_model:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "genericfakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -6903,6 +6905,60 @@ def test_tags_stream_mode_messages() -> None:
    ]


+def test_configurable_propagates_to_stream_metadata() -> None:
+    """Regression: thread_id, run_id, assistant_id, graph_id,
+    and langgraph_auth_user_id from configurable must appear
+    in stream_mode='messages' metadata."""
+
+    def my_node(state):
+        return {"messages": HumanMessage(content="hello")}
+
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("my_node", my_node)
+        .add_edge(START, "my_node")
+        .compile()
+    )
+
+    config = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+            # these should NOT be propagated into metadata
+            "some_api_key": "secret",
+            "custom_setting": {"nested": True},
+        },
+    }
+    results = list(graph.stream({"messages": []}, config, stream_mode="messages"))
+    assert len(results) == 1
+    _, metadata = results[0]
+    # propagated keys
+    assert metadata["thread_id"] == "th-123"
+    assert metadata["checkpoint_id"] == "ckpt-1"
+    assert metadata["checkpoint_ns"] == "ns-1"
+    assert metadata["task_id"] == "task-1"
+    assert metadata["run_id"] == "run-456"
+    assert metadata["assistant_id"] == "asst-789"
+    assert metadata["graph_id"] == "graph-0"
+    # These are only present in trace metadata by default as of langgraph 1.2
+    # assert metadata["model"] == "gpt-4o"
+    # assert metadata["user_id"] == "uid-1"
+    # assert metadata["cron_id"] == "cron-1"
+    # assert metadata["langgraph_auth_user_id"] == "user-1"
+    # non-allowlisted keys must not appear
+    assert "some_api_key" not in metadata
+    assert "custom_setting" not in metadata
+
+
 def test_stream_mode_messages_command() -> None:
    from langchain_core.messages import HumanMessage

@@ -20,6 +20,7 @@ from uuid import UUID

 import pytest
 from langchain_core.language_models import GenericFakeChatModel
+from langchain_core.messages import HumanMessage
 from langchain_core.runnables import RunnableConfig, RunnableLambda, RunnablePassthrough
 from langchain_core.utils.aiter import aclosing
 from langgraph.cache.base import BaseCache
@@ -2085,8 +2086,11 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
        )
    ]

-    assert len(new_history) == len(history) + 1
-    for original, new in zip(history, new_history[1:]):
+    # +2: one fork checkpoint from time travel, one from the new execution
+    assert len(new_history) == len(history) + 2
+    # new_history[0] is the new execution result, new_history[1] is the fork
+    assert new_history[1].metadata["source"] == "fork"
+    for original, new in zip(history, new_history[2:]):
        assert original.values == new.values
        assert original.next == new.next
        assert original.metadata["step"] == new.metadata["step"]
@@ -2094,7 +2098,7 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
    def _get_tasks(hist: list, start: int):
        return [h.tasks for h in hist[start:]]

-    assert _get_tasks(new_history, 1) == _get_tasks(history, 0)
+    assert _get_tasks(new_history, 2) == _get_tasks(history, 0)


 async def test_cond_edge_after_send() -> None:
@@ -7541,7 +7545,6 @@ async def test_tags_stream_mode_messages() -> None:
                "langgraph_path": ("__pregel_pull", "call_model"),
                "langgraph_checkpoint_ns": AnyStr("call_model:"),
                "checkpoint_ns": AnyStr("call_model:"),
-                "_type": "generic-fake-chat-model",
                "ls_provider": "genericfakechatmodel",
                "ls_model_type": "chat",
                "ls_integration": "langchain_chat_model",
@@ -7551,6 +7554,67 @@ async def test_tags_stream_mode_messages() -> None:
    ]


+async def test_configurable_propagates_to_stream_metadata() -> None:
+    """Regression: thread_id, run_id, assistant_id, graph_id,
+    and langgraph_auth_user_id from configurable must appear
+    in stream_mode='messages' metadata."""
+
+    def my_node(state):
+        return {"messages": HumanMessage(content="hello")}
+
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("my_node", my_node)
+        .add_edge(START, "my_node")
+        .compile()
+    )
+
+    config = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+            # these should NOT be propagated into metadata
+            "some_api_key": "secret",
+            "custom_setting": {"nested": True},
+        },
+    }
+    results = [
+        chunk
+        async for chunk in graph.astream(
+            {"messages": []}, config, stream_mode="messages"
+        )
+    ]
+    assert len(results) == 1
+    _, metadata = results[0]
+    # propagated keys
+    assert metadata["thread_id"] == "th-123"
+    assert metadata["checkpoint_id"] == "ckpt-1"
+    assert metadata["checkpoint_ns"] == "ns-1"
+    assert metadata["task_id"] == "task-1"
+    assert metadata["run_id"] == "run-456"
+    assert metadata["assistant_id"] == "asst-789"
+    assert metadata["graph_id"] == "graph-0"
+
+    # These will only be traced as of langgraph 1.2 and not present by default in
+    # metadata
+    # assert metadata["model"] == "gpt-4o"
+    # assert metadata["user_id"] == "uid-1"
+    # assert metadata["cron_id"] == "cron-1"
+    # assert metadata["langgraph_auth_user_id"] == "user-1"
+    # non-allowlisted keys must not appear
+    assert "some_api_key" not in metadata
+    assert "custom_setting" not in metadata
+
+
 async def test_stream_mode_messages_command() -> None:
    from langchain_core.messages import HumanMessage

@@ -501,13 +501,13 @@ async def test_execution_info_populated_in_graph_async() -> None:
    assert isinstance(info.node_first_attempt_time, float)


-def test_server_info_from_metadata() -> None:
-    """server_info is built from assistant_id/graph_id in config metadata."""
+def test_server_info_from_configurable() -> None:
+    """server_info is built from assistant_id/graph_id in config configurable."""
    captured: dict[str, Any] = {}
    compiled = _make_capture_graph(captured)
    compiled.invoke(
        {"message": "hi"},
-        config={"metadata": {"assistant_id": "asst-abc", "graph_id": "my-graph"}},
+        config={"configurable": {"assistant_id": "asst-abc", "graph_id": "my-graph"}},
    )
    si = captured["server_info"]
    assert si is not None
@@ -516,8 +516,8 @@ def test_server_info_from_metadata() -> None:
    assert si.user is None


-def test_server_info_none_without_metadata() -> None:
-    """server_info is None when no assistant_id/graph_id in metadata."""
+def test_server_info_none_without_configurable() -> None:
+    """server_info is None when no assistant_id/graph_id in configurable."""
    captured: dict[str, Any] = {}
    compiled = _make_capture_graph(captured)
    compiled.invoke({"message": "hi"})
@@ -579,8 +579,11 @@ def test_server_info_user_from_auth_user() -> None:
    compiled.invoke(
        {"message": "hi"},
        config={
-            "configurable": {"langgraph_auth_user": proxy},
-            "metadata": {"assistant_id": "asst-proxy", "graph_id": "graph-proxy"},
+            "configurable": {
+                "langgraph_auth_user": proxy,
+                "assistant_id": "asst-proxy",
+                "graph_id": "graph-proxy",
+            },
        },
    )
    si = captured["server_info"]
@@ -1,245 +0,0 @@
-import pytest
-
-from langgraph.stream.chat_model_stream import AsyncChatModelStream, ChatModelStream
-
-
-def _text_delta(text: str) -> dict:
-    return {"content_block": {"type": "text", "text": text}}
-
-
-def _reasoning_delta(text: str) -> dict:
-    return {"content_block": {"type": "reasoning", "reasoning": text}}
-
-
-# ---------------------------------------------------------------------------
-# Sync ChatModelStream tests
-# ---------------------------------------------------------------------------
-
-
-def test_sync_text_accumulates():
-    stream = ChatModelStream()
-    stream._push_content_block_delta(_text_delta("Hello"))
-    stream._push_content_block_delta(_text_delta(", world"))
-    stream._finish({"reason": "stop"})
-
-    assert stream.text == "Hello, world"
-    assert isinstance(stream.text, str)
-
-
-def test_sync_reasoning_accumulates():
-    stream = ChatModelStream()
-    stream._push_content_block_delta(_reasoning_delta("step 1"))
-    stream._push_content_block_delta(_reasoning_delta(" -> step 2"))
-    stream._finish({"reason": "stop"})
-
-    assert stream.reasoning == "step 1 -> step 2"
-    assert isinstance(stream.reasoning, str)
-
-
-def test_sync_usage():
-    stream = ChatModelStream()
-    usage = {"input_tokens": 10, "output_tokens": 5}
-    stream._finish({"reason": "stop", "usage": usage})
-    assert stream.usage == usage
-
-
-def test_sync_mixed_blocks():
-    stream = ChatModelStream()
-    stream._push_content_block_delta(_text_delta("answer"))
-    stream._push_content_block_delta(
-        {"content_block": {"type": "tool_call", "name": "search"}}
-    )
-    stream._push_content_block_delta(_text_delta(" here"))
-    stream._finish({"reason": "stop"})
-
-    assert stream.text == "answer here"
-
-
-def test_sync_tool_call_only_text_empty():
-    stream = ChatModelStream()
-    stream._push_content_block_delta(
-        {"content_block": {"type": "tool_call", "name": "search"}}
-    )
-    stream._finish({"reason": "stop"})
-    assert stream.text == ""
-
-
-def test_sync_fail_marks_done():
-    stream = ChatModelStream()
-    assert not stream.done
-    stream._fail(RuntimeError("err"))
-    assert stream.done
-
-
-def test_sync_namespace_and_node():
-    stream = ChatModelStream(
-        namespace=["agent:0", "tools:1"],
-        node="chat_model",
-        message_id="msg-123",
-    )
-    assert stream.namespace == ["agent:0", "tools:1"]
-    assert stream.node == "chat_model"
-    assert stream.message_id == "msg-123"
-
-
-def test_sync_content_block_finish_authoritative():
-    """content-block-finish with authoritative text overrides accumulated."""
-    stream = ChatModelStream()
-    stream._push_content_block_delta(_text_delta("partial"))
-    stream._push_content_block_finish(
-        {"content_block": {"type": "text", "text": "full text"}}
-    )
-    assert stream.text == "full text"
-
-
-# ---------------------------------------------------------------------------
-# Async ChatModelStream tests
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.anyio
-async def test_async_text_iterable_yields_deltas():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_text_delta("Hello"))
-    stream._push_content_block_delta(_text_delta(", world"))
-    stream._finish({"reason": "stop"})
-
-    collected = []
-    async for delta in stream.text:
-        collected.append(delta)
-    assert collected == ["Hello", ", world"]
-
-
-@pytest.mark.anyio
-async def test_async_text_awaitable_returns_full():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_text_delta("Hello"))
-    stream._push_content_block_delta(_text_delta(", world"))
-    stream._finish({"reason": "stop"})
-
-    result = await stream.text
-    assert result == "Hello, world"
-
-
-@pytest.mark.anyio
-async def test_async_reasoning_dual_pattern():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_reasoning_delta("step 1"))
-    stream._push_content_block_delta(_reasoning_delta(" -> step 2"))
-    stream._finish({"reason": "stop"})
-
-    collected = []
-    async for delta in stream.reasoning:
-        collected.append(delta)
-    assert collected == ["step 1", " -> step 2"]
-
-    stream2 = AsyncChatModelStream()
-    stream2._push_content_block_delta(_reasoning_delta("thinking"))
-    stream2._finish({"reason": "stop"})
-    full = await stream2.reasoning
-    assert full == "thinking"
-
-
-@pytest.mark.anyio
-async def test_async_usage_resolves():
-    stream = AsyncChatModelStream()
-    usage = {"input_tokens": 10, "output_tokens": 5}
-    stream._finish({"reason": "stop", "usage": usage})
-    result = await stream.usage
-    assert result == usage
-
-
-@pytest.mark.anyio
-async def test_async_mixed_blocks_text_only():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_text_delta("answer"))
-    stream._push_content_block_delta(
-        {"content_block": {"type": "tool_call", "name": "search"}}
-    )
-    stream._push_content_block_delta(_text_delta(" here"))
-    stream._finish({"reason": "stop"})
-
-    collected = []
-    async for delta in stream.text:
-        collected.append(delta)
-    assert collected == ["answer", " here"]
-
-
-@pytest.mark.anyio
-async def test_async_tool_call_only_text_empty():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(
-        {"content_block": {"type": "tool_call", "name": "search"}}
-    )
-    stream._finish({"reason": "stop"})
-    result = await stream.text
-    assert result == ""
-
-
-@pytest.mark.anyio
-async def test_async_fail_raises_on_text_await():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_text_delta("partial"))
-    stream._fail(RuntimeError("model error"))
-
-    with pytest.raises(RuntimeError, match="model error"):
-        await stream.text
-
-
-@pytest.mark.anyio
-async def test_async_fail_raises_on_reasoning_await():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_reasoning_delta("thinking"))
-    stream._fail(RuntimeError("model error"))
-
-    with pytest.raises(RuntimeError, match="model error"):
-        await stream.reasoning
-
-
-@pytest.mark.anyio
-async def test_async_fail_raises_on_usage_await():
-    stream = AsyncChatModelStream()
-    stream._fail(RuntimeError("model error"))
-
-    with pytest.raises(RuntimeError, match="model error"):
-        await stream.usage
-
-
-@pytest.mark.anyio
-async def test_async_fail_raises_during_text_iteration():
-    stream = AsyncChatModelStream()
-    stream._push_content_block_delta(_text_delta("partial"))
-    stream._fail(RuntimeError("model error"))
-
-    collected = []
-    with pytest.raises(RuntimeError, match="model error"):
-        async for delta in stream.text:
-            collected.append(delta)
-    assert collected == ["partial"]
-
-
-@pytest.mark.anyio
-async def test_async_fail_marks_done():
-    stream = AsyncChatModelStream()
-    assert not stream.done
-    stream._fail(RuntimeError("err"))
-    assert stream.done
-
-
-@pytest.mark.anyio
-async def test_async_namespace_and_node():
-    stream = AsyncChatModelStream(
-        namespace=["agent:0", "tools:1"],
-        node="chat_model",
-        message_id="msg-123",
-    )
-    assert stream.namespace == ["agent:0", "tools:1"]
-    assert stream.node == "chat_model"
-    assert stream.message_id == "msg-123"
-
-
-@pytest.mark.anyio
-async def test_async_inherits_from_sync():
-    """AsyncChatModelStream is a subclass of ChatModelStream."""
-    stream = AsyncChatModelStream()
-    assert isinstance(stream, ChatModelStream)
@@ -1,79 +0,0 @@
-from langgraph.stream._convert import STREAM_V2_MODES, convert_to_protocol_event
-
-
-def test_values_mode():
-    evt = convert_to_protocol_event((), "values", {"x": 1})
-    assert evt is not None
-    assert evt["method"] == "values"
-    assert evt["params"]["data"] == {"x": 1}
-
-
-def test_updates_mode():
-    evt = convert_to_protocol_event((), "updates", {"node": "out"})
-    assert evt is not None
-    assert evt["method"] == "updates"
-
-
-def test_messages_mode():
-    evt = convert_to_protocol_event((), "messages", {"event": "msg"})
-    assert evt is not None
-    assert evt["method"] == "messages"
-
-
-def test_custom_mode():
-    evt = convert_to_protocol_event((), "custom", "hello")
-    assert evt is not None
-    assert evt["method"] == "custom"
-    assert evt["params"]["data"] == "hello"
-
-
-def test_debug_mode():
-    evt = convert_to_protocol_event((), "debug", {})
-    assert evt is not None
-    assert evt["method"] == "debug"
-
-
-def test_checkpoints_mode():
-    evt = convert_to_protocol_event((), "checkpoints", {})
-    assert evt is not None
-    assert evt["method"] == "checkpoints"
-
-
-def test_tasks_mode():
-    evt = convert_to_protocol_event((), "tasks", {})
-    assert evt is not None
-    assert evt["method"] == "tasks"
-
-
-def test_namespace_passthrough():
-    evt = convert_to_protocol_event(("agent", "0"), "values", {})
-    assert evt is not None
-    assert evt["params"]["namespace"] == ["agent", "0"]
-
-
-def test_unknown_mode_returns_none():
-    assert convert_to_protocol_event((), "unknown_mode", {}) is None
-
-
-def test_node_parameter():
-    evt = convert_to_protocol_event((), "values", {}, node="agent")
-    assert evt is not None
-    assert evt["params"]["node"] == "agent"
-
-
-def test_type_is_event():
-    evt = convert_to_protocol_event((), "values", {})
-    assert evt is not None
-    assert evt["type"] == "event"
-
-
-def test_stream_v2_modes_complete():
-    assert set(STREAM_V2_MODES) == {
-        "values",
-        "updates",
-        "messages",
-        "custom",
-        "checkpoints",
-        "tasks",
-        "debug",
-    }
@@ -1,293 +0,0 @@
-from typing import Any
-
-import pytest
-
-from langgraph.stream._convert import convert_to_protocol_event
-from langgraph.stream._mux import AsyncStreamMux, StreamMux
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.stream_channel import StreamChannel
-
-
-def _event(mode: str, data: Any, ns: list[str] | None = None) -> ProtocolEvent:
-    ev = convert_to_protocol_event(tuple(ns or []), mode, data)
-    assert ev is not None
-    return ev
-
-
-class _MockTransformer(StreamTransformer):
-    def __init__(self, *, suppress: bool = False):
-        self.calls: list[ProtocolEvent] = []
-        self._suppress = suppress
-
-    def init(self) -> Any:
-        return None
-
-    def process(self, event: ProtocolEvent) -> bool:
-        self.calls.append(event)
-        return not self._suppress
-
-    def finalize(self) -> None:
-        pass
-
-    def fail(self, err: BaseException) -> None:
-        pass
-
-
-@pytest.mark.anyio
-async def test_events_through_reducer_pipeline():
-    reducer = _MockTransformer()
-    mux = StreamMux(transformers=[reducer])
-    event = _event("values", {"key": "val"})
-    mux.push(event)
-    assert len(reducer.calls) == 1
-    assert reducer.calls[0] is event
-
-
-@pytest.mark.anyio
-async def test_reducer_suppresses_event():
-    reducer = _MockTransformer(suppress=True)
-    mux = StreamMux(transformers=[reducer])
-    mux.push(_event("values", {"x": 1}))
-    mux.close()
-    assert len(reducer.calls) == 1
-    assert len(mux.event_log) == 0
-
-
-@pytest.mark.anyio
-async def test_namespace_discovery():
-    mux = StreamMux()
-    mux.push(_event("values", {"a": 1}, ns=["child:0"]))
-    assert "child:0" in mux._discovered_ns
-
-
-@pytest.mark.anyio
-async def test_top_level_ns_only():
-    mux = StreamMux()
-    mux.push(_event("values", {"a": 1}, ns=["agent:0", "tools:1"]))
-    assert "agent:0" in mux._discovered_ns
-    assert "tools:1" not in mux._discovered_ns
-
-
-@pytest.mark.anyio
-async def test_subscribe_events_filter():
-    mux = AsyncStreamMux()
-    mux.push(_event("values", {"a": 1}, ns=["child:0"]))
-    mux.push(_event("values", {"b": 2}, ns=["other:1"]))
-    mux.push(_event("values", {"c": 3}, ns=["child:0"]))
-    mux.close()
-
-    collected = []
-    async for ev in mux.subscribe_events(["child:0"]):
-        collected.append(ev)
-    assert len(collected) == 2
-    assert collected[0]["params"]["data"] == {"a": 1}
-    assert collected[1]["params"]["data"] == {"c": 3}
-
-
-@pytest.mark.anyio
-async def test_close_resolves_output():
-    mux = AsyncStreamMux()
-    fut = mux.get_output_future()
-    mux.push(_event("values", {"v": 1}))
-    mux.push(_event("values", {"v": 2}))
-    mux.close()
-    result = await fut
-    assert result == {"v": 2}
-
-
-@pytest.mark.anyio
-async def test_fail_rejects_output():
-    mux = AsyncStreamMux()
-    fut = mux.get_output_future()
-    mux.fail(ValueError("boom"))
-    with pytest.raises(ValueError, match="boom"):
-        await fut
-
-
-@pytest.mark.anyio
-async def test_latest_values_tracked():
-    mux = StreamMux()
-    mux.push(_event("values", {"v": 1}, ns=["child:0"]))
-    mux.push(_event("values", {"v": 2}, ns=["child:0"]))
-    assert mux.get_latest_values(["child:0"]) == {"v": 2}
-
-
-@pytest.mark.anyio
-async def test_interrupt_tracking():
-    """StreamMux should track __interrupt__ payloads in values events."""
-
-    class _FakeInterrupt:
-        def __init__(self, id: str, payload: Any):
-            self.id = id
-            self.payload = payload
-
-    mux = StreamMux()
-    interrupt_obj = _FakeInterrupt("int-1", "what do you want?")
-    mux.push(
-        _event(
-            "values",
-            {"__interrupt__": [interrupt_obj]},
-        )
-    )
-    assert mux.interrupted is True
-    assert len(mux.interrupts) == 1
-    assert mux.interrupts[0]["interrupt_id"] == "int-1"
-    assert mux.interrupts[0]["payload"] is interrupt_obj
-
-
-@pytest.mark.anyio
-async def test_no_interrupt_by_default():
-    mux = StreamMux()
-    mux.push(_event("values", {"x": 1}))
-    mux.close()
-    assert mux.interrupted is False
-    assert mux.interrupts == []
-
-
-@pytest.mark.anyio
-async def test_push_after_close_ignored():
-    mux = StreamMux()
-    mux.push(_event("values", {"a": 1}))
-    mux.close()
-    mux.push(_event("values", {"b": 2}))
-    assert len(mux.event_log) == 1
-
-
-@pytest.mark.anyio
-async def test_fail_rejects_all_futures():
-    mux = AsyncStreamMux()
-    fut1 = mux.get_output_future([])
-    fut2 = mux.get_output_future(["child:0"])
-    mux.fail(ValueError("boom"))
-    with pytest.raises(ValueError, match="boom"):
-        await fut1
-    with pytest.raises(ValueError, match="boom"):
-        await fut2
-
-
-@pytest.mark.anyio
-async def test_channel_events_bypass_transformer_pipeline():
-    """Events emitted via ``StreamChannel.push()`` are appended directly
-    to the event log, bypassing the transformer pipeline.  This matches
-    the JS implementation and avoids re-entrancy bugs.
-    """
-    mock = _MockTransformer()
-    mux = AsyncStreamMux(transformers=[mock])
-
-    channel: StreamChannel[str] = StreamChannel("my_channel")
-    mux.wire_channels({"ch": channel})
-
-    # Regular push — transformer sees it
-    mux.push(_event("values", {"a": 1}))
-    assert len(mock.calls) == 1
-
-    # Channel push — bypasses transformers, goes straight to event log
-    channel.push("hello from channel")
-
-    assert len(mock.calls) == 1, (
-        f"Transformer saw {len(mock.calls)} events (expected 1).  "
-        "Channel events should bypass the transformer pipeline."
-    )
-
-    # But the event IS in the log
-    mux.close()
-    events = []
-    async for ev in mux.subscribe_events():
-        events.append(ev)
-    assert len(events) == 2
-    assert events[1]["method"] == "my_channel"
-    assert events[1]["params"]["data"] == "hello from channel"
-
-
-@pytest.mark.anyio
-async def test_event_log_has_monotonic_seq_numbers():
-    """All events in the event log should have strictly monotonically
-    increasing seq numbers so consumers can reason about ordering.
-
-    Events from ``mux.push()`` carry seq numbers assigned by the pump
-    while channel-emitted events use a separate counter
-    (``_next_emit_seq``).  When interleaved, seq numbers can duplicate.
-    """
-    mux = AsyncStreamMux()
-    channel: StreamChannel[str] = StreamChannel("test_ch")
-    mux.wire_channels({"ch": channel})
-
-    mux.push(_event("values", {"a": 1}))  # log seq: 0
-    channel.push("from_channel")  # log seq: 0 (from _next_emit_seq)
-    mux.push(_event("values", {"b": 2}))  # log seq: 1
-    mux.close()
-
-    seqs: list[int] = []
-    async for event in mux.subscribe_events():
-        seqs.append(event["seq"])
-
-    assert len(seqs) == 3, f"Expected 3 events but got {len(seqs)}"
-
-    for i in range(1, len(seqs)):
-        assert seqs[i] > seqs[i - 1], (
-            f"Seq numbers not strictly monotonic: {seqs}.  "
-            f"seq[{i}]={seqs[i]} <= seq[{i - 1}]={seqs[i - 1]}.  "
-            "Channel events use a separate counter from push() events."
-        )
-
-
-@pytest.mark.anyio
-async def test_channel_push_during_process_preserves_namespace():
-    """When two transformers both call channel.push() during the same
-    outer mux.push(), the second transformer's channel event should
-    still carry the original event's namespace.
-
-    Bug: the first channel.push() re-enters mux.push(), which resets
-    ``_current_namespace`` to ``[]`` on exit.  The second transformer's
-    channel.push() then reads the clobbered value and its event gets
-    ``namespace: []`` instead of the original.
-    """
-
-    class _ChannelTransformer(StreamTransformer):
-        """Pushes to its channel whenever it sees a ``values`` event."""
-
-        def __init__(self, name: str) -> None:
-            self.name = name
-            self.channel: StreamChannel[str] = StreamChannel(name)
-
-        def init(self) -> Any:
-            return {self.name: self.channel}
-
-        def process(self, event: ProtocolEvent) -> bool:
-            if event["method"] == "values":
-                self.channel.push(f"from_{self.name}")
-            return True
-
-        def finalize(self) -> None:
-            pass
-
-        def fail(self, err: BaseException) -> None:
-            pass
-
-    t1 = _ChannelTransformer("first")
-    t2 = _ChannelTransformer("second")
-    mux = AsyncStreamMux(transformers=[t1, t2])
-    mux.wire_channels({"first": t1.channel})
-    mux.wire_channels({"second": t2.channel})
-
-    # Push a values event with a non-root namespace
-    mux.push(_event("values", {"x": 1}, ns=["agent:0"]))
-    mux.close()
-
-    # Collect channel events emitted by each transformer
-    channel_events: list[ProtocolEvent] = []
-    async for ev in mux.subscribe_events():
-        if ev["method"] in ("first", "second"):
-            channel_events.append(ev)
-
-    assert len(channel_events) == 2, (
-        f"Expected 2 channel events but got {len(channel_events)}"
-    )
-
-    for ev in channel_events:
-        assert ev["params"]["namespace"] == ["agent:0"], (
-            f"Channel event for method={ev['method']!r} has "
-            f"namespace={ev['params']['namespace']!r}, expected ['agent:0'].  "
-            "The nested mux.push() from the first channel.push() clobbered "
-            "_current_namespace before the second transformer ran."
-        )
@@ -1,161 +0,0 @@
-from typing import Any
-
-import pytest
-
-from langgraph.stream._convert import convert_to_protocol_event
-from langgraph.stream._types import ProtocolEvent
-from langgraph.stream.chat_model_stream import ChatModelStream
-from langgraph.stream.transformers import MessagesTransformer, ValuesTransformer
-
-
-def _event(
-    mode: str,
-    data: Any,
-    ns: list[str] | None = None,
-    node: str | None = None,
-) -> ProtocolEvent:
-    ev = convert_to_protocol_event(tuple(ns or []), mode, data, node=node)
-    assert ev is not None
-    return ev
-
-
-# -- ValuesTransformer ---------------------------------------------------------
-
-
-def test_values_captures_values_events():
-    reducer = ValuesTransformer()
-    reducer.init()
-    reducer.process(_event("values", {"a": 1}))
-    reducer.process(_event("values", {"b": 2}))
-    reducer.finalize()
-
-    assert len(reducer.values_log) == 2
-    assert reducer.values_log[0]["data"] == {"a": 1}
-    assert reducer.values_log[1]["data"] == {"b": 2}
-
-
-def test_values_ignores_other_modes():
-    reducer = ValuesTransformer()
-    reducer.init()
-    reducer.process(_event("updates", {"x": 1}))
-    reducer.process(_event("messages", {"event": "message-start"}))
-    reducer.finalize()
-
-    assert len(reducer.values_log) == 0
-
-
-def test_values_latest_per_namespace():
-    reducer = ValuesTransformer()
-    reducer.init()
-    reducer.process(_event("values", {"v": 1}, ns=["child:0"]))
-    reducer.process(_event("values", {"v": 2}, ns=["child:0"]))
-    assert reducer.get_latest("child:0") == {"v": 2}
-
-
-# -- MessagesTransformer -------------------------------------------------------
-
-
-def _msg_start(ns=None, node=None, message_id="msg-1"):
-    return _event(
-        "messages",
-        {"event": "message-start", "message_id": message_id},
-        ns=ns,
-        node=node,
-    )
-
-
-def _content_delta(text, ns=None, node=None):
-    return _event(
-        "messages",
-        {
-            "event": "content-block-delta",
-            "content_block": {"type": "text", "text": text},
-        },
-        ns=ns,
-        node=node,
-    )
-
-
-def _msg_finish(ns=None, node=None):
-    return _event(
-        "messages",
-        {"event": "message-finish", "reason": "stop"},
-        ns=ns,
-        node=node,
-    )
-
-
-def test_messages_groups_lifecycle():
-    reducer = MessagesTransformer()
-    reducer.init()
-    reducer.process(_msg_start())
-    reducer.process(_content_delta("hi"))
-    reducer.process(_msg_finish())
-    reducer.finalize()
-
-    assert len(reducer.messages_log) == 1
-    assert isinstance(reducer.messages_log[0], ChatModelStream)
-    assert reducer.messages_log[0].done
-
-
-def test_messages_multiple_sequential():
-    reducer = MessagesTransformer()
-    reducer.init()
-    reducer.process(_msg_start(message_id="m1"))
-    reducer.process(_msg_finish())
-    reducer.process(_msg_start(message_id="m2"))
-    reducer.process(_msg_finish())
-    reducer.finalize()
-
-    assert len(reducer.messages_log) == 2
-
-
-def test_messages_namespace_filter():
-    reducer = MessagesTransformer(namespace=["root"])
-    reducer.init()
-    reducer.process(_msg_start(ns=["root"]))
-    reducer.process(_msg_finish(ns=["root"]))
-    reducer.process(_msg_start(ns=["other"], message_id="m2"))
-    reducer.process(_msg_finish(ns=["other"]))
-    reducer.finalize()
-
-    assert len(reducer.messages_log) == 1
-
-
-def test_messages_node_filter():
-    reducer = MessagesTransformer(node_filter="agent")
-    reducer.init()
-    reducer.process(_msg_start(node="agent"))
-    reducer.process(_msg_finish(node="agent"))
-    reducer.process(_msg_start(node="tools", message_id="m2"))
-    reducer.process(_msg_finish(node="tools"))
-    reducer.finalize()
-
-    assert len(reducer.messages_log) == 1
-
-
-def test_messages_error_event():
-    """An error event should fail the active ChatModelStream."""
-    reducer = MessagesTransformer()
-    reducer.init()
-    reducer.process(_msg_start())
-    reducer.process(_content_delta("partial"))
-    reducer.process(
-        _event("messages", {"event": "error", "message": "connection lost"}),
-    )
-    reducer.finalize()
-
-    assert len(reducer.messages_log) == 1
-    assert reducer.messages_log[0].done
-
-
-def test_messages_fail_propagates_to_active():
-    """transformer.fail() should mark active streams as done."""
-    reducer = MessagesTransformer()
-    reducer.init()
-    reducer.process(_msg_start())
-    reducer.process(_content_delta("partial"))
-    reducer.fail(RuntimeError("graph failed"))
-
-    assert len(reducer.messages_log) == 1
-    assert reducer.messages_log[0].done
@@ -1,610 +0,0 @@
-import asyncio
-from collections.abc import AsyncIterator, Iterator
-from typing import Any
-
-import pytest
-
-from langgraph.stream._mux import AsyncStreamMux, StreamMux
-from langgraph.stream._types import ProtocolEvent
-from langgraph.stream.chat_model_stream import ChatModelStream
-from langgraph.stream.run_stream import (
-    AsyncGraphRunStream,
-    AsyncSubgraphRunStream,
-    create_async_graph_run_stream,
-    create_graph_run_stream,
-)
-from langgraph.stream.transformers import MessagesTransformer, ValuesTransformer
-
-
-async def _mock_source(
-    chunks: list[tuple[tuple[str, ...], str, Any]],
-) -> AsyncIterator[tuple[tuple[str, ...], str, Any]]:
-    for chunk in chunks:
-        yield chunk
-
-
-@pytest.mark.anyio
-async def test_aiter_yields_all_events():
-    chunks = [
-        ((), "values", {"step": 1}),
-        ((), "values", {"step": 2}),
-        ((), "updates", {"node": "a"}),
-    ]
-    run = await create_async_graph_run_stream(_mock_source(chunks))
-    await asyncio.sleep(0.05)
-
-    collected: list[ProtocolEvent] = []
-    async for event in run:
-        collected.append(event)
-    assert len(collected) == 3
-    assert collected[0]["method"] == "values"
-    assert collected[2]["method"] == "updates"
-
-
-@pytest.mark.anyio
-async def test_subgraph_name_and_index():
-    vr, mr = ValuesTransformer(), MessagesTransformer()
-    mux = AsyncStreamMux(transformers=[vr, mr])
-    sub = AsyncSubgraphRunStream(
-        mux=mux,
-        namespace=["researcher:2"],
-        transformers=[vr, mr],
-    )
-    assert sub.name == "researcher"
-    assert sub.index == 2
-
-
-@pytest.mark.anyio
-async def test_subgraph_name_no_index():
-    vr, mr = ValuesTransformer(), MessagesTransformer()
-    mux = AsyncStreamMux(transformers=[vr, mr])
-    sub = AsyncSubgraphRunStream(
-        mux=mux, namespace=["agent"], transformers=[vr, mr]
-    )
-    assert sub.name == "agent"
-    assert sub.index == 0
-
-
-@pytest.mark.anyio
-async def test_values_iterable():
-    chunks = [
-        ((), "values", {"v": 1}),
-        ((), "values", {"v": 2}),
-    ]
-    run = await create_async_graph_run_stream(_mock_source(chunks))
-    await asyncio.sleep(0.05)
-
-    collected = []
-    async for v in run.values:
-        collected.append(v)
-    assert len(collected) == 2
-    assert collected[0] == {"v": 1}
-    assert collected[1] == {"v": 2}
-
-
-@pytest.mark.anyio
-async def test_values_awaitable():
-    chunks = [
-        ((), "values", {"v": 1}),
-        ((), "values", {"v": 2}),
-    ]
-    run = await create_async_graph_run_stream(_mock_source(chunks))
-    await asyncio.sleep(0.05)
-
-    result = await run.values
-    assert result == {"v": 2}
-
-
-@pytest.mark.anyio
-async def test_output_resolves():
-    chunks = [((), "values", {"final": True})]
-    run = await create_async_graph_run_stream(_mock_source(chunks))
-    await asyncio.sleep(0.05)
-    result = await run.output
-    assert result == {"final": True}
-
-
-@pytest.mark.anyio
-async def test_messages_yields_streams():
-    chunks = [
-        ((), "messages", {"event": "message-start", "message_id": "m1"}),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "hi"},
-            },
-        ),
-        ((), "messages", {"event": "message-finish", "reason": "stop"}),
-    ]
-    run = await create_async_graph_run_stream(_mock_source(chunks))
-    await asyncio.sleep(0.05)
-
-    collected: list[ChatModelStream] = []
-    async for stream in run.messages:
-        collected.append(stream)
-    assert len(collected) == 1
-    assert isinstance(collected[0], ChatModelStream)
-    assert collected[0].done
-
-
-@pytest.mark.anyio
-async def test_interrupted_false_by_default():
-    vr, mr = ValuesTransformer(), MessagesTransformer()
-    mux = AsyncStreamMux(transformers=[vr, mr])
-    run = AsyncGraphRunStream(mux=mux, transformers=[vr, mr])
-    assert run.interrupted is False
-
-
-@pytest.mark.anyio
-async def test_abort_sets_signal():
-    vr, mr = ValuesTransformer(), MessagesTransformer()
-    mux = AsyncStreamMux(transformers=[vr, mr])
-    run = AsyncGraphRunStream(mux=mux, transformers=[vr, mr])
-    assert not run.signal.is_set()
-    run.abort()
-    assert run.signal.is_set()
-
-
-@pytest.mark.anyio
-async def test_abort_stops_pump():
-    """Calling abort() should stop the pump from processing further chunks."""
-    gate = asyncio.Event()
-
-    async def _gated_source():
-        yield ((), "values", {"v": 1})
-        yield ((), "values", {"v": 2})
-        await gate.wait()  # Block until released
-        yield ((), "values", {"v": 3})  # Should not be processed
-
-    run = await create_async_graph_run_stream(_gated_source())
-    await asyncio.sleep(0.05)  # Let first two events through
-    run.abort()
-    gate.set()  # Unblock the source so the pump can check abort and exit
-    await asyncio.sleep(0.05)  # Let pump close the mux
-
-    collected = []
-    async for event in run:
-        if event["method"] == "values":
-            collected.append(event["params"]["data"])
-    # v:3 should not have been processed because abort was set
-    assert all(v.get("v") != 3 for v in collected)
-
-
-@pytest.mark.anyio
-async def test_messages_from_filters_by_node():
-    """messages_from(node) should only yield messages from the specified node."""
-    chunks = [
-        (
-            (),
-            "messages",
-            {"event": "message-start", "message_id": "m1", "__node__": "agent"},
-        ),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "from agent"},
-                "__node__": "agent",
-            },
-        ),
-        (
-            (),
-            "messages",
-            {"event": "message-finish", "reason": "stop", "__node__": "agent"},
-        ),
-        (
-            (),
-            "messages",
-            {"event": "message-start", "message_id": "m2", "__node__": "tools"},
-        ),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "from tools"},
-                "__node__": "tools",
-            },
-        ),
-        (
-            (),
-            "messages",
-            {"event": "message-finish", "reason": "stop", "__node__": "tools"},
-        ),
-    ]
-    run = await create_async_graph_run_stream(_mock_source(chunks))
-    await asyncio.sleep(0.05)
-
-    agent_msgs: list[ChatModelStream] = []
-    async for stream in run.messages_from("agent"):
-        agent_msgs.append(stream)
-    assert len(agent_msgs) == 1
-    assert agent_msgs[0].node == "agent"
-
-
-# ---------------------------------------------------------------------------
-# GraphRunStream / create_graph_run_stream
-# ---------------------------------------------------------------------------
-
-
-def _sync_source(
-    chunks: list[tuple[tuple[str, ...], str, Any]],
-) -> Iterator[tuple[tuple[str, ...], str, Any]]:
-    yield from chunks
-
-
-def test_sync_create_yields_all_events():
-    chunks = [
-        ((), "values", {"step": 1}),
-        ((), "values", {"step": 2}),
-        ((), "updates", {"node": "a"}),
-    ]
-    run = create_graph_run_stream(_sync_source(chunks))
-    collected = list(run)
-    assert len(collected) == 3
-    assert collected[0]["method"] == "values"
-    assert collected[2]["method"] == "updates"
-
-
-def test_sync_output():
-    chunks = [
-        ((), "values", {"v": 1}),
-        ((), "values", {"v": 2}),
-    ]
-    run = create_graph_run_stream(_sync_source(chunks))
-    assert run.output == {"v": 2}
-
-
-def test_sync_values_iteration():
-    chunks = [
-        ((), "values", {"v": 1}),
-        ((), "values", {"v": 2}),
-    ]
-    run = create_graph_run_stream(_sync_source(chunks))
-    collected = list(run.values)
-    assert len(collected) == 2
-    assert collected[0] == {"v": 1}
-    assert collected[1] == {"v": 2}
-
-
-def test_sync_messages():
-    chunks = [
-        ((), "messages", {"event": "message-start", "message_id": "m1"}),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "hi"},
-            },
-        ),
-        ((), "messages", {"event": "message-finish", "reason": "stop"}),
-    ]
-    run = create_graph_run_stream(_sync_source(chunks))
-    collected = list(run.messages)
-    assert len(collected) == 1
-    assert isinstance(collected[0], ChatModelStream)
-    assert collected[0].done
-
-
-def test_sync_messages_text_accessible():
-    """Sync consumers should be able to read ChatModelStream text content
-    without an async event loop.
-    """
-    chunks = [
-        ((), "messages", {"event": "message-start", "message_id": "m1"}),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "Hello"},
-            },
-        ),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": " world"},
-            },
-        ),
-        ((), "messages", {"event": "message-finish", "reason": "stop"}),
-    ]
-    run = create_graph_run_stream(_sync_source(chunks))
-
-    for msg in run.messages:
-        assert isinstance(msg.text, str)
-        assert msg.text == "Hello world"
-        assert msg.done
-
-
-def test_sync_messages_content_populated_when_yielded():
-    """When sync run.messages yields a ChatModelStream, its content should
-    be fully populated (done=True) with all text accumulated.
-    """
-    chunks = [
-        ((), "messages", {"event": "message-start", "message_id": "m1"}),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "answer"},
-            },
-        ),
-        ((), "messages", {"event": "message-finish", "reason": "stop"}),
-        ((), "messages", {"event": "message-start", "message_id": "m2"}),
-        (
-            (),
-            "messages",
-            {
-                "event": "content-block-delta",
-                "content_block": {"type": "text", "text": "second"},
-            },
-        ),
-        ((), "messages", {"event": "message-finish", "reason": "stop"}),
-    ]
-    run = create_graph_run_stream(_sync_source(chunks))
-
-    messages = list(run.messages)
-    assert len(messages) == 2
-    assert messages[0].done
-    assert messages[0].text == "answer"
-    assert messages[1].done
-    assert messages[1].text == "second"
-
-
-def test_sync_output_mapper():
-    chunks = [((), "values", {"v": 1})]
-    run = create_graph_run_stream(
-        _sync_source(chunks), output_mapper=lambda x: {"mapped": x["v"]}
-    )
-    assert run.output == {"mapped": 1}
-
-
-def test_sync_interrupted_false():
-    chunks = [((), "values", {"v": 1})]
-    run = create_graph_run_stream(_sync_source(chunks))
-    assert run.interrupted is False
-
-
-def test_sync_source_error():
-    """If the source raises, the mux should fail and the error should propagate."""
-
-    def _bad_source():
-        yield ((), "values", {"v": 1})
-        raise ValueError("source error")
-
-    run = create_graph_run_stream(_bad_source())
-    collected = list(run)
-    # Events before the error are still accessible
-    assert len(collected) >= 1
-    assert collected[0]["method"] == "values"
-    # The mux recorded the failure
-    assert run._mux._error is not None
-    assert isinstance(run._mux._error, ValueError)
-    assert "source error" in str(run._mux._error)
-
-
-# ---------------------------------------------------------------------------
-# GraphRunStream — lazy consumption tests
-# ---------------------------------------------------------------------------
-
-
-def test_sync_lazy_not_consumed_on_creation():
-    """Source iterator should not be consumed when the stream is created."""
-    consumed = 0
-
-    def counting_source():
-        nonlocal consumed
-        for chunk in [
-            ((), "values", {"v": 1}),
-            ((), "values", {"v": 2}),
-            ((), "values", {"v": 3}),
-        ]:
-            consumed += 1
-            yield chunk
-
-    create_graph_run_stream(counting_source())
-    assert consumed == 0
-
-
-def test_sync_lazy_values_pull_incrementally():
-    """Iterating .values should pull from the source one event at a time."""
-    consumed = 0
-
-    def counting_source():
-        nonlocal consumed
-        for chunk in [
-            ((), "values", {"v": 1}),
-            ((), "values", {"v": 2}),
-            ((), "values", {"v": 3}),
-        ]:
-            consumed += 1
-            yield chunk
-
-    run = create_graph_run_stream(counting_source())
-    assert consumed == 0
-
-    it = iter(run.values)
-    v = next(it)
-    assert v == {"v": 1}
-    assert consumed == 1
-
-    v = next(it)
-    assert v == {"v": 2}
-    assert consumed == 2
-
-    # Source not fully drained yet
-    assert consumed < 3
-
-
-def test_sync_lazy_output_drains_all():
-    """Accessing .output should drain the entire source."""
-    consumed = 0
-
-    def counting_source():
-        nonlocal consumed
-        for chunk in [((), "values", {"v": i}) for i in range(5)]:
-            consumed += 1
-            yield chunk
-
-    run = create_graph_run_stream(counting_source())
-    assert consumed == 0
-    assert run.output == {"v": 4}
-    assert consumed == 5
-
-
-def test_sync_lazy_early_break():
-    """Breaking out of a projection early should leave the source partially consumed."""
-    consumed = 0
-
-    def counting_source():
-        nonlocal consumed
-        for chunk in [((), "values", {"v": i}) for i in range(10)]:
-            consumed += 1
-            yield chunk
-
-    run = create_graph_run_stream(counting_source())
-    for v in run.values:
-        break  # consume only the first value
-    assert consumed == 1
-    assert consumed < 10
-
-
-def test_sync_lazy_interleaved_projections():
-    """Switching between projections replays buffered items then resumes pumping."""
-    consumed = 0
-
-    def counting_source():
-        nonlocal consumed
-        for chunk in [
-            ((), "values", {"v": 1}),
-            ((), "messages", {"event": "message-start", "message_id": "m1"}),
-            ((), "messages", {"event": "message-finish", "reason": "stop"}),
-            ((), "values", {"v": 2}),
-        ]:
-            consumed += 1
-            yield chunk
-
-    run = create_graph_run_stream(counting_source())
-
-    # Pull first value — consumes 1 source item
-    vit = iter(run.values)
-    assert next(vit) == {"v": 1}
-    assert consumed == 1
-
-    # Pull first message — pumps until message-finish (item 3) so the
-    # ChatModelStream is fully populated before yielding.
-    mit = iter(run.messages)
-    msg = next(mit)
-    assert isinstance(msg, ChatModelStream)
-    assert msg.done
-    assert consumed == 3
-
-    # Pull second value — pumps values (item 4)
-    assert next(vit) == {"v": 2}
-    assert consumed == 4
-
-
-def test_sync_lazy_iter_pulls_incrementally():
-    """Raw __iter__ should pull from the source lazily."""
-    consumed = 0
-
-    def counting_source():
-        nonlocal consumed
-        for chunk in [
-            ((), "values", {"v": 1}),
-            ((), "updates", {"node": "a"}),
-            ((), "values", {"v": 2}),
-        ]:
-            consumed += 1
-            yield chunk
-
-    run = create_graph_run_stream(counting_source())
-    it = iter(run)
-    event = next(it)
-    assert event["method"] == "values"
-    assert consumed == 1
-
-    event = next(it)
-    assert event["method"] == "updates"
-    assert consumed == 2
-
-
-def test_sync_lazy_source_error():
-    """If the source raises mid-stream, earlier events are still accessible."""
-    consumed = 0
-
-    def bad_source():
-        nonlocal consumed
-        consumed += 1
-        yield ((), "values", {"v": 1})
-        raise ValueError("boom")
-
-    run = create_graph_run_stream(bad_source())
-    collected = list(run)
-    assert len(collected) >= 1
-    assert collected[0]["method"] == "values"
-
-
-@pytest.mark.anyio
-async def test_subgraph_child_values_receive_post_discovery_events():
-    """Child AsyncSubgraphRunStream.values iteration should include events
-    that arrive AFTER the subgraph namespace is first discovered.
-
-    ``_SubgraphsProjection`` creates a local ``ValuesTransformer`` for
-    each child and replays existing events, but never registers the
-    transformer with the mux.  Events that arrive after discovery are
-    not routed to it, and ``finalize()`` is not called (the mux wasn't
-    closed at discovery time), so the child's values_log is never
-    closed and iteration hangs.
-    """
-    gate = asyncio.Event()
-
-    async def _source() -> AsyncIterator[tuple[tuple[str, ...], str, Any]]:
-        # First event from child namespace — triggers discovery
-        yield (("child:0",), "values", {"v": 1})
-        await gate.wait()
-        # Second event from same child — arrives after discovery
-        yield (("child:0",), "values", {"v": 2})
-        # Root event so the mux tracks output
-        yield ((), "values", {"done": True})
-
-    run = await create_async_graph_run_stream(_source())
-    await asyncio.sleep(0.05)  # let pump process first event
-
-    # Get the first subgraph while the mux is still open
-    sub = None
-    async for s in run.subgraphs:
-        sub = s
-        break
-
-    assert sub is not None
-
-    # Release the gate so the pump finishes
-    gate.set()
-    await asyncio.sleep(0.05)  # let pump close mux
-
-    # ``await sub.output`` uses the mux's output future — works fine
-    output = await sub.output
-    assert output == {"v": 2}, "await sub.output should reflect the latest value"
-
-    # But ``async for v in sub.values`` only gets the replayed event
-    # and then hangs because the child's values_log is never closed.
-    values: list[Any] = []
-    try:
-        async with asyncio.timeout(1.0):
-            async for v in sub.values:
-                values.append(v)
-    except (asyncio.TimeoutError, TimeoutError):
-        pass
-
-    assert len(values) == 2, (
-        f"Expected 2 child value snapshots but got {len(values)}: {values}.  "
-        "Child transformer missed post-discovery events."
-    )
@@ -1,420 +0,0 @@
-"""Prove V1 and StreamingHandler APIs expose identical information.
-
-Each test runs the same graph through both APIs and asserts data
-equivalence — same state snapshots, same messages, same custom events,
-same interrupts.  Sync APIs are used where possible; async tests cover
-features without sync equivalents (subgraphs projection, messages_from).
-
-Run with:
-    TEST=tests/test_streaming_comparison.py make test
-"""
-
-from __future__ import annotations
-
-from typing import Annotated
-
-import pytest
-from langchain_core.messages import AIMessage, HumanMessage
-from langgraph.checkpoint.memory import MemorySaver
-from typing_extensions import TypedDict
-
-from langgraph.config import get_stream_writer
-from langgraph.graph import END, START, MessagesState, StateGraph
-from langgraph.stream import StreamingHandler
-from langgraph.stream._convert import STREAM_V2_MODES
-from langgraph.types import interrupt
-from tests.fake_chat import FakeChatModel
-
-# ---------------------------------------------------------------------------
-# Graph factories
-# ---------------------------------------------------------------------------
-
-
-class State(TypedDict):
-    value: str
-    items: Annotated[list[str], lambda a, b: a + b]
-
-
-def _linear_graph(n_nodes: int = 3):
-    """Chain of *n_nodes* that concatenate strings."""
-    g = StateGraph(State)
-    names = [f"node_{i}" for i in range(n_nodes)]
-    for name in names:
-
-        def make_fn(n):
-            def fn(state: State) -> dict:
-                return {"value": state["value"] + f"_{n}", "items": [n]}
-
-            return fn
-
-        g.add_node(name, make_fn(name))
-
-    g.add_edge(START, names[0])
-    for i in range(len(names) - 1):
-        g.add_edge(names[i], names[i + 1])
-    g.add_edge(names[-1], END)
-    return g.compile()
-
-
-def _chat_graph():
-    """Single agent node with a FakeChatModel."""
-    model = FakeChatModel(messages=[AIMessage(content="Hello from agent")])
-
-    def agent(state: dict) -> dict:
-        return {"messages": [model.invoke(state["messages"])]}
-
-    g = StateGraph(MessagesState)
-    g.add_node("agent", agent)
-    g.add_edge(START, "agent")
-    g.add_edge("agent", END)
-    return g.compile()
-
-
-def _multi_node_chat_graph():
-    """Two LLM nodes: agent -> reviewer."""
-    agent_model = FakeChatModel(messages=[AIMessage(content="Agent reply")])
-    reviewer_model = FakeChatModel(messages=[AIMessage(content="Reviewer reply")])
-
-    def agent(state: dict) -> dict:
-        return {"messages": [agent_model.invoke(state["messages"])]}
-
-    def reviewer(state: dict) -> dict:
-        return {"messages": [reviewer_model.invoke(state["messages"])]}
-
-    g = StateGraph(MessagesState)
-    g.add_node("agent", agent)
-    g.add_node("reviewer", reviewer)
-    g.add_edge(START, "agent")
-    g.add_edge("agent", "reviewer")
-    g.add_edge("reviewer", END)
-    return g.compile()
-
-
-def _custom_events_graph():
-    """Node that emits custom events via StreamWriter."""
-
-    def worker(state: State) -> dict:
-        writer = get_stream_writer()
-        writer({"step": 1, "msg": "started"})
-        writer({"step": 2, "msg": "processing"})
-        writer({"step": 3, "msg": "done"})
-        return {"value": state["value"] + "_done", "items": ["done"]}
-
-    g = StateGraph(State)
-    g.add_node("worker", worker)
-    g.add_edge(START, "worker")
-    g.add_edge("worker", END)
-    return g.compile()
-
-
-def _interrupt_graph():
-    """Graph that interrupts for human input."""
-
-    def ask_human(state: State) -> dict:
-        answer = interrupt("What next?")
-        return {"value": state["value"] + f"_{answer}", "items": [answer]}
-
-    g = StateGraph(State)
-    g.add_node("ask", ask_human)
-    g.add_edge(START, "ask")
-    g.add_edge("ask", END)
-    return g.compile(checkpointer=MemorySaver())
-
-
-def _subgraph():
-    """Parent with a compiled child subgraph."""
-
-    class ChildState(TypedDict):
-        value: str
-
-    class ParentState(TypedDict):
-        value: str
-
-    def child_node(state: ChildState) -> dict:
-        return {"value": state["value"] + "_child"}
-
-    child = StateGraph(ChildState)
-    child.add_node("inner", child_node)
-    child.add_edge(START, "inner")
-    child.add_edge("inner", END)
-    child_compiled = child.compile()
-
-    parent = StateGraph(ParentState)
-    parent.add_node("child", child_compiled)
-    parent.add_edge(START, "child")
-    parent.add_edge("child", END)
-    return parent.compile()
-
-
-# ===================================================================
-# 1. Final output
-# ===================================================================
-
-
-def test_output():
-    """graph.invoke() produces the same result as StreamingHandler().stream().output."""
-    graph = _linear_graph()
-    inp = {"value": "x", "items": []}
-
-    v1 = graph.invoke(inp)
-
-    run = StreamingHandler(graph).stream(inp)
-    v2 = run.output
-
-    assert v1 == v2
-
-
-# ===================================================================
-# 2. Intermediate state snapshots (values mode)
-# ===================================================================
-
-
-def test_values():
-    """stream(mode='values') snapshots == StreamingHandler().stream().values snapshots."""
-    graph = _linear_graph()
-    inp = {"value": "x", "items": []}
-
-    v1 = list(graph.stream(inp, stream_mode="values"))
-
-    run = StreamingHandler(graph).stream(inp)
-    v2 = list(run.values)
-
-    assert v1 == v2
-
-
-# ===================================================================
-# 3. Per-node updates (updates mode)
-# ===================================================================
-
-
-def test_updates():
-    """stream(mode='updates') data == StreamingHandler raw events[method=updates]."""
-    graph = _linear_graph()
-    inp = {"value": "x", "items": []}
-
-    v1 = list(graph.stream(inp, stream_mode="updates"))
-
-    run = StreamingHandler(graph).stream(inp)
-    v2 = [
-        e["params"]["data"]
-        for e in run
-        if e["method"] == "updates" and not e["params"]["namespace"]
-    ]
-
-    assert v1 == v2
-
-
-# ===================================================================
-# 4. Message text and node attribution
-# ===================================================================
-
-
-def test_messages():
-    """Reassembled V1 message text per node == V2 .messages text per node."""
-    graph = _multi_node_chat_graph()
-    inp = {"messages": [HumanMessage(content="hi")]}
-
-    # V1: collect (chunk, metadata) pairs, group text by node
-    v1_text_by_node: dict[str, list[str]] = {}
-    for chunk, metadata in graph.stream(inp, stream_mode="messages"):
-        node = metadata["langgraph_node"]
-        v1_text_by_node.setdefault(node, []).append(chunk.content)
-    v1_text = {k: "".join(v) for k, v in v1_text_by_node.items()}
-
-    # V2: each ChatModelStream has .text and .node
-    run = StreamingHandler(graph).stream(inp)
-    v2_text: dict[str, str] = {}
-    for msg in run.messages:
-        assert msg.done is True
-        v2_text[msg.node] = msg.text
-
-    assert v1_text == v2_text
-
-
-# ===================================================================
-# 5. Custom events
-# ===================================================================
-
-
-def test_custom_events():
-    """stream(mode='custom') payloads == StreamingHandler raw events[method=custom]."""
-    graph = _custom_events_graph()
-    inp = {"value": "x", "items": []}
-
-    v1 = list(graph.stream(inp, stream_mode="custom"))
-
-    run = StreamingHandler(graph).stream(inp)
-    v2 = [
-        e["params"]["data"]
-        for e in run
-        if e["method"] == "custom" and not e["params"]["namespace"]
-    ]
-
-    assert v1 == v2
-
-
-# ===================================================================
-# 6. Mode coverage
-# ===================================================================
-
-
-def test_mode_coverage():
-    """V2 produces events for the same set of modes as V1."""
-    graph = _chat_graph()
-    inp = {"messages": [HumanMessage(content="hi")]}
-
-    # V1: request all modes, collect which ones appear
-    v1_modes: set[str] = set()
-    for ns, mode, _ in graph.stream(
-        inp, stream_mode=STREAM_V2_MODES, subgraphs=True, version="v1"
-    ):
-        if not ns:
-            v1_modes.add(mode)
-
-    # V2: iterate raw events, collect methods
-    run = StreamingHandler(graph).stream(inp)
-    v2_modes = {e["method"] for e in run if not e["params"]["namespace"]}
-
-    assert v1_modes == v2_modes
-
-
-# ===================================================================
-# 7. Interrupt detection
-# ===================================================================
-
-
-def test_interrupts():
-    """V1 __interrupt__ value == V2 .interrupted and .interrupts payload."""
-    graph = _interrupt_graph()
-    inp = {"value": "x", "items": []}
-
-    # V1: detect __interrupt__ in values stream
-    config1 = {"configurable": {"thread_id": "equiv-1"}}
-    v1_interrupt_value = None
-    for chunk in graph.stream(inp, config1, stream_mode="values"):
-        if isinstance(chunk, dict) and "__interrupt__" in chunk:
-            info = chunk["__interrupt__"]
-            if info:
-                v1_interrupt_value = info[0].value
-
-    assert v1_interrupt_value is not None
-
-    # V2: .interrupted and .interrupts (fresh thread)
-    config2 = {"configurable": {"thread_id": "equiv-2"}}
-    run = StreamingHandler(graph).stream(inp, config=config2)
-    for _ in run:
-        pass
-
-    assert run.interrupted is True
-    assert len(run.interrupts) > 0
-    v2_interrupt_value = run.interrupts[0]["payload"].value
-
-    assert v1_interrupt_value == v2_interrupt_value
-
-
-# ===================================================================
-# 8. Subgraph state snapshots
-# ===================================================================
-
-
-def test_subgraph_values():
-    """V1 child namespace values == V2 child namespace values."""
-    graph = _subgraph()
-    inp = {"value": "x"}
-
-    # V1: stream with subgraphs=True, collect child values
-    v1_child_values = []
-    for ns, data in graph.stream(inp, stream_mode="values", subgraphs=True):
-        if ns:
-            v1_child_values.append(data)
-
-    # V2: filter raw events for child namespace + values mode
-    run = StreamingHandler(graph).stream(inp)
-    v2_child_values = [
-        e["params"]["data"]
-        for e in run
-        if e["method"] == "values" and e["params"]["namespace"]
-    ]
-
-    assert v1_child_values == v2_child_values
-
-
-# ===================================================================
-# 9. Node filtering on messages
-# ===================================================================
-
-
-def test_messages_node_filtering():
-    """V1 manual metadata filter == V2 .messages filtered by .node."""
-    graph = _multi_node_chat_graph()
-    inp = {"messages": [HumanMessage(content="hi")]}
-
-    # V1: manual filter for "agent" node only
-    v1_agent_text: list[str] = []
-    for chunk, metadata in graph.stream(inp, stream_mode="messages"):
-        if metadata.get("langgraph_node") == "agent":
-            v1_agent_text.append(chunk.content)
-    v1_text = "".join(v1_agent_text)
-
-    # V2: filter .messages by .node
-    run = StreamingHandler(graph).stream(inp)
-    v2_agent_msgs = [msg for msg in run.messages if msg.node == "agent"]
-    assert len(v2_agent_msgs) == 1
-    v2_text = v2_agent_msgs[0].text
-
-    assert v1_text == v2_text
-
-
-# ===================================================================
-# 10. Async: subgraphs projection
-# ===================================================================
-
-
-@pytest.mark.anyio
-async def test_async_subgraph_projection():
-    """V2 .subgraphs child output matches V1 child namespace output."""
-    graph = _subgraph()
-    inp = {"value": "x"}
-
-    # V1
-    v1_child_output = None
-    async for ns, data in graph.astream(inp, stream_mode="values", subgraphs=True):
-        if ns:
-            v1_child_output = data
-
-    # V2: .subgraphs yields typed child stream objects
-    run = await StreamingHandler(graph).astream(inp)
-    v2_child_output = None
-    async for sub in run.subgraphs:
-        v2_child_output = await sub.output
-
-    assert v1_child_output == v2_child_output
-
-
-# ===================================================================
-# 11. Async: messages_from projection
-# ===================================================================
-
-
-@pytest.mark.anyio
-async def test_async_messages_from():
-    """V2 .messages_from('agent') text matches V1 filtered by metadata."""
-    graph = _multi_node_chat_graph()
-    inp = {"messages": [HumanMessage(content="hi")]}
-
-    # V1: manual filter for agent node
-    v1_agent_text: list[str] = []
-    async for chunk, metadata in graph.astream(inp, stream_mode="messages"):
-        if metadata.get("langgraph_node") == "agent":
-            v1_agent_text.append(chunk.content)
-    v1_text = "".join(v1_agent_text)
-
-    # V2: declarative node filtering
-    run = await StreamingHandler(graph).astream(inp)
-    v2_texts: list[str] = []
-    async for msg in run.messages_from("agent"):
-        v2_texts.append(await msg.text)
-    assert len(v2_texts) == 1
-    v2_text = v2_texts[0]
-
-    assert v1_text == v2_text
@@ -37,6 +37,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
    Returns a list of dicts (newest-first, matching get_state_history order) with:
      - id: short checkpoint id suffix (last 6 chars)
      - parent_id: short parent checkpoint id suffix or None
+      - source: checkpoint metadata source (input, loop, fork, update)
      - next: tuple of next node names
      - values: channel values snapshot
    """
@@ -52,6 +53,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
            {
                "id": cid[-6:],
                "parent_id": pid[-6:] if pid else None,
+                "source": s.metadata.get("source"),
                "next": s.next,
                "values": s.values,
            }
@@ -280,6 +282,116 @@ def test_replay_from_before_interrupt_refires(
    assert call_count["node_b"] == 1  # NOT re-executed (after interrupt)


+def test_replay_from_before_interrupt_then_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Replay from checkpoint before interrupt node, then resume with a new
+    answer and verify the graph completes with the new value.
+
+    Graph: START --> node_a --> ask_human (interrupt) --> node_b --> END
+
+    Original run:
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(node_a,)     values=[]
+      source=loop   next=(ask_human,)  values=[a]            <-- replay from here
+      source=loop   next=(node_b,)     values=[a, human:old_answer]
+      source=loop   next=()            values=[a, human:old_answer, b]
+
+    After replay (fork created) + resume with "new_answer":
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(node_a,)     values=[]
+      source=loop   next=(ask_human,)  values=[a]            <-- branch point
+      source=loop   next=(node_b,)     values=[a, human:old_answer]
+      source=loop   next=()            values=[a, human:old_answer, b]  (old branch)
+      source=fork   next=(ask_human,)  values=[a]            <-- fork from branch point
+      source=loop   next=(node_b,)     values=[a, human:new_answer]
+      source=loop   next=()            values=[a, human:new_answer, b]  (new branch)
+    """
+
+    called: list[str] = []
+
+    def node_a(state: State) -> State:
+        called.append("node_a")
+        return {"value": ["a"]}
+
+    def ask_human(state: State) -> State:
+        called.append("ask_human")
+        answer = interrupt("What is your input?")
+        return {"value": [f"human:{answer}"]}
+
+    def node_b(state: State) -> State:
+        called.append("node_b")
+        return {"value": ["b"]}
+
+    graph = (
+        StateGraph(State)
+        .add_node("node_a", node_a)
+        .add_node("ask_human", ask_human)
+        .add_node("node_b", node_b)
+        .add_edge(START, "node_a")
+        .add_edge("node_a", "ask_human")
+        .add_edge("ask_human", "node_b")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: invoke until interrupt, then resume to complete ---
+    graph.invoke({"value": []}, config)
+    graph.invoke(Command(resume="old_answer"), config)
+
+    original_history = list(graph.get_state_history(config))
+    original = _checkpoint_summary(original_history)
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Replay from checkpoint before ask_human ---
+    before_ask = next(s for s in original_history if s.next == ("ask_human",))
+
+    called.clear()
+    replay_result = graph.invoke(None, before_ask.config)
+    assert replay_result["__interrupt__"][0].value == "What is your input?"
+    assert "ask_human" in called
+    assert "node_a" not in called  # before the replay point, not re-executed
+
+    # A fork checkpoint is now the latest — it branches from the replay point
+    post_replay = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"]) for s in post_replay] == [
+        ("fork", ("ask_human",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("node_b",)),
+        ("loop", ("ask_human",)),  # branch point
+        ("loop", ("node_a",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer ---
+    called.clear()
+    final_result = graph.invoke(Command(resume="new_answer"), config)
+    assert final_result["value"] == ["a", "human:new_answer", "b"]
+    assert "ask_human" in called
+    assert "node_b" in called
+
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from fork)
+        ("loop", (), {"value": ["a", "human:new_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:new_answer"]}),
+        ("fork", ("ask_human",), {"value": ["a"]}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
 def test_replay_interrupt_stable_across_replays(
    sync_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -320,8 +432,14 @@ def test_replay_interrupt_stable_across_replays(
        r = graph.invoke(None, before_ask.config)
        results.append(r)

-    assert all(r == results[0] for r in results)
-    assert "__interrupt__" in results[0]
+    # Each replay creates a fork with a unique interrupt ID, so we compare
+    # interrupt values and state values rather than full equality.
+    assert all("__interrupt__" in r for r in results)
+    assert all(
+        r["__interrupt__"][0].value == results[0]["__interrupt__"][0].value
+        for r in results
+    )
+    assert all(r["value"] == results[0]["value"] for r in results)


 def test_fork_from_before_interrupt_refires(
@@ -854,6 +972,354 @@ def test_subgraph_interrupt_replay_from_interrupt_checkpoint(
    assert "step_b" not in called


+def test_subgraph_interrupt_replay_from_parent_then_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Replay from the parent checkpoint where a subgraph interrupt fired,
+    then resume with a new answer. Verifies that a fork is created and the
+    full graph completes. Checks full checkpoint history at each stage."""
+
+    called: list[str] = []
+
+    def router(state: State) -> State:
+        called.append("router")
+        return {"value": ["routed"]}
+
+    def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["sub_a"]}
+
+    def ask_human(state: State) -> State:
+        called.append("ask_human")
+        answer = interrupt("Provide input:")
+        return {"value": [f"human:{answer}"]}
+
+    def step_b(state: State) -> State:
+        called.append("step_b")
+        return {"value": ["sub_b"]}
+
+    subgraph = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_human", ask_human)
+        .add_node("step_b", step_b)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_human")
+        .add_edge("ask_human", "step_b")
+        .compile(checkpointer=True)
+    )
+
+    def post_process(state: State) -> State:
+        called.append("post_process")
+        return {"value": ["post"]}
+
+    graph = (
+        StateGraph(State)
+        .add_node("router", router)
+        .add_node("subgraph_node", subgraph)
+        .add_node("post_process", post_process)
+        .add_edge(START, "router")
+        .add_edge("router", "subgraph_node")
+        .add_edge("subgraph_node", "post_process")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt, then resume to complete
+    graph.invoke({"value": []}, config)
+    graph.invoke(Command(resume="old_answer"), config)
+
+    # Original parent history (newest first)
+    original_history = list(graph.get_state_history(config))
+    assert [s.next for s in original_history] == [
+        (),  # done
+        ("post_process",),
+        ("subgraph_node",),  # subgraph ran, interrupt fired here
+        ("router",),
+        ("__start__",),
+    ]
+
+    # Find the parent checkpoint where the interrupt fired
+    interrupt_checkpoint = next(
+        s for s in original_history if s.next == ("subgraph_node",)
+    )
+
+    # Replay from parent checkpoint — subgraph re-executes, interrupt re-fires
+    called.clear()
+    replay_result = graph.invoke(None, interrupt_checkpoint.config)
+    assert "__interrupt__" in replay_result
+    assert replay_result["__interrupt__"][0].value == "Provide input:"
+    assert "step_a" in called
+    assert "ask_human" in called
+    assert "step_b" not in called
+
+    # Verify fork checkpoint was created
+    post_replay_history = list(graph.get_state_history(config))
+    assert [s.next for s in post_replay_history] == [
+        ("subgraph_node",),  # fork (interrupt pending)
+        (),  # original done
+        ("post_process",),
+        ("subgraph_node",),
+        ("router",),
+        ("__start__",),
+    ]
+    assert [s.metadata["source"] for s in post_replay_history] == [
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+    fork = post_replay_history[0]
+    assert (
+        fork.parent_config["configurable"]["checkpoint_id"]
+        == interrupt_checkpoint.config["configurable"]["checkpoint_id"]
+    )
+
+    # Resume with a new answer — full graph should complete
+    called.clear()
+    final_result = graph.invoke(Command(resume="new_answer"), config)
+    assert "__interrupt__" not in final_result
+    assert "human:new_answer" in final_result["value"]
+    assert "sub_b" in final_result["value"]
+    assert "post" in final_result["value"]
+    assert "ask_human" in called
+    assert "step_b" in called
+    assert "post_process" in called
+
+    # Final checkpoint history
+    final_history = list(graph.get_state_history(config))
+    assert [s.next for s in final_history] == [
+        (),  # new branch done
+        ("post_process",),  # new branch post_process
+        ("subgraph_node",),  # fork
+        (),  # original done
+        ("post_process",),
+        ("subgraph_node",),
+        ("router",),
+        ("__start__",),
+    ]
+    assert [s.metadata["source"] for s in final_history] == [
+        "loop",
+        "loop",
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+
+
+def test_subgraph_interrupt_resume_with_explicit_head_checkpoint_id(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Resume with Command(resume=...) plus the current head checkpoint_id
+    in config. The subgraph must continue from the interrupted node, not
+    restart from scratch. Explicit checkpoint_id triggers is_replaying but
+    this is a resume, not a time-travel, so ReplayState should not apply."""
+
+    called: list[str] = []
+
+    def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["sub_a"]}
+
+    def ask_human(state: State) -> State:
+        called.append("ask_human")
+        answer = interrupt("Provide input:")
+        return {"value": [f"human:{answer}"]}
+
+    def step_b(state: State) -> State:
+        called.append("step_b")
+        return {"value": ["sub_b"]}
+
+    subgraph = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_human", ask_human)
+        .add_node("step_b", step_b)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_human")
+        .add_edge("ask_human", "step_b")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("subgraph_node", subgraph)
+        .add_edge(START, "subgraph_node")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt fires in subgraph
+    graph.invoke({"value": []}, config)
+    assert called == ["step_a", "ask_human"]
+
+    # Resume with explicit head checkpoint_id in config
+    head_checkpoint_id = graph.get_state(config).config["configurable"]["checkpoint_id"]
+    called.clear()
+    resume_config = {
+        "configurable": {
+            "thread_id": "1",
+            "checkpoint_id": head_checkpoint_id,
+            "checkpoint_ns": "",
+        }
+    }
+    result = graph.invoke(Command(resume="answer"), resume_config)
+
+    assert called == ["ask_human", "step_b"]
+    assert "__interrupt__" not in result
+    assert result["value"] == ["sub_a", "human:answer", "sub_b"]
+
+
+def test_subgraph_replay_loads_accumulated_state_then_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Two parent invocations, then replay from before the subgraph in the
+    2nd invocation. The subgraph (checkpointer=True) should load its
+    accumulated state from the 1st invocation via ReplayState, re-fire
+    the interrupt, and then resume + complete.
+
+    This tests the ReplayState path: the parent is replaying and the
+    subgraph uses list(before=parent_checkpoint_id) to find its
+    corresponding checkpoint from the original execution.
+    """
+
+    class SubState(TypedDict):
+        value: Annotated[list[str], operator.add]
+
+    class ParentState(TypedDict):
+        results: Annotated[list[str], operator.add]
+
+    started_state: list[dict] = []
+
+    def step_a(state: SubState) -> SubState:
+        started_state.append(dict(state))
+        answer = interrupt("question_a")
+        return {"value": [f"a:{answer}"]}
+
+    subgraph = (
+        StateGraph(SubState)
+        .add_node("step_a", step_a)
+        .add_edge(START, "step_a")
+        .compile(checkpointer=True)
+    )
+
+    def parent_node(state: ParentState) -> ParentState:
+        return {"results": ["p"]}
+
+    graph = (
+        StateGraph(ParentState)
+        .add_node("parent_node", parent_node)
+        .add_node("sub_node", subgraph)
+        .add_edge(START, "parent_node")
+        .add_edge("parent_node", "sub_node")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # === 1st invocation: complete with answer "a1" ===
+    graph.invoke({"results": []}, config)
+    graph.invoke(Command(resume="a1"), config)
+
+    # step_a saw empty state (fresh subgraph)
+    assert started_state[0] == {"value": []}
+
+    # === 2nd invocation: complete with answer "a2" ===
+    started_state.clear()
+    graph.invoke({"results": []}, config)
+    graph.invoke(Command(resume="a2"), config)
+
+    # Stateful subgraph retained state from 1st invocation
+    assert started_state[0] == {"value": ["a:a1"]}
+
+    # Original history (newest first)
+    original_history = list(graph.get_state_history(config))
+    assert [s.next for s in original_history] == [
+        (),  # 2nd done
+        ("sub_node",),  # 2nd sub_node
+        ("parent_node",),  # 2nd parent_node
+        ("__start__",),  # 2nd input
+        (),  # 1st done
+        ("sub_node",),  # 1st sub_node
+        ("parent_node",),  # 1st parent_node
+        ("__start__",),  # 1st input
+    ]
+
+    # Replay from before sub_node in 2nd invocation (newest match)
+    before_sub_2nd = [s for s in original_history if s.next == ("sub_node",)][0]
+    started_state.clear()
+    replay = graph.invoke(None, before_sub_2nd.config)
+    assert "__interrupt__" in replay
+
+    # Subgraph should see accumulated state from END of 1st invocation
+    assert started_state[0] == {"value": ["a:a1"]}
+
+    # Verify fork was created
+    post_replay_history = list(graph.get_state_history(config))
+    assert [s.next for s in post_replay_history] == [
+        ("sub_node",),  # fork (interrupt pending)
+        (),  # 2nd done
+        ("sub_node",),  # 2nd sub_node
+        ("parent_node",),  # 2nd parent_node
+        ("__start__",),  # 2nd input
+        (),  # 1st done
+        ("sub_node",),  # 1st sub_node
+        ("parent_node",),  # 1st parent_node
+        ("__start__",),  # 1st input
+    ]
+    assert [s.metadata["source"] for s in post_replay_history] == [
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+
+    # Resume with a new answer
+    started_state.clear()
+    final = graph.invoke(Command(resume="a3"), config)
+    assert "__interrupt__" not in final
+    assert final["results"] == ["p", "p"]
+
+    # Final history
+    final_history = list(graph.get_state_history(config))
+    assert [s.next for s in final_history] == [
+        (),  # new branch done
+        ("sub_node",),  # fork
+        (),  # 2nd done
+        ("sub_node",),  # 2nd sub_node
+        ("parent_node",),  # 2nd parent_node
+        ("__start__",),  # 2nd input
+        (),  # 1st done
+        ("sub_node",),  # 1st sub_node
+        ("parent_node",),  # 1st parent_node
+        ("__start__",),  # 1st input
+    ]
+    assert [s.metadata["source"] for s in final_history] == [
+        "loop",
+        "fork",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+        "loop",
+        "loop",
+        "loop",
+        "input",
+    ]
+
+
 def test_subgraph_interrupt_full_flow(
    sync_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -1290,6 +1756,321 @@ def test_subgraph_time_travel_to_second_interrupt(
    assert "ask_1" not in called


+def test_subgraph_time_travel_resume_from_first_interrupt(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the first interrupt, then
+    resume through both interrupts with new answers.
+
+    This verifies the key bug fix: after time-traveling to a subgraph
+    checkpoint with an interrupt, a fork checkpoint is created so that
+    subsequent resumes find the correct state (not the old branch tip).
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+
+    Parent history after original run completes:
+      source=input  next=(__start__,)   values=[]
+      source=loop   next=(executor,)    values=[]
+      source=loop   next=()             values=[step_a_done, ask_1:answer_1, ask_2:answer_2]
+
+    After time-traveling to 1st interrupt + resuming with new answers:
+      source=input  next=(__start__,)   values=[]
+      source=loop   next=(executor,)    values=[]          <-- branch point
+      source=loop   next=()             values=[..., ask_2:answer_2]  (old branch)
+      source=fork   next=(executor,)    values=[]          <-- fork from time travel
+      source=loop   next=()             values=[..., ask_2:new_answer_2]  (new branch)
+    """
+
+    called: list[str] = []
+
+    def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    graph.invoke({"value": []}, config)
+    sub_config_at_first = graph.get_state(config, subgraphs=True).tasks[0].state.config
+    graph.invoke(Command(resume="answer_1"), config)
+    graph.invoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to first interrupt's subgraph checkpoint ---
+    called.clear()
+    replay_result = graph.invoke(None, sub_config_at_first)
+    assert replay_result["__interrupt__"][0].value == "Question 1?"
+    assert "step_a" not in called  # before interrupt, not re-executed
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume both interrupts with new answers ---
+    called.clear()
+    resume_1 = graph.invoke(Command(resume="new_answer_1"), config)
+    assert resume_1["__interrupt__"][0].value == "Question 2?"
+    assert "ask_1" in called
+
+    called.clear()
+    resume_2 = graph.invoke(Command(resume="new_answer_2"), config)
+    assert resume_2["value"] == [
+        "step_a_done",
+        "ask_1:new_answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history: original branch preserved, new branch appended
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:new_answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+def test_subgraph_time_travel_resume_from_second_interrupt(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the second interrupt, then
+    resume with a new answer. The first interrupt's answer should be preserved.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+
+    Key assertion: after resuming from a time-travel to the 2nd interrupt,
+    the final state keeps ask_1's original answer but uses the new ask_2 answer.
+    """
+
+    called: list[str] = []
+
+    def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    graph.invoke({"value": []}, config)
+    graph.invoke(Command(resume="answer_1"), config)
+    sub_config_at_second = graph.get_state(config, subgraphs=True).tasks[0].state.config
+    graph.invoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to second interrupt ---
+    called.clear()
+    replay_result = graph.invoke(None, sub_config_at_second)
+    assert replay_result["__interrupt__"][0].value == "Question 2?"
+    assert "step_a" not in called
+    assert "ask_1" not in called  # already resolved, not re-executed
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer for ask_2 only ---
+    called.clear()
+    resume_result = graph.invoke(Command(resume="new_answer_2"), config)
+    # ask_1's original answer preserved, ask_2 uses the new answer
+    assert resume_result["value"] == [
+        "step_a_done",
+        "ask_1:answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history: original branch preserved, new branch appended
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+def test_subgraph_time_travel_checkpoint_pattern(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Verify the checkpoint pattern created by time travel to a subgraph
+    interrupt. A fork checkpoint should branch from the replay point and
+    become the latest parent checkpoint.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> ask (interrupt) --> END
+
+    Original run (after completing):
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(executor,)   values=[]          <-- replay point
+      source=loop   next=()            values=[a:first]
+
+    After time travel to interrupt + resume with "second":
+      source=input  next=(__start__,)  values=[]
+      source=loop   next=(executor,)   values=[]          <-- branch point
+      source=loop   next=()            values=[a:first]   (old branch)
+      source=fork   next=(executor,)   values=[]          <-- fork
+      source=loop   next=()            values=[a:second]  (new branch)
+    """
+
+    def ask(state: State) -> State:
+        answer = interrupt("Q?")
+        return {"value": [f"a:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("ask", ask)
+        .add_edge(START, "ask")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt, then complete
+    graph.invoke({"value": []}, config)
+    sub_config = graph.get_state(config, subgraphs=True).tasks[0].state.config
+    graph.invoke(Command(resume="first"), config)
+
+    original = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # Time travel to the interrupt
+    graph.invoke(None, sub_config)
+
+    # Fork is now the latest, branching from the original replay point
+    post_tt = list(graph.get_state_history(config))
+    post_tt_summary = _checkpoint_summary(post_tt)
+    assert [(s["source"], s["next"]) for s in post_tt_summary] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),
+        ("loop", ("executor",)),  # <-- replay point / fork parent
+        ("input", ("__start__",)),
+    ]
+    # Verify the fork's parent is the original replay point
+    replay_point_id = sub_config["configurable"]["checkpoint_map"][""]
+    assert post_tt[0].parent_config["configurable"]["checkpoint_id"] == replay_point_id
+
+    # Resume from the fork — graph completes with new answer
+    result = graph.invoke(Command(resume="second"), config)
+    assert result["value"] == ["a:second"]
+
+    final = _checkpoint_summary(list(graph.get_state_history(config)))
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch
+        ("loop", (), {"value": ["a:second"]}),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
 def test_subgraph_time_travel_after_completion(
    sync_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -2283,14 +3064,16 @@ def test_replay_creates_branch_preserving_old_checkpoints(
    # -- Post-replay checkpoint history (newest first) --
    post_replay_history = list(graph.get_state_history(config))
    post_summary = _checkpoint_summary(post_replay_history)
-    assert len(post_summary) == 7  # 5 original + 2 new branch checkpoints
+    # 5 original + 1 fork + 2 new branch checkpoints = 8
+    assert len(post_summary) == 8

    # Verify the full shape after replay
    assert [s["next"] for s in post_summary] == [
-        (),  # new branch tip (C6)
-        ("node_c",),  # new branch (C5)
-        (),  # old branch tip (C4)
-        ("node_c",),  # old (C3)
+        (),  # new branch tip
+        ("node_c",),  # new branch
+        ("node_b",),  # fork from replay point
+        (),  # old branch tip
+        ("node_c",),  # old
        ("node_b",),  # branch point (C2)
        ("node_a",),  # old (C1)
        ("__start__",),  # old (C0)
@@ -2298,6 +3081,7 @@ def test_replay_creates_branch_preserving_old_checkpoints(
    assert [s["values"] for s in post_summary] == [
        {"value": ["a", "b2", "c"]},  # new branch tip
        {"value": ["a", "b2"]},  # new: node_b re-ran with call_count=2
+        {"value": ["a"]},  # fork from replay point
        {"value": ["a", "b1", "c"]},  # old branch tip preserved
        {"value": ["a", "b1"]},  # old
        {"value": ["a"]},  # branch point
@@ -46,6 +46,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
    Returns a list of dicts (newest-first, matching get_state_history order) with:
      - id: short checkpoint id suffix (last 6 chars)
      - parent_id: short parent checkpoint id suffix or None
+      - source: checkpoint metadata source (input, loop, fork, update)
      - next: tuple of next node names
      - values: channel values snapshot
    """
@@ -61,6 +62,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
            {
                "id": cid[-6:],
                "parent_id": pid[-6:] if pid else None,
+                "source": s.metadata.get("source"),
                "next": s.next,
                "values": s.values,
            }
@@ -335,8 +337,14 @@ async def test_replay_interrupt_stable_across_replays(
        r = await graph.ainvoke(None, before_ask.config)
        results.append(r)

-    assert all(r == results[0] for r in results)
-    assert "__interrupt__" in results[0]
+    # Each replay creates a fork with a unique interrupt ID, so we compare
+    # interrupt values and state values rather than full equality.
+    assert all("__interrupt__" in r for r in results)
+    assert all(
+        r["__interrupt__"][0].value == results[0]["__interrupt__"][0].value
+        for r in results
+    )
+    assert all(r["value"] == results[0]["value"] for r in results)


@NEEDS_CONTEXTVARS
@@ -1261,6 +1269,391 @@ async def test_subgraph_time_travel_after_completion_async(
    assert "ask_2:answer_2" in replay_result["value"]


+@NEEDS_CONTEXTVARS
+async def test_replay_from_before_interrupt_then_resume_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Replay from checkpoint before interrupt node, then resume with a new
+    answer and verify the graph completes with the new value.
+
+    Graph: START --> node_a --> ask_human (interrupt) --> node_b --> END
+    """
+
+    called: list[str] = []
+
+    async def node_a(state: State) -> State:
+        called.append("node_a")
+        return {"value": ["a"]}
+
+    async def ask_human(state: State) -> State:
+        called.append("ask_human")
+        answer = interrupt("What is your input?")
+        return {"value": [f"human:{answer}"]}
+
+    async def node_b(state: State) -> State:
+        called.append("node_b")
+        return {"value": ["b"]}
+
+    graph = (
+        StateGraph(State)
+        .add_node("node_a", node_a)
+        .add_node("ask_human", ask_human)
+        .add_node("node_b", node_b)
+        .add_edge(START, "node_a")
+        .add_edge("node_a", "ask_human")
+        .add_edge("ask_human", "node_b")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: invoke until interrupt, then resume to complete ---
+    await graph.ainvoke({"value": []}, config)
+    await graph.ainvoke(Command(resume="old_answer"), config)
+
+    original_history = [s async for s in graph.aget_state_history(config)]
+    original = _checkpoint_summary(original_history)
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Replay from checkpoint before ask_human ---
+    before_ask = next(s for s in original_history if s.next == ("ask_human",))
+
+    called.clear()
+    replay_result = await graph.ainvoke(None, before_ask.config)
+    assert replay_result["__interrupt__"][0].value == "What is your input?"
+    assert "ask_human" in called
+    assert "node_a" not in called
+
+    # A fork checkpoint is now the latest
+    post_replay = _checkpoint_summary(
+        [s async for s in graph.aget_state_history(config)]
+    )
+    assert [(s["source"], s["next"]) for s in post_replay] == [
+        ("fork", ("ask_human",)),
+        ("loop", ()),
+        ("loop", ("node_b",)),
+        ("loop", ("ask_human",)),
+        ("loop", ("node_a",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer ---
+    called.clear()
+    final_result = await graph.ainvoke(Command(resume="new_answer"), config)
+    assert final_result["value"] == ["a", "human:new_answer", "b"]
+    assert "ask_human" in called
+    assert "node_b" in called
+
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from fork)
+        ("loop", (), {"value": ["a", "human:new_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:new_answer"]}),
+        ("fork", ("ask_human",), {"value": ["a"]}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["a", "human:old_answer", "b"]}),
+        ("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
+        ("loop", ("ask_human",), {"value": ["a"]}),
+        ("loop", ("node_a",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+@NEEDS_CONTEXTVARS
+async def test_subgraph_time_travel_resume_from_first_interrupt_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the first interrupt, then
+    resume through both interrupts with new answers.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+    """
+
+    called: list[str] = []
+
+    async def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    async def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    async def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    await graph.ainvoke({"value": []}, config)
+    sub_config_at_first = (
+        (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
+    )
+    await graph.ainvoke(Command(resume="answer_1"), config)
+    await graph.ainvoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to first interrupt's subgraph checkpoint ---
+    called.clear()
+    replay_result = await graph.ainvoke(None, sub_config_at_first)
+    assert replay_result["__interrupt__"][0].value == "Question 1?"
+    assert "step_a" not in called
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume both interrupts with new answers ---
+    called.clear()
+    resume_1 = await graph.ainvoke(Command(resume="new_answer_1"), config)
+    assert resume_1["__interrupt__"][0].value == "Question 2?"
+    assert "ask_1" in called
+
+    called.clear()
+    resume_2 = await graph.ainvoke(Command(resume="new_answer_2"), config)
+    assert resume_2["value"] == [
+        "step_a_done",
+        "ask_1:new_answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history: original branch preserved, new branch appended
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:new_answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+@NEEDS_CONTEXTVARS
+async def test_subgraph_time_travel_resume_from_second_interrupt_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Time travel to a subgraph checkpoint at the second interrupt, then
+    resume with a new answer. The first interrupt's answer should be preserved.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
+    """
+
+    called: list[str] = []
+
+    async def step_a(state: State) -> State:
+        called.append("step_a")
+        return {"value": ["step_a_done"]}
+
+    async def ask_1(state: State) -> State:
+        called.append("ask_1")
+        answer = interrupt("Question 1?")
+        return {"value": [f"ask_1:{answer}"]}
+
+    async def ask_2(state: State) -> State:
+        called.append("ask_2")
+        answer = interrupt("Question 2?")
+        return {"value": [f"ask_2:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("ask_1", ask_1)
+        .add_node("ask_2", ask_2)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "ask_1")
+        .add_edge("ask_1", "ask_2")
+        .add_edge("ask_2", "__end__")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # --- Original run: hit both interrupts and resume ---
+    await graph.ainvoke({"value": []}, config)
+    await graph.ainvoke(Command(resume="answer_1"), config)
+    sub_config_at_second = (
+        (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
+    )
+    await graph.ainvoke(Command(resume="answer_2"), config)
+
+    original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # --- Time travel to second interrupt ---
+    called.clear()
+    replay_result = await graph.ainvoke(None, sub_config_at_second)
+    assert replay_result["__interrupt__"][0].value == "Question 2?"
+    assert "step_a" not in called
+    assert "ask_1" not in called
+
+    # Fork is now the latest parent checkpoint
+    post_tt = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"]) for s in post_tt] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),  # original done
+        ("loop", ("executor",)),
+        ("input", ("__start__",)),
+    ]
+
+    # --- Resume with a new answer for ask_2 only ---
+    called.clear()
+    resume_result = await graph.ainvoke(Command(resume="new_answer_2"), config)
+    assert resume_result["value"] == [
+        "step_a_done",
+        "ask_1:answer_1",
+        "ask_2:new_answer_2",
+    ]
+
+    # Verify final history
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch (from time travel fork)
+        (
+            "loop",
+            (),
+            {"value": ["step_a_done", "ask_1:answer_1", "ask_2:new_answer_2"]},
+        ),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch (preserved)
+        ("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
+@NEEDS_CONTEXTVARS
+async def test_subgraph_time_travel_checkpoint_pattern_async(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Verify the checkpoint pattern created by time travel to a subgraph
+    interrupt. A fork checkpoint should branch from the replay point.
+
+    Parent:    START --> executor (subgraph, checkpointer=True) --> END
+    Executor:  START --> ask (interrupt) --> END
+    """
+
+    async def ask(state: State) -> State:
+        answer = interrupt("Q?")
+        return {"value": [f"a:{answer}"]}
+
+    executor = (
+        StateGraph(State)
+        .add_node("ask", ask)
+        .add_edge(START, "ask")
+        .compile(checkpointer=True)
+    )
+
+    graph = (
+        StateGraph(State)
+        .add_node("executor", executor)
+        .add_edge(START, "executor")
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # Run until interrupt, then complete
+    await graph.ainvoke({"value": []}, config)
+    sub_config = (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
+    await graph.ainvoke(Command(resume="first"), config)
+
+    original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in original] == [
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+    # Time travel to the interrupt
+    await graph.ainvoke(None, sub_config)
+
+    # Fork is now the latest, branching from the original replay point
+    post_tt = [s async for s in graph.aget_state_history(config)]
+    post_tt_summary = _checkpoint_summary(post_tt)
+    assert [(s["source"], s["next"]) for s in post_tt_summary] == [
+        ("fork", ("executor",)),  # <-- new fork (latest)
+        ("loop", ()),
+        ("loop", ("executor",)),  # <-- replay point / fork parent
+        ("input", ("__start__",)),
+    ]
+    # Verify the fork's parent is the original replay point
+    replay_point_id = sub_config["configurable"]["checkpoint_map"][""]
+    assert post_tt[0].parent_config["configurable"]["checkpoint_id"] == replay_point_id
+
+    # Resume from the fork
+    result = await graph.ainvoke(Command(resume="second"), config)
+    assert result["value"] == ["a:second"]
+
+    final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
+    assert [(s["source"], s["next"], s["values"]) for s in final] == [
+        # New branch
+        ("loop", (), {"value": ["a:second"]}),
+        ("fork", ("executor",), {"value": []}),
+        # Original branch
+        ("loop", (), {"value": ["a:first"]}),
+        ("loop", ("executor",), {"value": []}),
+        ("input", ("__start__",), {"value": []}),
+    ]
+
+
@NEEDS_CONTEXTVARS
 async def test_3_levels_deep_time_travel_to_first_interrupt_async(
    async_checkpointer: BaseCheckpointSaver,
@@ -2088,13 +2481,15 @@ async def test_replay_creates_branch_preserving_old_checkpoints(
    # -- Post-replay checkpoint history (newest first) --
    post_replay_history = [s async for s in graph.aget_state_history(config)]
    post_summary = _checkpoint_summary(post_replay_history)
-    assert len(post_summary) == 7  # 5 original + 2 new branch checkpoints
+    # 5 original + 1 fork + 2 new branch checkpoints = 8
+    assert len(post_summary) == 8

    assert [s["next"] for s in post_summary] == [
-        (),  # new branch tip (C6)
-        ("node_c",),  # new branch (C5)
-        (),  # old branch tip (C4)
-        ("node_c",),  # old (C3)
+        (),  # new branch tip
+        ("node_c",),  # new branch
+        ("node_b",),  # fork from replay point
+        (),  # old branch tip
+        ("node_c",),  # old
        ("node_b",),  # branch point (C2)
        ("node_a",),  # old (C1)
        ("__start__",),  # old (C0)
@@ -2102,6 +2497,7 @@ async def test_replay_creates_branch_preserving_old_checkpoints(
    assert [s["values"] for s in post_summary] == [
        {"value": ["a", "b2", "c"]},  # new branch tip
        {"value": ["a", "b2"]},  # new: node_b re-ran with call_count=2
+        {"value": ["a"]},  # fork from replay point
        {"value": ["a", "b1", "c"]},  # old branch tip preserved
        {"value": ["a", "b1"]},  # old
        {"value": ["a"]},  # branch point
@@ -11,13 +11,19 @@ from typing import (
    TypeVar,
    Union,
 )
-from unittest.mock import patch
+from unittest.mock import MagicMock, patch

 import langsmith
 import pytest
+from langchain_core.runnables import RunnableConfig
+from langchain_core.tracers import LangChainTracer
 from typing_extensions import NotRequired, Required, TypedDict

-from langgraph._internal._config import _is_not_empty, ensure_config
+from langgraph._internal._config import (
+    _is_not_empty,
+    ensure_config,
+    get_callback_manager_for_config,
+)
 from langgraph._internal._fields import (
    _is_optional_type,
    get_enhanced_type_hints,
@@ -298,7 +304,7 @@ def test_is_not_empty() -> None:
    assert not _is_not_empty({})


-def test_configurable_metadata():
+def test_configurable_metadata() -> None:
    config = {
        "configurable": {
            "a-key": "foo",
@@ -309,11 +315,115 @@ def test_configurable_metadata():
            "andme": 42,
            "nested": {"foo": "bar"},
            "nooverride": -2,
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
        },
        "metadata": {"nooverride": 18},
    }
-    expected = {"includeme", "andme", "nooverride"}
    merged = ensure_config(config)
    metadata = merged["metadata"]
-    assert metadata.keys() == expected
+    assert set(metadata) == {
+        "nooverride",
+        "assistant_id",
+        "thread_id",
+        "checkpoint_id",
+        "run_id",
+        "graph_id",
+        "checkpoint_ns",
+        "task_id",
+    }
    assert metadata["nooverride"] == 18
+
+
+def test_callback_manager_copies_whitelisted_configurable_ids_to_metadata() -> None:
+    config = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+        },
+        "metadata": {
+            "thread_id": "from-metadata",
+            "nooverride": 18,
+        },
+    }
+    manager = ensure_config(config)
+    callback_manager = get_callback_manager_for_config(manager)
+    assert callback_manager.metadata == {
+        "thread_id": "from-metadata",
+        "nooverride": 18,
+        "checkpoint_id": "ckpt-1",
+        "checkpoint_ns": "ns-1",
+        "task_id": "task-1",
+        "run_id": "run-456",
+        "assistant_id": "asst-789",
+        "graph_id": "graph-0",
+    }
+
+
+def test_callback_manager_copies_configurable_ids_to_tracing_metadata() -> None:
+    tracer = LangChainTracer(client=MagicMock())
+    config: RunnableConfig = {
+        "configurable": {
+            "thread_id": "th-123",
+            "checkpoint_id": "ckpt-1",
+            "checkpoint_ns": "ns-1",
+            "task_id": "task-1",
+            "run_id": "run-456",
+            "assistant_id": "asst-789",
+            "graph_id": "graph-0",
+            "model": "gpt-4o",
+            "user_id": "uid-1",
+            "cron_id": "cron-1",
+            "langgraph_auth_user_id": "user-1",
+            "includeme": "hi",
+            "andme": 42,
+            "__dontinclude": "bar",
+            "some_api_key": "secret",
+            "custom_setting": {"nested": True},
+        },
+        "metadata": {
+            "thread_id": "from-metadata",
+            "user_id": "from-metadata-user",
+            "includeme": "from-metadata",
+        },
+        "callbacks": [tracer],
+    }
+
+    manager = ensure_config(config)
+    callback_manager = get_callback_manager_for_config(manager)
+    handlers = callback_manager.handlers
+    tracers = [handler for handler in handlers if isinstance(handler, LangChainTracer)]
+    assert len(tracers) == 1
+    tracer = tracers[0]
+    assert tracer.tracing_metadata == {
+        "checkpoint_id": "ckpt-1",
+        "checkpoint_ns": "ns-1",
+        "task_id": "task-1",
+        "run_id": "run-456",
+        "assistant_id": "asst-789",
+        "graph_id": "graph-0",
+        "model": "gpt-4o",
+        "cron_id": "cron-1",
+        "andme": 42,
+        "includeme": "hi",
+        "thread_id": "th-123",
+        "user_id": "uid-1",
+    }
@@ -1348,7 +1348,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.2.22"
+version = "1.3.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -1360,14 +1360,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/b1/a3/c4cd6827a1df46c821e7214b7f7b7a28b189e6c9b84ef15c6d629c5e3179/langchain_core-1.2.22.tar.gz", hash = "sha256:8d8f726d03d3652d403da915126626bb6250747e8ba406537d849e68b9f5d058", size = 842487, upload-time = "2026-03-24T18:48:44.9Z" }
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+    { url = "https://files.pythonhosted.org/packages/a1/c2/8493be505921857988db068b7c027f28a9b1587b4425c6a32b1221c9c9fe/langchain_core-1.3.1-py3-none-any.whl", hash = "sha256:8b13d19d3bed3f4768df12c7f6932d2ada715f3ac9fd020c63d28c693968269e", size = 515879, upload-time = "2026-04-23T18:53:59.94Z" },
 ]

 [[package]]
 name = "langgraph"
-version = "1.1.6"
+version = "1.1.10"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -1439,7 +1439,7 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.1" },
+    { name = "langchain-core", specifier = ">=1.3.0,<2" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "../prebuilt" },
    { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -1548,7 +1548,7 @@ wheels = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -1706,7 +1706,7 @@ inmem = [
 requires-dist = [
    { name = "click", specifier = ">=8.1.7" },
    { name = "httpx", specifier = ">=0.24.0" },
-    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.8.0" },
+    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.9.0" },
    { name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.7" },
    { name = "langgraph-sdk", marker = "python_full_version >= '3.11'", specifier = ">=0.1.0" },
    { name = "pathspec", specifier = ">=0.11.0" },
@@ -1742,7 +1742,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.9"
+version = "1.0.13"
 source = { editable = "../prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -1751,7 +1751,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", specifier = ">=1.3.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

@@ -1852,7 +1852,7 @@ test = [

 [[package]]
 name = "langsmith"
-version = "0.6.4"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -1862,11 +1862,12 @@ dependencies = [
    { name = "requests" },
    { name = "requests-toolbelt" },
    { name = "uuid-utils" },
+    { name = "xxhash" },
    { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/e7/85/9c7933052a997da1b85bc5c774f3865e9b1da1c8d71541ea133178b13229/langsmith-0.6.4.tar.gz", hash = "sha256:36f7223a01c218079fbb17da5e536ebbaf5c1468c028abe070aa3ae59bc99ec8", size = 919964, upload-time = "2026-01-15T20:02:28.873Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
 ]

 [package.optional-dependencies]
@@ -2139,7 +2140,7 @@ wheels = [

 [[package]]
 name = "nbconvert"
-version = "7.17.0"
+version = "7.17.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "beautifulsoup4" },
@@ -2157,9 +2158,9 @@ dependencies = [
    { name = "pygments" },
    { name = "traitlets" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/38/47/81f886b699450d0569f7bc551df2b1673d18df7ff25cc0c21ca36ed8a5ff/nbconvert-7.17.0.tar.gz", hash = "sha256:1b2696f1b5be12309f6c7d707c24af604b87dfaf6d950794c7b07acab96dda78", size = 862855, upload-time = "2026-01-29T16:37:48.478Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/01/b1/708e53fe2e429c103c6e6e159106bcf0357ac41aa4c28772bd8402339051/nbconvert-7.17.1.tar.gz", hash = "sha256:34d0d0a7e73ce3cbab6c5aae8f4f468797280b01fd8bd2ca746da8569eddd7d2", size = 865311, upload-time = "2026-04-08T00:44:14.914Z" }
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+    { url = "https://files.pythonhosted.org/packages/67/f8/bb0a9d5f46819c821dc1f004aa2cc29b1d91453297dbf5ff20470f00f193/nbconvert-7.17.1-py3-none-any.whl", hash = "sha256:aa85c087b435e7bf1ffd03319f658e285f2b89eccab33bc1ba7025495ab3e7c8", size = 261927, upload-time = "2026-04-08T00:44:12.845Z" },
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 [[package]]
@@ -2905,7 +2906,7 @@ 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'" },
@@ -2916,9 +2917,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
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+    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
 ]

 [[package]]
@@ -3017,11 +3018,11 @@ wheels = [

 [[package]]
 name = "python-dotenv"
-version = "1.2.1"
+version = "1.2.2"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/f0/26/19cadc79a718c5edbec86fd4919a6b6d3f681039a2f6d66d14be94e75fb9/python_dotenv-1.2.1.tar.gz", hash = "sha256:42667e897e16ab0d66954af0e60a9caa94f0fd4ecf3aaf6d2d260eec1aa36ad6", size = 44221, upload-time = "2025-10-26T15:12:10.434Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/82/ed/0301aeeac3e5353ef3d94b6ec08bbcabd04a72018415dcb29e588514bba8/python_dotenv-1.2.2.tar.gz", hash = "sha256:2c371a91fbd7ba082c2c1dc1f8bf89ca22564a087c2c287cd9b662adde799cf3", size = 50135, upload-time = "2026-03-01T16:00:26.196Z" }
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+    { url = "https://files.pythonhosted.org/packages/0b/d7/1959b9648791274998a9c3526f6d0ec8fd2233e4d4acce81bbae76b44b2a/python_dotenv-1.2.2-py3-none-any.whl", hash = "sha256:1d8214789a24de455a8b8bd8ae6fe3c6b69a5e3d64aa8a8e5d68e694bbcb285a", size = 22101, upload-time = "2026-03-01T16:00:25.09Z" },
 ]

 [[package]]
@@ -44,7 +44,7 @@ import inspect
 import json
 from collections.abc import Awaitable, Callable
 from copy import copy, deepcopy
-from dataclasses import dataclass, replace
+from dataclasses import dataclass, field, replace
 from types import UnionType
 from typing import (
    TYPE_CHECKING,
@@ -82,6 +82,7 @@ from langchain_core.tools.base import (
    _is_injected_arg_type,
    get_all_basemodel_annotations,
 )
+from langgraph._internal._constants import CONF, CONFIG_KEY_READ
 from langgraph._internal._runnable import RunnableCallable
 from langgraph.errors import GraphBubbleUp
 from langgraph.graph.message import REMOVE_ALL_MESSAGES
@@ -614,6 +615,7 @@ class _InjectedArgs:
    store: str | None
    runtime: str | None
    all_injected_keys: set[str]
+    _optional_state_args: set[str]


 class ToolNode(RunnableCallable):
@@ -799,7 +801,7 @@ class ToolNode(RunnableCallable):
        # Construct ToolRuntime instances at the top level for each tool call
        tool_runtimes = []
        for call, cfg in zip(tool_calls, config_list, strict=False):
-            state = self._extract_state(input)
+            state = self._extract_state(input, cfg)
            tool_runtime = ToolRuntime(
                state=state,
                tool_call_id=call["id"],
@@ -807,6 +809,7 @@ class ToolNode(RunnableCallable):
                context=runtime.context,
                store=runtime.store,
                stream_writer=runtime.stream_writer,
+                tools=list(self.tools_by_name.values()),
                execution_info=runtime.execution_info,
                server_info=runtime.server_info,
            )
@@ -833,7 +836,7 @@ class ToolNode(RunnableCallable):
        # Construct ToolRuntime instances at the top level for each tool call
        tool_runtimes = []
        for call, cfg in zip(tool_calls, config_list, strict=False):
-            state = self._extract_state(input)
+            state = self._extract_state(input, cfg)
            tool_runtime = ToolRuntime(
                state=state,
                tool_call_id=call["id"],
@@ -841,6 +844,7 @@ class ToolNode(RunnableCallable):
                context=runtime.context,
                store=runtime.store,
                stream_writer=runtime.stream_writer,
+                tools=list(self.tools_by_name.values()),
                execution_info=runtime.execution_info,
                server_info=runtime.server_info,
            )
@@ -856,14 +860,30 @@ class ToolNode(RunnableCallable):

    def _combine_tool_outputs(
        self,
-        outputs: list[ToolMessage | Command],
+        outputs: list[ToolMessage | Command | list[ToolMessage | Command]],
        input_type: Literal["list", "dict", "tool_calls"],
    ) -> list[Command | list[ToolMessage] | dict[str, list[ToolMessage]]]:
+        # Flatten list entries from tools that returned multiple items
+        flat_outputs: list[ToolMessage | Command]
+        if any(isinstance(output, list) for output in outputs):
+            flat_outputs = []
+            for output in outputs:
+                if isinstance(output, list):
+                    flat_outputs.extend(output)
+                else:
+                    flat_outputs.append(output)
+        else:
+            flat_outputs = cast("list[ToolMessage | Command]", outputs)
+
        # preserve existing behavior for non-command tool outputs for backwards
        # compatibility
-        if not any(isinstance(output, Command) for output in outputs):
+        if not any(isinstance(output, Command) for output in flat_outputs):
            # TypedDict, pydantic, dataclass, etc. should all be able to load from dict
-            return outputs if input_type == "list" else {self._messages_key: outputs}
+            return (
+                flat_outputs
+                if input_type == "list"
+                else {self._messages_key: flat_outputs}
+            )

        # LangGraph will automatically handle list of Command and non-command node
        # updates
@@ -873,7 +893,7 @@ class ToolNode(RunnableCallable):

        # combine all parent commands with goto into a single parent command
        parent_command: Command | None = None
-        for output in outputs:
+        for output in flat_outputs:
            if isinstance(output, Command):
                if (
                    output.graph is Command.PARENT
@@ -903,7 +923,7 @@ class ToolNode(RunnableCallable):
        request: ToolCallRequest,
        input_type: Literal["list", "dict", "tool_calls"],
        config: RunnableConfig,
-    ) -> ToolMessage | Command:
+    ) -> ToolMessage | Command | list[Command | ToolMessage]:
        """Execute tool call with configured error handling.

        Args:
@@ -912,7 +932,7 @@ class ToolNode(RunnableCallable):
            config: Runnable configuration.

        Returns:
-            ToolMessage or Command.
+            ToolMessage, Command, or list of Command/ToolMessage.

        Raises:
            Exception: If tool fails and handle_tool_errors is False.
@@ -944,6 +964,11 @@ class ToolNode(RunnableCallable):
                    call["name"], exc, call["args"], filtered_errors
                ) from exc

+            # Inside try so validation errors route through _handle_tool_errors
+            return self._normalize_tool_response(
+                response, request.tool_call, input_type
+            )
+
        # GraphInterrupt is a special exception that will always be raised.
        # It can be triggered in the following scenarios,
        # Where GraphInterrupt(GraphBubbleUp) is raised from an `interrupt` invocation
@@ -985,23 +1010,12 @@ class ToolNode(RunnableCallable):
                status="error",
            )

-        # Process successful response
-        if isinstance(response, Command):
-            # Validate Command before returning to handler
-            return self._validate_tool_command(response, request.tool_call, input_type)
-        if isinstance(response, ToolMessage):
-            response.content = cast("str | list", msg_content_output(response.content))
-            return response
-
-        msg = f"Tool {call['name']} returned unexpected type: {type(response)}"
-        raise TypeError(msg)
-
    def _run_one(
        self,
        call: ToolCall,
        input_type: Literal["list", "dict", "tool_calls"],
        tool_runtime: ToolRuntime,
-    ) -> ToolMessage | Command:
+    ) -> ToolMessage | Command | list[Command | ToolMessage]:
        """Execute single tool call with wrap_tool_call wrapper if configured.

        Args:
@@ -1056,7 +1070,7 @@ class ToolNode(RunnableCallable):
        request: ToolCallRequest,
        input_type: Literal["list", "dict", "tool_calls"],
        config: RunnableConfig,
-    ) -> ToolMessage | Command:
+    ) -> ToolMessage | Command | list[Command | ToolMessage]:
        """Execute tool call asynchronously with configured error handling.

        Args:
@@ -1065,7 +1079,7 @@ class ToolNode(RunnableCallable):
            config: Runnable configuration.

        Returns:
-            ToolMessage or Command.
+            ToolMessage, Command, or list of Command/ToolMessage.

        Raises:
            Exception: If tool fails and handle_tool_errors is False.
@@ -1097,6 +1111,11 @@ class ToolNode(RunnableCallable):
                    call["name"], exc, call["args"], filtered_errors
                ) from exc

+            # Inside try so validation errors route through _handle_tool_errors
+            return self._normalize_tool_response(
+                response, request.tool_call, input_type
+            )
+
        # GraphInterrupt is a special exception that will always be raised.
        # It can be triggered in the following scenarios,
        # Where GraphInterrupt(GraphBubbleUp) is raised from an `interrupt` invocation
@@ -1138,23 +1157,12 @@ class ToolNode(RunnableCallable):
                status="error",
            )

-        # Process successful response
-        if isinstance(response, Command):
-            # Validate Command before returning to handler
-            return self._validate_tool_command(response, request.tool_call, input_type)
-        if isinstance(response, ToolMessage):
-            response.content = cast("str | list", msg_content_output(response.content))
-            return response
-
-        msg = f"Tool {call['name']} returned unexpected type: {type(response)}"
-        raise TypeError(msg)
-
    async def _arun_one(
        self,
        call: ToolCall,
        input_type: Literal["list", "dict", "tool_calls"],
        tool_runtime: ToolRuntime,
-    ) -> ToolMessage | Command:
+    ) -> ToolMessage | Command | list[Command | ToolMessage]:
        """Execute single tool call asynchronously with awrap_tool_call wrapper if configured.

        Args:
@@ -1270,18 +1278,37 @@ class ToolNode(RunnableCallable):
        return None

    def _extract_state(
-        self, input: list[AnyMessage] | dict[str, Any] | BaseModel
+        self,
+        input: list[AnyMessage] | dict[str, Any] | BaseModel,
+        config: RunnableConfig,
    ) -> list[AnyMessage] | dict[str, Any] | BaseModel:
-        """Extract state from input, handling ToolCallWithContext if present.
+        """Extract state from input.

-        Args:
-            input: The input which may be raw state or ToolCallWithContext.
+        Three input shapes:

-        Returns:
-            The actual state to pass to wrap_tool_call wrappers.
+        - `ToolCallWithContext` dict — legacy Send payload carrying an inlined
+          state snapshot; return `input["state"]`.
+        - list of `ToolCall` dicts — new Send payload with no inlined state;
+          hydrate state from channels via `CONFIG_KEY_READ`.
+        - regular graph state (dict/list/BaseModel) — return `input` as-is.
        """
        if isinstance(input, dict) and input.get("__type") == "tool_call_with_context":
            return input["state"]
+        if (
+            isinstance(input, list)
+            and input
+            and isinstance(input[-1], dict)
+            and input[-1].get("type") == "tool_call"
+        ):
+            read = config.get(CONF, {}).get(CONFIG_KEY_READ)
+            if read is None:
+                return {}
+            # Pregel installs CONFIG_KEY_READ as
+            # `functools.partial(local_read, scratchpad, channels, managed, task)`.
+            # Match the previous inlined-state contract by reading channels only;
+            # managed values have their own injection path (`ToolRuntime.context`).
+            channels = read.args[1]
+            return cast("dict[str, Any]", read(list(channels), True))
        return input

    def _inject_tool_args(
@@ -1333,7 +1360,7 @@ class ToolNode(RunnableCallable):
            return tool_call

        tool_call_copy: ToolCall = copy(tool_call)
-        injected_args = {}
+        injected_args: dict[str, Any] = {}

        # Inject state
        if injected.state:
@@ -1361,14 +1388,20 @@ class ToolNode(RunnableCallable):
            # Extract state values
            if isinstance(state, dict):
                for tool_arg, state_field in injected.state.items():
-                    injected_args[tool_arg] = (
-                        state[state_field] if state_field else state
-                    )
+                    if not state_field:
+                        injected_args[tool_arg] = state
+                    elif state_field in state:
+                        injected_args[tool_arg] = state[state_field]
+                    elif tool_arg not in injected._optional_state_args:
+                        raise KeyError(state_field)
            else:
                for tool_arg, state_field in injected.state.items():
-                    injected_args[tool_arg] = (
-                        getattr(state, state_field) if state_field else state
-                    )
+                    if not state_field:
+                        injected_args[tool_arg] = state
+                    elif hasattr(state, state_field):
+                        injected_args[tool_arg] = getattr(state, state_field)
+                    elif tool_arg not in injected._optional_state_args:
+                        raise AttributeError(state_field)

        # Inject store
        if injected.store:
@@ -1395,11 +1428,84 @@ class ToolNode(RunnableCallable):
        tool_call_copy["args"] = {**stripped_args, **injected_args}
        return tool_call_copy

+    def _normalize_tool_response(
+        self,
+        response: Any,
+        tool_call: ToolCall,
+        input_type: Literal["list", "dict", "tool_calls"],
+    ) -> ToolMessage | Command | list[Command | ToolMessage]:
+        """Validate and normalize a tool's raw return value."""
+        if isinstance(response, Command):
+            return self._validate_tool_command(response, tool_call, input_type)
+        if isinstance(response, ToolMessage):
+            response.content = cast("str | list", msg_content_output(response.content))
+            return response
+        if isinstance(response, list):
+            if all(isinstance(r, (Command, ToolMessage)) for r in response):
+                return self._validate_tool_command_list(response, tool_call, input_type)
+            msg = (
+                f"Tool {tool_call['name']} returned a list with invalid element "
+                "types: expected all Command or ToolMessage"
+            )
+            raise TypeError(msg)
+        msg = f"Tool {tool_call['name']} returned unexpected type: {type(response)}"
+        raise TypeError(msg)
+
+    def _validate_tool_command_list(
+        self,
+        response: list[Command | ToolMessage],
+        tool_call: ToolCall,
+        input_type: Literal["list", "dict", "tool_calls"],
+    ) -> list[Command | ToolMessage]:
+        """Validate a list of Command/ToolMessage returned by a single tool call.
+
+        Requires exactly one terminating ToolMessage (matching the outer tool_call_id)
+        across the list — either as a top-level element or nested in a
+        Command.update["messages"].
+        """
+        expected_id = tool_call["id"]
+
+        terminator_count = 0
+        for item in response:
+            if isinstance(item, ToolMessage):
+                if item.tool_call_id == expected_id:
+                    terminator_count += 1
+            elif isinstance(item, Command) and isinstance(item.update, dict):
+                for msg in item.update.get(self._messages_key, []):
+                    if isinstance(msg, ToolMessage) and msg.tool_call_id == expected_id:
+                        terminator_count += 1
+
+        if terminator_count != 1:
+            msg = (
+                f"Tool {tool_call['name']} returned a list with "
+                f"{terminator_count} messages bound to tool_call_id "
+                f"{expected_id!r}; expected exactly one terminating ToolMessage."
+            )
+            raise ValueError(msg)
+
+        # Per-Command normalization still runs, but the list-level count above
+        # already guarantees exactly one terminator, so individual Commands may
+        # lack one.
+        validated: list[Command | ToolMessage] = []
+        for item in response:
+            if isinstance(item, Command):
+                validated.append(
+                    self._validate_tool_command(
+                        item, tool_call, input_type, require_terminator=False
+                    )
+                )
+            else:
+                item.content = cast("str | list", msg_content_output(item.content))
+                validated.append(item)
+        return validated
+
    def _validate_tool_command(
        self,
        command: Command,
        call: ToolCall,
        input_type: Literal["list", "dict", "tool_calls"],
+        *,
+        require_terminator: bool = True,
    ) -> Command:
        if isinstance(command.update, dict):
            # input type is dict when ToolNode is invoked with a dict input
@@ -1449,7 +1555,11 @@ class ToolNode(RunnableCallable):

        # validate that we always have a ToolMessage matching the tool call in
        # Command.update if command is sent to the CURRENT graph
-        if updated_command.graph is None and not has_matching_tool_message:
+        if (
+            require_terminator
+            and updated_command.graph is None
+            and not has_matching_tool_message
+        ):
            example_update = (
                '`Command(update={"messages": '
                '[ToolMessage("Success", tool_call_id=tool_call_id), ...]}, ...)`'
@@ -1569,6 +1679,7 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
    - `context`: Runtime context (shared with `Runtime`)
    - `store`: `BaseStore` instance for persistent storage (shared with `Runtime`)
    - `stream_writer`: `StreamWriter` for streaming output (shared with `Runtime`)
+    - `tools`: List of all available `BaseTool` instances

    No `Annotated` wrapper is needed - just use `runtime: ToolRuntime`
    as a parameter.
@@ -1613,6 +1724,7 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
    stream_writer: StreamWriter
    tool_call_id: str | None
    store: BaseStore | None
+    tools: list[BaseTool] = field(default_factory=list)
    execution_info: ExecutionInfo | None = None
    server_info: ServerInfo | None = None

@@ -1859,6 +1971,7 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
    store_arg: str | None = None
    runtime_arg: str | None = None
    all_injected_keys: set[str] = set()
+    _optional_state_args: set[str] = set()

    for name, type_ in all_annotations.items():
        # Track all InjectedToolArg-annotated params (including custom subclasses)
@@ -1873,6 +1986,9 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
        if state_inj := _get_injection_from_type(type_, InjectedState):
            if isinstance(state_inj, InjectedState) and state_inj.field:
                state_args[name] = state_inj.field
+                field_info = full_schema.model_fields.get(name)
+                if field_info and not field_info.is_required():
+                    _optional_state_args.add(name)
            else:
                state_args[name] = None

@@ -1889,4 +2005,5 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
        store=store_arg,
        runtime=runtime_arg,
        all_injected_keys=all_injected_keys,
+        _optional_state_args=_optional_state_args,
    )
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-prebuilt"
-version = "1.0.9"
+version = "1.0.13"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"
@@ -25,7 +25,7 @@ classifiers = [
 ]
 dependencies = [
    "langgraph-checkpoint>=2.1.0,<5.0.0",
-    "langchain-core>=1.0.0",
+    "langchain-core>=1.3.1",
 ]

 [project.urls]
@@ -0,0 +1,285 @@
+"""Test InjectedState with NotRequired state fields.
+
+This tests the fix for https://github.com/langchain-ai/langchain/issues/35585
+
+When using InjectedState(<field>) on a tool parameter, and the referenced field is
+declared as NotRequired in the custom state schema, the ToolNode should gracefully
+handle missing fields by injecting None instead of raising KeyError.
+"""
+
+import sys
+from typing import Annotated
+
+import pytest
+from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, ToolMessage
+from langchain_core.tools import tool
+from langgraph.graph.message import add_messages
+from pydantic import BaseModel, Field
+from typing_extensions import NotRequired
+
+from langgraph.prebuilt import InjectedState, ToolNode, create_react_agent
+from langgraph.prebuilt.chat_agent_executor import AgentState
+
+from .model import FakeToolCallingModel
+
+
+class CustomAgentStateWithNotRequired(AgentState):
+    """Custom state with a NotRequired field (TypedDict style)."""
+
+    city: NotRequired[str]
+
+
+class CustomAgentStatePydanticWithDefault(BaseModel):
+    """Custom state with Optional field and default (Pydantic style)."""
+
+    messages: Annotated[list[AnyMessage], add_messages]
+    remaining_steps: int = Field(default=10)
+    city: str | None = Field(default=None)
+
+
+@tool
+def get_weather(city: Annotated[str | None, InjectedState("city")] = None) -> str:
+    """Get weather for a given city."""
+    if city is None:
+        return "No city provided"
+    return f"It's always sunny in {city}!"
+
+
+def _create_mock_runtime(
+    state: dict | None = None,
+    store=None,
+):
+    """Create a mock Runtime for testing ToolNode directly."""
+    from unittest.mock import Mock
+
+    from langgraph.runtime import Runtime
+
+    mock_runtime = Mock(spec=Runtime)
+    mock_runtime.context = {}
+    return mock_runtime
+
+
+def _create_config_with_runtime(store=None, state=None):
+    """Create a RunnableConfig with mocked runtime for direct ToolNode testing."""
+    from langgraph.prebuilt.tool_node import ToolRuntime
+
+    tool_runtime = ToolRuntime(
+        state=state or {},
+        config={},
+        context={},
+        store=store,
+        stream_writer=None,
+        tools=[],
+        tool_call_id="test_id",
+    )
+    return {
+        "configurable": {
+            "__pregel_runtime": _create_mock_runtime(),
+            "__tool_runtime__": tool_runtime,
+        }
+    }
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_injected_state_not_required_field_missing_injects_none():
+    """Test that InjectedState with NotRequired field injects None when field is missing.
+
+    This verifies the fix for https://github.com/langchain-ai/langchain/issues/35585
+    """
+    tool_node = ToolNode([get_weather])
+
+    tool_call = {
+        "name": "get_weather",
+        "args": {},
+        "id": "call_1",
+        "type": "tool_call",
+    }
+    ai_msg = AIMessage("Let me check the weather", tool_calls=[tool_call])
+
+    # State WITHOUT the "city" field - should inject None instead of raising KeyError
+    state_without_city: CustomAgentStateWithNotRequired = {
+        "messages": [HumanMessage("What's the weather?"), ai_msg],
+    }
+
+    result = tool_node.invoke(
+        state_without_city,
+        config=_create_config_with_runtime(state=state_without_city),
+    )
+
+    assert len(result["messages"]) == 1
+    tool_msg = result["messages"][0]
+    assert isinstance(tool_msg, ToolMessage)
+    assert "No city provided" in tool_msg.content
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_injected_state_not_required_field_present_works():
+    """Test that InjectedState with NotRequired field works when field IS present."""
+    tool_node = ToolNode([get_weather])
+
+    tool_call = {
+        "name": "get_weather",
+        "args": {},
+        "id": "call_1",
+        "type": "tool_call",
+    }
+    ai_msg = AIMessage("Let me check the weather", tool_calls=[tool_call])
+
+    # State WITH the "city" field - this should work
+    state_with_city: CustomAgentStateWithNotRequired = {
+        "messages": [HumanMessage("What's the weather?"), ai_msg],
+        "city": "San Francisco",
+    }
+
+    result = tool_node.invoke(
+        state_with_city,
+        config=_create_config_with_runtime(state=state_with_city),
+    )
+
+    assert len(result["messages"]) == 1
+    tool_msg = result["messages"][0]
+    assert isinstance(tool_msg, ToolMessage)
+    assert "San Francisco" in tool_msg.content
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_create_react_agent_injected_state_not_required_field_missing():
+    """Test create_react_agent with InjectedState using NotRequired field that is missing.
+
+    This verifies the fix for https://github.com/langchain-ai/langchain/issues/35585
+    """
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather],
+        state_schema=CustomAgentStateWithNotRequired,
+    )
+
+    # Invoke WITHOUT the city field - should work, injecting None
+    result = agent.invoke(
+        {"messages": [HumanMessage("What's the weather?")]},
+    )
+
+    # Check that the tool was called successfully with None injected
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "No city provided" in tool_messages[0].content
+
+
+@pytest.mark.skipif(
+    sys.version_info < (3, 11),
+    reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
+)
+def test_create_react_agent_injected_state_not_required_field_present():
+    """Test create_react_agent with InjectedState using NotRequired field that IS present."""
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather],
+        state_schema=CustomAgentStateWithNotRequired,
+    )
+
+    # Invoke WITH the city field
+    result = agent.invoke(
+        {
+            "messages": [HumanMessage("What's the weather?")],
+            "city": "San Francisco",
+        },
+    )
+
+    # Check that the tool was called successfully
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "San Francisco" in tool_messages[0].content
+
+
+@tool
+def get_weather_optional(city: Annotated[str | None, InjectedState("city")]) -> str:
+    """Get weather for a given city (accepts None)."""
+    if city is None:
+        return "Please provide a city!"
+    return f"It's always sunny in {city}!"
+
+
+def test_pydantic_state_with_default_field_missing_works():
+    """Test that Pydantic state with Optional field and default=None works when field is missing.
+
+    This is the workaround suggested in the issue comments - using Pydantic BaseModel
+    with `city: Optional[str] = Field(default=None)` instead of TypedDict with NotRequired.
+    """
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather_optional", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather_optional],
+        state_schema=CustomAgentStatePydanticWithDefault,
+    )
+
+    # Invoke WITHOUT the city field - should work because Pydantic provides default
+    result = agent.invoke(
+        {"messages": [HumanMessage("What's the weather?")]},
+    )
+
+    # Check that the tool was called successfully with None
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "Please provide a city!" in tool_messages[0].content
+
+
+def test_pydantic_state_with_default_field_present_works():
+    """Test that Pydantic state with Optional field works when field IS present."""
+    model = FakeToolCallingModel(
+        tool_calls=[
+            [{"name": "get_weather_optional", "args": {}, "id": "call_1"}],
+            [],  # No more tool calls, agent should stop
+        ]
+    )
+
+    agent = create_react_agent(
+        model,
+        tools=[get_weather_optional],
+        state_schema=CustomAgentStatePydanticWithDefault,
+    )
+
+    # Invoke WITH the city field
+    result = agent.invoke(
+        {
+            "messages": [HumanMessage("What's the weather?")],
+            "city": "San Francisco",
+        },
+    )
+
+    # Check that the tool was called successfully
+    messages = result["messages"]
+    tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
+    assert len(tool_messages) == 1
+    assert "San Francisco" in tool_messages[0].content
@@ -1320,6 +1320,98 @@ async def test_state_extraction_with_tool_call_with_context_async() -> None:
    assert "tool_call" not in state_seen[0]


+def _config_with_channel_read(
+    channel_values: dict[str, object],
+    store: BaseStore | None = None,
+) -> RunnableConfig:
+    """Build a config that mimics `CONFIG_KEY_READ` as Pregel installs it.
+
+    Pregel always installs a `functools.partial(local_read, scratchpad,
+    channels, managed, task)`, and `ToolNode` introspects that partial to
+    learn channel names. The stub matches the shape: partial whose second and
+    third positional args are `channels` and `managed` mappings.
+    """
+    import functools
+
+    channels_stub = {k: None for k in channel_values}
+    managed_stub: dict[str, object] = {}
+
+    # Shape matches pregel's real partial:
+    # functools.partial(local_read, scratchpad, channels, managed, task)
+    def _read(scratchpad, channels, managed, task, select, fresh):  # noqa: ARG001
+        if isinstance(select, str):
+            return channel_values[select]
+        return {k: channel_values[k] for k in select if k in channel_values}
+
+    read = functools.partial(_read, None, channels_stub, managed_stub, None)
+    cfg = _create_config_with_runtime(store)
+    cfg["configurable"]["__pregel_read"] = read
+    return cfg
+
+
+def test_list_form_send_hydrates_state_from_channel_read() -> None:
+    """Send('tools', [tool_call]) with no inlined state should hydrate
+    ToolRuntime.state from CONFIG_KEY_READ (full state read)."""
+    state_seen = []
+
+    def state_inspector_handler(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        state_seen.append(request.state)
+        return execute(request)
+
+    channel_values = {
+        "messages": [AIMessage("from channels")],
+        "files": {"/a.md": "body"},
+    }
+
+    tool_node = ToolNode([add], wrap_tool_call=state_inspector_handler)
+
+    tool_call: ToolCall = {
+        "name": "add",
+        "args": {"a": 1, "b": 2},
+        "id": "call_1",
+        "type": "tool_call",
+    }
+
+    tool_node.invoke([tool_call], config=_config_with_channel_read(channel_values))
+
+    assert len(state_seen) == 1
+    got = state_seen[0]
+    assert got == channel_values
+    assert "messages" in got and "files" in got
+
+
+async def test_list_form_send_hydrates_state_async() -> None:
+    state_seen = []
+
+    def state_inspector_handler(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        state_seen.append(request.state)
+        return execute(request)
+
+    channel_values = {"messages": [AIMessage("from channels")], "files": {}}
+
+    tool_node = ToolNode([add], wrap_tool_call=state_inspector_handler)
+
+    tool_call: ToolCall = {
+        "name": "add",
+        "args": {"a": 1, "b": 2},
+        "id": "call_1",
+        "type": "tool_call",
+    }
+
+    await tool_node.ainvoke(
+        [tool_call], config=_config_with_channel_read(channel_values)
+    )
+
+    assert len(state_seen) == 1
+    assert state_seen[0] == channel_values
+
+
 def test_tool_call_request_is_frozen() -> None:
    """Test that ToolCallRequest raises deprecation warnings on direct attribute reassignment."""
    tool_call: ToolCall = {"name": "add", "args": {"a": 1, "b": 2}, "id": "call_1"}
@@ -2016,8 +2016,21 @@ async def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call_async()
    assert tool_message.tool_call_id == "call_dynamic_2"


-def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
-    """Test that execution_info and server_info are forwarded from Runtime to ToolRuntime."""
+def test_tool_runtime_defaults_tools_to_empty_list() -> None:
+    runtime = ToolRuntime(
+        state={},
+        context=None,
+        config={},
+        stream_writer=lambda *args, **kwargs: None,
+        tool_call_id=None,
+        store=None,
+    )
+
+    assert runtime.tools == []
+
+
+def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
+    """Test that execution_info, server_info, and tools are forwarded from Runtime to ToolRuntime."""
    from langgraph.runtime import ExecutionInfo, ServerInfo

    exec_info = ExecutionInfo(
@@ -2043,9 +2056,15 @@ def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
        """Tool that captures runtime info."""
        captured["execution_info"] = runtime.execution_info
        captured["server_info"] = runtime.server_info
+        captured["tools"] = runtime.tools
        return "ok"

-    node = ToolNode([info_tool])
+    @dec_tool
+    def other_tool(y: int) -> str:
+        """Another tool available to the runtime."""
+        return str(y)
+
+    node = ToolNode([info_tool, other_tool])
    tool_call = {
        "name": "info_tool",
        "args": {"x": 1},
@@ -2054,17 +2073,21 @@ def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
    }
    msg = AIMessage("", tool_calls=[tool_call])
    config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
-    node.invoke({"messages": [msg]}, config=config)
+    result = node.invoke({"messages": [msg]}, config=config)

+    assert result["messages"][-1].content == "ok"
    assert captured["execution_info"] is exec_info
    assert captured["execution_info"].thread_id == "t-1"
    assert captured["execution_info"].task_id == "tk-1"
    assert captured["server_info"] is server_info
    assert captured["server_info"].assistant_id == "asst-1"
+    assert [tool.name for tool in captured["tools"]] == ["info_tool", "other_tool"]


-async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> None:
-    """Test that execution_info and server_info are forwarded in async path."""
+async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async() -> (
+    None
+):
+    """Test that execution_info, server_info, and tools are forwarded in async path."""
    from langgraph.runtime import ExecutionInfo, ServerInfo

    exec_info = ExecutionInfo(
@@ -2090,9 +2113,15 @@ async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> N
        """Async tool that captures runtime info."""
        captured["execution_info"] = runtime.execution_info
        captured["server_info"] = runtime.server_info
+        captured["tools"] = runtime.tools
        return "ok"

-    node = ToolNode([info_tool_async])
+    @dec_tool
+    async def other_tool_async(y: int) -> str:
+        """Another async tool available to the runtime."""
+        return str(y)
+
+    node = ToolNode([info_tool_async, other_tool_async])
    tool_call = {
        "name": "info_tool_async",
        "args": {"x": 1},
@@ -2101,12 +2130,17 @@ async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> N
    }
    msg = AIMessage("", tool_calls=[tool_call])
    config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
-    await node.ainvoke({"messages": [msg]}, config=config)
+    result = await node.ainvoke({"messages": [msg]}, config=config)

+    assert result["messages"][-1].content == "ok"
    assert captured["execution_info"] is exec_info
    assert captured["execution_info"].thread_id == "t-2"
    assert captured["server_info"] is server_info
    assert captured["server_info"].graph_id == "graph-2"
+    assert [tool.name for tool in captured["tools"]] == [
+        "info_tool_async",
+        "other_tool_async",
+    ]


 # --- InjectedToolArg security tests ---
@@ -2202,3 +2236,195 @@ def test_tool_node_injected_state_overwrites_llm_value() -> None:
    )
    tool_message = result["messages"][-1]
    assert tool_message.content == "PUBLIC_DATA"
+
+
+class _ReturningTool(BaseTool):
+    """A tool that returns a configured value verbatim."""
+
+    name: str = "list_tool"
+    description: str = "Returns a configured value"
+    return_value: Any = None
+
+    def _run(self, **kwargs: Any) -> Any:
+        return self.return_value
+
+    async def _arun(self, **kwargs: Any) -> Any:
+        return self.return_value
+
+
+def _list_tool_call(outer_id: str = "call-1") -> dict[str, Any]:
+    return {"name": "list_tool", "args": {}, "id": outer_id, "type": "tool_call"}
+
+
+def _invoke_returning(
+    return_value: Any,
+    *,
+    outer_id: str = "call-1",
+    handle_tool_errors: bool = True,
+) -> Any:
+    node = ToolNode(
+        [_ReturningTool(return_value=return_value)],
+        handle_tool_errors=handle_tool_errors,
+    )
+    return node.invoke(
+        {"messages": [AIMessage("", tool_calls=[_list_tool_call(outer_id)])]},
+        config=_create_config_with_runtime(),
+    )
+
+
+def test_tool_node_list_return_command_and_tool_message() -> None:
+    """Valid: tool returns [Command(update={...}), ToolMessage(...)]."""
+    outer_id = "call-1"
+    result = _invoke_returning(
+        [
+            Command(update={"foo": "bar"}),
+            ToolMessage(content="done", tool_call_id=outer_id),
+        ]
+    )
+    assert isinstance(result, list)
+    commands = [r for r in result if isinstance(r, Command)]
+    assert len(commands) == 1
+    assert commands[0].update == {"foo": "bar"}
+    non_commands = [r for r in result if not isinstance(r, Command)]
+    assert len(non_commands) == 1
+    assert isinstance(non_commands[0], dict)
+    msgs = non_commands[0]["messages"]
+    assert len(msgs) == 1
+    assert isinstance(msgs[0], ToolMessage)
+    assert msgs[0].content == "done"
+    assert msgs[0].tool_call_id == outer_id
+
+
+def test_tool_node_list_return_nested_terminator() -> None:
+    """Valid: terminator nested inside Command.update['messages']."""
+    outer_id = "call-1"
+    result = _invoke_returning(
+        [
+            Command(update={"foo": "bar"}),
+            Command(
+                update={
+                    "messages": [ToolMessage(content="done", tool_call_id=outer_id)]
+                }
+            ),
+        ]
+    )
+    assert isinstance(result, list)
+    commands = [r for r in result if isinstance(r, Command)]
+    assert len(commands) == 2
+    updates = [c.update for c in commands]
+    assert {"foo": "bar"} in updates
+    msgs_update = next(u for u in updates if "messages" in (u or {}))
+    assert any(
+        isinstance(m, ToolMessage) and m.tool_call_id == outer_id
+        for m in msgs_update["messages"]
+    )
+
+
+def test_tool_node_list_return_parent_goto_with_terminator() -> None:
+    """Valid: [Command(graph=PARENT, goto=[Send(...)]), ToolMessage(...)]."""
+    outer_id = "call-1"
+    result = _invoke_returning(
+        [
+            Command(graph=Command.PARENT, goto=[Send("child", {})]),
+            ToolMessage(content="ok", tool_call_id=outer_id),
+        ]
+    )
+    assert isinstance(result, list)
+    parent_cmds = [
+        r for r in result if isinstance(r, Command) and r.graph is Command.PARENT
+    ]
+    assert len(parent_cmds) == 1
+    assert isinstance(parent_cmds[0].goto, list)
+    assert any(isinstance(s, Send) for s in parent_cmds[0].goto)
+    non_commands = [r for r in result if not isinstance(r, Command)]
+    assert len(non_commands) == 1
+
+
+def test_tool_node_list_return_no_terminator_raises() -> None:
+    """Invalid: list with no terminating ToolMessage."""
+    with pytest.raises(ValueError, match="0 messages bound to tool_call_id"):
+        _invoke_returning([Command(update={"foo": "bar"})], handle_tool_errors=False)
+
+
+def test_tool_node_list_return_multiple_terminators_raises() -> None:
+    """Invalid: list with two terminating ToolMessages."""
+    outer_id = "call-1"
+    with pytest.raises(ValueError, match="2 messages bound to tool_call_id"):
+        _invoke_returning(
+            [
+                ToolMessage(content="a", tool_call_id=outer_id),
+                ToolMessage(content="b", tool_call_id=outer_id),
+            ],
+            handle_tool_errors=False,
+        )
+
+
+def test_tool_node_list_return_validation_error_handled() -> None:
+    """handle_tool_errors=True converts validation errors to an error ToolMessage."""
+    result = _invoke_returning([Command(update={"foo": "bar"})])
+    assert isinstance(result, dict)
+    msg = result["messages"][0]
+    assert isinstance(msg, ToolMessage)
+    assert msg.status == "error"
+    assert "0 messages bound to tool_call_id" in msg.content
+
+
+async def test_tool_node_list_return_async_smoke() -> None:
+    """Async path parallels sync for the happy case."""
+    outer_id = "call-1"
+    node = ToolNode(
+        [
+            _ReturningTool(
+                return_value=[
+                    Command(update={"foo": "bar"}),
+                    ToolMessage(content="done", tool_call_id=outer_id),
+                ]
+            )
+        ]
+    )
+    result = await node.ainvoke(
+        {"messages": [AIMessage("", tool_calls=[_list_tool_call(outer_id)])]},
+        config=_create_config_with_runtime(),
+    )
+    assert isinstance(result, list)
+    commands = [r for r in result if isinstance(r, Command)]
+    assert len(commands) == 1 and commands[0].update == {"foo": "bar"}
+
+
+def test_tool_node_list_return_mixed_with_regular_tool() -> None:
+    """List-returning tool and a regular tool dispatched from the same AIMessage."""
+    list_tool_id = "call-list"
+    regular_tool_id = "call-regular"
+    list_tool = _ReturningTool(
+        return_value=[
+            Command(update={"foo": "bar"}),
+            ToolMessage(content="list done", tool_call_id=list_tool_id),
+        ]
+    )
+
+    def regular_tool(x: int) -> str:
+        """A normal tool."""
+        return f"regular: {x}"
+
+    tool_calls = [
+        {"name": "list_tool", "args": {}, "id": list_tool_id, "type": "tool_call"},
+        {
+            "name": "regular_tool",
+            "args": {"x": 7},
+            "id": regular_tool_id,
+            "type": "tool_call",
+        },
+    ]
+    node = ToolNode([list_tool, regular_tool])
+    result = node.invoke(
+        {"messages": [AIMessage("", tool_calls=tool_calls)]},
+        config=_create_config_with_runtime(),
+    )
+    assert isinstance(result, list)
+    commands = [r for r in result if isinstance(r, Command)]
+    assert len(commands) == 1
+    assert commands[0].update == {"foo": "bar"}
+    all_msgs = [m for r in result if isinstance(r, dict) for m in r["messages"]]
+    tool_call_ids = {m.tool_call_id for m in all_msgs}
+    assert list_tool_id in tool_call_ids
+    assert regular_tool_id in tool_call_ids
@@ -249,7 +249,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.2.25"
+version = "1.3.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -261,14 +261,14 @@ dependencies = [
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 ]
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+    { url = "https://files.pythonhosted.org/packages/a1/c2/8493be505921857988db068b7c027f28a9b1587b4425c6a32b1221c9c9fe/langchain_core-1.3.1-py3-none-any.whl", hash = "sha256:8b13d19d3bed3f4768df12c7f6932d2ada715f3ac9fd020c63d28c693968269e", size = 515879, upload-time = "2026-04-23T18:53:59.94Z" },
 ]

 [[package]]
 name = "langgraph"
-version = "1.1.6"
+version = "1.1.10"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -281,7 +281,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.1" },
+    { name = "langchain-core", specifier = ">=1.3.0,<2" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "." },
    { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -352,7 +352,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -490,7 +490,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.9"
+version = "1.0.13"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -535,7 +535,7 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", specifier = ">=1.3.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

@@ -619,7 +619,7 @@ test = [

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-version = "0.6.4"
+version = "0.7.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -629,11 +629,12 @@ dependencies = [
    { name = "requests" },
    { name = "requests-toolbelt" },
    { name = "uuid-utils" },
+    { name = "xxhash" },
    { name = "zstandard" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
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+    { url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
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+version = "9.0.3"
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 [[package]]
@@ -262,7 +262,7 @@ wheels = [

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-version = "1.2.28"
+version = "1.3.1"
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@@ -274,14 +274,14 @@ dependencies = [
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 [[package]]
 name = "langgraph"
-version = "1.1.6"
+version = "1.1.10"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -294,7 +294,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.1" },
+    { name = "langchain-core", specifier = ">=1.3.0,<2" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "../prebuilt" },
    { name = "langgraph-sdk", editable = "." },
@@ -365,7 +365,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.1"
+version = "4.0.3"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -413,7 +413,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.9"
+version = "1.0.13"
 source = { editable = "../prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -422,7 +422,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.0.0" },
+    { name = "langchain-core", specifier = ">=1.3.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

@@ -534,7 +534,7 @@ test = [

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-version = "0.7.20"
+version = "0.7.31"
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