Add sync StreamMux, SubgraphRunStream, and chat model stream enhancements

Adds AsyncStreamMux sync counterpart, exports SubgraphRunStream, improves EventLog future resolution safety, and expands run_stream with sync graph run support. Includes comprehensive test updates across event log, mux, reducers, and run stream modules.
feat(langgraph): add streamV2 infrastructure with unified transformer extensions
2026-08-28 10:49:56 +02:00 · 2026-04-15 11:00:46 -04:00 · 2026-04-14 15:20:03 -04:00
87 changed files with 7529 additions and 13380 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" != "1.1.14" ]; then
-            echo "LANGCHAIN_OPENAI_VERSION != 1.1.14; $LANGCHAIN_OPENAI_VERSION"
+          if [ "$LANGCHAIN_OPENAI_VERSION" != "1.0.1" ]; then
+            echo "LANGCHAIN_OPENAI_VERSION != 1.0.1; $LANGCHAIN_OPENAI_VERSION"
            exit 1
          fi
          LANGCHAIN_ANTHROPIC_VERSION=$(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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@@ -6,11 +6,6 @@ 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"
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    { name = "langchain-core" },
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 name = "zstandard"
 version = "0.25.0"
@@ -2,11 +2,6 @@

 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 = "1.2.28"
+version = "1.2.22"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -261,14 +261,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
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-]
-
 [[package]]
 name = "zstandard"
 version = "0.25.0"
@@ -26,9 +26,6 @@ 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.
@@ -1,10 +1,3 @@
-"""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
@@ -46,36 +46,6 @@ 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.
@@ -86,10 +56,6 @@ 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__(
@@ -104,11 +70,8 @@ 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 = (
@@ -177,23 +140,19 @@ class JsonPlusSerializer(SerializerProtocol):
        return out

    def _reviver(self, value: dict[str, Any]) -> Any:
-        if (
+        if self._allowed_json_modules and (
            value.get("lc", None) == 2
            and value.get("type", None) == "constructor"
            and value.get("id", None) is not None
        ):
-            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,
-                        )
+            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,
+                )

        return LC_REVIVER(value)

@@ -241,13 +200,6 @@ 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}). "
@@ -575,13 +527,10 @@ def _create_msgpack_ext_hook(
                    "name": name,
                }
            )
-            _warn_once(
-                _warned_unregistered_types,
-                key,
+            logger.warning(
                "Deserializing unregistered type %s.%s from checkpoint. "
                "This will be blocked in a future version. "
-                "Set LANGGRAPH_STRICT_MSGPACK=true to block now, or add "
-                "to allowed_msgpack_modules to allow explicitly: [(%r, %r)]",
+                "Add to allowed_msgpack_modules to silence: [(%r, %r)]",
                module,
                name,
                module,
@@ -599,9 +548,7 @@ def _create_msgpack_ext_hook(
                "name": name,
            }
        )
-        _warn_once(
-            _warned_blocked_types,
-            key,
+        logger.warning(
            "Blocked deserialization of %s.%s - not in allowed_msgpack_modules. "
            "Add to allowed_msgpack_modules to allow: [(%r, %r)]",
            module,
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-checkpoint"
-version = "4.0.3"
+version = "4.0.1"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"
@@ -45,9 +45,6 @@ dev = [
  "pycryptodome>=3.23.0",
 ]

-[tool.uv.sources]
-langchain-core = { git = "https://github.com/langchain-ai/langchain", branch = "cb/chat-model-updates", subdirectory = "libs/core" }
-
 [tool.hatch.build.targets.wheel]
 include = ["langgraph"]

@@ -29,8 +29,6 @@ from langgraph.checkpoint.serde.jsonplus import (
    EXT_METHOD_SINGLE_ARG,
    JsonPlusSerializer,
    _msgpack_enc,
-    _warned_blocked_types,
-    _warned_unregistered_types,
 )


@@ -104,13 +102,6 @@ def test_msgpack_method_pathlib_blocked_encrypted_strict(
 class TestEncryptedSerializerMsgpackAllowlist:
    """Test msgpack allowlist behavior through EncryptedSerializer."""

-    @pytest.fixture(autouse=True)
-    def _reset_warned_types(self) -> None:
-        # Warning dedup state is process-global; reset per-test so each case
-        # sees a fresh slate and assertions about warning emission are stable.
-        _warned_unregistered_types.clear()
-        _warned_blocked_types.clear()
-
    def test_safe_types_no_warning(self, caplog: pytest.LogCaptureFixture) -> None:
        """Test safe types deserialize without warnings through encryption."""
        serde = _make_encrypted_serde()
@@ -35,8 +35,6 @@ from langgraph.checkpoint.serde.jsonplus import (
    JsonPlusSerializer,
    _msgpack_enc,
    _msgpack_ext_hook_to_json,
-    _warned_blocked_types,
-    _warned_unregistered_types,
 )
 from langgraph.store.base import Item

@@ -333,57 +331,6 @@ 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 = {
@@ -633,14 +580,6 @@ def test_msgpack_safe_types_no_warning(caplog: pytest.LogCaptureFixture) -> None
        assert result is not None


-@pytest.fixture(autouse=True)
-def _reset_warned_types() -> None:
-    # Warning dedup state is process-global; reset per-test so each case sees
-    # a fresh slate and assertions about warning emission are stable.
-    _warned_unregistered_types.clear()
-    _warned_blocked_types.clear()
-
-
 def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) -> None:
    """Pydantic models not in allowlist should log warning but still deserialize."""
    current = _lg_msgpack.STRICT_MSGPACK_ENABLED
@@ -656,12 +595,6 @@ def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) ->
    assert "unregistered type" in caplog.text.lower()
    assert "allowed_msgpack_modules" in caplog.text
    assert result == obj
-
-    # Second deserialization of the same type should NOT produce another warning
-    caplog.clear()
-    result2 = serde.loads_typed(dumped)
-    assert "unregistered type" not in caplog.text.lower()
-    assert result2 == obj
    _lg_msgpack.STRICT_MSGPACK_ENABLED = current


@@ -706,6 +639,7 @@ def test_msgpack_allowlist_silences_warning(caplog: pytest.LogCaptureFixture) ->

 def test_msgpack_none_blocks_unregistered(caplog: pytest.LogCaptureFixture) -> None:
    """allowed_msgpack_modules=None should block unregistered types."""
+
    serde = JsonPlusSerializer(allowed_msgpack_modules=None)

    obj = MyPydantic(foo="test", bar=42, inner=InnerPydantic(hello="world"))
@@ -723,6 +657,7 @@ def test_msgpack_allowlist_blocks_non_listed(
    caplog: pytest.LogCaptureFixture,
 ) -> None:
    """Allowlists should block unregistered types even if msgpack is enabled."""
+
    serde = JsonPlusSerializer(
        allowed_msgpack_modules=[("tests.test_jsonplus", "MyPydantic")]
    )
@@ -12,25 +12,13 @@ from langgraph.checkpoint.base import (
    empty_checkpoint,
 )
 from langgraph.checkpoint.memory import InMemorySaver
-from langgraph.checkpoint.serde.jsonplus import (
-    JsonPlusSerializer,
-    _warned_blocked_types,
-    _warned_unregistered_types,
-)
+from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer


 class MemoryPydantic(BaseModel):
    foo: str


-@pytest.fixture(autouse=True)
-def _reset_warned_types() -> None:
-    # Warning dedup state is process-global; reset per-test so each case sees
-    # a fresh slate and assertions about warning emission are stable.
-    _warned_unregistered_types.clear()
-    _warned_blocked_types.clear()
-
-
 class TestMemorySaver:
    @pytest.fixture(autouse=True)
    def setup(self) -> None:
@@ -267,11 +267,10 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.3.2"
-source = { git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates#aee50839376e379891c99fcbe6d5264f66dedc68" }
+version = "1.2.28"
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
-    { name = "langchain-protocol" },
    { name = "langsmith" },
    { name = "packaging" },
    { name = "pydantic" },
@@ -280,22 +279,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-
-[[package]]
-name = "langchain-protocol"
-version = "0.0.14"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "typing-extensions" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/a8/92/32f785f077c7e898da97064f113c73fbd9ad55d1e2169cf3a391b183dedb/langchain_core-1.2.28-py3-none-any.whl", hash = "sha256:80764232581eaf8057bcefa71dbf8adc1f6a28d257ebd8b95ba9b8b452e8c6ac", size = 508727, upload-time = "2026-04-08T18:19:32.823Z" },
 ]

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.3"
+version = "4.0.1"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -339,7 +330,7 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=0.2.38" },
    { name = "ormsgpack", specifier = ">=1.12.0" },
 ]

@@ -378,7 +369,7 @@ test = [

 [[package]]
 name = "langsmith"
-version = "0.7.31"
+version = "0.6.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -388,12 +379,11 @@ dependencies = [
    { name = "requests" },
    { name = "requests-toolbelt" },
    { name = "uuid-utils" },
-    { name = "xxhash" },
    { name = "zstandard" },
 ]
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 [[package]]
@@ -1127,7 +1117,7 @@ wheels = [

 [[package]]
 name = "pytest"
-version = "9.0.3"
+version = "9.0.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -1138,9 +1128,9 @@ dependencies = [
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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==1.1.14"
+  "langchain-openai==1.0.1"
 ]
@@ -5,7 +5,7 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.1.14",
+  "langchain-openai==1.0.0a2",
  "langchain-anthropic==1.0.0a5",
  "langgraph==1.1.5"
 ]
@@ -5,7 +5,7 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.1.14",
+  "langchain-openai==1.0.0a2",
  "langgraph==1.1.2",
  "langchain_community>=0.3.0",
 ]
@@ -1086,6 +1086,11 @@
  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"
@@ -1777,6 +1782,13 @@ 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"
@@ -3676,12 +3688,16 @@ keyv@^4.5.4:
    json-buffer "3.0.1"

 "langsmith@>=0.5.0 <1.0.0":
-  version "0.5.20"
-  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.20.tgz#4021847d2ccd5a86c5eb96060f9bb5f19f80eca5"
-  integrity sha512-ULhLM8RswvQDXufLtNtvclHrWCBx8Cb5UPI6lAZC+8Dq59iHsVPz/3Ac9khWNm1VIvChRsuykixD/WrmzuuA3Q==
+  version "0.5.4"
+  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.4.tgz#f75b82b08e30db72a7d1d595b341e9666bd525e5"
+  integrity sha512-qYkNIoKpf0ZYt+cYzrDV+XI3FCexApmZmp8EMs3eDTMv0OvrHMLoxJ9IpkeoXJSX24+GPk0/jXjKx2hWerpy9w==
  dependencies:
-    p-queue "6.6.2"
-    uuid "10.0.0"
+    "@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"

 leven@^3.1.0:
  version "3.1.0"
@@ -3991,7 +4007,7 @@ 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==
@@ -4287,7 +4303,7 @@ 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@^7.7.2, semver@^7.7.3:
+semver@^7.5.3, semver@^7.5.4, semver@^7.6.3, 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==
@@ -4395,6 +4411,11 @@ 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"
@@ -4849,7 +4870,7 @@ 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==
@@ -217,6 +217,11 @@
  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"
@@ -338,6 +343,13 @@ 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"
@@ -496,11 +508,38 @@ 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"
@@ -1020,6 +1059,11 @@ 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"
@@ -1328,12 +1372,16 @@ keyv@^4.5.4:
    json-buffer "3.0.1"

 "langsmith@>=0.5.0 <1.0.0":
-  version "0.5.20"
-  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.20.tgz#4021847d2ccd5a86c5eb96060f9bb5f19f80eca5"
-  integrity sha512-ULhLM8RswvQDXufLtNtvclHrWCBx8Cb5UPI6lAZC+8Dq59iHsVPz/3Ac9khWNm1VIvChRsuykixD/WrmzuuA3Q==
+  version "0.5.4"
+  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.4.tgz#f75b82b08e30db72a7d1d595b341e9666bd525e5"
+  integrity sha512-qYkNIoKpf0ZYt+cYzrDV+XI3FCexApmZmp8EMs3eDTMv0OvrHMLoxJ9IpkeoXJSX24+GPk0/jXjKx2hWerpy9w==
  dependencies:
-    p-queue "6.6.2"
-    uuid "10.0.0"
+    "@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"

 levn@^0.4.1:
  version "0.4.1"
@@ -1480,7 +1528,7 @@ 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==
@@ -1642,6 +1690,11 @@ 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"
@@ -1730,6 +1783,11 @@ 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"
@@ -1780,6 +1838,13 @@ 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"
@@ -1901,7 +1966,7 @@ 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__ = "0.4.24"
+__version__ = "0.4.21"
@@ -1,124 +0,0 @@
-"""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,
-    )
@@ -26,15 +26,8 @@ class LogData(TypedDict):
    params: dict[str, Any]


-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
+def get_anonymized_params(kwargs: dict[str, Any]) -> dict[str, bool]:
+    params = {}

    # anonymize params with values
    if config := kwargs.get("config"):
@@ -95,7 +88,7 @@ def log_command(func):
            "python_version": platform.python_version(),
            "cli_version": __version__,
            "cli_command": func.__name__,
-            "params": get_anonymized_params(kwargs, cli_command=func.__name__),
+            "params": get_anonymized_params(kwargs),
        }

        background_thread = threading.Thread(target=log_data, args=(data,))
@@ -9,12 +9,35 @@ 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."""
@@ -10,13 +10,7 @@ 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


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


 def _uv_lock_package_copy_items(
-    package: UvLockPackage,
-    plan: UvLockPlan,
-    ignore_spec: pathspec.PathSpec,
+    package: UvLockPackage, plan: UvLockPlan
 ) -> 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,
@@ -483,32 +461,18 @@ 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))
            )
@@ -992,13 +956,10 @@ 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, ignore_spec
-        ):
+        for source, destination in _uv_lock_package_copy_items(package, plan):
            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,<0.9.0 ; python_version >= '3.11'",
+    "langgraph-api>=0.5.35,<0.8.0 ; python_version >= '3.11'",
    "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
 ]

@@ -99,13 +99,6 @@ 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__/")
@@ -4,7 +4,6 @@ import os
 import pathlib
 import tempfile
 import textwrap
-from unittest.mock import patch

 import click
 import pytest
@@ -1856,364 +1855,6 @@ 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 = "0.7.31"
+version = "0.7.26"
 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/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
+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" }
 wheels = [
-    { 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" },
+    { 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" },
 ]

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

 [[package]]
 name = "langsmith"
-version = "0.7.31"
+version = "0.7.26"
 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/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
+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" }
 wheels = [
-    { 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" },
+    { 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" },
 ]

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

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

@@ -217,16 +217,14 @@ def get_callback_manager_for_config(
            callbacks.add_tags(all_tags)
        if metadata := config.get("metadata"):
            callbacks.add_metadata(metadata)
-        manager = callbacks
+        return callbacks
    else:
        # otherwise create a new manager
-        manager = CallbackManager.configure(
+        return 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(
@@ -257,16 +255,14 @@ def get_async_callback_manager_for_config(
            callbacks.add_tags(all_tags)
        if metadata := config.get("metadata"):
            callbacks.add_metadata(metadata)
-        manager = callbacks
+        return callbacks
    else:
        # otherwise create a new manager
-        manager = AsyncCallbackManager.configure(
+        return 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:
@@ -312,54 +308,22 @@ 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
-
-    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
+    _empty_metadata = empty["metadata"]
+    for key, value in empty[CONF].items():
+        if _exclude_as_metadata(key, value, _empty_metadata):
+            continue
+        _empty_metadata[key] = value
    return empty


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


-def _exclude_as_metadata(key: str, value: Any) -> bool:
+def _exclude_as_metadata(key: str, value: Any, metadata: Mapping[str, 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",
-    )
-)
@@ -66,9 +66,6 @@ CONFIG_KEY_RUNTIME = sys.intern("__pregel_runtime")
 # holds a `Runtime` instance with context, store, stream writer, etc.
 CONFIG_KEY_RESUME_MAP = sys.intern("__pregel_resume_map")
 # holds a mapping of task ns -> resume value for resuming tasks
-CONFIG_KEY_STREAM_MESSAGES_V2 = sys.intern("__pregel_stream_messages_v2")
-# when True, attach StreamMessagesHandlerV2 so content-block (v2) events
-# flow through stream_mode="messages"; set by StreamingHandler only.

 # --- Other constants ---
 PUSH = sys.intern("__pregel_push")
@@ -110,7 +107,6 @@ RESERVED = {
    CONFIG_KEY_CHECKPOINT_ID,
    CONFIG_KEY_CHECKPOINT_NS,
    CONFIG_KEY_RESUME_MAP,
-    CONFIG_KEY_STREAM_MESSAGES_V2,
    # other constants
    PUSH,
    PULL,
@@ -1,394 +0,0 @@
-"""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,
-    )
@@ -1045,7 +1045,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        interrupt_after: All | list[str] | None = None,
        debug: bool = False,
        name: str | None = None,
-        transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
    ) -> CompiledStateGraph[StateT, ContextT, InputT, OutputT]:
        """Compiles the `StateGraph` into a `CompiledStateGraph` object.

@@ -1078,13 +1077,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
            interrupt_after: An optional list of node names to interrupt after.
            debug: A flag indicating whether to enable debug mode.
            name: The name to use for the compiled graph.
-            transformers: Optional sequence of `StreamTransformer` classes or
-                configured factories. Classes and factories are instantiated
-                per run whenever `stream_v2` / `astream_v2` is called and are
-                propagated to subgraph scopes. Custom factories should follow
-                the standard `StreamTransformer` constructor shape by
-                accepting `scope` as their first argument. Appended after the
-                built-in stream transformers.

        Returns:
            CompiledStateGraph: The compiled `StateGraph`.
@@ -1167,7 +1159,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
            store=store,
            cache=cache,
            name=name or "LangGraph",
-            stream_transformers=transformers,
        )
        compiled._serde_allowlist = serde_allowlist

@@ -62,11 +62,6 @@ 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
@@ -122,7 +117,6 @@ from langgraph.types import (
    CachePolicy,
    Command,
    Durability,
-    Interrupt,
    PregelExecutableTask,
    RetryPolicy,
    Send,
@@ -209,8 +203,6 @@ 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

@@ -236,7 +228,6 @@ 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
@@ -261,8 +252,6 @@ 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)
@@ -314,40 +303,6 @@ 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:
@@ -692,7 +647,7 @@ 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.
-        is_time_traveling = self.is_replaying and (
+        if self.is_replaying and (
            # Time-travel to a subgraph checkpoint: the parent sets
            # RESUMING=True (it can't distinguish time-travel from resume),
            # so we check if this subgraph's own ns is in checkpoint_map.
@@ -710,8 +665,7 @@ 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
            ]
@@ -766,26 +720,6 @@ 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
@@ -828,28 +762,14 @@ 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/fork), use the fork's parent
+            # parent. For forks (source=update), use the fork's parent
            # checkpoint ID since the fork was created after the subgraph's
            # checkpoints from the original execution.
-            #
-            # Only gate on is_time_traveling (not is_replaying). When the
-            # client resumes with an explicit checkpoint_id that happens to
-            # point at the current head (e.g. LangGraph Studio sending
-            # `checkpoint: {checkpoint_id}` alongside Command(resume=...)),
-            # is_replaying is True but is_time_traveling is False. In that
-            # case subgraphs should load their latest checkpoint normally,
-            # not go through ReplayState's before-bound lookup which would
-            # miss subgraph checkpoints created during processing of the
-            # current parent step.
            replay_state: ReplayState | None = None
-            if is_time_traveling:
+            if self.is_replaying:
                replay_checkpoint_id = self.checkpoint["id"]
                if (
-                    self.checkpoint_metadata.get("source")
-                    in (
-                        "update",
-                        "fork",
-                    )
+                    self.checkpoint_metadata.get("source") == "update"
                    and self.prev_checkpoint_config
                ):
                    replay_checkpoint_id = self.prev_checkpoint_config[CONF].get(
@@ -865,8 +785,6 @@ 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:
@@ -967,10 +885,8 @@ class PregelLoop:
            self._put_checkpoint(self.checkpoint_metadata)
            self._put_pending_writes()
        # suppress interrupt
-        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)
+        suppress = isinstance(exc_value, GraphInterrupt) and not self.is_nested
+        if suppress:
            # emit one last "values" event, with pending writes applied
            if (
                hasattr(self, "tasks")
@@ -997,11 +913,12 @@ class PregelLoop:
                        self.channels,
                    )
            # emit INTERRUPT if exception is empty (otherwise emitted by put_writes)
-            if not interrupt.args or not interrupt.args[0]:
-                interrupt_payload = interrupt.args[0] if interrupt.args else ()
+            if exc_value is not None and (not exc_value.args or not exc_value.args[0]):
                self._emit(
                    "updates",
-                    lambda: iter([{INTERRUPT: interrupt_payload}]),
+                    lambda: iter(
+                        [{INTERRUPT: cast(GraphInterrupt, exc_value).args[0]}]
+                    ),
                )
            # save final output
            self.output = read_channels(self.channels, self.output_keys)
@@ -1123,7 +1040,6 @@ 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,
@@ -1145,7 +1061,6 @@ 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:
@@ -1221,7 +1136,6 @@ 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):
@@ -1322,7 +1236,6 @@ 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,
@@ -1344,7 +1257,6 @@ 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:
@@ -1423,7 +1335,6 @@ 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):
@@ -24,11 +24,6 @@ try:
 except ImportError:
    _StreamingCallbackHandler = object  # type: ignore

-try:
-    from langchain_core.tracers._streaming import _V2StreamingCallbackHandler
-except ImportError:
-    _V2StreamingCallbackHandler = object  # type: ignore
-
 T = TypeVar("T")
 Meta = tuple[tuple[str, ...], dict[str, Any]]

@@ -253,126 +248,3 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
        **kwargs: Any,
    ) -> Any:
        self.metadata.pop(run_id, None)
-
-
-class StreamMessagesHandlerV2(StreamMessagesHandler, _V2StreamingCallbackHandler):
-    """v2 variant of `StreamMessagesHandler`.
-
-    Declaring `_V2StreamingCallbackHandler` as a base flips
-    `BaseChatModel.invoke` to route through `_stream_chat_model_events`
-    (firing `on_stream_event`) instead of `_stream` (firing
-    `on_llm_new_token`). Inherits `on_stream_event` from the parent,
-    which forwards protocol events onto the messages stream channel.
-
-    Pregel attaches this class instead of the v1 handler only when
-    `StreamingHandler` opts in via the internal
-    `CONFIG_KEY_STREAM_MESSAGES_V2` config key; direct
-    `graph.stream(stream_mode="messages")` callers keep the v1
-    AIMessageChunk shape.
-    """
-
-    def on_llm_new_token(
-        self,
-        token: str,
-        *,
-        chunk: ChatGenerationChunk | None = None,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        tags: list[str] | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Intentional no-op — v1 chunks are not used on v2-flagged runs.
-
-        The v2 marker already steers `invoke` to the event generator, so
-        `on_llm_new_token` should not fire under normal routing. This
-        override stays a pass-through (no call to `super()`) to make
-        the intent explicit and to guard against any caller (e.g. a
-        node that calls `model.stream()` directly, which still fires
-        the v1 callback) leaking AIMessageChunks onto a v2-flagged
-        messages stream.
-        """
-        # Intentionally empty: v2 handler does not forward v1 chunks.
-
-    def __init__(
-        self,
-        stream: Callable[[StreamChunk], None],
-        subgraphs: bool,
-        *,
-        parent_ns: tuple[str, ...] | None = None,
-    ) -> None:
-        super().__init__(stream, subgraphs, parent_ns=parent_ns)
-        self._streamed_run_ids: set[UUID] = set()
-
-    def on_llm_end(
-        self,
-        response: LLMResult,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        if meta := self.metadata.get(run_id):
-            if response.generations and response.generations[0]:
-                gen = response.generations[0][0]
-                if isinstance(gen, ChatGeneration):
-                    if run_id in self._streamed_run_ids:
-                        if gen.message.id is None:
-                            gen.message.id = str(uuid4())
-                        self.seen.add(gen.message.id)
-                    else:
-                        self._emit(meta, gen.message, dedupe=True)
-        self._streamed_run_ids.discard(run_id)
-        self.metadata.pop(run_id, None)
-
-    def on_llm_error(
-        self,
-        error: BaseException,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self._streamed_run_ids.discard(run_id)
-        super().on_llm_error(
-            error,
-            run_id=run_id,
-            parent_run_id=parent_run_id,
-            **kwargs,
-        )
-
-    def on_stream_event(
-        self,
-        event: dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        tags: list[str] | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Forward a protocol event from `stream_v2` as a messages stream part.
-
-        Fires once per `MessagesData` event (`message-start`, per-block
-        `content-block-*`, `message-finish`). The transformer layer
-        correlates events back to a single `ChatModelStream` via
-        `metadata["run_id"]` — attached here so the v1
-        `stream_mode="messages"` output (which emits
-        `(AIMessageChunk, metadata)` via `on_llm_new_token`) keeps its
-        original metadata shape.
-
-        Lives on the v2 handler rather than the v1 base: content-block
-        events are a v2-only concept, and forwarding them only when the
-        v2 handler is attached keeps the message channel's shape
-        predictable for v1 callers.
-        """
-        if meta := self.metadata.get(run_id):
-            # Record message_id on message-start so on_chain_end's
-            # dedupe skips the finalized AIMessage the node returns
-            # (otherwise the messages projection double-counts: once
-            # from streaming, once from the chain output).
-            if event.get("event") == "message-start":
-                self._streamed_run_ids.add(run_id)
-                msg_id = event.get("message_id")
-                if msg_id:
-                    self.seen.add(msg_id)
-            v2_meta = {**meta[1], "run_id": str(run_id)}
-            self.stream((meta[0], "messages", (event, v2_meta)))
@@ -0,0 +1,807 @@
+"""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"]
@@ -1,268 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import AsyncIterator, Callable, Iterator
-from contextvars import ContextVar, Token
-from typing import Any, TypeVar, cast
-from uuid import UUID
-
-from langchain_core.callbacks import BaseCallbackHandler
-
-from langgraph._internal._constants import NS_SEP
-from langgraph.constants import TAG_NOSTREAM
-from langgraph.pregel.protocol import StreamChunk
-
-try:
-    from langchain_core.tracers._streaming import _StreamingCallbackHandler
-except ImportError:
-    _StreamingCallbackHandler = object  # type: ignore[assignment,misc]
-
-
-T = TypeVar("T")
-
-ToolCallWriter = Callable[[Any], None]
-"""A closure bound to a single tool call that emits `tool-output-delta` events."""
-
-_tool_call_writer: ContextVar[ToolCallWriter | None] = ContextVar(
-    "langgraph_tool_call_writer", default=None
-)
-"""ContextVar holding the writer for the currently-executing tool call.
-
-Set by `StreamToolCallHandler.on_tool_start` and reset on end/error.
-Read by `ToolRuntime.emit_output_delta` (in `langgraph.prebuilt`).
-"""
-
-
-class StreamToolCallHandler(BaseCallbackHandler, _StreamingCallbackHandler):
-    """Callback handler that emits tool-call lifecycle events on the stream.
-
-    Fires on LangChain's `on_tool_*` callbacks and pushes to the `tools`
-    stream mode. Emits `tool-started` / `tool-output-delta` /
-    `tool-finished` / `tool-error` payloads keyed by `tool_call_id`.
-
-    While a tool is executing, this handler sets `_tool_call_writer` to a
-    closure bound to that call's namespace and `tool_call_id`.
-    `ToolRuntime.emit_output_delta` reads that ContextVar so tool bodies
-    can stream partial output without threading the writer through their
-    own signature.
-
-    Attached by `Pregel.stream` / `astream` when `"tools"` is in
-    `stream_modes`. `run_inline = True` keeps event ordering
-    deterministic.
-    """
-
-    run_inline = True
-
-    def __init__(
-        self,
-        stream: Callable[[StreamChunk], None],
-        subgraphs: bool,
-        *,
-        parent_ns: tuple[str, ...] | None = None,
-    ) -> None:
-        """Configure the handler to stream tool-call events.
-
-        Args:
-            stream: Callable that accepts a `StreamChunk` tuple
-                `(namespace, mode, payload)` and enqueues it.
-            subgraphs: Whether to emit events from tools called inside
-                nested subgraphs. When False, only tools at the
-                handler's own scope (`parent_ns`) emit.
-            parent_ns: Namespace where the handler was attached.
-                Mirrors the `StreamMessagesHandler` escape hatch:
-                tools whose containing namespace equals `parent_ns`
-                still emit even with `subgraphs=False`, so a node that
-                explicitly streams a subgraph with `stream_mode="tools"`
-                sees its own tools.
-        """
-        self.stream = stream
-        self.subgraphs = subgraphs
-        self.parent_ns = parent_ns
-        # run_id → (namespace, tool_call_id, ContextVar token)
-        # `on_tool_end` does not receive `tool_call_id` in kwargs, so
-        # we correlate by `run_id` which is present on every callback.
-        self._run_to_call: dict[
-            UUID, tuple[tuple[str, ...], str, Token[ToolCallWriter | None]]
-        ] = {}
-
-    def _ns_for_emit(
-        self,
-        metadata: dict[str, Any] | None,
-        tags: list[str] | None,
-    ) -> tuple[str, ...] | None:
-        """Resolve the namespace this tool call should emit at, or `None` to skip.
-
-        Mirrors `StreamMessagesHandler.on_chat_model_start`'s namespace
-        derivation: parses `langgraph_checkpoint_ns` (which ends with
-        the `node_name:task_id` of the calling node), drops that
-        trailing segment, and returns the containing subgraph's own
-        namespace. Returns `None` when the call should be silently
-        suppressed:
-
-        - `metadata` is missing — handler is attached to a context
-          without Pregel routing info.
-        - `TAG_NOSTREAM` is in `tags` — caller explicitly opted out.
-        - Tool runs in a subgraph (`len(ns) > 0`) and the handler was
-          attached with `subgraphs=False` and a different `parent_ns`
-          than the call's containing subgraph.
-        """
-        if not metadata:
-            return None
-        if tags and TAG_NOSTREAM in tags:
-            return None
-        nskey = metadata.get("langgraph_checkpoint_ns")
-        if not nskey:
-            ns: tuple[str, ...] = ()
-        else:
-            ns = tuple(cast(str, nskey).split(NS_SEP))[:-1]
-        if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
-            return None
-        return ns
-
-    def _start(
-        self,
-        serialized: dict[str, Any] | None,
-        input_str: str,
-        *,
-        run_id: UUID,
-        metadata: dict[str, Any] | None,
-        tags: list[str] | None,
-        inputs: dict[str, Any] | None,
-        kwargs: dict[str, Any],
-    ) -> None:
-        ns = self._ns_for_emit(metadata, tags)
-        if ns is None:
-            return
-        tool_call_id = cast("str | None", kwargs.get("tool_call_id")) or str(run_id)
-        tool_name = (
-            (serialized or {}).get("name")
-            or cast("str | None", kwargs.get("name"))
-            or ""
-        )
-
-        def writer(delta: Any) -> None:
-            self.stream(
-                (
-                    ns,
-                    "tools",
-                    {
-                        "event": "tool-output-delta",
-                        "tool_call_id": tool_call_id,
-                        "delta": delta,
-                    },
-                )
-            )
-
-        token = _tool_call_writer.set(writer)
-        self._run_to_call[run_id] = (ns, tool_call_id, token)
-
-        payload: dict[str, Any] = {
-            "event": "tool-started",
-            "tool_call_id": tool_call_id,
-            "tool_name": tool_name,
-        }
-        if inputs is not None:
-            payload["input"] = inputs
-        self.stream((ns, "tools", payload))
-
-    def _end(self, output: Any, *, run_id: UUID) -> None:
-        info = self._run_to_call.pop(run_id, None)
-        if info is None:
-            return
-        ns, tool_call_id, token = info
-        self._reset_writer(token)
-        self.stream(
-            (
-                ns,
-                "tools",
-                {
-                    "event": "tool-finished",
-                    "tool_call_id": tool_call_id,
-                    "output": output,
-                },
-            )
-        )
-
-    def _error(self, error: BaseException, *, run_id: UUID) -> None:
-        info = self._run_to_call.pop(run_id, None)
-        if info is None:
-            return
-        ns, tool_call_id, token = info
-        self._reset_writer(token)
-        self.stream(
-            (
-                ns,
-                "tools",
-                {
-                    "event": "tool-error",
-                    "tool_call_id": tool_call_id,
-                    "message": str(error),
-                },
-            )
-        )
-
-    def tap_output_aiter(
-        self, run_id: UUID, output: AsyncIterator[T]
-    ) -> AsyncIterator[T]:
-        """Pass-through — required by the `_StreamingCallbackHandler` protocol."""
-        return output
-
-    def tap_output_iter(self, run_id: UUID, output: Iterator[T]) -> Iterator[T]:
-        """Pass-through — sync counterpart to `tap_output_aiter`."""
-        return output
-
-    @staticmethod
-    def _reset_writer(token: Token[ToolCallWriter | None]) -> None:
-        # Token is invalid if `on_tool_end` runs in a different context
-        # than `on_tool_start` (e.g. langchain may hand off to a thread
-        # worker without copying the context). Swallow that case; the
-        # ContextVar lifetime is bounded by the enclosing task anyway.
-        try:
-            _tool_call_writer.reset(token)
-        except ValueError:
-            pass
-
-    # ------------------------------------------------------------------
-    # Sync callbacks
-    # ------------------------------------------------------------------
-
-    def on_tool_start(
-        self,
-        serialized: dict[str, Any],
-        input_str: str,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
-        inputs: dict[str, Any] | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self._start(
-            serialized,
-            input_str,
-            run_id=run_id,
-            metadata=metadata,
-            tags=tags,
-            inputs=inputs,
-            kwargs=kwargs,
-        )
-
-    def on_tool_end(
-        self,
-        output: Any,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self._end(output, run_id=run_id)
-
-    def on_tool_error(
-        self,
-        error: BaseException,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self._error(error, run_id=run_id)
@@ -16,7 +16,7 @@ from collections.abc import (
    Mapping,
    Sequence,
 )
-from dataclasses import is_dataclass, replace
+from dataclasses import is_dataclass
 from functools import partial
 from inspect import isclass
 from typing import (
@@ -73,7 +73,6 @@ from langgraph._internal._constants import (
    CONFIG_KEY_RUNTIME,
    CONFIG_KEY_SEND,
    CONFIG_KEY_STREAM,
-    CONFIG_KEY_STREAM_MESSAGES_V2,
    CONFIG_KEY_TASK_ID,
    CONFIG_KEY_THREAD_ID,
    ERROR,
@@ -97,12 +96,6 @@ 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
@@ -134,14 +127,14 @@ from langgraph.pregel._loop import (
    AsyncPregelLoop,
    SyncPregelLoop,
 )
-from langgraph.pregel._messages import (
-    StreamMessagesHandler,
-    StreamMessagesHandlerV2,
+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
-from langgraph.pregel._tools import StreamToolCallHandler
 from langgraph.pregel._utils import get_new_channel_versions
 from langgraph.pregel._validate import validate_graph, validate_keys
 from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
@@ -153,15 +146,6 @@ from langgraph.runtime import (
    Runtime,
    ServerInfo,
 )
-from langgraph.stream._mux import StreamMux
-from langgraph.stream._types import StreamTransformer
-from langgraph.stream.run_stream import AsyncGraphRunStream, GraphRunStream
-from langgraph.stream.transformers import (
-    LifecycleTransformer,
-    MessagesTransformer,
-    SubgraphTransformer,
-    ValuesTransformer,
-)
 from langgraph.types import (
    All,
    CachePolicy,
@@ -354,58 +338,6 @@ class NodeBuilder:
        )


-def _collect_stream_modes(mux: Any) -> list[StreamMode]:
-    """Return the union of `required_stream_modes` across registered transformers.
-
-    Transformers declare the stream modes they need to function, and
-    `stream_v2` asks the graph for exactly that union — no hardcoded
-    default set. If zero transformers declare a given mode, the graph
-    does not stream events for it.
-    """
-    modes: set[StreamMode] = set()
-    for transformer in mux._transformers:
-        modes.update(
-            cast(
-                "tuple[StreamMode, ...]",
-                getattr(transformer, "required_stream_modes", ()),
-            )
-        )
-    return list(modes)
-
-
-def _normalize_stream_transformer_factories(
-    specs: Sequence[Callable[[tuple[str, ...]], Any]] | None,
-) -> list[Callable[[tuple[str, ...]], Any]]:
-    """Normalize stream transformer specs to scoped factories.
-
-    A stream transformer spec is a callable that accepts
-    `scope: tuple[str, ...]` and returns a fresh `StreamTransformer`.
-    Transformer classes work when their constructor follows the same
-    shape. Pre-built instances are rejected because they cannot be
-    cloned into subgraph scopes.
-    """
-    factories: list[Callable[[tuple[str, ...]], Any]] = []
-    for spec in specs or ():
-        if isinstance(spec, StreamTransformer):
-            raise TypeError(
-                "stream_v2 transformers must be scope-aware callables, "
-                f"got pre-built instance {type(spec).__name__}. Pass the "
-                "transformer class or a factory like "
-                "`lambda scope: MyTransformer(scope, ...)`."
-            )
-        if not callable(spec):
-            raise TypeError(
-                "stream_v2 transformers must be scope-aware callables, "
-                f"got {type(spec).__name__}."
-            )
-
-        def factory(scope: tuple[str, ...], _spec: Callable[..., Any] = spec) -> Any:
-            return _spec(scope)
-
-        factories.append(factory)
-    return factories
-
-
 class Pregel(
    PregelProtocol[StateT, ContextT, InputT, OutputT],
    Generic[StateT, ContextT, InputT, OutputT],
@@ -737,7 +669,6 @@ class Pregel(
        config: RunnableConfig | None = None,
        trigger_to_nodes: Mapping[str, Sequence[str]] | None = None,
        name: str = "LangGraph",
-        stream_transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
        **deprecated_kwargs: Unpack[DeprecatedKwargs],
    ) -> None:
        if (
@@ -784,9 +715,6 @@ class Pregel(
        self.config = config
        self.trigger_to_nodes = trigger_to_nodes or {}
        self.name = name
-        self.stream_transformers: tuple[Callable[[tuple[str, ...]], Any], ...] = tuple(
-            stream_transformers or ()
-        )
        self._serde_allowlist: set[tuple[str, ...]] | None = None
        if auto_validate:
            self.validate()
@@ -2652,7 +2580,15 @@ class Pregel(
        stream = SyncQueue()

        config = ensure_config(self.config, config)
-        run_manager = None
+        callback_manager = get_callback_manager_for_config(config)
+        if "ls_integration" not in callback_manager.metadata:
+            callback_manager.add_metadata({"ls_integration": "langgraph"})
+        run_manager = callback_manager.on_chain_start(
+            None,
+            input,
+            name=config.get("run_name", self.get_name()),
+            run_id=config.get("run_id"),
+        )
        try:
            # assign defaults
            (
@@ -2673,36 +2609,6 @@ class Pregel(
                interrupt_after=interrupt_after,
                durability=durability,
            )
-            callback_manager = get_callback_manager_for_config(config)
-            if "messages" in stream_modes and version != "v2":
-                # Strip any inherited v2 messages handler so a v1 stream
-                # does not get routed through the content-block event
-                # protocol. Leave v1 handlers in place — an outer
-                # stream(stream_mode="messages", subgraphs=True) relies
-                # on its inheritable handler to observe events emitted
-                # by inner stream(stream_mode="messages") calls.
-                callback_manager.handlers = [
-                    h
-                    for h in callback_manager.handlers
-                    if not isinstance(h, StreamMessagesHandlerV2)
-                ]
-                callback_manager.inheritable_handlers = [
-                    h
-                    for h in callback_manager.inheritable_handlers
-                    if not isinstance(h, StreamMessagesHandlerV2)
-                ]
-            if "ls_integration" not in callback_manager.metadata:
-                callback_manager.add_metadata({"ls_integration": "langgraph"})
-            run_manager = callback_manager.on_chain_start(
-                None,
-                input,
-                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,
-            )
            if checkpointer is None and durability is not None:
                warnings.warn(
                    "`durability` has no effect when no checkpointer is present.",
@@ -2714,33 +2620,21 @@ class Pregel(
            # set up messages stream mode
            if "messages" in stream_modes:
                ns_ = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
-                use_stream_messages_v2 = bool(
-                    version == "v2" and config[CONF].get(CONFIG_KEY_STREAM_MESSAGES_V2)
-                )
-                messages_handler_cls = (
-                    StreamMessagesHandlerV2
-                    if use_stream_messages_v2
+                _msg_cls = (
+                    StreamProtocolMessagesHandler
+                    if config.get("configurable", {}).get(
+                        PROTOCOL_MESSAGES_STREAM_KEY, False
+                    )
                    else StreamMessagesHandler
                )
                run_manager.inheritable_handlers.append(
-                    messages_handler_cls(
+                    _msg_cls(
                        stream.put,
                        subgraphs,
                        parent_ns=tuple(ns_.split(NS_SEP)) if ns_ else None,
                    )
                )

-            # set up tools stream mode
-            if "tools" in stream_modes:
-                ns_tools = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
-                run_manager.inheritable_handlers.append(
-                    StreamToolCallHandler(
-                        stream.put,
-                        subgraphs,
-                        parent_ns=tuple(ns_tools.split(NS_SEP)) if ns_tools else None,
-                    )
-                )
-
            # set up custom stream mode
            if "custom" in stream_modes:

@@ -2786,17 +2680,6 @@ 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),
@@ -2817,9 +2700,7 @@ 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(
@@ -2881,11 +2762,9 @@ 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,
@@ -2911,8 +2790,7 @@ class Pregel(
            # set final channel values as run output
            run_manager.on_chain_end(loop.output)
        except BaseException as e:
-            if run_manager is not None:
-                run_manager.on_chain_error(e)
+            run_manager.on_chain_error(e)
            raise

    @overload
@@ -3052,7 +2930,32 @@ class Pregel(
        )

        config = ensure_config(self.config, config)
-        run_manager = None
+        callback_manager = get_async_callback_manager_for_config(config)
+        if "ls_integration" not in callback_manager.metadata:
+            callback_manager.add_metadata({"ls_integration": "langgraph"})
+        run_manager = await callback_manager.on_chain_start(
+            None,
+            input,
+            name=config.get("run_name", self.get_name()),
+            run_id=config.get("run_id"),
+        )
+        # if running from astream_log() run each proc with streaming
+        do_stream = (
+            next(
+                (
+                    True
+                    for h in run_manager.handlers
+                    if isinstance(h, _StreamingCallbackHandler)
+                    and not isinstance(
+                        h,
+                        (StreamMessagesHandler, StreamProtocolMessagesHandler),
+                    )
+                ),
+                False,
+            )
+            if _StreamingCallbackHandler is not None
+            else False
+        )
        try:
            # assign defaults
            (
@@ -3073,50 +2976,6 @@ class Pregel(
                interrupt_after=interrupt_after,
                durability=durability,
            )
-            callback_manager = get_async_callback_manager_for_config(config)
-            if "messages" in stream_modes and version != "v2":
-                # Strip any inherited v2 messages handler so a v1 stream
-                # does not get routed through the content-block event
-                # protocol. Leave v1 handlers in place — an outer
-                # astream(stream_mode="messages", subgraphs=True) relies
-                # on its inheritable handler to observe events emitted
-                # by inner astream(stream_mode="messages") calls.
-                callback_manager.handlers = [
-                    h
-                    for h in callback_manager.handlers
-                    if not isinstance(h, StreamMessagesHandlerV2)
-                ]
-                callback_manager.inheritable_handlers = [
-                    h
-                    for h in callback_manager.inheritable_handlers
-                    if not isinstance(h, StreamMessagesHandlerV2)
-                ]
-            if "ls_integration" not in callback_manager.metadata:
-                callback_manager.add_metadata({"ls_integration": "langgraph"})
-            run_manager = await callback_manager.on_chain_start(
-                None,
-                input,
-                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(
-                    (
-                        True
-                        for h in run_manager.handlers
-                        if isinstance(h, _StreamingCallbackHandler)
-                        and not isinstance(h, StreamMessagesHandler)
-                    ),
-                    False,
-                )
-                if _StreamingCallbackHandler is not None
-                else False
-            )
            if checkpointer is None and durability is not None:
                warnings.warn(
                    "`durability` has no effect when no checkpointer is present.",
@@ -3127,35 +2986,22 @@ 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))
-                use_stream_messages_v2 = bool(
-                    version == "v2" and config[CONF].get(CONFIG_KEY_STREAM_MESSAGES_V2)
-                )
-                messages_handler_cls = (
-                    StreamMessagesHandlerV2
-                    if use_stream_messages_v2
+                _msg_cls = (
+                    StreamProtocolMessagesHandler
+                    if config.get("configurable", {}).get(
+                        PROTOCOL_MESSAGES_STREAM_KEY, False
+                    )
                    else StreamMessagesHandler
                )
                run_manager.inheritable_handlers.append(
-                    messages_handler_cls(
+                    _msg_cls(
                        stream_put,
                        subgraphs,
                        parent_ns=tuple(ns_.split(NS_SEP)) if ns_ else None,
                    )
                )

-            # set up tools stream mode
-            if "tools" in stream_modes:
-                ns_tools = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
-                run_manager.inheritable_handlers.append(
-                    StreamToolCallHandler(
-                        stream_put,
-                        subgraphs,
-                        parent_ns=tuple(ns_tools.split(NS_SEP)) if ns_tools else None,
-                    )
-                )
-
            # set up custom stream mode
            def stream_writer(c: Any) -> None:
                aioloop.call_soon_threadsafe(
@@ -3216,28 +3062,6 @@ 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),
@@ -3258,9 +3082,7 @@ 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(
@@ -3342,7 +3164,6 @@ 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)
@@ -3351,8 +3172,6 @@ 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,
@@ -3379,150 +3198,9 @@ class Pregel(
            # set final channel values as run output
            await run_manager.on_chain_end(loop.output)
        except BaseException as e:
-            if run_manager is not None:
-                await asyncio.shield(run_manager.on_chain_error(e))
+            await asyncio.shield(run_manager.on_chain_error(e))
            raise

-    def stream_v2(
-        self,
-        input: InputT | Command | None,
-        config: RunnableConfig | None = None,
-        *,
-        interrupt_before: All | Sequence[str] | None = None,
-        interrupt_after: All | Sequence[str] | None = None,
-        transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
-    ) -> Any:
-        """Start a sync v2 streaming run driven by transformer projections.
-
-        Builds a `StreamMux` from the built-in `ValuesTransformer` /
-        `MessagesTransformer`, this graph's compile-time
-        `stream_transformers`, and any additional `transformers=`
-        supplied at the call site. Returns a `GraphRunStream` that the
-        caller drives by iterating any projection — no background
-        thread.
-
-        Note:
-            Nesting v1 `stream(stream_mode="messages")` inside a node
-            of a `stream_v2` run is not fully supported. The outer v2
-            messages handler is inheritable, so it sits in the inner
-            chat model's callback chain; `BaseChatModel.invoke` then
-            routes through the v2 event protocol and the inner v1
-            messages handler does not see `on_llm_new_token` chunks.
-            The inner stream still yields a finalized message via
-            `on_llm_end`, but token-by-token output is lost. Use
-            `stream_v2` for the inner graph as well, or call
-            `chat_model.stream(...)` explicitly inside the node, to
-            get token-level streaming.
-
-        Args:
-            input: Graph input.
-            config: Optional runnable config forwarded to the graph.
-            interrupt_before: Nodes to interrupt before, if any.
-            interrupt_after: Nodes to interrupt after, if any.
-            transformers: Extra transformer classes or configured factories
-                appended after compile-time `stream_transformers`. Factories
-                are called as `factory(scope)` so they can propagate to
-                subgraph scopes.
-
-        Returns:
-            A `GraphRunStream` the caller iterates to drive the run.
-        """
-        parent_ns = _resolve_parent_ns(self.config, config)
-        compiled_factories = _normalize_stream_transformer_factories(
-            self.stream_transformers
-        )
-        extra_factories = _normalize_stream_transformer_factories(transformers)
-        mux = StreamMux(
-            factories=[
-                ValuesTransformer,
-                MessagesTransformer,
-                LifecycleTransformer,
-                SubgraphTransformer,
-                *compiled_factories,
-                *extra_factories,
-            ],
-            scope=parent_ns,
-            is_async=False,
-        )
-        values_t = cast(ValuesTransformer, mux.transformer_by_key("values"))
-        graph_iter = iter(
-            self.stream(
-                input,
-                patch_configurable(config, {CONFIG_KEY_STREAM_MESSAGES_V2: True}),
-                stream_mode=_collect_stream_modes(mux),
-                subgraphs=True,
-                version="v2",
-                interrupt_before=interrupt_before,
-                interrupt_after=interrupt_after,
-            )
-        )
-        return GraphRunStream(graph_iter, mux, values_t)
-
-    async def astream_v2(
-        self,
-        input: InputT | Command | None,
-        config: RunnableConfig | None = None,
-        *,
-        interrupt_before: All | Sequence[str] | None = None,
-        interrupt_after: All | Sequence[str] | None = None,
-        transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
-    ) -> Any:
-        """Async counterpart to `stream_v2`.
-
-        Returns an `AsyncGraphRunStream` whose projections can be awaited
-        concurrently; each subscribed cursor drives the pump when its
-        buffer is empty.
-
-        Note:
-            Same nesting limitation as `stream_v2`: nesting v1
-            `astream(stream_mode="messages")` inside a node of an
-            `astream_v2` run drops `on_llm_new_token` chunks because
-            the outer v2 handler reroutes `BaseChatModel.invoke`
-            through the v2 event protocol. The inner stream still
-            yields a finalized message at end-of-call. Use
-            `astream_v2` for the inner graph as well, or call
-            `chat_model.astream(...)` explicitly inside the node, to
-            get token-level streaming.
-
-        Args:
-            input: Graph input.
-            config: Optional runnable config forwarded to the graph.
-            interrupt_before: Nodes to interrupt before, if any.
-            interrupt_after: Nodes to interrupt after, if any.
-            transformers: Extra transformer classes or configured factories
-                appended after compile-time `stream_transformers`. Factories
-                are called as `factory(scope)` so they can propagate to
-                subgraph scopes.
-        """
-        parent_ns = _resolve_parent_ns(self.config, config)
-        compiled_factories = _normalize_stream_transformer_factories(
-            self.stream_transformers
-        )
-        extra_factories = _normalize_stream_transformer_factories(transformers)
-        mux = StreamMux(
-            factories=[
-                ValuesTransformer,
-                MessagesTransformer,
-                LifecycleTransformer,
-                SubgraphTransformer,
-                *compiled_factories,
-                *extra_factories,
-            ],
-            scope=parent_ns,
-            is_async=True,
-        )
-        values_t = cast(ValuesTransformer, mux.transformer_by_key("values"))
-        graph_aiter = self.astream(
-            input,
-            patch_configurable(config, {CONFIG_KEY_STREAM_MESSAGES_V2: True}),
-            stream_mode=_collect_stream_modes(mux),
-            subgraphs=True,
-            version="v2",
-            interrupt_before=interrupt_before,
-            interrupt_after=interrupt_after,
-        ).__aiter__()
-        return AsyncGraphRunStream(graph_aiter, mux, values_t)
-
    @overload
    def invoke(
        self,
@@ -3998,35 +3676,18 @@ def _coerce_checkpoint_values(payload: Any, mapper: Callable[[Any], Any]) -> Non
        payload["values"] = mapper(payload["values"])


-def _resolve_parent_ns(
-    graph_config: RunnableConfig | None, call_config: RunnableConfig | None
-) -> tuple[str, ...]:
-    """Return the checkpoint namespace the caller is running under.
-
-    `stream_v2` uses this to scope its native projections
-    (`ValuesTransformer`, `MessagesTransformer`) to events emitted at
-    the run's own level. A root call resolves to `()`; a call made
-    from inside a node carries the outer graph's task namespace so the
-    projection still matches its own root-level events.
-    """
-    merged = ensure_config(graph_config, call_config)
-    ns = merged.get(CONF, {}).get(CONFIG_KEY_CHECKPOINT_NS)
-    if not ns:
-        return ()
-    return tuple(ns.split(NS_SEP))
-
-
 def _build_server_info(
    config: RunnableConfig, parent_runtime: Runtime[Any]
 ) -> ServerInfo | None:
-    """Build ServerInfo from config configurable.
+    """Build ServerInfo from config metadata and configurable.

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

    # Read authenticated user from configurable (set by LangGraph Server).
    # We prefer isinstance(BaseUser) but fall back to hasattr("identity")
@@ -1,35 +1,49 @@
-"""Streaming infrastructure for LangGraph.
+"""Stream protocol types and infrastructure for LangGraph."""

-Compile a graph with `transformers=[...]` and call `graph.stream_v2()` /
-`graph.astream_v2()` to drive a transformer pipeline that projects the
-graph's raw events into ergonomic per-channel streams.
-"""
-
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
+from langgraph.stream._convert import STREAM_V2_MODES, convert_to_protocol_event
+from langgraph.stream._event_log import EventLog
+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,
    SubgraphRunStream,
+    create_async_graph_run_stream,
+    create_graph_run_stream,
 )
-from langgraph.stream.stream_channel import StreamChannel
+from langgraph.stream.stream_channel import StreamChannel, is_stream_channel
+from langgraph.stream.streaming_handler import StreamingHandler
 from langgraph.stream.transformers import (
-    LifecyclePayload,
-    LifecycleTransformer,
-    SubgraphStatus,
-    SubgraphTransformer,
+    MessagesTransformer,
+    ValuesTransformer,
 )

 __all__ = [
+    "STREAM_V2_MODES",
+    "AsyncStreamMux",
+    "AsyncChatModelStream",
    "AsyncGraphRunStream",
    "AsyncSubgraphRunStream",
+    "ChatModelStream",
+    "EventLog",
    "GraphRunStream",
-    "LifecyclePayload",
-    "LifecycleTransformer",
+    "InterruptPayload",
+    "MessagesTransformer",
    "ProtocolEvent",
    "StreamChannel",
-    "StreamTransformer",
+    "StreamMux",
    "SubgraphRunStream",
-    "SubgraphStatus",
-    "SubgraphTransformer",
+    "StreamTransformer",
+    "StreamingHandler",
+    "ValuesTransformer",
+    "convert_to_protocol_event",
+    "create_async_graph_run_stream",
+    "create_graph_run_stream",
+    "is_stream_channel",
 ]
@@ -1,32 +1,79 @@
+"""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

 import time
-from typing import Any, cast
+from typing import Any

 from langgraph.stream._types import ProtocolEvent, _ProtocolEventParams
-from langgraph.types import StreamPart
+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(part: StreamPart) -> ProtocolEvent:
-    """Convert a v2 StreamPart to a ProtocolEvent.
+def convert_to_protocol_event(
+    ns: tuple[str, ...],
+    mode: str,
+    payload: Any,
+    *,
+    node: str | None = None,
+) -> ProtocolEvent | None:
+    """Convert a ``StreamChunk`` to a ``ProtocolEvent``.

-    Args:
-        part: A stream part with keys `type`, `ns`, `data`, and
-            optionally `interrupts` (present on values events).
+    Returns ``None`` for unsupported or unknown modes.

-    Returns:
-        The equivalent ProtocolEvent.
+    The ``seq`` field is left as ``0`` here; the :class:`StreamMux` is
+    the sole seq assigner and overwrites it inside ``push()``.
+
+    Parameters
+    ----------
+    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.
    """
-    part_dict = cast(dict[str, Any], part)
+    if mode not in _SUPPORTED_MODES:
+        return None
+
    params: _ProtocolEventParams = {
-        "namespace": list(part_dict["ns"]),
-        "timestamp": int(time.time() * 1000),
-        "data": part_dict["data"],
-    }
-    if "interrupts" in part_dict:
-        params["interrupts"] = part_dict["interrupts"]
-    return {
-        "type": "event",
-        "method": part_dict["type"],
-        "params": params,
+        "namespace": list(ns),
+        "timestamp": _now_ms(),
+        "data": payload,
    }
+    if node is not None:
+        params["node"] = node
+
+    return ProtocolEvent(
+        type="event",
+        method=mode,
+        params=params,
+    )
+
+
+def _now_ms() -> int:
+    """Current time in milliseconds since epoch."""
+    return int(time.time() * 1000)
+
+
+__all__ = ["STREAM_V2_MODES", "convert_to_protocol_event"]
@@ -0,0 +1,136 @@
+"""Replayable append-only event buffer for StreamingHandler.
+
+``EventLog`` stores protocol events in an ordered list and supports
+multiple independent async iterators, each with their own cursor
+offset.  Subscribers that join mid-stream replay from a given offset
+without losing earlier events.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import threading
+from typing import Generic, TypeVar
+
+T = TypeVar("T")
+
+
+def _resolve_future(fut: asyncio.Future[None]) -> None:
+    """Set a future's result if it hasn't already completed or been cancelled.
+
+    Runs on the event loop thread (scheduled via ``call_soon_threadsafe``)
+    so that the ``done()`` check and ``set_result`` are atomic with
+    respect to cancellation.
+    """
+    if not fut.done():
+        fut.set_result(None)
+
+
+class EventLog(Generic[T]):
+    """Append-only event buffer with cursor-based async iteration.
+
+    Multiple consumers can subscribe independently and each will see
+    every event from their starting offset onward.
+    """
+
+    __slots__ = ("_items", "_closed", "_error", "_waiters", "_lock")
+
+    def __init__(self) -> None:
+        self._items: list[T] = []
+        self._closed = False
+        self._error: BaseException | None = None
+        self._waiters: list[asyncio.Future[None]] = []
+        self._lock = threading.Lock()
+
+    # -- Producer API -------------------------------------------------------
+
+    def append(self, item: T) -> None:
+        """Append an event and wake all waiting consumers."""
+        with self._lock:
+            if self._closed:
+                raise RuntimeError("EventLog is closed")
+            self._items.append(item)
+            self._wake_all()
+
+    def close(self) -> None:
+        """Mark the log as complete.  Iterators will end gracefully."""
+        with self._lock:
+            self._closed = True
+            self._wake_all()
+
+    def fail(self, error: BaseException) -> None:
+        """Mark the log as failed.  Iterators will raise *error*."""
+        with self._lock:
+            self._error = error
+            self._closed = True
+            self._wake_all()
+
+    # -- Consumer API -------------------------------------------------------
+
+    def __aiter__(self) -> _Cursor[T]:
+        """Return a fresh cursor from the beginning of the log."""
+        return _Cursor(self)
+
+    # -- Inspection ---------------------------------------------------------
+
+    def __len__(self) -> int:
+        return len(self._items)
+
+    def __getitem__(self, index: int) -> T:
+        return self._items[index]
+
+    @property
+    def closed(self) -> bool:
+        return self._closed
+
+    # -- Internal -----------------------------------------------------------
+
+    def _wake_all(self) -> None:
+        for fut in self._waiters:
+            try:
+                fut.get_loop().call_soon_threadsafe(_resolve_future, fut)
+            except RuntimeError:
+                # Loop already closed — ignore.
+                pass
+        self._waiters.clear()
+
+
+class _Cursor(Generic[T]):
+    """An independent async iterator over an :class:`EventLog`."""
+
+    __slots__ = ("_log", "_offset")
+
+    def __init__(self, log: EventLog[T]) -> None:
+        self._log = log
+        self._offset = 0
+
+    def __aiter__(self) -> _Cursor[T]:
+        return self
+
+    async def __anext__(self) -> T:
+        while True:
+            with self._log._lock:
+                if self._offset < len(self._log._items):
+                    item = self._log._items[self._offset]
+                    self._offset += 1
+                    return item
+                if self._log._error is not None:
+                    raise self._log._error
+                if self._log._closed:
+                    raise StopAsyncIteration
+                # Nothing available yet — register a waiter
+                fut: asyncio.Future[None] = asyncio.get_running_loop().create_future()
+                self._log._waiters.append(fut)
+            # Wait outside the lock
+            try:
+                await fut
+            except asyncio.CancelledError:
+                with self._log._lock:
+                    try:
+                        self._log._waiters.remove(fut)
+                    except ValueError:
+                        pass  # Already removed by _wake_all
+                raise
+
+
+__all__ = ["EventLog"]
@@ -1,491 +1,425 @@
+"""Central event dispatcher with transformer pipeline for StreamingHandler.
+
+``StreamMux`` is the sync-safe core: it holds the main
+:class:`EventLog`, 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 the base with async subscription endpoints
+(output futures, namespace waiters, filtered event iteration).
+"""
+
 from __future__ import annotations

 import asyncio
 import time
-from collections.abc import Awaitable, Callable
+from collections.abc import AsyncIterator
 from typing import Any

-from langgraph.stream._types import (
-    ProtocolEvent,
-    StreamTransformer,
-    transformer_requires_async,
-)
-from langgraph.stream.stream_channel import StreamChannel
-
-TransformerFactory = Callable[["tuple[str, ...]"], StreamTransformer]
-"""Factory that builds a scoped transformer for a mux.
-
-Called once per `StreamMux` with the mux's scope (typically `()` for
-the root). Standard transformer classes accept a single positional
-scope argument, so the class itself is a valid factory. User
-transformers can close over their config:
-`lambda scope: MyTransformer(scope, foo=...)`.
-"""
+from langgraph.stream._event_log import EventLog
+from langgraph.stream._types import InterruptPayload, ProtocolEvent, StreamTransformer
+from langgraph.stream.stream_channel import StreamChannel, is_stream_channel


 class StreamMux:
-    """Central event dispatcher for the streaming infrastructure.
+    """Sync-safe event dispatcher for the StreamingHandler infrastructure.

-    Owns the main event log and routes events through a transformer
-    pipeline. StreamChannels with a name discovered in transformer
-    projections are auto-wired so that every `push()` also injects a
-    `ProtocolEvent` into the main log. StreamChannels without a name
-    are local-only.
+    The mux owns the main event log, applies the transformer pipeline to
+    every incoming event, and tracks namespace discovery and latest values.

-    Pass `is_async=True` when the mux will be consumed via async
-    iteration (`handler.astream()`). All StreamChannel instances
-    discovered during registration are automatically bound to the
-    matching mode.
-
-    Attributes:
-        extensions: Merged projection dict across all registered
-            transformers. Treat as read-only — mutations won't be
-            reflected back in individual transformers' state.
-        native_keys: Projection keys contributed by transformers with
-            `_native = True`.
+    For async subscription endpoints (output futures, namespace waiters,
+    filtered event iteration), use :class:`AsyncStreamMux`.
    """

-    def __init__(
-        self,
-        transformers: list[StreamTransformer] | None = None,
-        *,
-        is_async: bool = False,
-        factories: list[TransformerFactory] | None = None,
-        scope: tuple[str, ...] = (),
-        _assign_seq: bool = True,
-    ) -> None:
-        """Initialize the mux and register transformers in order.
-
-        Callers pass either `transformers` (pre-built instances) or
-        `factories` (callables producing fresh instances per mux). Each
-        transformer's `init()` is called, projections are merged into
-        `extensions`, `_native` keys are recorded in `native_keys`, and
-        any StreamChannel instances are bound and (if named) wired.
-
-        Args:
-            transformers: Already-built transformer instances. Registered
-                only on this mux — they are NOT cloned into child
-                mini-muxes built by `_make_child`. Use `factories` for
-                transformers that should propagate to nested scopes.
-            is_async: True for async dispatch (`apush` / `aclose` /
-                `afail`), False for the sync path.
-            factories: One-argument callables `(scope) -> StreamTransformer`.
-                Called once with this mux's `scope` here, and cloned
-                again per child scope by `_make_child` so each
-                sub-mux gets fresh instances.
-            scope: The namespace the mux operates within. The root mux
-                is `()`.
-            _assign_seq: Internal flag for child muxes. Root muxes assign
-                monotonic `seq` numbers when appending to their main event
-                log; child muxes share forwarded event objects and must not
-                mutate their envelopes.
-
-        Raises:
-            RuntimeError: If any transformer requires an async run but
-                the mux is in sync mode.
-            TypeError: If a transformer's `init()` doesn't return a dict.
-            ValueError: If transformers' projection keys collide.
-        """
-        self.is_async = is_async
-        self.scope: tuple[str, ...] = scope
-        self._assign_seq = _assign_seq
-        self._events: StreamChannel[ProtocolEvent] = StreamChannel()
-        self._events._bind(is_async=is_async)
-        self._transformers: list[StreamTransformer] = []
+    def __init__(self, transformers: list[StreamTransformer] | None = None) -> None:
+        self._event_log: EventLog[ProtocolEvent] = EventLog()
+        self._transformers: list[StreamTransformer] = list(transformers or [])
        self._channels: list[StreamChannel[Any]] = []
-        self._seq = 0
+        self._current_namespace: list[str] = []
+        self._next_emit_seq: int = 0

-        self.extensions: dict[str, Any] = {}
-        self.native_keys: set[str] = set()
-        self._projection_owners: dict[str, str] = {}
-        self._transformer_by_key: dict[str, StreamTransformer] = {}
+        # Namespace discovery: maps top-level ns segment → True
+        self._discovered_ns: dict[str, bool] = {}

-        # Stored only when constructed from factories — used by
-        # `_make_child` to clone the transformer pipeline at a deeper
-        # scope. Pre-built transformers can't be cloned, so a mux
-        # built with `transformers=` rejects child construction.
-        self._factories: list[TransformerFactory] | None = (
-            list(factories) if factories is not None else None
-        )
-        self._pump_fn: Callable[[], bool] | None = None
-        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
+        # Latest values per namespace (list-of-strings key)
+        self._latest_values: dict[str, Any] = {}

-        # Factories run first (they propagate to child mini-muxes
-        # via `_make_child`), then any pre-built `transformers=`
-        # instances are registered as root-only — they aren't cloned
-        # for child scopes.
-        if factories is not None:
-            for factory in factories:
-                self._register(factory(scope))
-        for transformer in transformers or ():
-            self._register(transformer)
+        # Interrupt tracking
+        self._interrupts: list[InterruptPayload] = []
+        self._interrupted = False

-    def transformer_by_key(self, key: str) -> StreamTransformer | None:
-        """Return the transformer that contributed `key` to the projection."""
-        return self._transformer_by_key.get(key)
+        # Closed state
+        self._closed = False
+        self._error: BaseException | None = None

-    # ------------------------------------------------------------------
-    # Pump wiring + mini-mux nesting
-    # ------------------------------------------------------------------
-
-    def bind_pump(self, fn: Callable[[], bool]) -> None:
-        """Wire the sync pull callback onto every projection in this mux.
-
-        Records the pump on the mux so child mini-muxes built by
-        `_make_child` can inherit it. Propagates to:
-        - the main event log (`self._events`)
-        - every projection StreamChannel in `extensions`
-        - any registered transformer that exposes `_bind_pump` (e.g.
-          `MessagesTransformer` so `ChatModelStream` instances drive the
-          shared pump from their cursors)
-        """
-        self._pump_fn = fn
-        self._events._request_more = fn
-        for ch in self._channels:
-            ch._request_more = fn
-        for transformer in self._transformers:
-            bind = getattr(transformer, "_bind_pump", None)
-            if bind is not None:
-                bind(fn)
-
-    def bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
-        """Async counterpart to `bind_pump`."""
-        self._apump_fn = fn
-        self._events._arequest_more = fn
-        for ch in self._channels:
-            ch._arequest_more = fn
-        for transformer in self._transformers:
-            abind = getattr(transformer, "_bind_apump", None)
-            if abind is not None:
-                abind(fn)
-
-    def _make_child(self, scope: tuple[str, ...]) -> StreamMux:
-        """Build a mini-mux with the same factories scoped to `scope`.
-
-        Used by `SubgraphTransformer` to attach a fresh transformer
-        pipeline to each discovered subgraph handle. The child mux
-        inherits the current pump bindings (so cursors on its
-        projection logs drive the root pump), carries the same factory
-        list forward to any grandchild subgraphs, and does not assign
-        `seq` numbers so forwarded events can be shared without
-        mutating their envelope.
-
-        Raises:
-            RuntimeError: If the mux was not constructed with
-                `factories=`. Mini-muxes require factories so each scope
-                gets its own fresh transformer instances.
-        """
-        if self._factories is None:
-            raise RuntimeError(
-                "StreamMux._make_child requires the mux to be constructed "
-                "with `factories=`; pre-built transformers can't be "
-                "cloned to a new scope."
-            )
-        child = StreamMux(
-            factories=self._factories,
-            is_async=self.is_async,
-            scope=scope,
-            _assign_seq=False,
-        )
-        if self._pump_fn is not None:
-            child.bind_pump(self._pump_fn)
-        if self._apump_fn is not None:
-            child.bind_apump(self._apump_fn)
-        return child
-
-    def _register(self, transformer: StreamTransformer) -> None:
-        """Register a single transformer.
-
-        Calls `transformer.init()`, stores the transformer for event
-        processing, binds any StreamChannel instances in the projection,
-        and merges the projection into `extensions`.
-        """
-        if transformer_requires_async(transformer) and not self.is_async:
-            raise RuntimeError(
-                f"{type(transformer).__name__} requires an async run — "
-                "it overrides aprocess/afinalize/afail or sets "
-                "requires_async=True. Use astream(), not stream()."
-            )
-        projection = transformer.init()
-        if not isinstance(projection, dict):
-            raise TypeError(
-                f"StreamTransformer.init() must return a dict, "
-                f"got {type(projection).__name__}"
-            )
-        conflicts = set(projection) & set(self.extensions)
-        if conflicts:
-            attributions = ", ".join(
-                f"{key!r} (owned by {self._projection_owners[key]})"
-                for key in sorted(conflicts)
-            )
-            raise ValueError(
-                f"Transformer {type(transformer).__name__} returned "
-                f"projection keys that conflict with already-registered "
-                f"keys: {attributions}"
-            )
-        is_native = bool(getattr(transformer, "_native", False))
-        self._transformers.append(transformer)
-        self._bind_and_wire(projection, native=is_native)
-        self.extensions.update(projection)
-        owner_name = type(transformer).__name__
-        for key in projection:
-            self._projection_owners[key] = owner_name
-            self._transformer_by_key[key] = transformer
-        if is_native:
-            self.native_keys.update(projection.keys())
-        transformer._on_register(self)
+    # -- Producer API -------------------------------------------------------

    def push(self, event: ProtocolEvent) -> None:
-        """Route an event through all transformers, then append to the main log.
+        """Push an event through the transformer pipeline and into the log.

-        Each transformer's `process()` is called in registration order.
-        If any transformer returns False, the event is suppressed from
-        the main log, but transformers that already saw it keep their
-        side effects.
-
-        On the root mux, `seq` is assigned right before an event enters
-        the main log, not before the transformer pipeline runs. This
-        ensures that events auto-forwarded from StreamChannels during
-        `process()` get earlier seq numbers than the original event,
-        preserving monotonic ordering in the root log. Child muxes do
-        not assign `seq`, so subgraph forwarding can share event objects
-        without mutating their envelopes.
-
-        Args:
-            event: The protocol event to dispatch.
+        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
+                self._on_ns_discovered(top_segment)
+
+        # 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:
-            if not transformer.process(event):
+            result = transformer.process(event)
+            if result is False:
                keep = False
+        self._current_namespace = []
+
+        # Append to main log if not suppressed
        if keep:
-            if self._assign_seq:
-                self._seq += 1
-                event["seq"] = self._seq
-            self._events.push(event)
+            self._event_log.append(event)

-    def close(self) -> None:
-        """Finalize all transformers, close all projections and the main log.
+    def close(self, output: Any = None) -> None:
+        """Close the mux, finalizing transformers and the event log."""
+        if self._closed:
+            return
+        self._closed = True

-        StreamChannels discovered in transformer projections are
-        auto-closed after `finalize()` runs — transformers don't need
-        to close them manually. If any transformer's `finalize()` raises,
-        the remaining transformers, projections, and the main log are
-        still closed; the first error is re-raised after cleanup
-        completes.
-
-        Raises:
-            BaseException: The first error raised by a transformer's
-                `finalize()`, re-raised after cleanup finishes.
-        """
-        first_error: BaseException | None = None
+        # Finalize transformers (optional method)
        for transformer in self._transformers:
-            try:
+            if hasattr(transformer, "finalize"):
                transformer.finalize()
-            except BaseException as e:
-                if first_error is None:
-                    first_error = e
-        for ch in self._channels:
-            if not ch._closed:
-                ch.close()
-        self._events.close()
-        if first_error is not None:
-            raise first_error

-    def fail(self, err: BaseException) -> None:
-        """Fail all transformers, projections, and the main log.
+        # Close wired channels
+        for channel in self._channels:
+            channel._close()

-        StreamChannels discovered in transformer projections are
-        auto-failed — transformers don't need to fail them manually.
-        If any transformer's `fail()` raises, the remaining
-        transformers, projections, and the main log are still failed.
+        # Close the event log
+        self._event_log.close()

-        Args:
-            err: The exception that ended the run.
-        """
+    def fail(self, error: BaseException) -> None:
+        """Fail the mux, propagating the error to transformers and channels."""
+        if self._closed:
+            return
+        self._closed = True
+        self._error = error
+
+        # Fail transformers (optional method)
        for transformer in self._transformers:
-            try:
-                transformer.fail(err)
-            except BaseException:
-                pass
-        for ch in self._channels:
-            if not ch._closed:
-                ch.fail(err)
-        self._events.fail(err)
+            if hasattr(transformer, "fail"):
+                transformer.fail(error)

-    # ------------------------------------------------------------------
-    # Async dispatch
-    # ------------------------------------------------------------------
+        # Fail wired channels
+        for channel in self._channels:
+            channel._fail(error)

-    async def apush(self, event: ProtocolEvent) -> None:
-        """Dispatch an event on the async lane.
+        # Fail the event log
+        self._event_log.fail(error)

-        Awaits each transformer's `aprocess` in registration order
-        before appending to the main log. A slow `aprocess` serializes
-        the pipeline by design — that's the guarantee that lets a later
-        transformer (or a synchronous consumer) see the result of the
-        async work. For decoupled work, use `schedule()` from inside
-        `process` / `aprocess` instead.
+    # -- Inspection ---------------------------------------------------------

-        The main log append is a non-blocking `push` — matching v1's
-        `put_nowait` shape. The root mux assigns `seq`; child muxes do
-        not, so forwarded subgraph events can be shared without copying.
-        Memory is bounded by caller pace via the caller-driven pump; see
-        `StreamChannel` for the full tradeoff story.
+    @property
+    def interrupted(self) -> bool:
+        return self._interrupted

-        Args:
-            event: The protocol event to dispatch.
+    @property
+    def interrupts(self) -> list[InterruptPayload]:
+        return list(self._interrupts)
+
+    @property
+    def event_log(self) -> EventLog[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 _on_ns_discovered(self, segment: str) -> None:
+        """Hook called when a new top-level namespace segment is discovered.
+
+        The base implementation is a no-op.  :class:`AsyncStreamMux`
+        overrides this to wake namespace waiters.
        """
-        keep = True
-        for transformer in self._transformers:
-            if not await transformer.aprocess(event):
-                keep = False
-        if keep:
-            if self._assign_seq:
-                self._seq += 1
-                event["seq"] = self._seq
-            self._events.push(event)

-    async def aclose(self) -> None:
-        """Finalize on the async lane.
+    def register_transformer(self, transformer: StreamTransformer) -> None:
+        """Register a new transformer and replay all buffered events through it.

-        Awaits every task started via `StreamTransformer.schedule()`
-        across all transformers, then calls `afinalize()` on each,
-        then auto-closes channels and the main event log.
+        This is the safe way to add a late-arriving transformer after the mux
+        has already started processing events.  The sequence is:

-        If any scheduled task raised under `on_error="raise"`, or any
-        transformer's `afinalize` raises, the exception propagates.
-        The caller (the pump) handles it by routing into `afail`.
+        1. Snapshot the current log length (no await → no gap possible in
+           asyncio's cooperative threading model).
+        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.

-        Raises:
-            BaseException: The first scheduled-task or `afinalize`
-                error, re-raised after cleanup.
+        ``process()`` is only called for events whose namespace starts with
+        any prefix — callers that need namespace filtering should do so inside
+        their ``process()`` implementation, or wrap this call with their own
+        filtering logic.
        """
-        pending = self._collect_scheduled_tasks()
-        if pending:
-            results = await asyncio.gather(*pending, return_exceptions=True)
-            first_err = next(
-                (
-                    r
-                    for r in results
-                    if isinstance(r, BaseException)
-                    and not isinstance(r, asyncio.CancelledError)
-                ),
-                None,
-            )
-            if first_err is not None:
-                raise first_err
+        snapshot = len(self._event_log)
+        self._transformers.append(transformer)
+        for i in range(snapshot):
+            transformer.process(self._event_log[i])
+        if self._closed:
+            if hasattr(transformer, "finalize"):
+                transformer.finalize()

-        first_error: BaseException | None = None
-        for transformer in self._transformers:
-            try:
-                await transformer.afinalize()
-            except BaseException as e:
-                if first_error is None:
-                    first_error = e
-        for ch in self._channels:
-            if not ch._closed:
-                ch.close()
-        self._events.close()
-        if first_error is not None:
-            raise first_error
+    def wire_channels(self, projection: Any) -> None:
+        """Scan *projection* for :class:`StreamChannel` instances and wire them.

-    async def afail(self, err: BaseException) -> None:
-        """Fail on the async lane.
+        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.

-        Cancels every scheduled task across all transformers, awaits
-        them to completion, then runs each transformer's `afail` hook
-        and auto-fails channels and the main event log.
-
-        Args:
-            err: The exception that ended the run.
+        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()``.
        """
-        pending = self._collect_scheduled_tasks()
-        for task in pending:
-            task.cancel()
-        if pending:
-            await asyncio.gather(*pending, return_exceptions=True)
+        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
+                self._channels.append(channel)

-        for transformer in self._transformers:
-            try:
-                await transformer.afail(err)
-            except BaseException:
-                pass
-        for ch in self._channels:
-            if not ch._closed:
-                ch.fail(err)
-        if not self._events._closed:
-            self._events.fail(err)
+                def _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),
+                                    "timestamp": int(time.time() * 1000),
+                                    "data": item,
+                                },
+                            )
+                        )
+                        self._next_emit_seq += 1

-    def _collect_scheduled_tasks(self) -> list[asyncio.Task[Any]]:
-        """Return a snapshot of in-flight tasks scheduled via transformers."""
-        return [
-            task
-            for transformer in self._transformers
-            for task in getattr(transformer, "_stream_scheduled_tasks", ())
-            if not task.done()
-        ]
+                    return _forward

-    # ------------------------------------------------------------------
-    # Binding and StreamChannel auto-wiring
-    # ------------------------------------------------------------------
+                channel._wire(_make_forwarder(channel))

-    def _bind_and_wire(
-        self, projection: dict[str, Any], *, native: bool = False
-    ) -> None:
-        """Bind and optionally wire StreamChannel instances in a projection.

-        All StreamChannels are bound and tracked. Channels with a name
-        are additionally wired for protocol auto-forwarding.
+class AsyncStreamMux(StreamMux):
+    """Async extension of :class:`StreamMux`.

-        Args:
-            projection: The projection dict returned by a transformer's
-                `init()`.
-            native: True when the owning transformer is `_native`.
-                Named channels owned by a native transformer use the
-                channel name directly as the protocol method;
-                user-defined channels are prefixed with `custom:`.
+    Adds output futures, namespace waiters, and async subscription
+    endpoints (``subscribe_events``, ``subscribe_subgraphs``,
+    ``get_output_future``).
+    """
+
+    def __init__(self, transformers: list[StreamTransformer] | None = None) -> None:
+        super().__init__(transformers)
+        # Waiters for new namespace discovery
+        self._ns_waiters: list[asyncio.Future[None]] = []
+        # Output promise tracking
+        self._output_futures: dict[str, asyncio.Future[Any]] = {}
+
+    # -- Producer API overrides ---------------------------------------------
+
+    def close(self, output: Any = None) -> None:
+        """Close the mux, resolving all output futures."""
+        if self._closed:
+            return
+
+        # Let the base class finalize transformers, channels, and event log
+        super().close(output)
+
+        # 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:
+        """Fail the mux, rejecting all output futures."""
+        if self._closed:
+            return
+
+        # Let the base class fail transformers, channels, and event log
+        super().fail(error)
+
+        # 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()
+
+    # -- Consumer API -------------------------------------------------------
+
+    def subscribe_events(
+        self, path: list[str] | None = None
+    ) -> AsyncIterator[ProtocolEvent]:
+        """Return an async iterator over events matching *path*.
+
+        If *path* is ``None`` or empty, all events are yielded.
+        Otherwise, only events whose namespace starts with *path*
+        are yielded.
        """
-        for value in projection.values():
-            if isinstance(value, StreamChannel):
-                value._bind(is_async=self.is_async)
-                self._channels.append(value)
-                if value.name is not None:
-                    method = value.name if native else f"custom:{value.name}"
+        cursor = aiter(self._event_log)
+        if not path:
+            return cursor
+        return _FilteredEventIterator(cursor, path)

-                    def _make_forward(method_name: str) -> Callable[[Any], None]:
-                        def _forward(item: Any) -> None:
-                            self._forward(method_name, item)
+    async def subscribe_subgraphs(
+        self, path: list[str] | None = None, offset: int = 0
+    ) -> AsyncIterator[str]:
+        """Yield top-level namespace segments as they are discovered.

-                        return _forward
-
-                    value._wire(_make_forward(method))
-
-    def _forward(self, method: str, item: Any) -> None:
-        """Inject a ProtocolEvent for a StreamChannel push.
-
-        Forwarded events bypass the transformer pipeline to avoid
-        infinite recursion (a transformer that pushes to a channel
-        during `process()` would re-trigger itself). These events are
-        visible in this mux's main event log but are not passed through
-        transformers' `process()` methods. Only the root mux assigns
-        `seq` to forwarded channel events.
-
-        Args:
-            method: The full protocol method (already with or without
-                the `custom:` prefix; resolved by `_bind_and_wire`).
-            item: The payload pushed onto the channel.
+        Each yielded value is the first namespace segment of a newly
+        discovered subgraph (e.g. ``"agent:0"``).
        """
-        event: ProtocolEvent = {
-            "type": "event",
-            "method": method,
-            "params": {
-                "namespace": [],
-                "timestamp": int(time.time() * 1000),
-                "data": item,
-            },
-        }
-        if self._assign_seq:
-            self._seq += 1
-            event["seq"] = self._seq
-        self._events.push(event)
+        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 _on_ns_discovered(self, segment: str) -> None:
+        """Wake namespace waiters when a new namespace is discovered."""
+        self._wake_ns_waiters()
+
+    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()
+
+
+class _FilteredEventIterator:
+    """Async iterator that filters events by namespace prefix."""
+
+    __slots__ = ("_cursor", "_path")
+
+    def __init__(self, cursor: AsyncIterator[ProtocolEvent], path: list[str]) -> None:
+        self._cursor = cursor
+        self._path = path
+
+    def __aiter__(self) -> _FilteredEventIterator:
+        return self
+
+    async def __anext__(self) -> ProtocolEvent:
+        while True:
+            event = await self._cursor.__anext__()
+            ns = event["params"].get("namespace", [])
+            if _ns_starts_with(ns, self._path):
+                return event
+
+
+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"]
@@ -1,313 +1,167 @@
+"""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

-import asyncio
-import logging
-from abc import ABC, abstractmethod
-from collections.abc import Coroutine
-from typing import Any, ClassVar, Literal
+from typing import Any, Protocol, runtime_checkable

+# ---------------------------------------------------------------------------
+# 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

-_logger = logging.getLogger(__name__)
+# ---------------------------------------------------------------------------
+# In-process types (not in the CDDL spec)
+# ---------------------------------------------------------------------------


 class _ProtocolEventParams(TypedDict):
-    """Parameters for a protocol event.
+    """Payload envelope for a :class:`ProtocolEvent`."""

-    `timestamp` is wall-clock milliseconds since the epoch and can go
-    backwards across NTP adjustments — use `ProtocolEvent.seq` for
-    ordering.
-    """
-
-    namespace: list[str]
+    namespace: Namespace
    timestamp: int
+    node: NotRequired[str]
    data: Any
-    interrupts: NotRequired[tuple[Any, ...]]


 class ProtocolEvent(TypedDict):
-    """A protocol event emitted by the streaming infrastructure.
+    """A single protocol event emitted by the StreamingHandler infrastructure.

-    Wraps a raw stream part (values, messages, custom, etc.) in a uniform
-    envelope with a monotonic sequence number assigned by the root StreamMux.
-    Consumers that need a total order across root events should use `seq`, not
-    `params.timestamp` (which is wall-clock and not monotonic).
+    ``method`` corresponds to a
+    :pydata:`~langgraph.types.StreamMode` value (``"messages"``,
+    ``"updates"``, etc.).
    """

-    type: Literal["event"]
-    eventId: NotRequired[str]
-    seq: NotRequired[int]
-    method: str  # StreamMode value: "values", "messages", "custom", etc.
+    type: str  # always "event"
+    seq: NotRequired[int]  # assigned by StreamMux.push(); absent before push()
+    method: str  # StreamMode value
    params: _ProtocolEventParams


-class StreamTransformer(ABC):
+@runtime_checkable
+class StreamTransformer(Protocol):
    """Extension point for custom stream projections.

-    Transformers observe protocol events flowing through the StreamMux and
-    build typed derived projections (StreamChannels, promises, etc.).
+    Implementations are registered with ``StreamingHandler`` and receive every
+    :class:`ProtocolEvent` before it is appended to the event log.

-    Set `_native = True` on a transformer to have its projection keys
-    exposed as direct attributes on the run stream (in addition to
-    appearing in `run.extensions`).
+    Any :class:`~langgraph.stream.stream_channel.StreamChannel` instances
+    returned by ``init()`` are automatically wired to the protocol event
+    stream by the mux.

-    Subclasses must implement `init` and override at least one of
-    `process` / `aprocess`. The `finalize` / `afinalize` and `fail` /
-    `afail` hooks are optional — the default implementations are no-ops.
-    StreamChannel instances in the projection dict are auto-closed /
-    auto-failed by the mux, so most transformers don't need `finalize`
-    or `fail` at all.
-
-    Transformers that need async work pick the async lane by:
-
-    1. Overriding `aprocess` (and optionally `afinalize` / `afail`), or
-    2. Calling `self.schedule(coro)` from inside a sync `process`, or
-    3. Setting `requires_async = True` explicitly.
-
-    The mux detects these cases at registration and raises if they're
-    used under sync `stream()` — they only work under `astream()`.
-
-    Use `aprocess` when the pump must wait for async work before the
-    next transformer sees the event (e.g. PII redaction that mutates
-    `event` in place). Use `schedule()` for decoupled async work whose
-    result lands on an independent projection (e.g. async moderation
-    scoring, cost lookup, external tracing).
-
-    Attributes:
-        scope: Namespace the transformer operates within — `()` for the
-            root mux. Set at construction from the mux's scope (each
-            factory is called as `factory(scope)`).
-        requires_async: Explicit opt-in for transformers that need a
-            running event loop but don't override any async method (for
-            example, transformers that call `schedule()` from a sync
-            `process`). The mux also auto-detects the async lane when
-            `aprocess`, `afinalize`, or `afail` is overridden.
-        supports_sync: Set True only for transformers that override
-            async-lane hooks while still fully supporting the sync lane.
-            Such transformers may be registered under `stream()`.
-        required_stream_modes: Stream modes the graph must emit for
-            this transformer to have anything to process. Computed as
-            the union across all registered transformers to determine
-            which modes a `stream_v2` run requests from the graph.
-            Empty tuple means the transformer consumes only synthetic
-            events (or is purely passive).
    """

-    requires_async: ClassVar[bool] = False
-    supports_sync: ClassVar[bool] = False
-    required_stream_modes: ClassVar[tuple[str, ...]] = ()
+    def init(self) -> Any:
+        """Return the initial projection value.

-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        """Initialize the transformer with its mux's scope.
-
-        Args:
-            scope: The namespace tuple the owning mux is scoped to.
-                `()` for the root. Factories receive this at
-                construction time (`factory(scope)` in `StreamMux`).
-        """
-        self.scope: tuple[str, ...] = scope
-
-    @abstractmethod
-    def init(self) -> dict[str, Any]:
-        """Return the projection dict.
-
-        Keys become entries in `run.extensions`. If the transformer has
-        `_native = True`, keys are also set as direct attributes on the
-        run stream.
-
-        StreamChannel instances in the return value are automatically
-        wired by the StreamMux for protocol event auto-forwarding.
+        Called once before the run.  Any
+        :class:`~langgraph.stream.stream_channel.StreamChannel` instances
+        in the return value are automatically wired by the mux.
        """
        ...

-    def _on_register(self, mux: Any) -> None:
-        """Called by `StreamMux._register` after this transformer is wired in.
-
-        Default is a no-op. Override to capture a reference to the
-        owning mux — needed for transformers that build mini-muxes
-        via `mux._make_child(...)` (e.g. `SubgraphTransformer`).
-        """
-
    def process(self, event: ProtocolEvent) -> bool:
-        """Handle an event on the sync lane.
+        """Process an event.

-        Called for every event before it is appended to the main event
-        log. Subclasses must override either `process` or `aprocess`.
-        The default raises so a missing override fails loudly rather
-        than silently passing every event through.
-
-        Args:
-            event: The protocol event to observe.
-
-        Returns:
-            True to keep the event in the main log, False to suppress it.
+        Return ``True`` to keep the event in the log, ``False`` to suppress
+        it.
        """
-        raise NotImplementedError(
-            f"{type(self).__name__} must override process() or aprocess()"
-        )
-
-    async def aprocess(self, event: ProtocolEvent) -> bool:
-        """Handle an event on the async lane.
-
-        The mux awaits this before dispatching to the next transformer,
-        so a slow `aprocess` serializes the pipeline. Use it only when
-        a later transformer — or a consumer reading the event
-        synchronously — must see the result of the async work (e.g.
-        PII redaction that mutates `event` in place).
-
-        The default delegates to `process`, so purely-sync transformers
-        run unchanged under `astream()`.
-
-        Args:
-            event: The protocol event to observe.
-
-        Returns:
-            True to keep the event in the main log, False to suppress it.
-        """
-        return self.process(event)
+        ...

    def finalize(self) -> None:
-        """Called when the run ends normally (sync lane).
+        """Called once when the run completes successfully.

-        Override to close StreamChannels, resolve promises, or perform
-        other teardown. StreamChannel instances in the projection dict
-        are auto-closed by the mux.
+        Optional — the mux auto-closes any :class:`StreamChannel` instances,
+        so transformers that only use channels can omit this.
        """
-
-    async def afinalize(self) -> None:
-        """Called when the run ends normally (async lane).
-
-        By the time this runs, the mux has already awaited every task
-        started via `schedule()`, so StreamChannels can be closed here
-        without a last-task-wins race.
-
-        The default delegates to `finalize`.
-        """
-        self.finalize()
+        ...

    def fail(self, err: BaseException) -> None:
-        """Called when the run ends with an error (sync lane).
+        """Called once when the run fails.

-        Override to fail StreamChannels, reject promises, or perform
-        other teardown. StreamChannel instances in the projection dict
-        are auto-failed by the mux.
-
-        Args:
-            err: The exception that ended the run.
+        Optional — the mux auto-fails any :class:`StreamChannel` instances,
+        so transformers that only use channels can omit this.
        """
-
-    async def afail(self, err: BaseException) -> None:
-        """Called when the run ends with an error (async lane).
-
-        The mux cancels and awaits every task started via `schedule()`
-        before calling this, so cleanup doesn't race with in-flight work.
-
-        The default delegates to `fail`.
-
-        Args:
-            err: The exception that ended the run.
-        """
-        self.fail(err)
-
-    # ------------------------------------------------------------------
-    # Scheduled async work
-    # ------------------------------------------------------------------
-
-    def schedule(
-        self,
-        coro: Coroutine[Any, Any, Any],
-        *,
-        on_error: Literal["log", "raise"] = "log",
-    ) -> asyncio.Task[Any]:
-        """Schedule a coroutine tied to this transformer's lifecycle.
-
-        The mux holds the task reference, awaits all scheduled tasks
-        during `aclose()` before calling `afinalize()`, and cancels
-        them on `afail()`. Authors don't need to track tasks or
-        implement the last-task-closes-the-log dance.
-
-        Requires a running event loop — call only under `astream()`.
-        Set `requires_async = True` on the class so registration under
-        sync `stream()` fails fast with a clear message.
-
-        Args:
-            coro: The coroutine to run. Its lifecycle is owned by the
-                mux from this point on.
-            on_error: `"log"` (default) catches and logs any exception
-                the coroutine raises, so a single failure doesn't tear
-                down the run. `"raise"` lets the exception propagate
-                when the mux joins pendings, converting the close path
-                into the fail path.
-
-        Returns:
-            The asyncio Task. Authors rarely need to await it directly
-            — consumers read results from whatever projection the
-            coroutine pushes into.
-
-        Raises:
-            RuntimeError: If called without a running event loop (i.e.
-                under sync `stream()` rather than `astream()`).
-        """
-        try:
-            asyncio.get_running_loop()
-        except RuntimeError:
-            raise RuntimeError(
-                f"{type(self).__name__}.schedule() requires a running "
-                "event loop; this transformer must run under astream(), "
-                "not stream(). Set requires_async=True on the class so "
-                "this fails at registration rather than at first event."
-            ) from None
-
-        wrapped = self._wrap_scheduled(coro) if on_error == "log" else coro
-        task = asyncio.create_task(wrapped)
-        tasks = self._scheduled_task_set()
-        tasks.add(task)
-        task.add_done_callback(tasks.discard)
-        return task
-
-    @staticmethod
-    async def _wrap_scheduled(coro: Coroutine[Any, Any, Any]) -> Any:
-        try:
-            return await coro
-        except asyncio.CancelledError:
-            raise
-        except BaseException:
-            _logger.exception("Scheduled StreamTransformer task failed")
-
-    def _scheduled_task_set(self) -> set[asyncio.Task[Any]]:
-        """Return the lazily-allocated task set.
-
-        Avoids requiring subclasses to call `super().__init__()`.
-        """
-        tasks: set[asyncio.Task[Any]] | None = getattr(
-            self, "_stream_scheduled_tasks", None
-        )
-        if tasks is None:
-            tasks = set()
-            self._stream_scheduled_tasks = tasks
-        return tasks
+        ...


-def transformer_requires_async(transformer: StreamTransformer) -> bool:
-    """Return True if the transformer needs a running event loop.
+class InterruptPayload(TypedDict):
+    """An interrupt produced during a StreamingHandler run."""

-    A transformer requires async if it explicitly opts in
-    (`requires_async = True`) or overrides any of the async-lane methods
-    (`aprocess`, `afinalize`, `afail`) without also declaring that it
-    supports the sync lane.
+    interrupt_id: str
+    payload: Any

-    Args:
-        transformer: The transformer to inspect.

-    Returns:
-        True if the transformer cannot run under sync `stream()`.
-    """
-    if transformer.requires_async:
-        return True
-    if transformer.supports_sync:
-        return False
-    cls = type(transformer)
-    for name in ("aprocess", "afinalize", "afail"):
-        if getattr(cls, name) is not getattr(StreamTransformer, name):
-            return True
-    return False
+__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",
+]
@@ -0,0 +1,402 @@
+"""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 Callable, Generator, Iterator
+from typing import Any
+
+from langgraph.stream._types import UsageInfo
+
+
+# ---------------------------------------------------------------------------
+# Sync dual projection — iterable of deltas, str() for accumulated text
+# ---------------------------------------------------------------------------
+
+
+class _SyncDualProjection:
+    """Pump-driven sync iterable of string deltas.
+
+    Iterating yields incremental text fragments as the pump delivers
+    new ``content-block-delta`` events.  Calling ``str()`` drains the
+    pump and returns the full accumulated string.
+
+    This is the sync counterpart of :class:`_DualProjection` (the async
+    variant used by ``AsyncChatModelStream``).
+    """
+
+    __slots__ = ("_stream", "_attr", "_pump_one")
+
+    def __init__(
+        self,
+        stream: ChatModelStream,
+        attr: str,
+        pump_one: Callable[[], bool],
+    ) -> None:
+        self._stream = stream
+        self._attr = attr
+        self._pump_one = pump_one
+
+    def __iter__(self) -> Iterator[str]:
+        prev_len = 0
+        while True:
+            cur = getattr(self._stream, self._attr)
+            if len(cur) > prev_len:
+                yield cur[prev_len:]
+                prev_len = len(cur)
+            if self._stream._done:
+                return
+            if not self._pump_one():
+                # Source exhausted — yield any remaining
+                cur = getattr(self._stream, self._attr)
+                if len(cur) > prev_len:
+                    yield cur[prev_len:]
+                return
+
+    def __str__(self) -> str:
+        while not self._stream._done:
+            if not self._pump_one():
+                break
+        return getattr(self._stream, self._attr)
+
+    def __repr__(self) -> str:
+        return repr(getattr(self._stream, self._attr))
+
+    def __bool__(self) -> bool:
+        return bool(getattr(self._stream, self._attr))
+
+
+# ---------------------------------------------------------------------------
+# 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
+
+        # Optional pump for sync streaming (set via _bind_pump)
+        self._pump_one: Callable[[], bool] | None = None
+
+    # -- Pump binding (called by GraphRunStream) ---------------------------
+
+    def _bind_pump(self, pump_one: Callable[[], bool]) -> None:
+        """Bind a pump function for sync token-by-token streaming.
+
+        When bound, ``.text`` and ``.reasoning`` return
+        :class:`_SyncDualProjection` instances that drive the pump and
+        yield deltas as the LLM produces tokens.
+        """
+        self._pump_one = pump_one
+
+    # -- Public projections ------------------------------------------------
+
+    @property
+    def text(self) -> str | _SyncDualProjection:
+        """Text content.
+
+        When a pump is bound (sync streaming), returns a
+        :class:`_SyncDualProjection` — iterable of deltas,
+        ``str()`` for the full accumulated text.  Otherwise returns
+        the accumulated text string directly.
+        """
+        if self._pump_one is not None and not self._done:
+            return _SyncDualProjection(self, "_text_acc", self._pump_one)
+        return self._text_acc
+
+    @property
+    def reasoning(self) -> str | _SyncDualProjection:
+        """Reasoning content.
+
+        Same dual behavior as :attr:`text`.
+        """
+        if self._pump_one is not None and not self._done:
+            return _SyncDualProjection(self, "_reasoning_acc", self._pump_one)
+        return self._reasoning_acc
+
+    @property
+    def usage(self) -> UsageInfo | None:
+        """Usage info, available after the message finishes."""
+        if self._pump_one is not None and not self._done:
+            while not self._done:
+                if not self._pump_one():
+                    break
+        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
+
+
+# ---------------------------------------------------------------------------
+# Async dual-projection helpers
+# ---------------------------------------------------------------------------
+
+
+class _DualProjection:
+    """Async iterable of deltas that is also awaitable for the final value.
+
+    When iterated, yields delta values (e.g. text fragments) as they arrive.
+    When awaited, returns the accumulated final value (e.g. full text string).
+    """
+
+    def __init__(self) -> None:
+        self._deltas: list[Any] = []
+        self._done = False
+        self._error: BaseException | None = None
+        self._waiters: list[asyncio.Future[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)
+        self._wake()
+
+    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
+        self._wake()
+
+    def _fail(self, error: BaseException) -> None:
+        self._error = error
+        self._done = True
+        self._wake()
+
+    def _wake(self) -> None:
+        for fut in self._waiters:
+            if not fut.done():
+                try:
+                    fut.get_loop().call_soon_threadsafe(fut.set_result, None)
+                except RuntimeError:
+                    pass
+        self._waiters.clear()
+
+    # -- Async iterable (yields deltas) ------------------------------------
+
+    def __aiter__(self) -> _DualProjectionIterator:
+        return _DualProjectionIterator(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
+            loop = asyncio.get_running_loop()
+            fut: asyncio.Future[None] = loop.create_future()
+            self._waiters.append(fut)
+            await fut
+        if self._error is not None:
+            raise self._error
+        return self._final_value
+
+
+class _DualProjectionIterator:
+    """Async iterator over a :class:`_DualProjection`'s deltas."""
+
+    __slots__ = ("_proj", "_offset")
+
+    def __init__(self, proj: _DualProjection) -> None:
+        self._proj = proj
+        self._offset = 0
+
+    def __aiter__(self) -> _DualProjectionIterator:
+        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
+            loop = asyncio.get_running_loop()
+            fut: asyncio.Future[None] = loop.create_future()
+            self._proj._waiters.append(fut)
+            await fut
+
+
+# ---------------------------------------------------------------------------
+# 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 = _DualProjection()
+        self._reasoning_proj = _DualProjection()
+        self._usage_proj = _DualProjection()
+
+    # -- Public projections (override sync properties) ---------------------
+
+    @property
+    def text(self) -> _DualProjection:
+        """Text content — async iterable of deltas, awaitable for full text."""
+        return self._text_proj
+
+    @property
+    def reasoning(self) -> _DualProjection:
+        """Reasoning content — async iterable of deltas, awaitable for full text."""
+        return self._reasoning_proj
+
+    @property
+    def usage(self) -> _DualProjection:
+        """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", "_SyncDualProjection"]
@@ -1,327 +1,76 @@
+"""StreamChannel — typed push-based channel for StreamTransformer projections.
+
+A ``StreamChannel`` wraps an :class:`EventLog` 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``.
+
+In-process consumers iterate the channel directly (it is an async
+iterable).  Remote SDK clients subscribe via
+``session.subscribe("custom:<channelName>")``.
+
+"""
+
 from __future__ import annotations

-import asyncio
-from collections import deque
-from collections.abc import AsyncIterator, Awaitable, Callable, Iterator
-from typing import Generic, TypeVar
+from collections.abc import AsyncIterator, Callable
+from typing import Any, Generic, TypeVar
+
+from langgraph.stream._event_log import EventLog

 T = TypeVar("T")


 class StreamChannel(Generic[T]):
-    """Single-consumer drainable queue for streaming events, with optional
-    protocol auto-forwarding.
+    """A typed push-based channel that integrates with the mux.

-    When constructed with a `name`, the StreamMux auto-wires every
-    `push()` to also inject a `ProtocolEvent` into the main event stream
-    using the channel's name as the method. When constructed without a
-    name, the channel is local-only — items are only visible to
-    in-process consumers that iterate the channel directly.
-
-    Items are popped off the front as the consumer advances — there is
-    no retention beyond what's currently queued. A channel accepts
-    exactly one subscriber; a second `__iter__` / `__aiter__` call
-    raises. Use `tee(n)` / `atee(n)` for fan-out.
-
-    Starts unbound — neither `__iter__` nor `__aiter__` is available
-    until the StreamMux calls `_bind(is_async)`. After binding, only
-    the matching iteration protocol works; the other raises `TypeError`.
-
-    Pump wiring (set by the run stream, not by `_bind`):
-        - `_request_more`: sync pump callable, returns True if a new
-          event was produced.
-        - `_arequest_more`: async pump coroutine factory, same contract.
-
-    Memory is bounded by caller pace: both sync and async use caller-
-    driven pumps, so each cursor advance produces at most one event.
-
-    Lazy-subscribe: `push` appends to the local buffer only when a
-    subscriber has registered. Auto-forward via `_wire_fn` always fires
-    regardless of subscription state.
-
-    Lifecycle (`close` / `fail`) is managed by the mux — transformers
-    don't need to close their channels manually.
+    Transformer authors create a ``StreamChannel`` in ``init()`` and
+    call ``push()`` inside ``process()`` to emit domain objects.  The
+    mux auto-wires pushes to protocol events and auto-closes/fails the
+    channel on run completion.
    """

-    def __init__(self, name: str | None = None, *, maxlen: int | None = None) -> None:
-        """Initialize the channel.
+    __slots__ = ("channel_name", "_log", "_on_push")

-        Args:
-            name: Optional protocol channel name. When set, the
-                StreamMux wires every `push()` to also inject a
-                `ProtocolEvent` into the main event stream. Surfaced
-                on the wire as `custom:<name>` for user-defined
-                transformers, or as `<name>` for channels owned by a
-                native transformer (`_native = True`). When `None`,
-                the channel is local-only.
-            maxlen: Accepted for forward compatibility; currently
-                unused. The caller-driven pump bounds memory naturally
-                for single-consumer use.
-
-        Raises:
-            ValueError: If `maxlen` is not a positive integer or `None`.
-        """
-        if maxlen is not None and maxlen <= 0:
-            raise ValueError("StreamChannel maxlen must be a positive int or None")
-        self.name = name
-        self._items: deque[T] = deque()
-        self._maxlen: int | None = maxlen
-        self._closed = False
-        self._error: BaseException | None = None
-
-        self._is_async: bool | None = None
-
-        self._subscribed = False
-
-        self._request_more: Callable[[], bool] | None = None
-        self._arequest_more: Callable[[], Awaitable[bool]] | None = None
-
-        self._wire_fn: Callable[[T], None] | None = None
-
-    # ------------------------------------------------------------------
-    # Binding
-    # ------------------------------------------------------------------
-
-    def _bind(self, *, is_async: bool) -> None:
-        """Bind this channel to sync or async mode.
-
-        Called by the StreamMux after transformer registration. Must be
-        called exactly once before any iteration.
-
-        Args:
-            is_async: True to enable async iteration, False for sync.
-
-        Raises:
-            RuntimeError: If the channel has already been bound.
-        """
-        if self._is_async is not None:
-            raise RuntimeError("StreamChannel is already bound")
-        self._is_async = is_async
-
-    # ------------------------------------------------------------------
-    # Mux wiring (not called by transformers directly)
-    # ------------------------------------------------------------------
-
-    def _wire(self, fn: Callable[[T], None]) -> None:
-        """Install the auto-forward callback (called by StreamMux)."""
-        self._wire_fn = fn
-
-    # ------------------------------------------------------------------
-    # Producer API
-    # ------------------------------------------------------------------
+    def __init__(self, name: str) -> None:
+        self.channel_name = name
+        self._log: EventLog[T] = EventLog()
+        self._on_push: Callable[[Any], None] | None = None

    def push(self, item: T) -> None:
-        """Append an item. Auto-forwards if wired.
+        """Push an item to the channel.

-        The local buffer append is a no-op when no subscriber is
-        registered, but auto-forwarding always fires so wired events
-        reach the main event log regardless of subscription state.
-
-        Raises:
-            RuntimeError: If the channel is closed (and subscribed).
+        If the mux has wired this channel, the push also injects a
+        protocol event into the main event stream.
        """
-        if self._subscribed:
-            if self._closed:
-                raise RuntimeError("Cannot push to a closed StreamChannel")
-            self._items.append(item)
-        if self._wire_fn is not None:
-            self._wire_fn(item)
+        self._log.append(item)
+        if self._on_push is not None:
+            self._on_push(item)

-    def close(self) -> None:
-        """Mark the channel as complete."""
-        self._closed = True
-
-    def fail(self, err: BaseException) -> None:
-        """Mark the channel as errored.
-
-        Args:
-            err: The exception to surface to the subscriber.
-        """
-        self._error = err
-        self._closed = True
-
-    # ------------------------------------------------------------------
-    # Sync iteration (caller-driven pump)
-    # ------------------------------------------------------------------
-
-    def __iter__(self) -> Iterator[T]:
-        """Subscribe and return a sync cursor. Can be called only once.
-
-        Raises:
-            TypeError: If the channel is unbound or bound to async mode.
-            RuntimeError: If the channel already has a subscriber.
-        """
-        if self._is_async is None:
-            raise TypeError(
-                "StreamChannel has not been bound yet. "
-                "Register the transformer with a StreamMux first."
-            )
-        if self._is_async:
-            raise TypeError(
-                "This StreamChannel is bound to async mode — use 'async for' instead."
-            )
-        if self._subscribed:
-            raise RuntimeError(
-                "StreamChannel already has a subscriber; use .tee(n) for fan-out."
-            )
-        self._subscribed = True
-        return self._sync_cursor()
-
-    def _sync_cursor(self) -> Iterator[T]:
-        while True:
-            if self._items:
-                yield self._items.popleft()
-            elif self._closed:
-                if self._error is not None:
-                    raise self._error
-                return
-            elif self._request_more is not None:
-                if not self._request_more():
-                    if not self._items and not self._closed:
-                        return
-            else:
-                return
-
-    # ------------------------------------------------------------------
-    # Async iteration (caller-driven pump)
-    # ------------------------------------------------------------------
+    # -- Async iteration (in-process consumption) ---------------------------

    def __aiter__(self) -> AsyncIterator[T]:
-        """Subscribe and return an async cursor. Can be called only once.
+        return aiter(self._log)

-        Raises:
-            TypeError: If the channel is unbound or bound to sync mode.
-            RuntimeError: If the channel already has a subscriber.
-        """
-        if self._is_async is None:
-            raise TypeError(
-                "StreamChannel has not been bound yet. "
-                "Register the transformer with a StreamMux first."
-            )
-        if not self._is_async:
-            raise TypeError(
-                "This StreamChannel is bound to sync mode — use 'for' instead."
-            )
-        if self._subscribed:
-            raise RuntimeError(
-                "StreamChannel already has a subscriber; use .atee(n) for fan-out."
-            )
-        self._subscribed = True
-        return self._async_cursor()
+    # -- Internal (called by the mux) ---------------------------------------

-    async def _async_cursor(self) -> AsyncIterator[T]:
-        while True:
-            if self._items:
-                yield self._items.popleft()
-            elif self._closed:
-                if self._error is not None:
-                    raise self._error
-                return
-            elif self._arequest_more is not None:
-                if not await self._arequest_more():
-                    if not self._items and not self._closed:
-                        return
-            else:
-                return
+    def _wire(self, fn: Callable[[Any], None]) -> None:
+        """Wire a callback invoked on every ``push()``.  Called by the mux."""
+        self._on_push = fn

-    # ------------------------------------------------------------------
-    # Fan-out via tee
-    # ------------------------------------------------------------------
+    def _close(self) -> None:
+        """Close the underlying log.  Called by the mux on normal completion."""
+        self._log.close()

-    def tee(self, n: int = 2) -> tuple[Iterator[T], ...]:
-        """Subscribe and return `n` independent sync iterators.
+    def _fail(self, err: BaseException) -> None:
+        """Fail the underlying log.  Called by the mux on failure."""
+        self._log.fail(err)

-        Each branch has its own buffer; items pulled from the
-        underlying cursor are copied into every branch. Branches are
-        naturally bounded by caller pace since the sync pump is
-        caller-driven.

-        Args:
-            n: Number of branches to create. Must be >= 1.
+def is_stream_channel(value: object) -> bool:
+    """Check if *value* is a :class:`StreamChannel` instance."""
+    return isinstance(value, StreamChannel)

-        Returns:
-            A tuple of `n` iterators over the same underlying stream.

-        Raises:
-            TypeError: If the channel is unbound or bound to async mode.
-            RuntimeError: If the channel already has a subscriber.
-            ValueError: If `n` < 1.
-        """
-        if n < 1:
-            raise ValueError("tee() requires n >= 1")
-        source = self.__iter__()
-        buffers: list[deque[T]] = [deque() for _ in range(n)]
-        exhausted = [False]
-
-        def branch(i: int) -> Iterator[T]:
-            buf = buffers[i]
-            while True:
-                if buf:
-                    yield buf.popleft()
-                elif exhausted[0]:
-                    return
-                else:
-                    try:
-                        item = next(source)
-                    except StopIteration:
-                        exhausted[0] = True
-                        return
-                    for b in buffers:
-                        b.append(item)
-
-        return tuple(branch(i) for i in range(n))
-
-    def atee(self, n: int = 2) -> tuple[AsyncIterator[T], ...]:
-        """Subscribe and return `n` independent async iterators.
-
-        Caller-driven fan-out: each branch's `__anext__` either pops
-        from its own buffer or, under a shared `asyncio.Lock`, pulls
-        one item from the underlying cursor and distributes it to
-        every branch's buffer.
-
-        Args:
-            n: Number of branches to create. Must be >= 1.
-
-        Returns:
-            A tuple of `n` async iterators over the same underlying
-            stream.
-
-        Raises:
-            TypeError: If the channel is unbound or bound to sync mode.
-            RuntimeError: If the channel already has a subscriber.
-            ValueError: If `n` < 1.
-        """
-        if n < 1:
-            raise ValueError("atee() requires n >= 1")
-        source = self.__aiter__()
-        buffers: list[deque[T]] = [deque() for _ in range(n)]
-        exhausted = [False]
-        error: list[BaseException | None] = [None]
-        lock = asyncio.Lock()
-
-        async def branch(i: int) -> AsyncIterator[T]:
-            buf = buffers[i]
-            while True:
-                if buf:
-                    yield buf.popleft()
-                    continue
-                if exhausted[0]:
-                    if error[0] is not None:
-                        raise error[0]
-                    return
-                async with lock:
-                    if buf or exhausted[0]:
-                        continue
-                    try:
-                        item = await source.__anext__()
-                    except StopAsyncIteration:
-                        exhausted[0] = True
-                        continue
-                    except Exception as e:
-                        error[0] = e
-                        exhausted[0] = True
-                        continue
-                    for b in buffers:
-                        b.append(item)
-
-        return tuple(branch(i) for i in range(n))
+__all__ = ["StreamChannel", "is_stream_channel"]
@@ -0,0 +1,168 @@
+"""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,
+        )
@@ -1,749 +1,179 @@
+"""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

-import logging
-from typing import TYPE_CHECKING, Any, Literal, cast
+from typing import Any

-from langchain_core.language_models._compat_bridge import message_to_events
-from langchain_core.language_models.chat_model_stream import (
-    AsyncChatModelStream,
-    ChatModelStream,
-)
-from langchain_core.messages import AIMessageChunk, BaseMessage
-from langchain_protocol.protocol import MessagesData
-from typing_extensions import NotRequired, TypedDict
+from langgraph.stream._event_log import EventLog
+from langgraph.stream._types import ProtocolEvent
+from langgraph.stream.chat_model_stream import ChatModelStream

-from langgraph.errors import GraphInterrupt
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.run_stream import AsyncSubgraphRunStream, SubgraphRunStream
-from langgraph.stream.stream_channel import StreamChannel
-
-if TYPE_CHECKING:
-    from collections.abc import Awaitable, Callable
-
-    from langgraph.stream._mux import StreamMux
-
-_logger = logging.getLogger(__name__)
+# Type alias for the stream class constructor signature
+_StreamCls = type[ChatModelStream]


-class ValuesTransformer(StreamTransformer):
-    """Capture values events as a drainable stream of state snapshots.
+class ValuesTransformer:
+    """Extracts ``values`` events and populates a values event log.

-    Keeps `_latest` / `_interrupted` / `_interrupts` as scalar state
-    regardless of whether the log has a subscriber — so `run.output()`
-    and `run.interrupted` work without forcing the caller to iterate
-    `run.values`. Log pushes are silent no-ops when unsubscribed.
+    Maintains the latest state per namespace and provides a separate
+    event log that :class:`AsyncGraphRunStream` / :class:`GraphRunStream` uses for ``.values``
+    iteration.

-    Native transformer — projection keys are exposed as direct
-    attributes on the run stream (e.g. `run.values`).
-
-    Only values events at the run's own level are captured; snapshots
-    from deeper subgraphs are left in the main event log but excluded
-    from the projection. "Own level" is defined by `scope`, which
-    `stream_v2` / `astream_v2` populate from the caller's checkpoint
-    namespace so that a nested `stream_v2` call still sees its own
-    root snapshots.
+    Implements the :class:`StreamTransformer` protocol.
    """

-    _native = True
-    required_stream_modes = ("values",)
+    name = "values"

-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[dict[str, Any]] = StreamChannel()
-        self._latest: dict[str, Any] | None = None
-        self._interrupted = False
-        self._interrupts: list[Any] = []
-        # Cached as a list once for cheap equality with the protocol
-        # event's `namespace` field, which is `list[str]`.
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"values": self._log}
+    def __init__(self) -> None:
+        self._values_log: EventLog[dict[str, Any]] = EventLog()
+        self._latest: dict[str, Any] = {}

    @property
-    def error(self) -> BaseException | None:
-        """The error that ended the run, or `None` if it succeeded.
+    def value(self) -> EventLog[dict[str, Any]]:
+        return self._values_log

-        Set by the mux when it auto-fails the projection log.
-        """
-        return self._log._error
+    @property
+    def values_log(self) -> EventLog[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
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True
-        self._latest = params["data"]
-        interrupts = params.get("interrupts", ())
-        if interrupts:
-            self._interrupted = True
-            self._interrupts.extend(interrupts)
-        self._log.push(params["data"])
+
+        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:
+        self._values_log.close()

-class MessagesTransformer(StreamTransformer):
-    """Capture messages events as ChatModelStream objects.
+    def fail(self, err: BaseException) -> None:
+        self._values_log.fail(err)

-    The messages projection yields one `ChatModelStream` (or
-    `AsyncChatModelStream`) per LLM call. Consumers iterate
-    `run.messages` to get stream handles, then use each handle's typed
-    projections (`.text`, `.reasoning`, `.tool_calls`, `.usage`,
-    `.output`) for per-message content.

-    Two input shapes are handled (via `params["data"] = (payload,
-    metadata)` from `StreamMessagesHandler`):
+class MessagesTransformer:
+    """Groups ``messages`` events into :class:`ChatModelStream` instances.

-    1. Protocol event (dict with `"event"` key) — emitted by
-       `stream_v2()` / `astream_v2()` via the `on_stream_event`
-       callback. Routed to an existing `ChatModelStream` by
-       `metadata["run_id"]`. A `message-start` event creates a new
-       stream; `message-finish` closes it.
-    2. Whole `AIMessage` — emitted from `on_chain_end` when a node
-       returns a finalized message. Replayed as a synthetic protocol
-       event lifecycle via `message_to_events`, then the
-       already-complete stream is pushed to the log.
+    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.

-    V1 `AIMessageChunk` tuples (from `on_llm_new_token`) are not
-    streamed into this projection: chat models that want to populate
-    `run.messages` with content-block streaming must use
-    `stream_v2()` / `astream_v2()`. Models called via the legacy
-    `stream()` method still surface their final `AIMessage` via
-    `on_chain_end` when a node returns it as state.
-
-    Only events at the run's own level are projected; tokens from
-    deeper subgraphs are left in the main event log but excluded from
-    `.messages`. "Own level" is defined by `scope`, which
-    `stream_v2` / `astream_v2` populate from the caller's checkpoint
-    namespace so that a `stream_v2` call inside a node still sees its
-    own root chat model streams on `.messages`. Consumers that need
-    subgraph tokens should iterate the raw event stream or register a
-    custom transformer.
-
-    Native transformer — the `messages` projection is exposed as a
-    direct attribute on the run stream.
+    Implements the :class:`StreamTransformer` protocol.
    """

-    _native = True
-    required_stream_modes = ("messages",)
+    name = "messages"

-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[ChatModelStream] = StreamChannel()
-        # Correlate protocol events back to a ChatModelStream by run_id
-        # (attached to the event's metadata by StreamMessagesHandler).
-        self._by_run: dict[str, ChatModelStream] = {}
-        self._pump_fn: Callable[[], bool] | None = None
-        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
-        # Cached as a list once for cheap equality with the protocol
-        # event's `namespace` field, which is `list[str]`.
-        self._scope_list: list[str] = list(scope)
-
-    def init(self) -> dict[str, Any]:
-        return {"messages": self._log}
-
-    def _bind_pump(self, fn: Callable[[], bool]) -> None:
-        """Wire the sync pull callback. Called by GraphRunStream._wire_request_more."""
-        self._pump_fn = fn
-
-    def _bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
-        """Wire the async pull callback.
-
-        Called by `AsyncGraphRunStream._wire_arequest_more` so each
-        `AsyncChatModelStream` this transformer creates can drive the
-        shared graph pump from its projection cursors.
-        """
-        self._apump_fn = fn
-
-    def _make_stream(
+    def __init__(
        self,
        *,
-        namespace: list[str],
-        node: str | None,
-        message_id: str | None,
-    ) -> ChatModelStream:
-        """Create a ChatModelStream (sync) or AsyncChatModelStream (async).
+        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

-        Wires whichever pump is bound. Prefers the async pump so nested
-        iteration under `AsyncGraphRunStream` drives the graph forward
-        without a background task. The unwired fallback (no pump bound)
-        is used by unit tests that dispatch events manually.
-        """
-        if self._apump_fn is not None:
-            astream = AsyncChatModelStream(
-                namespace=namespace,
-                node=node,
-                message_id=message_id,
-            )
-            astream.set_arequest_more(self._apump_fn)
-            return astream
-        if self._pump_fn is not None:
-            stream: ChatModelStream = ChatModelStream(
-                namespace=namespace,
-                node=node,
-                message_id=message_id,
-            )
-            stream.set_request_more(self._pump_fn)
-            return stream
-        return AsyncChatModelStream(
-            namespace=namespace,
-            node=node,
-            message_id=message_id,
-        )
+        # Message log for .messages iteration
+        self._messages_log: EventLog[ChatModelStream] = EventLog()
+
+        # Current active stream per namespace key
+        self._active: dict[str, ChatModelStream] = {}
+
+    @property
+    def value(self) -> EventLog[ChatModelStream]:
+        return self._messages_log
+
+    @property
+    def messages_log(self) -> EventLog[ChatModelStream]:
+        return self._messages_log
+
+    def init(self) -> Any:
+        return None

    def process(self, event: ProtocolEvent) -> bool:
        if event["method"] != "messages":
            return True
-        params = event["params"]
-        if params["namespace"] != self._scope_list:
-            return True

-        payload, metadata = params["data"]
-        node: str | None = metadata.get("langgraph_node")
-        run_id = str(metadata.get("run_id", "")) if metadata else ""
-
-        if isinstance(payload, dict) and "event" in payload:
-            self._route_protocol_event(
-                cast("MessagesData", payload), run_id=run_id, node=node
-            )
-        elif isinstance(payload, BaseMessage) and not isinstance(
-            payload, AIMessageChunk
-        ):
-            self._route_whole_message(payload, node=node)
-        # Legacy AIMessageChunk tuples (from on_llm_new_token) are ignored;
-        # v1 streaming callers must switch to stream_v2() to populate this
-        # projection.
-
-        return True
-
-    def _route_protocol_event(
-        self,
-        event: MessagesData,
-        *,
-        run_id: str,
-        node: str | None,
-    ) -> None:
-        event_type = event.get("event")
-        if event_type == "message-start":
-            message_id = event.get("message_id")
-            stream = self._make_stream(
-                namespace=[],
-                node=node,
-                message_id=str(message_id) if message_id is not None else None,
-            )
-            self._by_run[run_id] = stream
-            self._log.push(stream)
-            stream.dispatch(event)
-        elif run_id in self._by_run:
-            stream = self._by_run[run_id]
-            stream.dispatch(event)
-            if event_type == "message-finish":
-                del self._by_run[run_id]
-
-    def _route_whole_message(self, message: BaseMessage, *, node: str | None) -> None:
-        stream = self._make_stream(namespace=[], node=node, message_id=message.id)
-        for evt in message_to_events(message, message_id=message.id):
-            stream.dispatch(evt)
-        self._log.push(stream)
-
-    def finalize(self) -> None:
-        """Clear any routing state — streams close themselves via `message-finish`."""
-        self._by_run.clear()
-
-    def fail(self, err: BaseException) -> None:
-        """Propagate run error to any streams still open when the graph fails."""
-        for stream in list(self._by_run.values()):
-            stream.fail(err)
-        self._by_run.clear()
-
-
-SubgraphStatus = Literal["started", "completed", "failed", "interrupted"]
-
-
-def _parse_ns_segment(segment: str) -> tuple[str, str | None]:
-    """Split a namespace segment into `(graph_name, trigger_call_id)`.
-
-    Segments are formatted `node_name:task_id` by `prepare_next_tasks`.
-    Returns `(segment, None)` if no `:` is present.
-    """
-    name, sep, task_id = segment.partition(":")
-    return name, task_id if sep else None
-
-
-class LifecyclePayload(TypedDict, total=False):
-    """Payload of a lifecycle event surfaced on the `lifecycle` channel.
-
-    Auto-forwarded as `lifecycle` protocol events (no `custom:` prefix
-    because `LifecycleTransformer` is a native transformer) so remote
-    SDK clients receive the same data in-process consumers see via
-    `run.lifecycle`.
-    """
-
-    event: SubgraphStatus
-    namespace: list[str]
-    graph_name: NotRequired[str]
-    trigger_call_id: NotRequired[str]
-    error: NotRequired[str]
-
-
-class _TasksLifecycleBase(StreamTransformer):
-    """Shared bookkeeping for `tasks`-event-driven lifecycle inference.
-
-    Both `LifecycleTransformer` (wire-serializable channel) and
-    `SubgraphTransformer` (in-process navigation handles) discover
-    subgraphs by watching the same `tasks` stream — `started` on the
-    first event at a tracked namespace, terminal status when the
-    parent's `TaskResultPayload` arrives. Centralizing the dispatch
-    + open-set bookkeeping here keeps the inference rules from
-    drifting between the two surfaces.
-
-    Subclasses provide three template-method hooks:
-
-    - `_should_track(ns)` — scope filter (e.g. multi-depth vs
-      direct-children-only).
-    - `_on_started(ns, graph_name, trigger_call_id)` — first sighting
-      action (push payload / build handle / etc.). Called once per
-      discovered namespace.
-    - `_on_terminal(ns, status, error)` — terminal action (push
-      terminal payload / mark handle status). Called once per
-      tracked namespace at result time, or via `finalize` / `fail`
-      sweeps if no parent result arrived.
-
-    Tasks events are suppressed from the main event log (`process`
-    returns False) — they're folded into whichever projection the
-    subclass populates; consumers iterating the raw protocol stream
-    see the higher-level view.
-    """
-
-    required_stream_modes = ("tasks",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._seen: set[tuple[str, ...]] = set()
-        # Maps tracked namespace -> task_id of the parent task whose
-        # `TaskResultPayload` will close it.
-        self._open: dict[tuple[str, ...], str] = {}
-
-    # --- Template-method hooks (subclass overrides) ---
-
-    def _should_track(self, ns: tuple[str, ...]) -> bool:
-        """Scope filter — return True iff `ns` is in this transformer's region."""
-        raise NotImplementedError
-
-    def _on_started(
-        self,
-        ns: tuple[str, ...],
-        graph_name: str | None,
-        trigger_call_id: str | None,
-    ) -> None:
-        """Fired once per discovered namespace (first observed task event)."""
-        raise NotImplementedError
-
-    def _on_terminal(
-        self,
-        ns: tuple[str, ...],
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> None:
-        """Fired once per tracked namespace when its parent's result arrives,
-        or via finalize/fail safety-net sweeps.
-        """
-        raise NotImplementedError
-
-    # --- Dispatch + bookkeeping (shared) ---
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] != "tasks":
-            return True
-        ns = tuple(event["params"]["namespace"])
+        ns = event["params"].get("namespace", [])
+        node = event["params"].get("node")
        data = event["params"]["data"]
-        if "result" in data:
-            self._handle_task_result(ns, data)
-        else:
-            self._handle_task_start(ns)
-        # Tasks events are folded into the synthesized projections;
-        # suppress from the main event log so iterators don't double-see
-        # the same information in two shapes.
-        return False

-    def _handle_task_start(self, ns: tuple[str, ...]) -> None:
-        if not self._should_track(ns) or ns in self._seen:
-            return
-        self._seen.add(ns)
-        graph_name, trigger_call_id = _parse_ns_segment(ns[-1])
-        self._on_started(ns, graph_name or None, trigger_call_id)
-        if trigger_call_id is not None:
-            self._open[ns] = trigger_call_id
+        # Apply namespace filter
+        if self._namespace is not None:
+            if ns[: len(self._namespace)] != self._namespace:
+                return True

-    def _pop_terminal_transitions(
-        self, ns: tuple[str, ...], data: dict[str, Any]
-    ) -> list[tuple[tuple[str, ...], SubgraphStatus, str | None]]:
-        """Return and remove tracked children closed by this task result."""
-        result_id = data.get("id")
-        if not result_id:
-            return []
-        transitions: list[tuple[tuple[str, ...], SubgraphStatus, str | None]] = []
-        for child_ns, parent_task_id in list(self._open.items()):
-            if child_ns[:-1] != ns or parent_task_id != result_id:
-                continue
-            status, error = _terminal_from_result(data)
-            transitions.append((child_ns, status, error))
-            del self._open[child_ns]
-        return transitions
+        # Apply node filter
+        if self._node_filter is not None and node != self._node_filter:
+            return True

-    def _handle_task_result(self, ns: tuple[str, ...], data: dict[str, Any]) -> None:
-        for child_ns, status, error in self._pop_terminal_transitions(ns, data):
-            self._on_terminal(child_ns, status, error)
+        ns_key = "|".join(ns) if ns else ""
+        event_type = data.get("event") if isinstance(data, dict) else None

-    def finalize(self) -> None:
-        """Emit `completed` for any tracked namespace still open at run end."""
-        for ns in list(self._open):
-            self._on_terminal(ns, "completed", None)
-        self._open.clear()
+        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)

-    def fail(self, err: BaseException) -> None:
-        """Emit `failed` / `interrupted` for any tracked namespace still open."""
-        is_interrupt = isinstance(err, GraphInterrupt)
-        status: SubgraphStatus = "interrupted" if is_interrupt else "failed"
-        error_str = None if is_interrupt else str(err)
-        for ns in list(self._open):
-            self._on_terminal(ns, status, error_str)
-        self._open.clear()
+        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)

-def _status_from_exception(err: BaseException) -> tuple[SubgraphStatus, str | None]:
-    """Map a run exception to a subgraph terminal status and error string."""
-    if isinstance(err, GraphInterrupt):
-        return "interrupted", None
-    return "failed", str(err)
+        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))

-def _terminal_from_result(
-    payload: dict[str, Any],
-) -> tuple[SubgraphStatus, str | None]:
-    """Map a `TaskResultPayload` to a `(status, error)` pair.
-
-    Order matters: a result with both `error` and `interrupts` prefers
-    the interrupt classification, since `GraphInterrupt` manifests as
-    a populated `interrupts` list, not as `error`.
-    """
-    if payload.get("interrupts"):
-        return "interrupted", None
-    error = payload.get("error")
-    if error:
-        return "failed", str(error)
-    return "completed", None
-
-
-class LifecycleTransformer(_TasksLifecycleBase):
-    """Surface subgraph lifecycle as `lifecycle` protocol events.
-
-    Pushes `LifecyclePayload` to a `StreamChannel` named `lifecycle`.
-    The channel is auto-forwarded by the mux so payloads land in the
-    main event log under `method = "lifecycle"` (native transformer —
-    no `custom:` prefix) — visible to remote SDK clients over the
-    wire and to in-process consumers via `run.lifecycle`.
-
-    Tracks subgraphs at every depth strictly below the transformer's
-    scope, so a graph → subgraph → subgraph chain produces lifecycle
-    events for both nested levels in a flat stream.
-
-    Native transformer — projection key `lifecycle` is exposed as
-    `run.lifecycle`.
-    """
-
-    _native = True
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._channel: StreamChannel[LifecyclePayload] = StreamChannel("lifecycle")
-
-    def init(self) -> dict[str, Any]:
-        return {"lifecycle": self._channel}
-
-    def _should_track(self, ns: tuple[str, ...]) -> bool:
-        depth = len(self.scope)
-        return len(ns) > depth and ns[:depth] == self.scope
-
-    def _on_started(
-        self,
-        ns: tuple[str, ...],
-        graph_name: str | None,
-        trigger_call_id: str | None,
-    ) -> None:
-        if trigger_call_id is None:
-            # Without a task id we can't correlate a parent-result
-            # event back to this namespace — skip the started payload
-            # and rely on finalize/fail to close.
-            return
-        payload: LifecyclePayload = {"event": "started", "namespace": list(ns)}
-        if graph_name:
-            payload["graph_name"] = graph_name
-        payload["trigger_call_id"] = trigger_call_id
-        self._channel.push(payload)
-
-    def _on_terminal(
-        self,
-        ns: tuple[str, ...],
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> None:
-        payload: LifecyclePayload = {"event": status, "namespace": list(ns)}
-        if error is not None:
-            payload["error"] = error
-        self._channel.push(payload)
-
-
-class SubgraphTransformer(_TasksLifecycleBase):
-    """Discover subgraph invocations as in-process navigation handles.
-
-    Per discovered direct-child subgraph, builds a `SubgraphRunStream`
-    (or `AsyncSubgraphRunStream`) wrapping a child mini-mux scoped to
-    the subgraph's namespace. Consumers iterate `run.subgraphs` to
-    receive handles, then drill into `handle.values` / `handle.messages`
-    / `handle.subgraphs` (recursive grandchildren) / `handle.lifecycle`.
-
-    Each mini-mux owns its own scope and uses its own
-    `SubgraphTransformer` to discover its direct children, so
-    grandchildren live on the child handle — never on the root's
-    `subgraphs` log. Forwarding events into the matching child mini-mux
-    is what keeps the child's projections populated.
-
-    Native transformer — `subgraphs` is exposed as `run.subgraphs`.
-    """
-
-    _native = True
-    supports_sync = True
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[SubgraphRunStream | AsyncSubgraphRunStream] = (
-            StreamChannel()
-        )
-        self._handles: dict[
-            tuple[str, ...], SubgraphRunStream | AsyncSubgraphRunStream
-        ] = {}
-        self._mux: StreamMux | None = None
-
-    def init(self) -> dict[str, Any]:
-        return {"subgraphs": self._log}
-
-    def _on_register(self, mux: Any) -> None:
-        self._mux = mux
-
-    def _should_track(self, ns: tuple[str, ...]) -> bool:
-        # Direct children only — grandchildren are picked up by the
-        # child mini-mux's own SubgraphTransformer.
-        depth = len(self.scope)
-        return len(ns) == depth + 1 and ns[:depth] == self.scope
-
-    def _on_started(
-        self,
-        ns: tuple[str, ...],
-        graph_name: str | None,
-        trigger_call_id: str | None,
-    ) -> None:
-        if self._mux is None:
-            return
-        try:
-            child_mux = self._mux._make_child(ns)
-        except RuntimeError:
-            # Mux wasn't built from factories — no mini-mux navigation
-            # available. Skip; LifecycleTransformer still tracks the
-            # subgraph via the flat event stream.
-            return
-        values_t = child_mux.transformer_by_key("values")
-        if not isinstance(values_t, ValuesTransformer):
-            return
-        handle_cls = AsyncSubgraphRunStream if child_mux.is_async else SubgraphRunStream
-        handle = handle_cls(
-            mux=child_mux,
-            values_transformer=values_t,
-            path=ns,
-            graph_name=graph_name,
-            trigger_call_id=trigger_call_id,
-        )
-        self._handles[ns] = handle
-        self._log.push(handle)
-
-    def _on_terminal(
-        self,
-        ns: tuple[str, ...],
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> None:
-        handle = self._handles.get(ns)
-        if handle is None or not self._mark_terminal(handle, status, error):
-            return
-        self._close_or_fail_handle(handle, status, error)
-
-    async def _aon_terminal(
-        self,
-        ns: tuple[str, ...],
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> None:
-        handle = self._handles.get(ns)
-        if handle is None or not self._mark_terminal(handle, status, error):
-            return
-        await self._aclose_or_fail_handle(handle, status, error)
-
-    def _mark_terminal(
-        self,
-        handle: SubgraphRunStream | AsyncSubgraphRunStream,
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> bool:
-        """Mark a handle terminal once. Returns True on first transition."""
-        if handle._seen_terminal:
-            return False
-        handle.status = status
-        if error is not None and handle.error is None:
-            handle.error = error
-        handle._seen_terminal = True
        return True

-    def _close_or_fail_handle(
-        self,
-        handle: SubgraphRunStream | AsyncSubgraphRunStream,
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> None:
-        if handle._mux is None or handle._mux._events._closed:
-            return
-        if status == "failed":
-            handle._mux.fail(RuntimeError(error or "Subgraph failed"))
-        else:
-            handle._mux.close()
-
-    async def _aclose_or_fail_handle(
-        self,
-        handle: SubgraphRunStream | AsyncSubgraphRunStream,
-        status: SubgraphStatus,
-        error: str | None,
-    ) -> None:
-        if handle._mux is None or handle._mux._events._closed:
-            return
-        if status == "failed":
-            await handle._mux.afail(RuntimeError(error or "Subgraph failed"))
-        else:
-            await handle._mux.aclose()
-
-    def _child_mux_for_event(self, event: ProtocolEvent) -> StreamMux | None:
-        ns = tuple(event["params"]["namespace"])
-        depth = len(self.scope)
-        if len(ns) < depth + 1:
-            return None
-        handle = self._handles.get(ns[: depth + 1])
-        if handle is None or handle._mux is None or handle._mux._events._closed:
-            return None
-        return handle._mux
-
-    def process(self, event: ProtocolEvent) -> bool:
-        # Discover / update terminal status before forwarding so a
-        # `started` handle exists by the time the child mini-mux sees
-        # its own first event.
-        keep = super().process(event)
-        child_mux = self._child_mux_for_event(event)
-        if child_mux is not None:
-            child_mux.push(event)
-        return keep
-
-    async def aprocess(self, event: ProtocolEvent) -> bool:
-        # Async counterpart to `process`: repeat the tasks bookkeeping
-        # here instead of delegating to `process`, so child mini-muxes
-        # receive events through their async lane.
-        if event["method"] == "tasks":
-            ns = tuple(event["params"]["namespace"])
-            data = event["params"]["data"]
-            if "result" in data:
-                for child_ns, status, error in self._pop_terminal_transitions(ns, data):
-                    await self._aon_terminal(child_ns, status, error)
-            else:
-                self._handle_task_start(ns)
-            keep = False
-        else:
-            keep = True
-        child_mux = self._child_mux_for_event(event)
-        if child_mux is not None:
-            await child_mux.apush(event)
-        return keep
-
-    def _complete_open_handles(self) -> BaseException | None:
-        first_error: BaseException | None = None
-        for ns in list(self._open):
-            try:
-                self._on_terminal(ns, "completed", None)
-            except BaseException as e:
-                if first_error is None:
-                    first_error = e
-        self._open.clear()
-        for handle in self._handles.values():
-            if self._mark_terminal(handle, "completed", None):
-                try:
-                    self._close_or_fail_handle(handle, "completed", None)
-                except BaseException as e:
-                    if first_error is None:
-                        first_error = e
-        return first_error
-
-    async def _acomplete_open_handles(self) -> BaseException | None:
-        first_error: BaseException | None = None
-        for ns in list(self._open):
-            try:
-                await self._aon_terminal(ns, "completed", None)
-            except BaseException as e:
-                if first_error is None:
-                    first_error = e
-        self._open.clear()
-        for handle in self._handles.values():
-            if self._mark_terminal(handle, "completed", None):
-                try:
-                    await self._aclose_or_fail_handle(handle, "completed", None)
-                except BaseException as e:
-                    if first_error is None:
-                        first_error = e
-        return first_error
-
    def finalize(self) -> None:
-        first_error = self._complete_open_handles()
-        if first_error is not None:
-            raise first_error
-
-    async def afinalize(self) -> None:
-        first_error = await self._acomplete_open_handles()
-        if first_error is not None:
-            raise first_error
+        # Close any remaining active streams
+        for stream in self._active.values():
+            stream._finish({"reason": "stop"})
+        self._active.clear()
+        self._messages_log.close()

    def fail(self, err: BaseException) -> None:
-        status, error_str = _status_from_exception(err)
-        self._open.clear()
-        for handle in self._handles.values():
-            self._mark_terminal(handle, status, error_str)
-            if handle._mux is not None and not handle._mux._events._closed:
-                try:
-                    handle._mux.fail(err)
-                except Exception:
-                    _logger.warning(
-                        "Error failing subgraph mini-mux at %s; "
-                        "subscribers may not see the terminal error.",
-                        handle.path,
-                        exc_info=True,
-                    )
+        for stream in self._active.values():
+            stream._fail(err)
+        self._active.clear()
+        self._messages_log.fail(err)

-    async def afail(self, err: BaseException) -> None:
-        status, error_str = _status_from_exception(err)
-        self._open.clear()
-        for handle in self._handles.values():
-            self._mark_terminal(handle, status, error_str)
-            if handle._mux is not None and not handle._mux._events._closed:
-                try:
-                    await handle._mux.afail(err)
-                except Exception:
-                    _logger.warning(
-                        "Error failing subgraph mini-mux at %s; "
-                        "subscribers may not see the terminal error.",
-                        handle.path,
-                        exc_info=True,
-                    )
+
+__all__ = [
+    "MessagesTransformer",
+    "ValuesTransformer",
+]
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph"
-version = "1.1.10"
+version = "1.1.6"
 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>=1.3.2,<2",
+    "langchain-core>=0.1",
    "langgraph-checkpoint>=2.1.0,<5.0.0",
    "langgraph-sdk>=0.3.0,<0.4.0",
-    "langgraph-prebuilt>=1.0.12,<1.1.0",
+    "langgraph-prebuilt>=1.0.9,<1.1.0",
    "xxhash>=3.5.0",
    "pydantic>=2.7.4",
 ]
@@ -81,7 +81,6 @@ dev = [


 [tool.uv.sources]
-langchain-core = { git = "https://github.com/langchain-ai/langchain", branch = "cb/chat-model-updates", subdirectory = "libs/core" }
 langgraph-prebuilt = { path = "../prebuilt", editable = true }
 langgraph-checkpoint = { path = "../checkpoint", editable = true }
 langgraph-checkpoint-sqlite = { path = "../checkpoint-sqlite", editable = true }
@@ -1,344 +0,0 @@
-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 == []
@@ -0,0 +1,558 @@
+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
+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:
+    """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
+
+
+# ---------------------------------------------------------------------------
+# 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:
+    """Groups tool-started/tool-finished custom events into _ToolExecution objects."""
+
+    name = "tools"
+
+    def __init__(self) -> None:
+        from langgraph.stream._event_log import EventLog
+
+        self._log: EventLog[_ToolExecution] = EventLog()
+        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:
+        self._log.close()
+
+    def fail(self, err: BaseException) -> None:
+        self._log.fail(err)
+
+
+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}
@@ -1396,6 +1396,7 @@ 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",
@@ -1458,6 +1459,7 @@ 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",
@@ -1510,6 +1512,7 @@ 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",
@@ -6881,6 +6884,7 @@ 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",
@@ -6908,6 +6912,7 @@ 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",
@@ -6944,6 +6949,7 @@ 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",
@@ -1147,6 +1147,7 @@ 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",
@@ -1209,6 +1210,7 @@ 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",
@@ -1261,6 +1263,7 @@ 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",
@@ -3978,6 +3981,7 @@ 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",
@@ -4005,6 +4009,7 @@ 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",
@@ -4041,6 +4046,7 @@ 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",
@@ -0,0 +1,531 @@
+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"
@@ -615,11 +615,8 @@ def test_run_from_checkpoint_id_retains_previous_writes(
        )
    ]

-    # +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 len(new_history) == len(history) + 1
+    for original, new in zip(history, new_history[1:]):
        assert original.values == new.values
        assert original.next == new.next
        assert original.metadata["step"] == new.metadata["step"]
@@ -627,7 +624,7 @@ 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, 2) == _get_tasks(history, 0)
+    assert _get_tasks(new_history, 1) == _get_tasks(history, 0)


 def test_batch_two_processes_in_out() -> None:
@@ -6274,7 +6271,7 @@ 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.monotonic()}
+        return {"tic": time.time()}

    @entrypoint()
    def graph(inputs: dict) -> list:
@@ -6287,7 +6284,7 @@ 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.monotonic())
+        arrival_times.append(time.time())

    assert len(arrival_times) == 2
    delta = arrival_times[1] - arrival_times[0]
@@ -6896,6 +6893,7 @@ 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",
@@ -6905,60 +6903,6 @@ 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

@@ -20,7 +20,6 @@ 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
@@ -2086,11 +2085,8 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
        )
    ]

-    # +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 len(new_history) == len(history) + 1
+    for original, new in zip(history, new_history[1:]):
        assert original.values == new.values
        assert original.next == new.next
        assert original.metadata["step"] == new.metadata["step"]
@@ -2098,7 +2094,7 @@ 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, 2) == _get_tasks(history, 0)
+    assert _get_tasks(new_history, 1) == _get_tasks(history, 0)


 async def test_cond_edge_after_send() -> None:
@@ -7545,6 +7541,7 @@ 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",
@@ -7554,67 +7551,6 @@ 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_configurable() -> None:
-    """server_info is built from assistant_id/graph_id in config configurable."""
+def test_server_info_from_metadata() -> None:
+    """server_info is built from assistant_id/graph_id in config metadata."""
    captured: dict[str, Any] = {}
    compiled = _make_capture_graph(captured)
    compiled.invoke(
        {"message": "hi"},
-        config={"configurable": {"assistant_id": "asst-abc", "graph_id": "my-graph"}},
+        config={"metadata": {"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_configurable() -> None:
    assert si.user is None


-def test_server_info_none_without_configurable() -> None:
-    """server_info is None when no assistant_id/graph_id in configurable."""
+def test_server_info_none_without_metadata() -> None:
+    """server_info is None when no assistant_id/graph_id in metadata."""
    captured: dict[str, Any] = {}
    compiled = _make_capture_graph(captured)
    compiled.invoke({"message": "hi"})
@@ -579,11 +579,8 @@ def test_server_info_user_from_auth_user() -> None:
    compiled.invoke(
        {"message": "hi"},
        config={
-            "configurable": {
-                "langgraph_auth_user": proxy,
-                "assistant_id": "asst-proxy",
-                "graph_id": "graph-proxy",
-            },
+            "configurable": {"langgraph_auth_user": proxy},
+            "metadata": {"assistant_id": "asst-proxy", "graph_id": "graph-proxy"},
        },
    )
    si = captured["server_info"]
@@ -0,0 +1,245 @@
+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)
@@ -0,0 +1,86 @@
+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_timestamp_populated():
+    evt = convert_to_protocol_event((), "values", {})
+    assert evt is not None
+    assert isinstance(evt["params"]["timestamp"], int)
+    assert evt["params"]["timestamp"] > 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",
+    }
@@ -0,0 +1,133 @@
+import asyncio
+
+import pytest
+
+from langgraph.stream._event_log import EventLog
+
+
+@pytest.mark.anyio
+async def test_push_and_iterate_in_order():
+    log = EventLog()
+    log.append("a")
+    log.append("b")
+    log.append("c")
+    log.close()
+    items = [item async for item in aiter(log)]
+    assert items == ["a", "b", "c"]
+
+
+@pytest.mark.anyio
+async def test_multiple_independent_cursors():
+    log = EventLog()
+    log.append("x")
+    log.append("y")
+    log.close()
+    items1 = [item async for item in aiter(log)]
+    items2 = [item async for item in aiter(log)]
+    assert items1 == ["x", "y"]
+    assert items2 == ["x", "y"]
+
+
+@pytest.mark.anyio
+async def test_close_ends_iteration():
+    log = EventLog()
+    log.close()
+    items = [item async for item in aiter(log)]
+    assert items == []
+
+
+@pytest.mark.anyio
+async def test_fail_raises_error():
+    log = EventLog()
+    log.fail(RuntimeError("boom"))
+    with pytest.raises(RuntimeError, match="boom"):
+        async for _ in aiter(log):
+            pass
+
+
+@pytest.mark.anyio
+async def test_concurrent_push_and_iterate():
+    log = EventLog()
+    received = []
+
+    async def consumer():
+        async for item in aiter(log):
+            received.append(item)
+
+    async def producer():
+        for i in range(5):
+            log.append(i)
+            await asyncio.sleep(0.01)
+        log.close()
+
+    await asyncio.gather(producer(), consumer())
+    assert received == [0, 1, 2, 3, 4]
+
+
+@pytest.mark.anyio
+async def test_items_before_cursor_visible():
+    log = EventLog()
+    log.append("a")
+    log.append("b")
+    cursor = aiter(log)
+    log.append("c")
+    log.close()
+    items = [item async for item in cursor]
+    assert items == ["a", "b", "c"]
+
+
+@pytest.mark.anyio
+async def test_empty_log_closed_yields_nothing():
+    log = EventLog()
+    log.close()
+    items = [item async for item in aiter(log)]
+    assert items == []
+
+
+@pytest.mark.anyio
+async def test_fail_mid_iteration():
+    """A cursor that has consumed some items should raise when fail() is called."""
+    log = EventLog()
+    received = []
+
+    async def consumer():
+        async for item in aiter(log):
+            received.append(item)
+
+    async def producer():
+        log.append("a")
+        log.append("b")
+        await asyncio.sleep(0.02)
+        log.fail(RuntimeError("mid-stream error"))
+
+    with pytest.raises(RuntimeError, match="mid-stream error"):
+        await asyncio.gather(producer(), consumer())
+    assert received == ["a", "b"]
+
+
+@pytest.mark.anyio
+async def test_abandoned_cursor_cleans_up_waiters():
+    """Abandoned async cursors should not leave stale futures in the
+    EventLog waiter list.
+
+    When a cursor's __anext__ is cancelled (e.g. consumer breaks out of
+    ``async for``), the Future it registered in ``_waiters`` should be
+    cleaned up.  Otherwise the list grows without bound until the next
+    append/close/fail triggers ``_wake_all()``.
+    """
+    log: EventLog[str] = EventLog()
+
+    for _ in range(10):
+        cursor = aiter(log)
+        task = asyncio.ensure_future(cursor.__anext__())
+        await asyncio.sleep(0)  # let task register its waiter
+        task.cancel()
+        try:
+            await task
+        except asyncio.CancelledError:
+            pass
+
+    assert len(log._waiters) == 0, (
+        f"Expected 0 waiters after abandoning 10 cursors, "
+        f"got {len(log._waiters)}.  Abandoned cursors leak futures."
+    )
@@ -1,401 +0,0 @@
-"""Tests for LifecycleTransformer.
-
-Consumes the `tasks` stream mode and emits subgraph lifecycle payloads
-on the `lifecycle` channel for both in-process iteration via
-`run.lifecycle` and wire delivery via `custom:lifecycle` protocol
-events. Most tests dispatch synthetic protocol events through a
-`StreamMux` to keep the inference logic isolated; the end-of-file
-group exercises the path through real graphs (multi-depth
-discovery, nested `stream_v2` calls with non-empty `parent_ns`).
-"""
-
-from __future__ import annotations
-
-import operator
-import time
-from typing import Annotated, Any
-
-from typing_extensions import TypedDict
-
-from langgraph._internal._constants import CONF, CONFIG_KEY_CHECKPOINT_NS
-from langgraph.constants import END, START
-from langgraph.errors import GraphInterrupt
-from langgraph.graph import StateGraph
-from langgraph.stream._mux import StreamMux
-from langgraph.stream.transformers import (
-    LifecyclePayload,
-    LifecycleTransformer,
-)
-
-TS = int(time.time() * 1000)
-
-
-def _tasks_start(
-    namespace: list[str],
-    *,
-    task_id: str,
-    name: str,
-) -> dict[str, Any]:
-    """Build a `tasks` ProtocolEvent carrying a TaskPayload (start)."""
-    return {
-        "type": "event",
-        "method": "tasks",
-        "params": {
-            "namespace": namespace,
-            "timestamp": TS,
-            "data": {
-                "id": task_id,
-                "name": name,
-                "input": None,
-                "triggers": [],
-            },
-        },
-    }
-
-
-def _tasks_result(
-    namespace: list[str],
-    *,
-    task_id: str,
-    name: str,
-    error: str | None = None,
-    interrupts: list[dict[str, Any]] | None = None,
-) -> dict[str, Any]:
-    """Build a `tasks` ProtocolEvent carrying a TaskResultPayload (finish)."""
-    return {
-        "type": "event",
-        "method": "tasks",
-        "params": {
-            "namespace": namespace,
-            "timestamp": TS,
-            "data": {
-                "id": task_id,
-                "name": name,
-                "error": error,
-                "interrupts": interrupts or [],
-                "result": {},
-            },
-        },
-    }
-
-
-def _arm(mux: StreamMux) -> None:
-    """Force projection channels to accept pushes (skip lazy-subscribe gate).
-
-    `StreamChannel.push` only appends to the local buffer when a
-    subscriber is attached. Tests that inspect `_items` directly need
-    the gate flipped before any event is dispatched.
-    """
-    mux._events._subscribed = True
-    for transformer in mux._transformers:
-        if isinstance(transformer, LifecycleTransformer):
-            transformer._channel._subscribed = True
-
-
-def _drain_lifecycle(mux: StreamMux) -> list[LifecyclePayload]:
-    """Snapshot the lifecycle channel's buffer."""
-    transformer = mux.transformer_by_key("lifecycle")
-    assert isinstance(transformer, LifecycleTransformer)
-    return list(transformer._channel._items)
-
-
-def _build_lifecycle_mux(*, scope: tuple[str, ...] = ()) -> StreamMux:
-    mux = StreamMux([LifecycleTransformer(scope=scope)], is_async=False)
-    _arm(mux)
-    return mux
-
-
-# ---------------------------------------------------------------------------
-# LifecycleTransformer
-# ---------------------------------------------------------------------------
-
-
-def test_started_emitted_on_first_direct_child_task() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc123"], task_id="t1", name="tool"))
-
-    [payload] = _drain_lifecycle(mux)
-    assert payload["event"] == "started"
-    assert payload["namespace"] == ["agent:abc123"]
-    assert payload["graph_name"] == "agent"
-    assert payload["trigger_call_id"] == "abc123"
-
-
-def test_started_dedup_on_repeat_namespace() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="a"))
-    mux.push(_tasks_start(["agent:abc"], task_id="t2", name="b"))
-
-    payloads = _drain_lifecycle(mux)
-    assert [p["event"] for p in payloads] == ["started"]
-
-
-def test_grandchild_namespace_discovered() -> None:
-    """Subgraphs at any depth below scope are tracked, not just direct children."""
-    mux = _build_lifecycle_mux()
-    # First-seen task at length-2 ns means a 2nd-level subgraph started.
-    mux.push(_tasks_start(["agent:abc", "tool:def"], task_id="t1", name="x"))
-
-    [payload] = _drain_lifecycle(mux)
-    assert payload["event"] == "started"
-    assert payload["namespace"] == ["agent:abc", "tool:def"]
-
-
-def test_nested_chain_emits_started_at_each_depth() -> None:
-    """A graph → subgraph → subgraph chain produces a started event per level."""
-    mux = _build_lifecycle_mux()
-    # Subgraph1 starts emitting tasks (events tagged with its own ns).
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    # Subgraph1 invokes subgraph2; subgraph2's first task event arrives.
-    mux.push(_tasks_start(["agent:abc", "tool:def"], task_id="t2", name="deep"))
-
-    payloads = _drain_lifecycle(mux)
-    assert [p["namespace"] for p in payloads] == [
-        ["agent:abc"],
-        ["agent:abc", "tool:def"],
-    ]
-    assert all(p["event"] == "started" for p in payloads)
-
-
-def test_nested_chain_emits_completed_at_each_depth() -> None:
-    """Each subgraph in a nested chain closes when its parent task result arrives."""
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_start(["agent:abc", "tool:def"], task_id="t2", name="deep"))
-
-    # Subgraph2's owning task (id=def, inside subgraph1) finishes.
-    mux.push(_tasks_result(["agent:abc"], task_id="def", name="tool"))
-    # Subgraph1's owning task (id=abc, at root) finishes.
-    mux.push(_tasks_result([], task_id="abc", name="agent"))
-
-    payloads = _drain_lifecycle(mux)
-    events = [(p["event"], p["namespace"]) for p in payloads]
-    assert events == [
-        ("started", ["agent:abc"]),
-        ("started", ["agent:abc", "tool:def"]),
-        ("completed", ["agent:abc", "tool:def"]),
-        ("completed", ["agent:abc"]),
-    ]
-
-
-def test_completed_on_parent_task_result() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent"))
-
-    events = [p["event"] for p in _drain_lifecycle(mux)]
-    assert events == ["started", "completed"]
-
-
-def test_failed_on_parent_task_result_with_error() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent", error="boom"))
-
-    payloads = _drain_lifecycle(mux)
-    assert [p["event"] for p in payloads] == ["started", "failed"]
-    assert payloads[1]["error"] == "boom"
-
-
-def test_interrupted_on_parent_task_result_with_interrupts() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(
-        _tasks_result(
-            [],
-            task_id="abc",
-            name="agent",
-            interrupts=[{"value": "pause"}],
-        )
-    )
-
-    payloads = _drain_lifecycle(mux)
-    assert [p["event"] for p in payloads] == ["started", "interrupted"]
-
-
-def test_interrupt_takes_precedence_over_error() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(
-        _tasks_result(
-            [],
-            task_id="abc",
-            name="agent",
-            error="should-be-suppressed",
-            interrupts=[{"value": "pause"}],
-        )
-    )
-
-    last = _drain_lifecycle(mux)[-1]
-    assert last["event"] == "interrupted"
-    assert "error" not in last
-
-
-def test_finalize_completes_open_subgraphs() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    mux.close()
-    payloads = _drain_lifecycle(mux)
-    assert [p["event"] for p in payloads] == ["started", "completed"]
-
-
-def test_fail_emits_interrupted_for_graph_interrupt() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    mux.fail(GraphInterrupt())
-    payloads = _drain_lifecycle(mux)
-    assert [p["event"] for p in payloads] == ["started", "interrupted"]
-    assert "error" not in payloads[1]
-
-
-def test_fail_emits_failed_for_other_exceptions() -> None:
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    mux.fail(RuntimeError("boom"))
-    payloads = _drain_lifecycle(mux)
-    assert [p["event"] for p in payloads] == ["started", "failed"]
-    assert payloads[1]["error"] == "boom"
-
-
-def test_unrelated_methods_pass_through() -> None:
-    """Non-`tasks` events are not consumed and don't emit lifecycle."""
-    mux = _build_lifecycle_mux()
-    mux.push(
-        {
-            "type": "event",
-            "method": "values",
-            "params": {"namespace": ["agent:abc"], "timestamp": TS, "data": {}},
-        }
-    )
-    assert _drain_lifecycle(mux) == []
-
-
-def test_scoped_transformer_filters_outside_scope_but_tracks_all_depths() -> None:
-    """Scope filters the prefix; subgraphs at any depth below scope are tracked."""
-    mux = _build_lifecycle_mux(scope=("agent:abc",))
-    # Root-level task — out of scope (no shared prefix).
-    mux.push(_tasks_start(["other:1"], task_id="t1", name="other"))
-    # Direct child of agent:abc — in scope.
-    mux.push(_tasks_start(["agent:abc", "tool:def"], task_id="t2", name="tool"))
-    # Grandchild of agent:abc — also in scope, tracked at its own depth.
-    mux.push(
-        _tasks_start(["agent:abc", "tool:def", "deep:ghi"], task_id="t3", name="deep")
-    )
-
-    payloads = _drain_lifecycle(mux)
-    assert [p["namespace"] for p in payloads] == [
-        ["agent:abc", "tool:def"],
-        ["agent:abc", "tool:def", "deep:ghi"],
-    ]
-
-
-def test_required_stream_modes_declared() -> None:
-    assert LifecycleTransformer.required_stream_modes == ("tasks",)
-
-
-def test_protocol_event_method_is_native() -> None:
-    """Native transformer — auto-forwarded events use `lifecycle`, not `custom:lifecycle`."""
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    methods = {evt["method"] for evt in mux._events._items}
-    assert "lifecycle" in methods
-    assert "custom:lifecycle" not in methods
-
-
-def test_tasks_events_suppressed_from_main_log() -> None:
-    """Tasks events are folded into lifecycle and don't appear on the main log."""
-    mux = _build_lifecycle_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent"))
-
-    methods = [evt["method"] for evt in mux._events._items]
-    assert "tasks" not in methods
-    # Lifecycle events did make it through, though.
-    assert "lifecycle" in methods
-
-
-# ---------------------------------------------------------------------------
-# End-to-end: real graphs through stream_v2
-# ---------------------------------------------------------------------------
-
-
-class _State(TypedDict):
-    value: str
-    items: Annotated[list[str], operator.add]
-
-
-def _passthrough(state: _State) -> dict[str, Any]:
-    return {"value": state["value"] + "!", "items": ["x"]}
-
-
-def _make_two_level_nested() -> Any:
-    """Build outer → middle → inner. Three Pregel instances, two nesting levels."""
-    inner_b: StateGraph = StateGraph(_State, input_schema=_State)
-    inner_b.add_node("inner_node", _passthrough)
-    inner_b.add_edge(START, "inner_node")
-    inner_b.add_edge("inner_node", END)
-    inner = inner_b.compile()
-
-    middle_b: StateGraph = StateGraph(_State, input_schema=_State)
-    middle_b.add_node("inner", inner)
-    middle_b.add_edge(START, "inner")
-    middle_b.add_edge("inner", END)
-    middle = middle_b.compile()
-
-    outer_b: StateGraph = StateGraph(_State, input_schema=_State)
-    outer_b.add_node("middle", middle)
-    outer_b.add_edge(START, "middle")
-    outer_b.add_edge("middle", END)
-    return outer_b.compile()
-
-
-def test_stream_v2_real_graph_emits_lifecycle_at_each_depth() -> None:
-    """Outer graph with two nested subgraphs surfaces lifecycle for both."""
-    graph = _make_two_level_nested()
-    run = graph.stream_v2({"value": "x", "items": []})
-
-    # Iterating the projection drives the pump and drains synthesized
-    # lifecycle events at the same time.
-    payloads = list(run.lifecycle)
-    # Each subgraph instance produces a started + a terminal event. Two
-    # nested instances, so four payloads total in some interleaving.
-    by_event = {p["event"] for p in payloads}
-    assert "started" in by_event
-    assert "completed" in by_event
-    # Two distinct namespaces — direct child of root, and grandchild.
-    namespaces = {tuple(p["namespace"]) for p in payloads}
-    direct_children = {ns for ns in namespaces if len(ns) == 1}
-    grandchildren = {ns for ns in namespaces if len(ns) == 2}
-    assert direct_children, f"expected a level-1 lifecycle namespace, got {namespaces}"
-    assert grandchildren, f"expected a level-2 lifecycle namespace, got {namespaces}"
-    # Every direct-child namespace has a matching grandchild whose path extends it.
-    for parent in direct_children:
-        assert any(gc[: len(parent)] == parent for gc in grandchildren), (
-            f"grandchild does not extend parent {parent}: {grandchildren}"
-        )
-
-
-def test_stream_v2_with_nested_parent_ns_scopes_lifecycle() -> None:
-    """When `stream_v2` is called with a non-empty checkpoint_ns in config,
-    `_resolve_parent_ns` returns that namespace and the registered
-    `LifecycleTransformer` is constructed with `scope=parent_ns`. This
-    exercises the path that exists today purely for nested-stream_v2
-    callers; the test simulates such a caller by injecting a
-    checkpoint_ns into the config.
-    """
-    graph = _make_two_level_nested()
-    config = {CONF: {CONFIG_KEY_CHECKPOINT_NS: "outer:abc"}}
-    run = graph.stream_v2({"value": "x", "items": []}, config=config)
-
-    payloads = list(run.lifecycle)
-    # Every emitted lifecycle namespace must extend the caller's scope —
-    # nothing at root-level, nothing under a sibling prefix.
-    for p in payloads:
-        ns = tuple(p["namespace"])
-        assert ns[:1] == ("outer:abc",), (
-            f"namespace {ns} not within scoped prefix ('outer:abc',)"
-        )
@@ -1,876 +0,0 @@
-"""Tests for MessagesTransformer: protocol event routing, whole-message fallback,
-legacy v1 chunk filtering, and end-to-end via stream_v2 / astream_v2."""
-
-from __future__ import annotations
-
-import time
-from typing import Any
-
-import pytest
-from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.language_models.chat_model_stream import (
-    AsyncChatModelStream,
-    ChatModelStream,
-)
-from langchain_core.messages import AIMessage, AIMessageChunk
-from langchain_core.runnables import RunnableConfig
-from typing_extensions import TypedDict
-
-from langgraph.constants import END, START
-from langgraph.graph import MessagesState, StateGraph
-from langgraph.stream._mux import StreamMux
-from langgraph.stream.run_stream import GraphRunStream
-from langgraph.stream.stream_channel import StreamChannel
-from langgraph.stream.transformers import MessagesTransformer, ValuesTransformer
-
-TS = int(time.time() * 1000)
-
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-
-def _proto_event(
-    event: dict[str, Any],
-    *,
-    run_id: str = "run-1",
-    node: str = "llm",
-) -> dict[str, Any]:
-    """Build a messages ProtocolEvent carrying a protocol event dict (v2 path)."""
-    return {
-        "type": "event",
-        "method": "messages",
-        "params": {
-            "namespace": [],
-            "timestamp": TS,
-            "data": (event, {"langgraph_node": node, "run_id": run_id}),
-        },
-    }
-
-
-def _v1_chunk(
-    text: str,
-    msg_id: str = "msg-1",
-    *,
-    finish: bool = False,
-    node: str = "llm",
-) -> dict[str, Any]:
-    """Build a messages ProtocolEvent carrying a v1 AIMessageChunk tuple."""
-    rm: dict[str, Any] = {"finish_reason": "stop"} if finish else {}
-    return {
-        "type": "event",
-        "method": "messages",
-        "params": {
-            "namespace": [],
-            "timestamp": TS,
-            "data": (
-                AIMessageChunk(content=text, id=msg_id, response_metadata=rm),
-                {"langgraph_node": node},
-            ),
-        },
-    }
-
-
-def _whole_msg(
-    text: str,
-    msg_id: str = "msg-10",
-    *,
-    node: str = "node",
-) -> dict[str, Any]:
-    """Build a messages ProtocolEvent carrying a completed AIMessage."""
-    return {
-        "type": "event",
-        "method": "messages",
-        "params": {
-            "namespace": [],
-            "timestamp": TS,
-            "data": (AIMessage(content=text, id=msg_id), {"langgraph_node": node}),
-        },
-    }
-
-
-def _make_sync_transformer() -> tuple[
-    MessagesTransformer, StreamChannel[ChatModelStream]
-]:
-    t = MessagesTransformer()
-    log: StreamChannel[ChatModelStream] = t.init()["messages"]
-    log._bind(is_async=False)
-    # Subscribe up front so pushes during process() are retained.
-    log._subscribed = True
-    t._bind_pump(lambda: False)
-    return t, log
-
-
-def _make_async_transformer() -> tuple[
-    MessagesTransformer, StreamChannel[ChatModelStream]
-]:
-    t = MessagesTransformer()
-    log: StreamChannel[ChatModelStream] = t.init()["messages"]
-    log._bind(is_async=True)
-    log._subscribed = True
-    return t, log
-
-
-def _lifecycle(
-    *, text: str = "hello world", message_id: str = "run-1"
-) -> list[dict[str, Any]]:
-    """Produce a valid protocol event lifecycle: start, delta, finish."""
-    half = len(text) // 2
-    first, second = text[:half], text[half:]
-    return [
-        {"event": "message-start", "role": "ai", "message_id": message_id},
-        {
-            "event": "content-block-start",
-            "index": 0,
-            "content_block": {"type": "text", "text": ""},
-        },
-        {
-            "event": "content-block-delta",
-            "index": 0,
-            "content_block": {"type": "text", "text": first},
-        },
-        {
-            "event": "content-block-delta",
-            "index": 0,
-            "content_block": {"type": "text", "text": second},
-        },
-        {
-            "event": "content-block-finish",
-            "index": 0,
-            "content_block": {"type": "text", "text": text},
-        },
-        {"event": "message-finish", "reason": "stop"},
-    ]
-
-
-def _simple_graph():
-    def call_model(state: MessagesState) -> dict[str, Any]:
-        model = GenericFakeChatModel(messages=iter(["hello world"]))
-        stream = model.stream_v2(state["messages"])
-        return {"messages": stream.output}
-
-    return (
-        StateGraph(MessagesState)
-        .add_node("call_model", call_model)
-        .add_edge(START, "call_model")
-        .add_edge("call_model", END)
-        .compile()
-    )
-
-
-# ---------------------------------------------------------------------------
-# Protocol event routing
-# ---------------------------------------------------------------------------
-
-
-class TestProtocolEventRouting:
-    def test_message_start_creates_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "role": "ai", "message_id": "run-1"},
-                run_id="run-1",
-            )
-        )
-        log.close()
-        (stream,) = list(log._items)
-        assert isinstance(stream, ChatModelStream)
-        assert stream.message_id == "run-1"
-
-    def test_full_lifecycle_yields_done_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        for evt in _lifecycle(text="hello world"):
-            t.process(_proto_event(evt, run_id="run-1"))
-        log.close()
-        (stream,) = list(log._items)
-        assert stream.done
-        assert stream.output.text == "hello world"
-
-    def test_message_finish_cleans_up_routing(self) -> None:
-        t, log = _make_sync_transformer()
-        for evt in _lifecycle():
-            t.process(_proto_event(evt, run_id="run-1"))
-        assert t._by_run == {}
-
-    def test_events_without_prior_start_are_ignored(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {
-                    "event": "content-block-delta",
-                    "index": 0,
-                    "content_block": {"type": "text", "text": "orphan"},
-                },
-                run_id="unknown",
-            )
-        )
-        log.close()
-        assert list(log._items) == []
-
-    def test_concurrent_streams_routed_by_run_id(self) -> None:
-        t, log = _make_sync_transformer()
-        life_a = _lifecycle(text="aaaa", message_id="run-a")
-        life_b = _lifecycle(text="bbbb", message_id="run-b")
-        for a, b in zip(life_a, life_b):
-            t.process(_proto_event(a, run_id="run-a"))
-            t.process(_proto_event(b, run_id="run-b"))
-        log.close()
-        streams = list(log._items)
-        assert len(streams) == 2
-        by_id = {s.message_id: s for s in streams}
-        assert by_id["run-a"].output.text == "aaaa"
-        assert by_id["run-b"].output.text == "bbbb"
-
-    def test_text_deltas_accumulated_on_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        for evt in _lifecycle(text="abcdef"):
-            t.process(_proto_event(evt))
-        log.close()
-        (stream,) = list(log._items)
-        assert "".join(stream._text_proj._deltas) == "abcdef"
-
-    def test_stream_pushed_on_message_start_not_finish(self) -> None:
-        # Consumer can see the stream before message-finish arrives.
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "role": "ai", "message_id": "run-1"},
-                run_id="run-1",
-            )
-        )
-        assert len(log._items) == 1
-
-    def test_node_metadata_set_on_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "role": "ai", "message_id": "run-1"},
-                run_id="run-1",
-                node="my_llm",
-            )
-        )
-        (stream,) = list(log._items)
-        assert stream.node == "my_llm"
-
-
-# ---------------------------------------------------------------------------
-# Whole-message fallback
-# ---------------------------------------------------------------------------
-
-
-class TestWholeMessageFallback:
-    def test_whole_ai_message_produces_complete_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(_whole_msg("the full answer"))
-        log.close()
-        (stream,) = list(log._items)
-        assert stream.done
-        assert stream.output.text == "the full answer"
-
-    def test_whole_message_has_full_lifecycle(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(_whole_msg("full"))
-        log.close()
-        (stream,) = list(log._items)
-        assert [e["event"] for e in stream._events] == [
-            "message-start",
-            "content-block-start",
-            "content-block-delta",
-            "content-block-finish",
-            "message-finish",
-        ]
-
-
-# ---------------------------------------------------------------------------
-# Filtering
-# ---------------------------------------------------------------------------
-
-
-class TestFiltering:
-    def test_non_messages_events_pass_through(self) -> None:
-        t, _ = _make_sync_transformer()
-        assert (
-            t.process(
-                {
-                    "type": "event",
-                    "method": "values",
-                    "params": {"namespace": [], "timestamp": TS, "data": {"x": 1}},
-                }
-            )
-            is True
-        )
-
-    def test_subgraph_namespace_dropped(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            {
-                "type": "event",
-                "method": "messages",
-                "params": {
-                    "namespace": ["subgraph"],
-                    "timestamp": TS,
-                    "data": (
-                        {"event": "message-start", "message_id": "run-x"},
-                        {"run_id": "run-x"},
-                    ),
-                },
-            }
-        )
-        log.close()
-        assert list(log._items) == []
-
-    def test_legacy_v1_chunks_ignored(self) -> None:
-        # v1 AIMessageChunk tuples (from on_llm_new_token) are not streamed
-        # into this projection; callers must migrate to stream_v2.
-        t, log = _make_sync_transformer()
-        t.process(_v1_chunk("hello"))
-        t.process(_v1_chunk(" world", finish=True))
-        log.close()
-        assert list(log._items) == []
-
-
-# ---------------------------------------------------------------------------
-# Lifecycle: fail / finalize
-# ---------------------------------------------------------------------------
-
-
-class TestLifecycle:
-    def test_fail_propagates_to_open_streams(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "message_id": "run-1"}, run_id="run-1"
-            )
-        )
-        streams = list(log._items)
-        err = RuntimeError("graph died")
-        t.fail(err)
-        assert t._by_run == {}
-        assert streams[0]._error is err
-
-    def test_finalize_clears_routing_state(self) -> None:
-        t, _ = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "message_id": "run-1"}, run_id="run-1"
-            )
-        )
-        assert "run-1" in t._by_run
-        t.finalize()
-        assert t._by_run == {}
-
-
-# ---------------------------------------------------------------------------
-# Async mode
-# ---------------------------------------------------------------------------
-
-
-class TestAsyncMode:
-    def test_async_mode_creates_async_stream(self) -> None:
-        t, log = _make_async_transformer()
-        for evt in _lifecycle(text="async stream"):
-            t.process(_proto_event(evt))
-        assert isinstance(list(log._items)[0], AsyncChatModelStream)
-
-    @pytest.mark.anyio
-    async def test_text_projection_yields_deltas(self) -> None:
-        t, log = _make_async_transformer()
-        for evt in _lifecycle(text="hello world"):
-            t.process(_proto_event(evt))
-        (stream,) = list(log._items)
-        assert isinstance(stream, AsyncChatModelStream)
-        assert "".join([d async for d in stream.text]) == "hello world"
-
-    @pytest.mark.anyio
-    async def test_output_awaitable(self) -> None:
-        t, log = _make_async_transformer()
-        for evt in _lifecycle(text="async"):
-            t.process(_proto_event(evt))
-        (stream,) = list(log._items)
-        assert (await stream.output).text == "async"
-
-
-# ---------------------------------------------------------------------------
-# GraphRunStream integration
-# ---------------------------------------------------------------------------
-
-
-class TestWireRequestMore:
-    def test_bind_pump_called_on_wire(self) -> None:
-        values_t = ValuesTransformer()
-        messages_t = MessagesTransformer()
-        mux = StreamMux([values_t, messages_t], is_async=False)
-
-        assert messages_t._pump_fn is None
-        run = GraphRunStream(iter([]), mux, values_t)
-        assert messages_t._pump_fn is not None
-        assert messages_t._pump_fn() is False
-        assert run._exhausted
-
-    def test_created_streams_have_request_more(self) -> None:
-        values_t = ValuesTransformer()
-        messages_t = MessagesTransformer()
-        mux = StreamMux([values_t, messages_t], is_async=False)
-        GraphRunStream(iter([]), mux, values_t)
-
-        log: StreamChannel[ChatModelStream] = mux.extensions["messages"]
-        log._subscribed = True
-        for evt in _lifecycle():
-            messages_t.process(_proto_event(evt))
-
-        (stream,) = list(log._items)
-        assert stream._request_more is messages_t._pump_fn
-
-
-# ---------------------------------------------------------------------------
-# End-to-end via StreamMux
-# ---------------------------------------------------------------------------
-
-
-class TestViaMux:
-    def _make_mux(
-        self,
-    ) -> tuple[MessagesTransformer, StreamMux, StreamChannel[ChatModelStream]]:
-        t = MessagesTransformer()
-        v = ValuesTransformer()
-        mux = StreamMux([v, t], is_async=False)
-        t._bind_pump(lambda: False)
-        log: StreamChannel[ChatModelStream] = mux.extensions["messages"]
-        log._subscribed = True
-        return t, mux, log
-
-    def test_streaming_via_mux(self) -> None:
-        t, mux, log = self._make_mux()
-        for evt in _lifecycle(text="mux stream"):
-            mux.push(_proto_event(evt))
-        mux.close()
-        (stream,) = list(log._items)
-        assert stream.output.text == "mux stream"
-
-    def test_whole_message_via_mux(self) -> None:
-        t, mux, log = self._make_mux()
-        mux.push(_whole_msg("result"))
-        mux.close()
-        (stream,) = list(log._items)
-        assert stream.output.text == "result"
-
-    @pytest.mark.anyio
-    async def test_async_streaming_via_mux(self) -> None:
-        t = MessagesTransformer()
-        v = ValuesTransformer()
-        mux = StreamMux([v, t], is_async=True)
-        log: StreamChannel[ChatModelStream] = mux.extensions["messages"]
-        log._subscribed = True
-
-        for evt in _lifecycle(text="async mux"):
-            await mux.apush(_proto_event(evt))
-
-        (stream,) = list(log._items)
-        assert (await stream.output).text == "async mux"
-        await mux.aclose()
-
-
-# ---------------------------------------------------------------------------
-# End-to-end: graph → stream_v2 → run.messages (node calls stream_v2)
-# ---------------------------------------------------------------------------
-
-
-class TestEndToEnd:
-    """stream_v2 path: node calls model.stream_v2() explicitly."""
-
-    def test_node_calling_stream_v2_populates_messages(self) -> None:
-        model = GenericFakeChatModel(messages=iter(["hello world"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = model.stream_v2(state["messages"])
-            return {"messages": stream.output}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        (stream,) = list(run.messages)
-        assert isinstance(stream, ChatModelStream)
-        assert stream.output.text == "hello world"
-
-    def test_node_stream_v2_text_deltas_iterate(self) -> None:
-        """Consumer can iterate `.text` on the streamed message in real time."""
-        model = GenericFakeChatModel(messages=iter(["streamed answer"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = model.stream_v2(state["messages"])
-            return {"messages": stream.output}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "go"})
-        (stream,) = list(run.messages)
-        assert "".join(stream.text) == "streamed answer"
-
-    def test_non_llm_message_returned_from_node(self) -> None:
-        """Whole-message fallback: node returns a finalized AIMessage directly."""
-
-        def return_message(state: MessagesState) -> dict[str, Any]:
-            return {"messages": AIMessage(content="hardcoded", id="msg-abc")}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("return_message", return_message)
-            .add_edge(START, "return_message")
-            .add_edge("return_message", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        (stream,) = list(run.messages)
-        assert stream.output.text == "hardcoded"
-
-    @pytest.mark.anyio
-    async def test_async_node_calling_astream_v2(self) -> None:
-        model = GenericFakeChatModel(messages=iter(["async answer"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = await model.astream_v2(state["messages"])
-            return {"messages": await stream}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-        streams = [s async for s in run.messages]
-        assert len(streams) == 1
-        assert isinstance(streams[0], AsyncChatModelStream)
-        assert (await streams[0].output).text == "async answer"
-
-    @pytest.mark.anyio
-    async def test_nested_async_iteration_yields_text_deltas(self) -> None:
-        """Inner stream.text drives the shared graph pump via the async pump binding."""
-        import asyncio
-
-        model = GenericFakeChatModel(messages=iter(["hello world"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = await model.astream_v2(state["messages"])
-            return {"messages": await stream}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-
-        async def consume() -> list[str]:
-            collected: list[str] = []
-            async for stream in run.messages:
-                async for delta in stream.text:
-                    collected.append(delta)
-            return collected
-
-        assert "".join(await asyncio.wait_for(consume(), timeout=2.0)) == "hello world"
-
-
-# ---------------------------------------------------------------------------
-# End-to-end: graph → stream_v2 → run.messages (node calls invoke)
-# ---------------------------------------------------------------------------
-
-
-class TestEndToEndV2Invoke:
-    """Auto-routing path: stream_v2 injects CONFIG_KEY_STREAM_MESSAGES_V2,
-    causing BaseChatModel to drive the v2 protocol event generator even for
-    model.invoke()."""
-
-    def _graph(self, model):
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        return (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-    def test_invoke_populates_messages(self) -> None:
-        run = self._graph(
-            GenericFakeChatModel(messages=iter(["hello world"]))
-        ).stream_v2({"messages": "hi"})
-        (stream,) = list(run.messages)
-        assert isinstance(stream, ChatModelStream)
-        assert stream.output.text == "hello world"
-
-    def test_invoke_emits_protocol_events(self) -> None:
-        """Iterating the stream yields the full v2 lifecycle, not v1 chunks."""
-        run = self._graph(
-            GenericFakeChatModel(messages=iter(["streamed answer"]))
-        ).stream_v2({"messages": "go"})
-        (stream,) = list(run.messages)
-
-        events = list(stream)
-        event_types = [e.get("event") for e in events]
-        assert "message-start" in event_types
-        assert "content-block-start" in event_types
-        assert "content-block-delta" in event_types
-        assert "content-block-finish" in event_types
-        assert "message-finish" in event_types
-        # Sanity: every event is a dict carrying an "event" key — not an
-        # AIMessageChunk tuple from the v1 path.
-        for event in events:
-            assert isinstance(event, dict)
-            assert "event" in event
-        # Typed projection still assembles the final text.
-        assert stream.output.text == "streamed answer"
-
-    def test_invoke_text_deltas_iterate(self) -> None:
-        run = self._graph(
-            GenericFakeChatModel(messages=iter(["delta streaming works"]))
-        ).stream_v2({"messages": "hi"})
-        (stream,) = list(run.messages)
-        assert "".join(stream.text) == "delta streaming works"
-
-    def test_invoke_two_nodes_two_streams(self) -> None:
-        model_a = GenericFakeChatModel(messages=iter(["alpha"]))
-        model_b = GenericFakeChatModel(messages=iter(["beta"]))
-
-        def node_a(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model_a.invoke(state["messages"])}
-
-        def node_b(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model_b.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("node_a", node_a)
-            .add_node("node_b", node_b)
-            .add_edge(START, "node_a")
-            .add_edge("node_a", "node_b")
-            .add_edge("node_b", END)
-            .compile()
-        )
-
-        streams = list(graph.stream_v2({"messages": "hi"}).messages)
-        assert len(streams) == 2
-        assert {s.output.text for s in streams} == {"alpha", "beta"}
-
-    def test_invoke_plus_constructed_message_two_streams(self) -> None:
-        """Live-streamed node + constructed-message node → two ChatModelStreams."""
-        model = GenericFakeChatModel(messages=iter(["live stream"]))
-
-        def streaming_node(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        def constructed_node(state: MessagesState) -> dict[str, Any]:
-            return {"messages": [AIMessage(content="hardcoded", id="constructed-1")]}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("streaming_node", streaming_node)
-            .add_node("constructed_node", constructed_node)
-            .add_edge(START, "streaming_node")
-            .add_edge("streaming_node", "constructed_node")
-            .add_edge("constructed_node", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-        assert len(streams) == 2
-        assert streams[0].node == "streaming_node"
-        assert streams[0].output.text == "live stream"
-        assert streams[1].node == "constructed_node"
-        assert streams[1].output.text == "hardcoded"
-        assert streams[1].message_id == "constructed-1"
-
-    @pytest.mark.anyio
-    async def test_ainvoke_populates_messages(self) -> None:
-        model = GenericFakeChatModel(messages=iter(["async invoke"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": await model.ainvoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-        streams = [s async for s in run.messages]
-        assert len(streams) == 1
-        assert isinstance(streams[0], AsyncChatModelStream)
-        assert (await streams[0].output).text == "async invoke"
-
-
-# ---------------------------------------------------------------------------
-# Regression: direct stream_mode="messages" must stay v1
-# ---------------------------------------------------------------------------
-
-
-class TestDirectMessagesModeStaysV1:
-    def test_direct_graph_stream_messages_yields_ai_message_chunks(self) -> None:
-        """graph.stream(stream_mode="messages") must not leak v2 event dicts —
-        the v2 flag is only injected by stream_v2 / astream_v2."""
-        model = GenericFakeChatModel(messages=iter(["legacy path"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        parts = list(graph.stream({"messages": "hi"}, stream_mode="messages"))
-        assert parts, "expected stream_mode='messages' to emit tuples"
-        for payload, _metadata in parts:
-            assert isinstance(payload, AIMessageChunk)
-        assert (
-            "".join(p[0].content for p in parts if isinstance(p[0].content, str))
-            == "legacy path"
-        )
-
-    def test_nested_graph_stream_messages_stays_v1_under_outer_stream_v2(self) -> None:
-        """An outer `stream_v2()` run must not flip an inner direct
-        `stream_mode="messages"` call onto the v2 event protocol."""
-        model = GenericFakeChatModel(messages=iter(["nested legacy path"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        inner = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        class OuterState(TypedDict, total=False):
-            saw_only_chunks: bool
-            first_payload_type: str
-            text: str
-
-        def call_subgraph(state: OuterState, config: RunnableConfig) -> dict[str, Any]:
-            parts = list(
-                inner.stream(
-                    {"messages": "hi"},
-                    config,
-                    stream_mode="messages",
-                )
-            )
-            assert parts
-            payloads = [payload for payload, _metadata in parts]
-            return {
-                "saw_only_chunks": all(
-                    isinstance(payload, AIMessageChunk) for payload in payloads
-                ),
-                "first_payload_type": type(payloads[0]).__name__,
-                "text": "".join(
-                    payload.content
-                    for payload in payloads
-                    if isinstance(payload, AIMessageChunk)
-                    and isinstance(payload.content, str)
-                ),
-            }
-
-        outer = (
-            StateGraph(OuterState)
-            .add_node("call_subgraph", call_subgraph)
-            .add_edge(START, "call_subgraph")
-            .add_edge("call_subgraph", END)
-            .compile()
-        )
-
-        result = outer.stream_v2({}).output
-
-        assert result is not None
-        assert result["saw_only_chunks"] is True
-        assert result["first_payload_type"] == "AIMessageChunk"
-        assert result["text"] == "nested legacy path"
-
-
-# ---------------------------------------------------------------------------
-# StreamMessagesHandlerV2 unit
-# ---------------------------------------------------------------------------
-
-
-class TestStreamMessagesHandlerV2Unit:
-    def test_on_llm_new_token_is_noop(self) -> None:
-        """v2 handler must not emit v1 chunks even when on_llm_new_token fires."""
-        from uuid import uuid4
-
-        from langchain_core.outputs import ChatGenerationChunk
-
-        from langgraph.pregel._messages import StreamMessagesHandlerV2
-
-        emitted: list[Any] = []
-        handler = StreamMessagesHandlerV2(emitted.append, subgraphs=False)
-        run_id = uuid4()
-        handler.metadata[run_id] = ((), {"langgraph_node": "x"})
-
-        handler.on_llm_new_token(
-            "hello",
-            chunk=ChatGenerationChunk(message=AIMessageChunk(content="hello")),
-            run_id=run_id,
-        )
-
-        assert emitted == []
-
-    def test_on_llm_end_dedupes_when_final_message_id_differs(self) -> None:
-        """A streamed v2 message should not be emitted again from the final
-        AIMessage fallback when its final id does not match `message-start`."""
-        from uuid import uuid4
-
-        from langchain_core.outputs import ChatGeneration, LLMResult
-
-        from langgraph.pregel._messages import StreamMessagesHandlerV2
-
-        emitted: list[Any] = []
-        handler = StreamMessagesHandlerV2(emitted.append, subgraphs=False)
-        run_id = uuid4()
-        handler.metadata[run_id] = ((), {"langgraph_node": "x"})
-
-        handler.on_stream_event(
-            {"event": "message-start", "message_id": "stream-msg-1"},
-            run_id=run_id,
-        )
-        handler.on_llm_end(
-            LLMResult(
-                generations=[
-                    [
-                        ChatGeneration(
-                            message=AIMessage(content="hello", id="final-msg-1")
-                        )
-                    ]
-                ]
-            ),
-            run_id=run_id,
-        )
-
-        assert len(emitted) == 1
@@ -0,0 +1,293 @@
+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
+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:
+    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:
+        """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."
+        )
@@ -0,0 +1,214 @@
+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 ---------------------------------------------------------
+
+
+@pytest.mark.anyio
+async def test_values_captures_values_events():
+    reducer = ValuesTransformer()
+    reducer.init()
+    reducer.process(_event("values", {"a": 1}))
+    reducer.process(_event("values", {"b": 2}))
+    reducer.finalize()
+
+    collected = []
+    async for item in reducer.values_log:
+        collected.append(item)
+    assert len(collected) == 2
+    assert collected[0]["data"] == {"a": 1}
+    assert collected[1]["data"] == {"b": 2}
+
+
+@pytest.mark.anyio
+async 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()
+
+    collected = []
+    async for item in reducer.values_log:
+        collected.append(item)
+    assert len(collected) == 0
+
+
+@pytest.mark.anyio
+async 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}
+
+
+@pytest.mark.anyio
+async def test_values_finalize_closes_log():
+    reducer = ValuesTransformer()
+    reducer.init()
+    reducer.process(_event("values", {"a": 1}))
+    reducer.finalize()
+    assert reducer.values_log.closed
+
+
+# -- 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,
+    )
+
+
+@pytest.mark.anyio
+async def test_messages_groups_lifecycle():
+    reducer = MessagesTransformer()
+    reducer.init()
+    reducer.process(_msg_start())
+    reducer.process(_content_delta("hi"))
+    reducer.process(_msg_finish())
+    reducer.finalize()
+
+    collected = []
+    async for stream in reducer.messages_log:
+        collected.append(stream)
+    assert len(collected) == 1
+    assert isinstance(collected[0], ChatModelStream)
+    assert collected[0].done
+
+
+@pytest.mark.anyio
+async 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()
+
+    collected = []
+    async for stream in reducer.messages_log:
+        collected.append(stream)
+    assert len(collected) == 2
+
+
+@pytest.mark.anyio
+async 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()
+
+    collected = []
+    async for stream in reducer.messages_log:
+        collected.append(stream)
+    assert len(collected) == 1
+
+
+@pytest.mark.anyio
+async 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()
+
+    collected = []
+    async for stream in reducer.messages_log:
+        collected.append(stream)
+    assert len(collected) == 1
+
+
+@pytest.mark.anyio
+async 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()
+
+    collected: list[ChatModelStream] = []
+    async for stream in reducer.messages_log:
+        collected.append(stream)
+    assert len(collected) == 1
+    assert collected[0].done
+
+
+@pytest.mark.anyio
+async def test_messages_fail_propagates_to_active():
+    """transformer.fail() should propagate the error to any active streams."""
+    reducer = MessagesTransformer()
+    reducer.init()
+    reducer.process(_msg_start())
+    reducer.process(_content_delta("partial"))
+    reducer.fail(RuntimeError("graph failed"))
+
+    # The messages log should be failed too
+    with pytest.raises(RuntimeError, match="graph failed"):
+        async for _ in reducer.messages_log:
+            pass
+
+
+@pytest.mark.anyio
+async def test_values_fail_propagates():
+    reducer = ValuesTransformer()
+    reducer.init()
+    reducer.process(_event("values", {"a": 1}))
+    reducer.fail(RuntimeError("graph failed"))
+
+    with pytest.raises(RuntimeError, match="graph failed"):
+        async for _ in reducer.values_log:
+            pass
@@ -0,0 +1,980 @@
+import asyncio
+from collections.abc import AsyncIterator, Iterator
+from typing import Any
+
+import pytest
+
+from langgraph.stream._mux import AsyncStreamMux
+from langgraph.stream._types import ProtocolEvent
+from langgraph.stream.chat_model_stream import ChatModelStream
+from langgraph.stream.run_stream import (
+    AsyncGraphRunStream,
+    AsyncSubgraphRunStream,
+    SubgraphRunStream,
+    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_streaming():
+    """Sync consumers can iterate msg.text for deltas."""
+    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"}),
+    ]
+
+    # Iterate deltas
+    run = create_graph_run_stream(_sync_source(chunks))
+    for msg in run.messages:
+        deltas = list(msg.text)
+        assert deltas == ["Hello", " world"]
+        assert msg.done
+
+    # str() returns full text
+    run = create_graph_run_stream(_sync_source(chunks))
+    for msg in run.messages:
+        assert str(msg.text) == "Hello world"
+
+    # After message is done, .text returns plain str
+    run = create_graph_run_stream(_sync_source(chunks))
+    for msg in run.messages:
+        list(msg.text)  # exhaust deltas
+        assert isinstance(msg.text, str)
+        assert msg.text == "Hello world"
+
+
+def test_sync_messages_multiple():
+    """Multiple sync messages each stream their own deltas."""
+    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))
+
+    all_deltas = []
+    for msg in run.messages:
+        all_deltas.append(list(msg.text))
+    assert all_deltas == [["answer"], ["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 — yielded on message-start (item 2).
+    # Consuming str(msg.text) drives the pump to message-finish (item 3).
+    mit = iter(run.messages)
+    msg = next(mit)
+    assert isinstance(msg, ChatModelStream)
+    assert consumed == 2
+    assert not msg.done
+    str(msg.text)  # pump until message completes
+    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."
+    )
+
+
+# ---------------------------------------------------------------------------
+# SubgraphRunStream — sync subgraph tests
+# ---------------------------------------------------------------------------
+
+
+def test_sync_subgraphs_discovery():
+    """Iterating .subgraphs should discover child namespaces and yield
+    SubgraphRunStream instances with correct name and index.
+    """
+    chunks = [
+        (("agent:0",), "values", {"v": 1}),
+        (("agent:1",), "values", {"v": 2}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    subs = list(run.subgraphs)
+    assert len(subs) == 2
+    assert all(isinstance(s, SubgraphRunStream) for s in subs)
+    assert subs[0].name == "agent"
+    assert subs[0].index == 0
+    assert subs[1].name == "agent"
+    assert subs[1].index == 1
+
+
+def test_sync_subgraph_name_no_index():
+    """Subgraph without a colon-delimited index should have index=0."""
+    chunks = [
+        (("planner",), "values", {"v": 1}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    subs = list(run.subgraphs)
+    assert len(subs) == 1
+    assert subs[0].name == "planner"
+    assert subs[0].index == 0
+
+
+def test_sync_subgraph_no_subgraphs():
+    """When all events are root-level, .subgraphs should yield nothing."""
+    chunks = [
+        ((), "values", {"v": 1}),
+        ((), "values", {"v": 2}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    subs = list(run.subgraphs)
+    assert subs == []
+
+
+def test_sync_subgraph_values():
+    """SubgraphRunStream.values should yield only values from the child namespace."""
+    chunks = [
+        (("child:0",), "values", {"v": 1}),
+        ((), "values", {"root": True}),
+        (("child:0",), "values", {"v": 2}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    for sub in run.subgraphs:
+        vals = list(sub.values)
+        assert vals == [{"v": 1}, {"v": 2}]
+
+
+def test_sync_subgraph_values_multiple_children():
+    """Each child stream should only see its own values."""
+    chunks = [
+        (("a:0",), "values", {"who": "a0"}),
+        (("b:0",), "values", {"who": "b0"}),
+        (("a:0",), "values", {"who": "a0-2"}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    children: dict[str, list[Any]] = {}
+    for sub in run.subgraphs:
+        children[f"{sub.name}:{sub.index}"] = list(sub.values)
+
+    assert children["a:0"] == [{"who": "a0"}, {"who": "a0-2"}]
+    assert children["b:0"] == [{"who": "b0"}]
+
+
+def test_sync_subgraph_output():
+    """SubgraphRunStream.output should return the last values for the child."""
+    chunks = [
+        (("child:0",), "values", {"v": 1}),
+        (("child:0",), "values", {"v": 2}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    for sub in run.subgraphs:
+        assert sub.output == {"v": 2}
+
+
+def test_sync_subgraph_output_with_mapper():
+    """Output mapper should apply to subgraph output."""
+    chunks = [
+        (("child:0",), "values", {"v": 42}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(
+        _sync_source(chunks), output_mapper=lambda x: {"mapped": x.get("v")}
+    )
+    for sub in run.subgraphs:
+        assert sub.output == {"mapped": 42}
+
+
+def test_sync_subgraph_values_with_mapper():
+    """Output mapper should apply to each yielded value snapshot."""
+    chunks = [
+        (("child:0",), "values", {"v": 1}),
+        (("child:0",), "values", {"v": 2}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(
+        _sync_source(chunks), output_mapper=lambda x: {"m": x.get("v")}
+    )
+    for sub in run.subgraphs:
+        vals = list(sub.values)
+        assert vals == [{"m": 1}, {"m": 2}]
+
+
+def test_sync_subgraph_messages():
+    """SubgraphRunStream.messages should yield fully populated ChatModelStream instances."""
+    chunks = [
+        (
+            ("agent:0",),
+            "messages",
+            {"event": "message-start", "message_id": "m1", "__node__": "agent"},
+        ),
+        (
+            ("agent:0",),
+            "messages",
+            {
+                "event": "content-block-delta",
+                "content_block": {"type": "text", "text": "hello"},
+                "__node__": "agent",
+            },
+        ),
+        (
+            ("agent:0",),
+            "messages",
+            {"event": "message-finish", "reason": "stop", "__node__": "agent"},
+        ),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    for sub in run.subgraphs:
+        msgs = list(sub.messages)
+        assert len(msgs) == 1
+        assert isinstance(msgs[0], ChatModelStream)
+        assert msgs[0].done
+        assert msgs[0].text == "hello"
+
+
+def test_sync_subgraph_messages_isolated():
+    """Messages from different subgraphs should not leak between children."""
+    chunks = [
+        (
+            ("a:0",),
+            "messages",
+            {"event": "message-start", "message_id": "m-a", "__node__": "a"},
+        ),
+        (
+            ("a:0",),
+            "messages",
+            {
+                "event": "content-block-delta",
+                "content_block": {"type": "text", "text": "from-a"},
+                "__node__": "a",
+            },
+        ),
+        (
+            ("a:0",),
+            "messages",
+            {"event": "message-finish", "reason": "stop", "__node__": "a"},
+        ),
+        (
+            ("b:0",),
+            "messages",
+            {"event": "message-start", "message_id": "m-b", "__node__": "b"},
+        ),
+        (
+            ("b:0",),
+            "messages",
+            {
+                "event": "content-block-delta",
+                "content_block": {"type": "text", "text": "from-b"},
+                "__node__": "b",
+            },
+        ),
+        (
+            ("b:0",),
+            "messages",
+            {"event": "message-finish", "reason": "stop", "__node__": "b"},
+        ),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    msg_texts: dict[str, list[str]] = {}
+    for sub in run.subgraphs:
+        msg_texts[sub.name] = [str(m.text) for m in sub.messages]
+
+    assert msg_texts["a"] == ["from-a"]
+    assert msg_texts["b"] == ["from-b"]
+
+
+def test_sync_subgraph_raw_iter():
+    """Iterating a SubgraphRunStream directly should yield events scoped
+    to the child namespace.
+    """
+    chunks = [
+        (("child:0",), "values", {"v": 1}),
+        ((), "values", {"root": True}),
+        (("child:0",), "updates", {"node": "x"}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    for sub in run.subgraphs:
+        events = list(sub)
+        methods = [e["method"] for e in events]
+        assert "values" in methods
+        assert "updates" in methods
+        # Root events should not appear
+        for e in events:
+            assert e["params"]["namespace"] == ["child:0"]
+
+
+def test_sync_subgraph_events_after_discovery():
+    """Events arriving after a namespace is first discovered should still
+    be visible in the child's values iteration.
+    """
+    chunks = [
+        (("child:0",), "values", {"v": 1}),  # triggers discovery
+        ((), "values", {"root": 1}),
+        (("child:0",), "values", {"v": 2}),  # after discovery
+        (("child:0",), "values", {"v": 3}),  # after discovery
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    for sub in run.subgraphs:
+        vals = list(sub.values)
+        assert vals == [{"v": 1}, {"v": 2}, {"v": 3}]
+
+
+def test_sync_subgraph_lazy_pump():
+    """Subgraph iteration should pump the source lazily."""
+    consumed = 0
+
+    def counting_source():
+        nonlocal consumed
+        for chunk in [
+            (("child:0",), "values", {"v": 1}),
+            (("child:0",), "values", {"v": 2}),
+            (("child:0",), "values", {"v": 3}),
+            ((), "values", {"done": True}),
+        ]:
+            consumed += 1
+            yield chunk
+
+    run = create_graph_run_stream(counting_source())
+    assert consumed == 0
+
+    for sub in run.subgraphs:
+        # Discovery pumped the first event
+        it = iter(sub.values)
+        v = next(it)
+        assert v == {"v": 1}
+        # Should not have consumed everything yet
+        assert consumed < 4
+        break  # don't exhaust subgraphs
+
+
+def test_sync_subgraph_interleave_parent_values():
+    """Parent values and subgraph values should both be accessible
+    when interleaving iteration.
+    """
+    chunks = [
+        ((), "values", {"root": 1}),
+        (("child:0",), "values", {"child": 1}),
+        ((), "values", {"root": 2}),
+        (("child:0",), "values", {"child": 2}),
+        ((), "values", {"root": 3}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+
+    # First drain parent values
+    root_vals = list(run.values)
+    assert root_vals == [{"root": 1}, {"root": 2}, {"root": 3}]
+
+    # Source is exhausted, but subgraph transformers were registered
+    # via replay — subgraph iteration should still see buffered events
+    # Note: subgraphs must be iterated while source is being pumped
+    # to discover namespaces. Since we drained via values, namespace
+    # "child:0" was already discovered. But subgraphs iteration also
+    # needs to pump — and the source is exhausted. Let's verify it
+    # yields the discovered child.
+    subs = list(run.subgraphs)
+    assert len(subs) == 1
+    assert subs[0].name == "child"
+    # The child transformer was registered via replay, so it saw the events
+    vals = list(subs[0].values)
+    assert vals == [{"child": 1}, {"child": 2}]
+
+
+def test_sync_subgraph_interrupted():
+    """Subgraph .interrupted should reflect the mux's interrupt state."""
+
+    class _FakeInterrupt:
+        def __init__(self, id: str):
+            self.id = id
+
+    chunks = [
+        (("child:0",), "values", {"__interrupt__": [_FakeInterrupt("i1")]}),
+        ((), "values", {"done": True}),
+    ]
+    run = create_graph_run_stream(_sync_source(chunks))
+    for sub in run.subgraphs:
+        # Pump to process the interrupt
+        _ = sub.output
+        assert sub.interrupted is True
+        assert len(sub.interrupts) == 1
+
+
+def test_sync_subgraph_source_error():
+    """If the source raises mid-stream, subgraphs that were already
+    discovered should still have their buffered data.
+    """
+
+    def bad_source():
+        yield (("child:0",), "values", {"v": 1})
+        yield (("child:0",), "values", {"v": 2})
+        raise ValueError("boom")
+
+    run = create_graph_run_stream(bad_source())
+    for sub in run.subgraphs:
+        vals = list(sub.values)
+        assert vals == [{"v": 1}, {"v": 2}]
+        assert run._mux._error is not None
+
+
+def test_sync_subgraph_output_drains_source():
+    """Accessing subgraph .output should drain the full source."""
+    consumed = 0
+
+    def counting_source():
+        nonlocal consumed
+        for chunk in [
+            (("child:0",), "values", {"v": 1}),
+            (("child:0",), "values", {"v": 2}),
+            ((), "values", {"done": True}),
+        ]:
+            consumed += 1
+            yield chunk
+
+    run = create_graph_run_stream(counting_source())
+    for sub in run.subgraphs:
+        result = sub.output
+        assert result == {"v": 2}
+        assert consumed == 3
@@ -1,863 +0,0 @@
-"""Tests for SubgraphTransformer.
-
-Subscribes to `tasks` events and produces in-process `SubgraphRunStream`
-handles backed by mini-muxes (built via `StreamMux._make_child`). The
-synthetic-event tests isolate the inference / mini-mux wiring; the
-real-graph tests exercise the end-to-end navigation path through
-`stream_v2`.
-"""
-
-from __future__ import annotations
-
-import operator
-import time
-from collections.abc import AsyncIterator
-from functools import partial
-from typing import Annotated, Any
-
-import pytest
-from typing_extensions import TypedDict
-
-from langgraph.constants import END, START
-from langgraph.errors import GraphInterrupt
-from langgraph.graph import StateGraph
-from langgraph.pregel.main import _normalize_stream_transformer_factories
-from langgraph.stream._mux import StreamMux
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.run_stream import (
-    AsyncGraphRunStream,
-    AsyncSubgraphRunStream,
-    GraphRunStream,
-    SubgraphRunStream,
-)
-from langgraph.stream.transformers import (
-    LifecycleTransformer,
-    MessagesTransformer,
-    SubgraphTransformer,
-    ValuesTransformer,
-)
-
-TS = int(time.time() * 1000)
-
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-
-def _tasks_start(
-    namespace: list[str],
-    *,
-    task_id: str,
-    name: str,
-) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "tasks",
-        "params": {
-            "namespace": namespace,
-            "timestamp": TS,
-            "data": {
-                "id": task_id,
-                "name": name,
-                "input": None,
-                "triggers": [],
-            },
-        },
-    }
-
-
-def _tasks_result(
-    namespace: list[str],
-    *,
-    task_id: str,
-    name: str,
-    error: str | None = None,
-    interrupts: list[dict[str, Any]] | None = None,
-) -> dict[str, Any]:
-    return {
-        "type": "event",
-        "method": "tasks",
-        "params": {
-            "namespace": namespace,
-            "timestamp": TS,
-            "data": {
-                "id": task_id,
-                "name": name,
-                "error": error,
-                "interrupts": interrupts or [],
-                "result": {},
-            },
-        },
-    }
-
-
-def _native_factories() -> list[Any]:
-    """Mirror the factory list `Pregel.stream_v2` registers."""
-    return [
-        ValuesTransformer,
-        MessagesTransformer,
-        LifecycleTransformer,
-        SubgraphTransformer,
-    ]
-
-
-def _stream_part(
-    method: str,
-    namespace: tuple[str, ...],
-    data: Any,
-) -> dict[str, Any]:
-    return {"type": method, "ns": namespace, "data": data}
-
-
-async def _astream_parts(*parts: dict[str, Any]) -> AsyncIterator[dict[str, Any]]:
-    for part in parts:
-        yield part
-
-
-def _arm(mux: StreamMux) -> None:
-    """Pre-subscribe every projection in the mux so synthetic pushes accumulate.
-
-    Real consumer code subscribes by iterating the projection; tests
-    inspect `_items` directly, so the lazy-subscribe gate has to be
-    flipped manually before any synthetic events are pushed.
-    """
-    mux._events._subscribed = True
-    for value in mux.extensions.values():
-        if hasattr(value, "_subscribed"):
-            value._subscribed = True
-
-
-def _arm_recursive(mux: StreamMux) -> None:
-    """Arm `mux` and every mini-mux currently held by SubgraphTransformer handles.
-
-    Mini-muxes are created during `mux.push(...)` when a new direct
-    child is discovered. Tests must call this after each push that
-    might have created a new mini-mux so subsequent pushes' projection
-    side effects accumulate (rather than dropping silently against an
-    unsubscribed log).
-    """
-    _arm(mux)
-    for handle in _subgraph_transformer(mux)._handles.values():
-        if handle._mux is not None:
-            _arm_recursive(handle._mux)
-
-
-def _build_root_mux(*, scope: tuple[str, ...] = ()) -> StreamMux:
-    mux = StreamMux(
-        factories=_native_factories(),
-        scope=scope,
-        is_async=False,
-    )
-    _arm(mux)
-    return mux
-
-
-def _subgraph_transformer(mux: StreamMux) -> SubgraphTransformer:
-    transformer = mux.transformer_by_key("subgraphs")
-    assert isinstance(transformer, SubgraphTransformer)
-    return transformer
-
-
-def _drain_subgraphs(mux: StreamMux) -> list[SubgraphRunStream]:
-    return list(_subgraph_transformer(mux)._log._items)
-
-
-def _child_mux(handle: SubgraphRunStream | AsyncSubgraphRunStream) -> StreamMux:
-    assert handle._mux is not None
-    return handle._mux
-
-
-def _event_items(mux: StreamMux) -> list[ProtocolEvent]:
-    return list(mux._events._items)
-
-
-def _lifecycle_payloads(mux: StreamMux) -> list[dict[str, Any]]:
-    lifecycle_t = mux.transformer_by_key("lifecycle")
-    assert isinstance(lifecycle_t, LifecycleTransformer)
-    return list(lifecycle_t._channel._items)
-
-
-# ---------------------------------------------------------------------------
-# Synthetic-event tests
-# ---------------------------------------------------------------------------
-
-
-def test_handle_created_on_first_direct_child_task() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    [handle] = _drain_subgraphs(mux)
-    assert handle.path == ("agent:abc",)
-    assert handle.graph_name == "agent"
-    assert handle.trigger_call_id == "abc"
-    assert handle.status == "started"
-    _child_mux(handle)  # mini-mux backed
-
-
-def test_handle_status_completes_on_parent_result() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent"))
-
-    [handle] = _drain_subgraphs(mux)
-    assert handle.status == "completed"
-    assert handle.error is None
-
-
-def test_handle_status_failed_with_error() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent", error="boom"))
-
-    [handle] = _drain_subgraphs(mux)
-    assert handle.status == "failed"
-    assert handle.error == "boom"
-
-
-def test_handle_status_interrupted() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(
-        _tasks_result(
-            [],
-            task_id="abc",
-            name="agent",
-            interrupts=[{"value": "pause"}],
-        )
-    )
-
-    [handle] = _drain_subgraphs(mux)
-    assert handle.status == "interrupted"
-
-
-def test_grandchild_discovered_via_child_mini_mux() -> None:
-    """Each mini-mux owns its own scope; grandchildren live on the child handle."""
-    mux = _build_root_mux()
-    # Direct child started — creates the mini-mux.
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    # Pre-subscribe the freshly-created mini-mux so subsequent
-    # forwarded events land on its projections (consumer would
-    # subscribe naturally by iterating handle.subgraphs, but the
-    # test inspects `_items` directly).
-    _arm_recursive(mux)
-    # Grandchild's first task event flows down into the child mini-mux.
-    mux.push(_tasks_start(["agent:abc", "tool:def"], task_id="t2", name="deep"))
-
-    [child_handle] = _drain_subgraphs(mux)
-    assert child_handle.path == ("agent:abc",)
-    # The grandchild appears on the CHILD'S subgraphs projection.
-    grandchildren = list(child_handle.subgraphs._items)
-    assert len(grandchildren) == 1
-    assert grandchildren[0].path == ("agent:abc", "tool:def")
-
-
-def test_finalize_completes_open_handles() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    mux.close()
-    [handle] = _drain_subgraphs(mux)
-    assert handle.status == "completed"
-
-
-def test_fail_marks_open_handles_interrupted_for_graph_interrupt() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    mux.fail(GraphInterrupt())
-    [handle] = _drain_subgraphs(mux)
-    assert handle.status == "interrupted"
-
-
-def test_fail_marks_open_handles_failed_for_other_errors() -> None:
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    mux.fail(RuntimeError("boom"))
-    [handle] = _drain_subgraphs(mux)
-    assert handle.status == "failed"
-    assert handle.error == "boom"
-
-
-def test_child_mux_requires_factories() -> None:
-    """A mux constructed only from `transformers=` can't clone factories."""
-    transformer = SubgraphTransformer()
-    mux = StreamMux(transformers=[transformer], is_async=False)
-    with pytest.raises(RuntimeError, match="factories"):
-        mux._make_child(("anything",))
-
-
-def test_subgraph_and_lifecycle_agree_on_terminal_status() -> None:
-    """Both transformers consume the same tasks signal — no drift."""
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent", error="boom"))
-
-    [handle] = _drain_subgraphs(mux)
-    payloads = _lifecycle_payloads(mux)
-    assert handle.status == "failed"
-    assert payloads[-1]["event"] == "failed"
-    assert handle.error == payloads[-1]["error"]
-
-
-def test_required_stream_modes_declared() -> None:
-    assert SubgraphTransformer.required_stream_modes == ("tasks",)
-
-
-def test_tasks_events_suppressed_from_main_log() -> None:
-    """Tasks events are folded into discovery and don't appear on the main log."""
-    mux = _build_root_mux()
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    mux.push(_tasks_result([], task_id="abc", name="agent"))
-
-    methods = [evt["method"] for evt in _event_items(mux)]
-    assert "tasks" not in methods
-
-
-class _ChildEventObserver(StreamTransformer):
-    """Records child-scope event identity without mutating it."""
-
-    records: list[tuple[tuple[str, ...], int, int, bool]] = []
-
-    def init(self) -> dict[str, Any]:
-        return {}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if self.scope and event["method"] == "values":
-            self.records.append(
-                (
-                    self.scope,
-                    id(event),
-                    id(event["params"]["data"]),
-                    "seq" in event,
-                )
-            )
-        return True
-
-
-def test_child_forwarding_reuses_event_without_assigning_seq() -> None:
-    _ChildEventObserver.records = []
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _ChildEventObserver,
-        ],
-        is_async=False,
-    )
-    _arm(mux)
-    mux.push(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-    data = {"x": 1}
-    event: ProtocolEvent = {
-        "type": "event",
-        "method": "values",
-        "params": {
-            "namespace": ["agent:abc"],
-            "timestamp": TS,
-            "data": data,
-        },
-    }
-    mux.push(event)
-
-    assert _ChildEventObserver.records == [(("agent:abc",), id(event), id(data), False)]
-    [root_event] = [evt for evt in _event_items(mux) if evt["method"] == "values"]
-    assert root_event is event
-    assert "seq" in root_event
-
-
-class _AsyncProbeTransformer(StreamTransformer):
-    """Async-only transformer used to verify mini-mux async dispatch."""
-
-    required_stream_modes = ("tasks",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self.seen: list[tuple[str, ...]] = []
-        self.finalized = False
-        self.failed: BaseException | None = None
-
-    def init(self) -> dict[str, Any]:
-        return {"async_probe": self}
-
-    async def aprocess(self, event: ProtocolEvent) -> bool:
-        self.seen.append(tuple(event["params"]["namespace"]))
-        return True
-
-    async def afinalize(self) -> None:
-        self.finalized = True
-
-    async def afail(self, err: BaseException) -> None:
-        self.failed = err
-
-
-@pytest.mark.anyio
-async def test_async_child_mini_mux_uses_async_lane() -> None:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _AsyncProbeTransformer,
-        ],
-        is_async=True,
-    )
-    await mux.apush(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    handle = _subgraph_transformer(mux)._handles[("agent:abc",)]
-    assert isinstance(handle, AsyncSubgraphRunStream)
-    probe = _child_mux(handle).transformer_by_key("async_probe")
-    assert isinstance(probe, _AsyncProbeTransformer)
-    assert probe.seen == [("agent:abc",)]
-
-    await mux.apush(_tasks_result([], task_id="abc", name="agent"))
-    assert probe.finalized is True
-
-
-@pytest.mark.anyio
-async def test_async_child_mini_mux_fail_uses_async_lane() -> None:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _AsyncProbeTransformer,
-        ],
-        is_async=True,
-    )
-    await mux.apush(_tasks_start(["agent:abc"], task_id="t1", name="tool"))
-
-    handle = _subgraph_transformer(mux)._handles[("agent:abc",)]
-    probe = _child_mux(handle).transformer_by_key("async_probe")
-    assert isinstance(probe, _AsyncProbeTransformer)
-
-    err = RuntimeError("boom")
-    await mux.afail(err)
-    assert probe.failed is err
-
-
-class _StandardCtorTransformer(StreamTransformer):
-    """Transformer class that inherits the standard scoped constructor."""
-
-    def init(self) -> dict[str, Any]:
-        return {"standard_ctor": self}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        return True
-
-
-class _ScopedTransformer(StreamTransformer):
-    """Transformer class that uses the inherited scoped construction."""
-
-    def init(self) -> dict[str, Any]:
-        return {"scoped": self}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        return True
-
-
-class _ConfigurableFactoryTransformer(StreamTransformer):
-    """Transformer built by a configured per-scope factory."""
-
-    def __init__(self, scope: tuple[str, ...] = (), *, label: str) -> None:
-        super().__init__(scope)
-        self.label = label
-
-    def init(self) -> dict[str, Any]:
-        return {"configurable": self}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        return True
-
-
-class _ChildExploder(StreamTransformer):
-    """Raise from child mini-muxes to verify errors propagate upstream."""
-
-    def init(self) -> dict[str, Any]:
-        return {}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if self.scope and event["method"] == "values":
-            raise RuntimeError("child boom")
-        return True
-
-
-class _ChildFinalizeExploder(StreamTransformer):
-    """Raise from child mini-mux finalization."""
-
-    supports_sync = True
-
-    def init(self) -> dict[str, Any]:
-        return {}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        return True
-
-    def finalize(self) -> None:
-        if self.scope:
-            raise RuntimeError("child finalize boom")
-
-    async def afinalize(self) -> None:
-        if self.scope:
-            raise RuntimeError("child afinalize boom")
-
-
-def test_normalize_transformer_factories_supports_scoped_classes() -> None:
-    factories = _normalize_stream_transformer_factories(
-        [_StandardCtorTransformer, _ScopedTransformer]
-    )
-
-    standard_ctor = factories[0](("child",))
-    scoped = factories[1](("child",))
-    assert isinstance(standard_ctor, _StandardCtorTransformer)
-    assert standard_ctor.scope == ("child",)
-    assert isinstance(scoped, _ScopedTransformer)
-    assert scoped.scope == ("child",)
-
-
-def test_normalize_transformer_factories_supports_configured_factories() -> None:
-    factories = _normalize_stream_transformer_factories(
-        [partial(_ConfigurableFactoryTransformer, label="configured")]
-    )
-
-    built = factories[0](("child",))
-    assert isinstance(built, _ConfigurableFactoryTransformer)
-    assert built.label == "configured"
-    assert built.scope == ("child",)
-
-
-def test_normalize_transformer_factories_rejects_instances() -> None:
-    with pytest.raises(TypeError, match="pre-built instance"):
-        _normalize_stream_transformer_factories([_StandardCtorTransformer()])
-
-
-def test_child_forwarding_errors_fail_sync_run() -> None:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _ChildExploder,
-        ],
-        is_async=False,
-    )
-    values_t = mux.transformer_by_key("values")
-    assert isinstance(values_t, ValuesTransformer)
-    run = GraphRunStream(
-        iter(
-            [
-                _stream_part(
-                    "tasks",
-                    ("agent:abc",),
-                    {
-                        "id": "t1",
-                        "name": "tool",
-                        "input": None,
-                        "triggers": [],
-                    },
-                ),
-                _stream_part("values", ("agent:abc",), {"x": 1}),
-            ]
-        ),
-        mux,
-        values_t,
-    )
-
-    handle = next(iter(run.subgraphs))
-    assert handle.path == ("agent:abc",)
-    with pytest.raises(RuntimeError, match="child boom"):
-        _ = run.output
-    assert run._mux._events._error is not None
-
-
-@pytest.mark.anyio
-async def test_child_forwarding_errors_fail_async_run() -> None:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _ChildExploder,
-        ],
-        is_async=True,
-    )
-    values_t = mux.transformer_by_key("values")
-    assert isinstance(values_t, ValuesTransformer)
-    run = AsyncGraphRunStream(
-        _astream_parts(
-            _stream_part(
-                "tasks",
-                ("agent:abc",),
-                {
-                    "id": "t1",
-                    "name": "tool",
-                    "input": None,
-                    "triggers": [],
-                },
-            ),
-            _stream_part("values", ("agent:abc",), {"x": 1}),
-        ),
-        mux,
-        values_t,
-    )
-
-    handle = await run.subgraphs.__aiter__().__anext__()
-    assert handle.path == ("agent:abc",)
-    with pytest.raises(RuntimeError, match="child boom"):
-        await run.output()
-    assert run._mux._events._error is not None
-
-
-def test_child_finalize_errors_propagate_to_sync_run() -> None:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _ChildFinalizeExploder,
-        ],
-        is_async=False,
-    )
-    values_t = mux.transformer_by_key("values")
-    assert isinstance(values_t, ValuesTransformer)
-    run = GraphRunStream(
-        iter(
-            [
-                _stream_part(
-                    "tasks",
-                    ("agent:abc",),
-                    {
-                        "id": "t1",
-                        "name": "tool",
-                        "input": None,
-                        "triggers": [],
-                    },
-                )
-            ]
-        ),
-        mux,
-        values_t,
-    )
-
-    with pytest.raises(RuntimeError, match="child finalize boom"):
-        _ = run.output
-
-
-@pytest.mark.anyio
-async def test_child_finalize_errors_propagate_to_async_run() -> None:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            LifecycleTransformer,
-            SubgraphTransformer,
-            _ChildFinalizeExploder,
-        ],
-        is_async=True,
-    )
-    values_t = mux.transformer_by_key("values")
-    assert isinstance(values_t, ValuesTransformer)
-    run = AsyncGraphRunStream(
-        _astream_parts(
-            _stream_part(
-                "tasks",
-                ("agent:abc",),
-                {
-                    "id": "t1",
-                    "name": "tool",
-                    "input": None,
-                    "triggers": [],
-                },
-            )
-        ),
-        mux,
-        values_t,
-    )
-
-    with pytest.raises(RuntimeError, match="child afinalize boom"):
-        await run.output()
-
-
-# ---------------------------------------------------------------------------
-# End-to-end real-graph tests
-# ---------------------------------------------------------------------------
-
-
-class _State(TypedDict):
-    value: str
-    items: Annotated[list[str], operator.add]
-
-
-def _passthrough(state: _State) -> dict[str, Any]:
-    return {"value": state["value"] + "!", "items": ["x"]}
-
-
-def _make_two_level_nested() -> Any:
-    """outer → middle → inner. Three Pregel instances, two nesting levels."""
-    inner_b: StateGraph = StateGraph(_State, input_schema=_State)
-    inner_b.add_node("inner_node", _passthrough)
-    inner_b.add_edge(START, "inner_node")
-    inner_b.add_edge("inner_node", END)
-    inner = inner_b.compile()
-
-    middle_b: StateGraph = StateGraph(_State, input_schema=_State)
-    middle_b.add_node("inner", inner)
-    middle_b.add_edge(START, "inner")
-    middle_b.add_edge("inner", END)
-    middle = middle_b.compile()
-
-    outer_b: StateGraph = StateGraph(_State, input_schema=_State)
-    outer_b.add_node("middle", middle)
-    outer_b.add_edge(START, "middle")
-    outer_b.add_edge("middle", END)
-    return outer_b.compile()
-
-
-def _item_node(item: str):
-    def node(state: _State) -> dict[str, Any]:
-        return {"items": [item]}
-
-    return node
-
-
-def _make_two_sibling_subgraphs() -> Any:
-    """outer → one → two, where both nodes are compiled subgraphs."""
-    one_b: StateGraph = StateGraph(_State, input_schema=_State)
-    one_b.add_node("add_one", _item_node("one"))
-    one_b.add_edge(START, "add_one")
-    one_b.add_edge("add_one", END)
-    one = one_b.compile()
-
-    two_b: StateGraph = StateGraph(_State, input_schema=_State)
-    two_b.add_node("add_two", _item_node("two"))
-    two_b.add_edge(START, "add_two")
-    two_b.add_edge("add_two", END)
-    two = two_b.compile()
-
-    outer_b: StateGraph = StateGraph(_State, input_schema=_State)
-    outer_b.add_node("one", one)
-    outer_b.add_node("two", two)
-    outer_b.add_edge(START, "one")
-    outer_b.add_edge("one", "two")
-    outer_b.add_edge("two", END)
-    return outer_b.compile()
-
-
-def _failing_node(state: _State) -> dict[str, Any]:
-    raise ValueError("child boom")
-
-
-def _make_failing_nested() -> Any:
-    inner_b: StateGraph = StateGraph(_State, input_schema=_State)
-    inner_b.add_node("fail", _failing_node)
-    inner_b.add_edge(START, "fail")
-    inner_b.add_edge("fail", END)
-    inner = inner_b.compile()
-
-    outer_b: StateGraph = StateGraph(_State, input_schema=_State)
-    outer_b.add_node("inner", inner)
-    outer_b.add_edge(START, "inner")
-    outer_b.add_edge("inner", END)
-    return outer_b.compile()
-
-
-def test_stream_v2_real_graph_yields_subgraph_handles() -> None:
-    """Iterating `run.subgraphs` yields handles for direct-child subgraphs."""
-    graph = _make_two_level_nested()
-    run = graph.stream_v2({"value": "x", "items": []})
-
-    handle_paths: list[tuple[str, ...]] = []
-    final_status: dict[tuple[str, ...], str] = {}
-    for handle in run.subgraphs:
-        # Drill into the handle's projections inside the loop body so
-        # the mini-mux is subscribed before the next pump cycle.
-        list(handle.values)
-        handle_paths.append(handle.path)
-        final_status[handle.path] = handle.status
-
-    assert len(handle_paths) == 1
-    assert handle_paths[0][0].startswith("middle:")
-    assert final_status[handle_paths[0]] == "completed"
-
-
-def test_stream_v2_grandchild_visible_on_child_handle() -> None:
-    """Drilling into `handle.subgraphs` surfaces nested grandchildren."""
-    graph = _make_two_level_nested()
-    run = graph.stream_v2({"value": "x", "items": []})
-
-    grandchild_paths: list[tuple[str, ...]] = []
-    middle_path: tuple[str, ...] | None = None
-    for middle_handle in run.subgraphs:
-        # Subscribe to grandchildren before the next pump cycle.
-        for inner_handle in middle_handle.subgraphs:
-            # Subscribe to inner.values so its mini-mux drains.
-            list(inner_handle.values)
-            grandchild_paths.append(inner_handle.path)
-        middle_path = middle_handle.path
-
-    assert middle_path is not None
-    assert len(grandchild_paths) == 1
-    inner_path = grandchild_paths[0]
-    assert inner_path[1].startswith("inner:")
-    assert inner_path[: len(middle_path)] == middle_path
-
-
-def test_subgraph_output_stops_at_own_terminal_without_draining_siblings() -> None:
-    """A handle's `output` must not pump past its terminal event.
-
-    If it over-pumps the root run, the second sibling handle is yielded
-    only after it has already completed, so subscribing to `values`
-    inside the loop body misses its events.
-    """
-    graph = _make_two_sibling_subgraphs()
-    run = graph.stream_v2({"value": "x", "items": []})
-
-    paths: list[tuple[str, ...]] = []
-    second_values: list[dict[str, Any]] = []
-    for handle in run.subgraphs:
-        paths.append(handle.path)
-        if handle.graph_name == "one":
-            assert handle.output is not None
-            assert handle.status == "completed"
-        elif handle.graph_name == "two":
-            second_values = list(handle.values)
-
-    assert [path[0].split(":", 1)[0] for path in paths] == ["one", "two"]
-    assert second_values
-    assert second_values[-1]["items"] == ["one", "two"]
-
-
-def test_aborted_subgraph_handle_does_not_fail_parent_forwarding() -> None:
-    graph = _make_two_sibling_subgraphs()
-    run = graph.stream_v2({"value": "x", "items": []})
-
-    seen: list[str | None] = []
-    for handle in run.subgraphs:
-        seen.append(handle.graph_name)
-        if handle.graph_name == "one":
-            # Subscribe before aborting to ensure forwarding into the
-            # closed mini-mux would have raised without the closed check.
-            iter(handle.values)
-            handle.abort()
-        elif handle.graph_name == "two":
-            assert list(handle.values)
-
-    assert seen == ["one", "two"]
-
-
-def test_failed_subgraph_output_raises_terminal_error() -> None:
-    graph = _make_failing_nested()
-    run = graph.stream_v2({"value": "x", "items": []})
-
-    handle = next(iter(run.subgraphs))
-    with pytest.raises(RuntimeError, match="child boom"):
-        _ = handle.output
-    assert handle.status == "failed"
-    assert handle.error == "child boom"
@@ -1,792 +0,0 @@
-"""End-to-end tests exercising all stream_v2 projections together.
-
-Each test builds a realistic graph (subgraphs, LLM calls, custom writers,
-interrupts) and verifies that every projection — values, messages, lifecycle,
-subgraphs, raw events, output, interleave — produces correct, consistent
-results through a single stream_v2 / astream_v2 run.
-"""
-
-from __future__ import annotations
-
-import operator
-import sys
-from typing import Annotated, Any
-
-import pytest
-from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.language_models.chat_model_stream import (
-    AsyncChatModelStream,
-    ChatModelStream,
-)
-from langchain_core.messages import AIMessage
-from langgraph.checkpoint.memory import InMemorySaver
-from typing_extensions import TypedDict
-
-from langgraph.constants import END, START
-from langgraph.graph import MessagesState, StateGraph
-from langgraph.stream import StreamChannel, StreamTransformer
-from langgraph.stream._types import ProtocolEvent
-from langgraph.types import StreamWriter, interrupt
-
-NEEDS_CONTEXTVARS = pytest.mark.skipif(
-    sys.version_info < (3, 11),
-    reason="Python 3.11+ is required for async contextvars support",
-)
-
-
-# ---------------------------------------------------------------------------
-# State and graph builders
-# ---------------------------------------------------------------------------
-
-
-class AgentState(TypedDict):
-    value: str
-    items: Annotated[list[str], operator.add]
-
-
-def _make_nested_graph():
-    """Build a two-level graph with pure state transforms.
-
-    Structure:
-        outer:
-            router_node  (state transform)
-            inner_graph  (compiled subgraph)
-
-        inner_graph:
-            process_node  (state transform)
-    """
-
-    def process_node(state: AgentState) -> dict[str, Any]:
-        return {"value": state["value"] + "_processed", "items": ["processed"]}
-
-    inner_builder: StateGraph = StateGraph(AgentState, input_schema=AgentState)
-    inner_builder.add_node("process_node", process_node)
-    inner_builder.add_edge(START, "process_node")
-    inner_builder.add_edge("process_node", END)
-    inner_graph = inner_builder.compile()
-
-    def router_node(state: AgentState) -> dict[str, Any]:
-        return {"value": state["value"] + "_routed", "items": ["routed"]}
-
-    outer_builder: StateGraph = StateGraph(AgentState, input_schema=AgentState)
-    outer_builder.add_node("router", router_node)
-    outer_builder.add_node("inner", inner_graph)
-    outer_builder.add_edge(START, "router")
-    outer_builder.add_edge("router", "inner")
-    outer_builder.add_edge("inner", END)
-    return outer_builder.compile()
-
-
-def _make_messages_graph():
-    """Flat graph with an LLM call for messages projection testing."""
-    model = GenericFakeChatModel(messages=iter(["hello world"]))
-
-    def call_model(state: MessagesState) -> dict[str, Any]:
-        return {"messages": model.invoke(state["messages"])}
-
-    return (
-        StateGraph(MessagesState)
-        .add_node("call_model", call_model)
-        .add_edge(START, "call_model")
-        .add_edge("call_model", END)
-        .compile()
-    )
-
-
-def _make_messages_subgraph():
-    """Outer graph with a MessagesState subgraph that returns an AIMessage.
-
-    Uses the whole-message fallback path (node returns AIMessage directly)
-    to exercise messages through a subgraph boundary.
-    """
-
-    def return_message(state: MessagesState) -> dict[str, Any]:
-        return {"messages": AIMessage(content="from subgraph", id="sub-msg-1")}
-
-    inner = (
-        StateGraph(MessagesState)
-        .add_node("return_message", return_message)
-        .add_edge(START, "return_message")
-        .add_edge("return_message", END)
-        .compile()
-    )
-
-    class OuterState(TypedDict):
-        messages: Annotated[list[Any], operator.add]
-        done: bool
-
-    def pre_node(state: OuterState) -> dict[str, Any]:
-        return {"done": False}
-
-    return (
-        StateGraph(OuterState)
-        .add_node("pre", pre_node)
-        .add_node("inner", inner)
-        .add_edge(START, "pre")
-        .add_edge("pre", "inner")
-        .add_edge("inner", END)
-        .compile()
-    )
-
-
-def _make_custom_writer_graph():
-    """Graph where a node emits custom stream events via StreamWriter."""
-
-    def writer_node(state: AgentState, *, writer: StreamWriter) -> dict[str, Any]:
-        writer({"step": "start", "detail": "beginning work"})
-        writer({"step": "middle", "detail": "processing"})
-        writer({"step": "end", "detail": "done"})
-        return {"value": state["value"] + "_custom", "items": ["custom"]}
-
-    builder = StateGraph(AgentState)
-    builder.add_node("writer_node", writer_node)
-    builder.add_edge(START, "writer_node")
-    builder.add_edge("writer_node", END)
-    return builder.compile()
-
-
-def _make_interrupt_graph():
-    """Graph that interrupts after the first node."""
-
-    def step_one(state: AgentState) -> dict[str, Any]:
-        return {"value": state["value"] + "_step1", "items": ["step1"]}
-
-    def step_two(state: AgentState) -> dict[str, Any]:
-        answer = interrupt("need approval")
-        return {"value": state["value"] + f"_{answer}", "items": ["step2"]}
-
-    builder = StateGraph(AgentState)
-    builder.add_node("step_one", step_one)
-    builder.add_node("step_two", step_two)
-    builder.add_edge(START, "step_one")
-    builder.add_edge("step_one", "step_two")
-    builder.add_edge("step_two", END)
-    return builder.compile(checkpointer=InMemorySaver())
-
-
-def _make_error_subgraph():
-    """Graph with a subgraph that raises."""
-
-    def failing_node(state: AgentState) -> dict[str, Any]:
-        raise ValueError("subgraph explosion")
-
-    inner_builder = StateGraph(AgentState)
-    inner_builder.add_node("fail", failing_node)
-    inner_builder.add_edge(START, "fail")
-    inner_builder.add_edge("fail", END)
-    inner = inner_builder.compile()
-
-    outer_builder = StateGraph(AgentState)
-    outer_builder.add_node("inner", inner)
-    outer_builder.add_edge(START, "inner")
-    outer_builder.add_edge("inner", END)
-    return outer_builder.compile()
-
-
-class _CustomPassthroughTransformer(StreamTransformer):
-    required_stream_modes = ("custom",)
-
-    def init(self) -> dict[str, Any]:
-        return {}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        return True
-
-
-class _CounterTransformer(StreamTransformer):
-    """Custom transformer that counts values events via a StreamChannel."""
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._channel: StreamChannel[int] = StreamChannel("counter")
-        self._count = 0
-
-    def init(self) -> dict[str, Any]:
-        return {"counter": self._channel}
-
-    def process(self, event: ProtocolEvent) -> bool:
-        if event["method"] == "values":
-            self._count += 1
-            self._channel.push(self._count)
-        return True
-
-
-# ---------------------------------------------------------------------------
-# Sync end-to-end: all projections on nested graph
-# ---------------------------------------------------------------------------
-
-
-class TestStreamV2E2ESync:
-    def test_all_projections_nested_graph(self) -> None:
-        """Run a nested graph through stream_v2 and verify values + lifecycle."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2({"value": "x", "items": []})
-
-        values_snapshots: list[dict[str, Any]] = []
-        lifecycle_events: list[dict[str, Any]] = []
-        for name, item in run.interleave("values", "lifecycle"):
-            if name == "values":
-                values_snapshots.append(item)
-            elif name == "lifecycle":
-                lifecycle_events.append(item)
-
-        assert len(values_snapshots) >= 1
-        final = values_snapshots[-1]
-        assert "routed" in final["items"]
-        assert "processed" in final["items"]
-        assert "_routed" in final["value"]
-        assert "_processed" in final["value"]
-
-        assert len(lifecycle_events) >= 2
-        started = [e for e in lifecycle_events if e["event"] == "started"]
-        completed = [e for e in lifecycle_events if e["event"] == "completed"]
-        assert len(started) >= 1
-        assert len(completed) >= 1
-
-    def test_subgraph_handles_with_drill_down(self) -> None:
-        """Subgraph handles yield and support values drill-down."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2({"value": "x", "items": []})
-
-        handles = []
-        for handle in run.subgraphs:
-            child_values = list(handle.values)
-            handles.append(
-                {
-                    "path": handle.path,
-                    "graph_name": handle.graph_name,
-                    "values_count": len(child_values),
-                }
-            )
-
-        assert len(handles) >= 1
-        assert handles[0]["values_count"] >= 1
-
-        output = run.output
-        assert output is not None
-        assert "_routed" in output["value"]
-        assert "_processed" in output["value"]
-
-    def test_raw_events_have_monotonic_seq(self) -> None:
-        """Raw protocol events have monotonically increasing seq numbers."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2({"value": "x", "items": []})
-        events = list(run)
-        assert len(events) > 0
-
-        seqs = [e["seq"] for e in events]
-        for i in range(1, len(seqs)):
-            assert seqs[i] > seqs[i - 1], f"seq not monotonic at {i}: {seqs}"
-
-        for event in events:
-            assert event["type"] == "event"
-            assert "method" in event
-            assert isinstance(event["params"]["timestamp"], int)
-
-    def test_output_matches_final_values_snapshot(self) -> None:
-        """output property returns the same state as the last values snapshot."""
-        run1 = _make_nested_graph().stream_v2({"value": "x", "items": []})
-        snapshots = list(run1.values)
-        final_via_values = snapshots[-1]
-
-        run2 = _make_nested_graph().stream_v2({"value": "x", "items": []})
-        final_via_output = run2.output
-
-        assert final_via_values == final_via_output
-
-    def test_context_manager_and_abort(self) -> None:
-        """Context manager calls abort, marking the stream exhausted."""
-        graph = _make_nested_graph()
-        with graph.stream_v2({"value": "x", "items": []}) as run:
-            first_val = next(iter(run.values))
-            assert isinstance(first_val, dict)
-        assert run._exhausted is True
-
-    def test_extensions_has_all_native_keys(self) -> None:
-        """Extensions dict exposes all native projection keys."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2({"value": "x", "items": []})
-        _ = run.output
-
-        assert "values" in run.extensions
-        assert "messages" in run.extensions
-        assert "lifecycle" in run.extensions
-        assert "subgraphs" in run.extensions
-        assert run.values is run.extensions["values"]
-        assert run.messages is run.extensions["messages"]
-        assert run.lifecycle is run.extensions["lifecycle"]
-        assert run.subgraphs is run.extensions["subgraphs"]
-
-
-# ---------------------------------------------------------------------------
-# Sync: messages projection
-# ---------------------------------------------------------------------------
-
-
-class TestStreamV2E2EMessages:
-    def test_messages_projection_from_invoke(self) -> None:
-        """Messages projection captures LLM calls via model.invoke() auto-routing."""
-        graph = _make_messages_graph()
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-
-        assert len(streams) >= 1
-        for stream in streams:
-            assert isinstance(stream, ChatModelStream)
-        assert streams[0].output.text == "hello world"
-
-    def test_messages_text_deltas(self) -> None:
-        """Text deltas from the messages projection concatenate correctly."""
-        model = GenericFakeChatModel(messages=iter(["streamed answer"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "go"})
-        (stream,) = list(run.messages)
-        assert "".join(stream.text) == "streamed answer"
-
-    def test_messages_from_whole_ai_message(self) -> None:
-        """Node returning AIMessage directly produces a complete stream."""
-
-        def return_msg(state: MessagesState) -> dict[str, Any]:
-            return {"messages": AIMessage(content="hardcoded", id="msg-1")}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("return_msg", return_msg)
-            .add_edge(START, "return_msg")
-            .add_edge("return_msg", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        (stream,) = list(run.messages)
-        assert stream.output.text == "hardcoded"
-        assert stream.message_id == "msg-1"
-
-    def test_root_messages_only_shows_root_scope(self) -> None:
-        """Root messages projection doesn't surface subgraph-scoped messages."""
-        graph = _make_messages_subgraph()
-        run = graph.stream_v2({"messages": ["hi"], "done": False})
-        root_streams = list(run.messages)
-        # The message is emitted inside the subgraph, so the root
-        # messages projection (scoped to root namespace) doesn't see it.
-        assert root_streams == []
-
-    def test_subgraph_handle_messages_drill_down(self) -> None:
-        """Drilling into subgraph handle's messages surfaces subgraph messages."""
-        graph = _make_messages_subgraph()
-        run = graph.stream_v2({"messages": ["hi"], "done": False})
-
-        found_messages = False
-        for handle in run.subgraphs:
-            child_messages = list(handle.messages)
-            if child_messages:
-                found_messages = True
-                assert isinstance(child_messages[0], ChatModelStream)
-                assert child_messages[0].output.text == "from subgraph"
-        assert found_messages
-
-
-# ---------------------------------------------------------------------------
-# Sync: custom stream writer + custom transformer
-# ---------------------------------------------------------------------------
-
-
-class TestStreamV2E2ECustom:
-    def test_custom_events_with_passthrough_transformer(self) -> None:
-        """Custom StreamWriter events appear on the main log when a
-        transformer declares the custom mode."""
-        graph = _make_custom_writer_graph()
-        run = graph.stream_v2(
-            {"value": "x", "items": []},
-            transformers=[_CustomPassthroughTransformer],
-        )
-        events = list(run)
-        custom = [e for e in events if e["method"] == "custom"]
-        assert len(custom) == 3
-        steps = [e["params"]["data"]["step"] for e in custom]
-        assert steps == ["start", "middle", "end"]
-
-    def test_custom_events_suppressed_without_transformer(self) -> None:
-        """Without a custom-mode transformer, custom events don't flow."""
-        graph = _make_custom_writer_graph()
-        run = graph.stream_v2({"value": "x", "items": []})
-        events = list(run)
-        custom = [e for e in events if e["method"] == "custom"]
-        assert custom == []
-
-    def test_custom_transformer_with_stream_channel(self) -> None:
-        """A custom transformer with a StreamChannel produces extension data."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2(
-            {"value": "x", "items": []},
-            transformers=[_CounterTransformer],
-        )
-
-        assert "counter" in run.extensions
-        counter_iter = iter(run.extensions["counter"])
-        _ = run.output
-        counts = list(counter_iter)
-        assert len(counts) >= 1
-        assert all(isinstance(c, int) for c in counts)
-        assert counts == sorted(counts)
-
-    def test_custom_channel_events_on_main_log(self) -> None:
-        """StreamChannel auto-forward injects custom:<name> events into the main log."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2(
-            {"value": "x", "items": []},
-            transformers=[_CounterTransformer],
-        )
-        events = list(run)
-        counter_events = [e for e in events if e["method"] == "custom:counter"]
-        assert len(counter_events) >= 1
-        assert all(isinstance(e["params"]["data"], int) for e in counter_events)
-
-
-# ---------------------------------------------------------------------------
-# Sync: interrupt handling
-# ---------------------------------------------------------------------------
-
-
-class TestStreamV2E2EInterrupt:
-    def test_interrupt_sets_flags_and_surfaces_interrupts(self) -> None:
-        """Interrupted run has correct flags and interrupt payloads."""
-        graph = _make_interrupt_graph()
-        config: dict[str, Any] = {"configurable": {"thread_id": "int-1"}}
-        run = graph.stream_v2({"value": "x", "items": []}, config)
-
-        output = run.output
-        assert output is not None
-        assert run.interrupted is True
-        assert len(run.interrupts) > 0
-        assert output["items"] == ["step1"]
-        assert "_step1" in output["value"]
-
-    def test_interrupt_values_snapshot_has_partial_state(self) -> None:
-        """Values snapshots captured before the interrupt reflect partial state."""
-        graph = _make_interrupt_graph()
-        config: dict[str, Any] = {"configurable": {"thread_id": "int-2"}}
-        run = graph.stream_v2({"value": "x", "items": []}, config)
-
-        snapshots = list(run.values)
-        assert len(snapshots) >= 1
-        last = snapshots[-1]
-        assert "step1" in last["items"]
-
-
-# ---------------------------------------------------------------------------
-# Sync: error propagation
-# ---------------------------------------------------------------------------
-
-
-class TestStreamV2E2EErrors:
-    def test_subgraph_error_propagates_through_output(self) -> None:
-        """Error in a subgraph propagates through output."""
-        graph = _make_error_subgraph()
-        run = graph.stream_v2({"value": "x", "items": []})
-
-        with pytest.raises(ValueError, match="subgraph explosion"):
-            _ = run.output
-
-    def test_subgraph_error_propagates_through_raw_events(self) -> None:
-        graph = _make_error_subgraph()
-        run = graph.stream_v2({"value": "x", "items": []})
-
-        with pytest.raises(ValueError, match="subgraph explosion"):
-            list(run)
-
-    def test_error_subgraph_handle_status(self) -> None:
-        """Subgraph handle surfaces the error status."""
-        graph = _make_error_subgraph()
-        run = graph.stream_v2({"value": "x", "items": []})
-
-        handle = next(iter(run.subgraphs))
-        with pytest.raises(RuntimeError, match="subgraph explosion"):
-            _ = handle.output
-        assert handle.status == "failed"
-        assert handle.error == "subgraph explosion"
-
-
-# ---------------------------------------------------------------------------
-# Async end-to-end
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.anyio
-@NEEDS_CONTEXTVARS
-class TestStreamV2E2EAsync:
-    async def test_all_projections_async(self) -> None:
-        """Async run exercises values projection."""
-        graph = _make_nested_graph()
-        run = await graph.astream_v2({"value": "x", "items": []})
-
-        values_snapshots = [s async for s in run.values]
-        assert len(values_snapshots) >= 1
-        final = values_snapshots[-1]
-        assert "_routed" in final["value"]
-        assert "_processed" in final["value"]
-
-    async def test_async_output(self) -> None:
-        """Async output returns the final state."""
-        graph = _make_nested_graph()
-        run = await graph.astream_v2({"value": "x", "items": []})
-        output = await run.output()
-        assert output is not None
-        assert output["value"] == "x_routed_processed"
-        assert "routed" in output["items"]
-        assert "processed" in output["items"]
-
-    async def test_async_raw_events(self) -> None:
-        """Async raw event iteration yields well-formed ProtocolEvents."""
-        graph = _make_nested_graph()
-        run = await graph.astream_v2({"value": "x", "items": []})
-        events = [e async for e in run]
-        assert len(events) > 0
-        seqs = [e["seq"] for e in events]
-        for i in range(1, len(seqs)):
-            assert seqs[i] > seqs[i - 1]
-
-    async def test_async_messages_projection(self) -> None:
-        """Async messages projection captures LLM streams."""
-        model = GenericFakeChatModel(messages=iter(["async answer"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": await model.ainvoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-        streams = [s async for s in run.messages]
-        assert len(streams) >= 1
-        for s in streams:
-            assert isinstance(s, AsyncChatModelStream)
-        assert (await streams[0].output).text == "async answer"
-
-    async def test_async_interrupt(self) -> None:
-        """Async interrupted run has correct flags."""
-        graph = _make_interrupt_graph()
-        config: dict[str, Any] = {"configurable": {"thread_id": "async-int-1"}}
-        run = await graph.astream_v2({"value": "x", "items": []}, config)
-
-        output = await run.output()
-        assert output is not None
-        assert await run.interrupted() is True
-        assert len(await run.interrupts()) > 0
-
-    async def test_async_error_propagation(self) -> None:
-        """Async error from subgraph propagates through output."""
-        graph = _make_error_subgraph()
-        run = await graph.astream_v2({"value": "x", "items": []})
-        with pytest.raises(ValueError, match="subgraph explosion"):
-            await run.output()
-
-    async def test_async_context_manager(self) -> None:
-        """Async context manager calls abort on exit."""
-        graph = _make_nested_graph()
-        run = await graph.astream_v2({"value": "x", "items": []})
-        async with run:
-            _ = await anext(aiter(run.values))
-        assert run._exhausted is True
-
-    async def test_async_extensions_present(self) -> None:
-        """Async run has all native extensions."""
-        graph = _make_nested_graph()
-        run = await graph.astream_v2({"value": "x", "items": []})
-        _ = await run.output()
-        assert "values" in run.extensions
-        assert "messages" in run.extensions
-        assert "lifecycle" in run.extensions
-        assert "subgraphs" in run.extensions
-
-    async def test_async_custom_transformer(self) -> None:
-        """Async custom transformer with StreamChannel works."""
-        graph = _make_nested_graph()
-        run = await graph.astream_v2(
-            {"value": "x", "items": []},
-            transformers=[_CounterTransformer],
-        )
-        assert "counter" in run.extensions
-        counter_cursor = aiter(run.extensions["counter"])
-        _ = await run.output()
-        counts = [c async for c in counter_cursor]
-        assert len(counts) >= 1
-        assert counts == sorted(counts)
-
-
-# ---------------------------------------------------------------------------
-# Sync: combined projections stress test
-# ---------------------------------------------------------------------------
-
-
-class TestStreamV2E2ECombined:
-    def test_interleave_all_native_projections(self) -> None:
-        """Interleave values + messages + lifecycle without deadlock."""
-        graph = _make_nested_graph()
-        run = graph.stream_v2({"value": "x", "items": []})
-
-        seen_names: set[str] = set()
-        for name, _item in run.interleave("values", "messages", "lifecycle"):
-            seen_names.add(name)
-
-        assert "values" in seen_names
-        assert "lifecycle" in seen_names
-
-    def test_multiple_custom_transformers(self) -> None:
-        """Multiple custom transformers can coexist."""
-
-        class TagTransformer(StreamTransformer):
-            def __init__(self, scope: tuple[str, ...] = ()) -> None:
-                super().__init__(scope)
-                self._channel: StreamChannel[str] = StreamChannel("tags")
-
-            def init(self) -> dict[str, Any]:
-                return {"tags": self._channel}
-
-            def process(self, event: ProtocolEvent) -> bool:
-                if event["method"] == "values":
-                    self._channel.push(
-                        f"tag:{event['params']['data'].get('value', '')}"
-                    )
-                return True
-
-        graph = _make_nested_graph()
-        run = graph.stream_v2(
-            {"value": "x", "items": []},
-            transformers=[_CounterTransformer, TagTransformer],
-        )
-
-        assert "counter" in run.extensions
-        assert "tags" in run.extensions
-
-        counter_iter = iter(run.extensions["counter"])
-        tags_iter = iter(run.extensions["tags"])
-        _ = run.output
-        counts = list(counter_iter)
-        tags = list(tags_iter)
-
-        assert len(counts) >= 1
-        assert len(tags) >= 1
-        assert all(t.startswith("tag:") for t in tags)
-
-    def test_two_sibling_subgraphs_both_discoverable(self) -> None:
-        """Two sequential subgraph invocations produce two handles."""
-
-        class _S(TypedDict):
-            items: Annotated[list[str], operator.add]
-
-        def _item(name: str):
-            def node(state: _S) -> dict[str, Any]:
-                return {"items": [name]}
-
-            return node
-
-        inner_a = (
-            StateGraph(_S)
-            .add_node("add_a", _item("a"))
-            .add_edge(START, "add_a")
-            .add_edge("add_a", END)
-            .compile()
-        )
-        inner_b = (
-            StateGraph(_S)
-            .add_node("add_b", _item("b"))
-            .add_edge(START, "add_b")
-            .add_edge("add_b", END)
-            .compile()
-        )
-
-        outer = (
-            StateGraph(_S)
-            .add_node("sub_a", inner_a)
-            .add_node("sub_b", inner_b)
-            .add_edge(START, "sub_a")
-            .add_edge("sub_a", "sub_b")
-            .add_edge("sub_b", END)
-            .compile()
-        )
-
-        run = outer.stream_v2({"items": []})
-        handles = []
-        for handle in run.subgraphs:
-            list(handle.values)
-            handles.append(handle)
-
-        assert len(handles) == 2
-        names = [h.graph_name for h in handles]
-        assert "sub_a" in names
-        assert "sub_b" in names
-        assert all(h.status == "completed" for h in handles)
-
-        output = run.output
-        assert output is not None
-        assert set(output["items"]) == {"a", "b"}
-
-    def test_lifecycle_matches_subgraph_handles(self) -> None:
-        """Lifecycle events and subgraph handles agree on discovered subgraphs."""
-        run1 = _make_nested_graph().stream_v2({"value": "x", "items": []})
-        handle_paths: list[tuple[str, ...]] = []
-        for handle in run1.subgraphs:
-            list(handle.values)
-            handle_paths.append(handle.path)
-
-        run2 = _make_nested_graph().stream_v2({"value": "x", "items": []})
-        lifecycle = list(run2.lifecycle)
-
-        started_ns = [
-            tuple(e["namespace"]) for e in lifecycle if e["event"] == "started"
-        ]
-        # Handle paths use format "graph_name:call_id", lifecycle namespaces
-        # use the same format. Both should have the same graph_name prefix.
-        handle_prefixes = {p[0].split(":")[0] for p in handle_paths}
-        lifecycle_prefixes = {ns[0].split(":")[0] for ns in started_ns}
-        assert handle_prefixes == lifecycle_prefixes
-
-    def test_values_plus_messages_plus_custom(self) -> None:
-        """Values, messages, and a custom transformer all produce data in one run."""
-        model = GenericFakeChatModel(messages=iter(["combined test"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2(
-            {"messages": "hi"},
-            transformers=[_CounterTransformer],
-        )
-
-        counter_iter = iter(run.extensions["counter"])
-        values_iter = iter(run.values)
-        messages_iter = iter(run.messages)
-
-        values = list(values_iter)
-        messages = list(messages_iter)
-        counts = list(counter_iter)
-
-        assert len(values) >= 1
-        assert len(messages) >= 1
-        assert len(counts) >= 1
-        assert messages[0].output.text == "combined test"
@@ -0,0 +1,420 @@
+"""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
@@ -37,7 +37,6 @@ 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
    """
@@ -53,7 +52,6 @@ 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,
            }
@@ -282,116 +280,6 @@ 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:
@@ -432,14 +320,8 @@ def test_replay_interrupt_stable_across_replays(
        r = graph.invoke(None, before_ask.config)
        results.append(r)

-    # 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)
+    assert all(r == results[0] for r in results)
+    assert "__interrupt__" in results[0]


 def test_fork_from_before_interrupt_refires(
@@ -972,354 +854,6 @@ 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:
@@ -1756,321 +1290,6 @@ 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:
@@ -3064,16 +2283,14 @@ 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)
-    # 5 original + 1 fork + 2 new branch checkpoints = 8
-    assert len(post_summary) == 8
+    assert len(post_summary) == 7  # 5 original + 2 new branch checkpoints

    # Verify the full shape after replay
    assert [s["next"] for s in post_summary] == [
-        (),  # new branch tip
-        ("node_c",),  # new branch
-        ("node_b",),  # fork from replay point
-        (),  # old branch tip
-        ("node_c",),  # old
+        (),  # new branch tip (C6)
+        ("node_c",),  # new branch (C5)
+        (),  # old branch tip (C4)
+        ("node_c",),  # old (C3)
        ("node_b",),  # branch point (C2)
        ("node_a",),  # old (C1)
        ("__start__",),  # old (C0)
@@ -3081,7 +2298,6 @@ 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
@@ -46,7 +46,6 @@ 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
    """
@@ -62,7 +61,6 @@ 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,
            }
@@ -337,14 +335,8 @@ async def test_replay_interrupt_stable_across_replays(
        r = await graph.ainvoke(None, before_ask.config)
        results.append(r)

-    # 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)
+    assert all(r == results[0] for r in results)
+    assert "__interrupt__" in results[0]


@NEEDS_CONTEXTVARS
@@ -1269,391 +1261,6 @@ 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,
@@ -2481,15 +2088,13 @@ 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)
-    # 5 original + 1 fork + 2 new branch checkpoints = 8
-    assert len(post_summary) == 8
+    assert len(post_summary) == 7  # 5 original + 2 new branch checkpoints

    assert [s["next"] for s in post_summary] == [
-        (),  # new branch tip
-        ("node_c",),  # new branch
-        ("node_b",),  # fork from replay point
-        (),  # old branch tip
-        ("node_c",),  # old
+        (),  # new branch tip (C6)
+        ("node_c",),  # new branch (C5)
+        (),  # old branch tip (C4)
+        ("node_c",),  # old (C3)
        ("node_b",),  # branch point (C2)
        ("node_a",),  # old (C1)
        ("__start__",),  # old (C0)
@@ -2497,7 +2102,6 @@ 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
@@ -1,290 +0,0 @@
-"""Tests for StreamToolCallHandler and ToolRuntime.emit_output_delta.
-
-These tests exercise the langgraph-core piece in isolation — the prebuilt
-`ToolCallTransformer` has its own test file. Here we feed real graphs
-through `Pregel.stream(stream_mode=["tools", ...])` and inspect the raw
-`(ns, mode, payload)` tuples on the `tools` channel.
-"""
-
-from __future__ import annotations
-
-from typing import Annotated, Any
-
-import pytest
-from langchain_core.messages import AIMessage
-from langchain_core.tools import tool
-from langgraph.prebuilt import ToolNode, ToolRuntime
-from typing_extensions import TypedDict
-
-from langgraph.constants import END, START
-from langgraph.graph import StateGraph
-from langgraph.graph.message import add_messages
-from langgraph.pregel._tools import _tool_call_writer
-
-
-class _State(TypedDict):
-    messages: Annotated[list, add_messages]
-
-
-def _caller_sync(tool_name: str, tool_args: dict[str, Any], tc_id: str = "tc1"):
-    def caller(state: _State) -> dict:
-        return {
-            "messages": [
-                AIMessage(
-                    content="",
-                    tool_calls=[{"name": tool_name, "args": tool_args, "id": tc_id}],
-                )
-            ]
-        }
-
-    return caller
-
-
-def _caller_async(tool_name: str, tool_args: dict[str, Any], tc_id: str = "tc1"):
-    async def caller(state: _State) -> dict:
-        return {
-            "messages": [
-                AIMessage(
-                    content="",
-                    tool_calls=[{"name": tool_name, "args": tool_args, "id": tc_id}],
-                )
-            ]
-        }
-
-    return caller
-
-
-def _build_graph(caller, tools) -> Any:
-    sg = StateGraph(_State)
-    sg.add_node("caller", caller)
-    sg.add_node("tools", ToolNode(tools))
-    sg.add_edge(START, "caller")
-    sg.add_edge("caller", "tools")
-    sg.add_edge("tools", END)
-    return sg.compile()
-
-
-def _tool_events(stream) -> list[tuple[tuple[str, ...], dict]]:
-    """Collect `(ns, payload)` for every `tools`-mode chunk."""
-    out: list[tuple[tuple[str, ...], dict]] = []
-    for ns, mode, payload in stream:
-        if mode == "tools":
-            out.append((tuple(ns), payload))
-    return out
-
-
-class TestSyncGraphSyncTool:
-    def test_started_finished_cycle(self) -> None:
-        @tool
-        def echo(text: str) -> str:
-            """echo."""
-            return f"echoed:{text}"
-
-        graph = _build_graph(_caller_sync("echo", {"text": "hi"}), [echo])
-        events = _tool_events(
-            graph.stream(
-                {"messages": []},
-                stream_mode=["tools"],
-                subgraphs=True,
-            )
-        )
-
-        assert [p["event"] for _, p in events] == [
-            "tool-started",
-            "tool-finished",
-        ]
-        assert events[0][1]["tool_call_id"] == "tc1"
-        assert events[0][1]["tool_name"] == "echo"
-        assert events[0][1]["input"] == {"text": "hi"}
-        # ToolNode wraps the return in a ToolMessage.
-        assert events[1][1]["tool_call_id"] == "tc1"
-
-    def test_emit_output_delta_produces_delta_events(self) -> None:
-        @tool
-        def streaming_echo(text: str, runtime: ToolRuntime) -> str:
-            """stream chunks."""
-            for chunk in ("a", "b", "c"):
-                runtime.emit_output_delta(chunk)
-            return text
-
-        graph = _build_graph(
-            _caller_sync("streaming_echo", {"text": "x"}), [streaming_echo]
-        )
-        events = _tool_events(
-            graph.stream(
-                {"messages": []},
-                stream_mode=["tools"],
-                subgraphs=True,
-            )
-        )
-
-        deltas = [p["delta"] for _, p in events if p["event"] == "tool-output-delta"]
-        assert deltas == ["a", "b", "c"]
-        # The deltas must be bracketed by started and finished.
-        ordered = [p["event"] for _, p in events]
-        assert ordered[0] == "tool-started"
-        assert ordered[-1] == "tool-finished"
-
-    def test_tool_error_event(self) -> None:
-        @tool
-        def boom() -> str:
-            """raises."""
-            raise ValueError("nope")
-
-        graph = _build_graph(_caller_sync("boom", {}), [boom])
-        events: list[tuple[tuple[str, ...], dict]] = []
-        with pytest.raises(ValueError, match="nope"):
-            for ns, mode, payload in graph.stream(
-                {"messages": []},
-                stream_mode=["tools"],
-                subgraphs=True,
-            ):
-                if mode == "tools":
-                    events.append((tuple(ns), payload))
-
-        kinds = [p["event"] for _, p in events]
-        assert kinds == ["tool-started", "tool-error"]
-        assert events[1][1]["message"] == "nope"
-
-    def test_writer_unset_outside_tool(self) -> None:
-        # Outside any tool body the ContextVar that ToolRuntime reads
-        # is unset — emitting from there would be a no-op.
-        assert _tool_call_writer.get() is None
-
-    def test_no_events_without_tools_mode(self) -> None:
-        @tool
-        def echo(text: str) -> str:
-            """echo."""
-            return text
-
-        graph = _build_graph(_caller_sync("echo", {"text": "hi"}), [echo])
-        # No "tools" in stream_mode — handler is not attached and zero
-        # `tools`-method events fire.
-        chunks = list(
-            graph.stream(
-                {"messages": []},
-                stream_mode=["values"],
-                subgraphs=True,
-            )
-        )
-        assert all(
-            not (isinstance(c, tuple) and len(c) == 3 and c[1] == "tools")
-            for c in chunks
-        )
-
-
-class TestAsyncGraphAsyncTool:
-    @pytest.mark.anyio
-    async def test_async_tool_produces_events(self) -> None:
-        @tool
-        async def aecho(text: str, runtime: ToolRuntime) -> str:
-            """async echo."""
-            runtime.emit_output_delta(text)
-            return f"got:{text}"
-
-        graph = _build_graph(_caller_async("aecho", {"text": "hi"}), [aecho])
-        events: list[tuple[tuple[str, ...], dict]] = []
-        async for ns, mode, payload in graph.astream(
-            {"messages": []},
-            stream_mode=["tools"],
-            subgraphs=True,
-        ):
-            if mode == "tools":
-                events.append((tuple(ns), payload))
-
-        kinds = [p["event"] for _, p in events]
-        assert kinds == ["tool-started", "tool-output-delta", "tool-finished"]
-        assert events[1][1]["delta"] == "hi"
-
-
-class TestConcurrentToolCalls:
-    def test_parallel_tool_calls_do_not_bleed(self) -> None:
-        @tool
-        def streamer(marker: str, runtime: ToolRuntime) -> str:
-            """emits marker twice."""
-            runtime.emit_output_delta(f"{marker}-1")
-            runtime.emit_output_delta(f"{marker}-2")
-            return marker
-
-        def caller(state: _State) -> dict:
-            return {
-                "messages": [
-                    AIMessage(
-                        content="",
-                        tool_calls=[
-                            {"name": "streamer", "args": {"marker": "A"}, "id": "a"},
-                            {"name": "streamer", "args": {"marker": "B"}, "id": "b"},
-                        ],
-                    )
-                ]
-            }
-
-        graph = _build_graph(caller, [streamer])
-        events = _tool_events(
-            graph.stream(
-                {"messages": []},
-                stream_mode=["tools"],
-                subgraphs=True,
-            )
-        )
-
-        # Group deltas by tool_call_id.
-        by_id: dict[str, list[str]] = {}
-        for _, p in events:
-            if p["event"] == "tool-output-delta":
-                by_id.setdefault(p["tool_call_id"], []).append(p["delta"])
-        assert by_id["a"] == ["A-1", "A-2"]
-        assert by_id["b"] == ["B-1", "B-2"]
-
-
-class TestSubgraphNamespacePropagation:
-    def test_tool_inside_subgraph_emits_with_subgraph_ns(self) -> None:
-        @tool
-        def inner_tool(text: str) -> str:
-            """inner tool."""
-            return text
-
-        def sub_caller(state: _State) -> dict:
-            return {
-                "messages": [
-                    AIMessage(
-                        content="",
-                        tool_calls=[
-                            {
-                                "name": "inner_tool",
-                                "args": {"text": "x"},
-                                "id": "tc1",
-                            }
-                        ],
-                    )
-                ]
-            }
-
-        inner = StateGraph(_State)
-        inner.add_node("sub_caller", sub_caller)
-        inner.add_node("sub_tools", ToolNode([inner_tool]))
-        inner.add_edge(START, "sub_caller")
-        inner.add_edge("sub_caller", "sub_tools")
-        inner.add_edge("sub_tools", END)
-        inner_graph = inner.compile()
-
-        outer = StateGraph(_State)
-        outer.add_node("sub", inner_graph)
-        outer.add_edge(START, "sub")
-        outer.add_edge("sub", END)
-        graph = outer.compile()
-
-        events = _tool_events(
-            graph.stream(
-                {"messages": []},
-                stream_mode=["tools"],
-                subgraphs=True,
-            )
-        )
-
-        # All `tools` events should carry a non-empty namespace rooted
-        # at the `sub` node.
-        assert events, "expected at least one tools event"
-        for ns, _ in events:
-            assert ns  # non-empty
-            assert ns[0].startswith("sub:")
@@ -11,19 +11,13 @@ from typing import (
    TypeVar,
    Union,
 )
-from unittest.mock import MagicMock, patch
+from unittest.mock import 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,
-    get_callback_manager_for_config,
-)
+from langgraph._internal._config import _is_not_empty, ensure_config
 from langgraph._internal._fields import (
    _is_optional_type,
    get_enhanced_type_hints,
@@ -304,7 +298,7 @@ def test_is_not_empty() -> None:
    assert not _is_not_empty({})


-def test_configurable_metadata() -> None:
+def test_configurable_metadata():
    config = {
        "configurable": {
            "a-key": "foo",
@@ -315,115 +309,11 @@ def test_configurable_metadata() -> None:
            "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 set(metadata) == {
-        "nooverride",
-        "assistant_id",
-        "thread_id",
-        "checkpoint_id",
-        "run_id",
-        "graph_id",
-        "checkpoint_ns",
-        "task_id",
-    }
+    assert metadata.keys() == expected
    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",
-    }
@@ -1348,11 +1348,10 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.3.2"
-source = { git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates#aee50839376e379891c99fcbe6d5264f66dedc68" }
+version = "1.2.22"
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
-    { name = "langchain-protocol" },
    { name = "langsmith" },
    { name = "packaging" },
    { name = "pydantic" },
@@ -1361,22 +1360,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-
-[[package]]
-name = "langchain-protocol"
-version = "0.0.14"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "typing-extensions" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
+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" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/c7/a6/2ffacf0f1a3788f250e75d0b52a24896c413be11be3a6d42bcdf46fbea48/langchain_core-1.2.22-py3-none-any.whl", hash = "sha256:7e30d586b75918e828833b9ec1efc25465723566845dd652c277baf751e9c04b", size = 506829, upload-time = "2026-03-24T18:48:43.286Z" },
 ]

 [[package]]
 name = "langgraph"
-version = "1.1.10"
+version = "1.1.6"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -1448,7 +1439,7 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=0.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "../prebuilt" },
    { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -1460,7 +1451,7 @@ requires-dist = [
 dev = [
    { name = "httpx" },
    { name = "jupyter" },
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1493,7 +1484,7 @@ lint = [
 ]
 test = [
    { name = "httpx" },
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1557,7 +1548,7 @@ wheels = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.3"
+version = "4.0.1"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -1566,7 +1557,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=0.2.38" },
    { name = "ormsgpack", specifier = ">=1.12.0" },
 ]

@@ -1715,7 +1706,7 @@ inmem = [
 requires-dist = [
    { name = "click", specifier = ">=8.1.7" },
    { name = "httpx", specifier = ">=0.24.0" },
-    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.9.0" },
+    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.8.0" },
    { name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.7" },
    { name = "langgraph-sdk", marker = "python_full_version >= '3.11'", specifier = ">=0.1.0" },
    { name = "pathspec", specifier = ">=0.11.0" },
@@ -1751,7 +1742,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.12"
+version = "1.0.9"
 source = { editable = "../prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -1760,14 +1751,14 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

 [package.metadata.requires-dev]
 dev = [
    { name = "codespell" },
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core" },
    { name = "langgraph", editable = "." },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
@@ -1787,7 +1778,7 @@ lint = [
    { name = "ruff" },
 ]
 test = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core" },
    { name = "langgraph", editable = "." },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
@@ -1835,20 +1826,20 @@ requires-dist = [
 dev = [
    { name = "codespell" },
    { name = "langgraph", editable = "." },
-    { name = "mypy", specifier = "==1.20.2" },
+    { name = "mypy", specifier = "==1.19.1" },
    { name = "pydantic", specifier = ">=2.12.4" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
    { name = "pytest-watch" },
-    { name = "ruff", specifier = "==0.15.12" },
+    { name = "ruff", specifier = "==0.15.6" },
    { name = "starlette" },
    { name = "ty", specifier = "==0.0.23" },
 ]
 lint = [
    { name = "codespell" },
-    { name = "mypy", specifier = "==1.20.2" },
-    { name = "ruff", specifier = "==0.15.12" },
+    { name = "mypy", specifier = "==1.19.1" },
+    { name = "ruff", specifier = "==0.15.6" },
    { name = "starlette" },
    { name = "ty", specifier = "==0.0.23" },
 ]
@@ -1861,7 +1852,7 @@ test = [

 [[package]]
 name = "langsmith"
-version = "0.7.31"
+version = "0.6.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -1871,12 +1862,11 @@ dependencies = [
    { name = "requests" },
    { name = "requests-toolbelt" },
    { name = "uuid-utils" },
-    { name = "xxhash" },
    { name = "zstandard" },
 ]
-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" }
+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" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/66/0f/09a6637a7ba777eb307b7c80852d9ee26438e2bdafbad6fcc849ff9d9192/langsmith-0.6.4-py3-none-any.whl", hash = "sha256:ac4835860160be371042c7adbba3cb267bcf8d96a5ea976c33a8a4acad6c5486", size = 283503, upload-time = "2026-01-15T20:02:26.662Z" },
 ]

 [package.optional-dependencies]
@@ -2149,7 +2139,7 @@ wheels = [

 [[package]]
 name = "nbconvert"
-version = "7.17.1"
+version = "7.17.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "beautifulsoup4" },
@@ -2167,9 +2157,9 @@ dependencies = [
    { name = "pygments" },
    { name = "traitlets" },
 ]
-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" }
+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" }
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+    { url = "https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl", hash = "sha256:4f99a63b337b9a23504347afdab24a11faa7d86b405e5c8f9881cd313336d518", size = 261510, upload-time = "2026-01-29T16:37:46.322Z" },
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 [[package]]
@@ -2915,7 +2905,7 @@ wheels = [

 [[package]]
 name = "pytest"
-version = "9.0.3"
+version = "9.0.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -2926,9 +2916,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/d1/db/7ef3487e0fb0049ddb5ce41d3a49c235bf9ad299b6a25d5780a89f19230f/pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11", size = 1568901, upload-time = "2025-12-06T21:30:51.014Z" }
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+    { url = "https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b", size = 374801, upload-time = "2025-12-06T21:30:49.154Z" },
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 [[package]]
@@ -3027,11 +3017,11 @@ wheels = [

 [[package]]
 name = "python-dotenv"
-version = "1.2.2"
+version = "1.2.1"
 source = { registry = "https://pypi.org/simple" }
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+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" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/14/1b/a298b06749107c305e1fe0f814c6c74aea7b2f1e10989cb30f544a1b3253/python_dotenv-1.2.1-py3-none-any.whl", hash = "sha256:b81ee9561e9ca4004139c6cbba3a238c32b03e4894671e181b671e8cb8425d61", size = 21230, upload-time = "2025-10-26T15:12:09.109Z" },
 ]

 [[package]]
@@ -1,6 +1,5 @@
 """langgraph.prebuilt exposes a higher-level API for creating and executing agents and tools."""

-from langgraph.prebuilt._tool_call_transformer import ToolCallTransformer
 from langgraph.prebuilt.chat_agent_executor import create_react_agent
 from langgraph.prebuilt.tool_node import (
    InjectedState,
@@ -14,7 +13,6 @@ from langgraph.prebuilt.tool_validator import ValidationNode
 __all__ = [
    "create_react_agent",
    "ToolNode",
-    "ToolCallTransformer",
    "tools_condition",
    "ValidationNode",
    "InjectedState",
@@ -1,117 +0,0 @@
-"""In-process handle for a single tool call's streaming execution.
-
-Mirrors the shape of `ChatModelStream` from langchain-core but simpler —
-a tool has one output channel, no content-block multiplexing. Populated
-by `ToolCallTransformer` as `tool-started` / `tool-output-delta` /
-`tool-finished` / `tool-error` events flow in on the `tools` channel.
-"""
-
-from __future__ import annotations
-
-from collections.abc import AsyncIterator, Iterator
-from typing import Any
-
-from langgraph.stream.stream_channel import StreamChannel
-
-
-class ToolCallStream:
-    """Scoped view of a single tool call's lifecycle.
-
-    Yielded on `run.tool_calls` once per `tool-started` event. Fields
-    are populated as events arrive:
-
-    - `tool_call_id`, `tool_name`, `input`: stable from the start event.
-    - `output_deltas`: a `StreamChannel` of delta chunks. Iterate (sync or
-      async) to consume partial output in arrival order.
-    - `output`: terminal payload from `tool-finished`, or `None` if the
-      call failed or is still in flight.
-    - `error`: terminal error string from `tool-error`, or `None` if the
-      call succeeded or is still in flight.
-    - `completed`: True once a terminal event (`tool-finished` or
-      `tool-error`) has been observed.
-
-    `ToolCallStream` is not meant to be constructed by end users — it's
-    produced by `ToolCallTransformer` as events flow through the mux.
-    """
-
-    def __init__(
-        self,
-        tool_call_id: str,
-        tool_name: str,
-        input: dict[str, Any] | None = None,
-    ) -> None:
-        """Initialize a fresh handle for a tool call.
-
-        Args:
-            tool_call_id: The `tool_call_id` from the AIMessage.
-            tool_name: The tool's name.
-            input: The tool's input arguments (as reported by
-                `on_tool_start`), or `None` if none were captured.
-        """
-        self.tool_call_id = tool_call_id
-        self.tool_name = tool_name
-        self.input = input
-        self._output_deltas: StreamChannel[Any] = StreamChannel()
-        self.output: Any = None
-        self.error: str | None = None
-        self.completed = False
-
-    @property
-    def output_deltas(self) -> StreamChannel[Any]:
-        """The channel of streamed `tool-output-delta` payloads.
-
-        Iterate (sync or async depending on how the run was started)
-        to consume partial output in arrival order. The log closes when
-        the tool finishes or errors.
-        """
-        return self._output_deltas
-
-    def _bind(self, *, is_async: bool) -> None:
-        """Bind the deltas log to sync or async iteration.
-
-        Called by `ToolCallTransformer` when constructing this handle so
-        the log matches the enclosing mux's mode.
-        """
-        self._output_deltas._bind(is_async=is_async)
-
-    def _push_delta(self, delta: Any) -> None:
-        self._output_deltas.push(delta)
-
-    def _finish(self, output: Any) -> None:
-        self.output = output
-        self.completed = True
-        self._output_deltas.close()
-
-    def _fail(self, message: str) -> None:
-        self.error = message
-        self.completed = True
-        self._output_deltas.close()
-
-    def __iter__(self) -> Iterator[Any]:
-        """Iterate delta chunks synchronously.
-
-        Equivalent to `iter(self.output_deltas)`. Raises `TypeError` if
-        the underlying log is bound to async mode.
-        """
-        return iter(self._output_deltas)
-
-    def __aiter__(self) -> AsyncIterator[Any]:
-        """Iterate delta chunks asynchronously.
-
-        Equivalent to `aiter(self.output_deltas)`. Raises `TypeError`
-        if the underlying log is bound to sync mode.
-        """
-        return self._output_deltas.__aiter__()
-
-    def __repr__(self) -> str:
-        status = (
-            "completed"
-            if self.completed and self.error is None
-            else "failed"
-            if self.completed
-            else "running"
-        )
-        return (
-            f"ToolCallStream(tool_call_id={self.tool_call_id!r}, "
-            f"tool_name={self.tool_name!r}, status={status})"
-        )
@@ -1,129 +0,0 @@
-"""Transformer that projects `tools` channel events into `ToolCallStream`s."""
-
-from __future__ import annotations
-
-from collections.abc import Awaitable, Callable
-from typing import Any
-
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.stream_channel import StreamChannel
-
-from langgraph.prebuilt._tool_call_stream import ToolCallStream
-
-
-class ToolCallTransformer(StreamTransformer):
-    """Project `tools` channel events into `ToolCallStream` handles.
-
-    Each `tool-started` event spawns a `ToolCallStream`, pushed onto
-    `run.tool_calls`. Subsequent `tool-output-delta` events append to
-    that stream's deltas log; `tool-finished` and `tool-error` close it.
-
-    Native transformer — the `tool_calls` projection is exposed as a
-    direct attribute on the run stream.
-
-    A nameless `StreamChannel[ToolCallStream]` is used (no protocol
-    auto-forwarding) because the live handles are not serializable and
-    should not be injected into the main event log. Wire consumers
-    subscribe to the `tools` channel instead, where the raw protocol
-    events flow through untouched by this transformer (`process`
-    returns `True`).
-
-    Registered explicitly by users at compile time via
-    `builder.compile(transformers=[ToolCallTransformer])` — not a
-    default built-in, so the `tools` channel is user-opt-in.
-    """
-
-    _native = True
-    required_stream_modes = ("tools",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: StreamChannel[ToolCallStream] = StreamChannel()
-        self._active: dict[str, ToolCallStream] = {}
-        self._is_async = False
-        self._pump_fn: Callable[[], bool] | None = None
-        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
-
-    def init(self) -> dict[str, Any]:
-        return {"tool_calls": self._log}
-
-    def _bind_pump(self, fn: Callable[[], bool]) -> None:
-        """Wire the sync pull callback onto this transformer.
-
-        Called by `StreamMux.bind_pump`. Stored so each new
-        `ToolCallStream` created by `process` can wire its deltas log
-        for pump-driven iteration.
-        """
-        self._pump_fn = fn
-        self._is_async = False
-
-    def _bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
-        """Async counterpart to `_bind_pump`."""
-        self._apump_fn = fn
-        self._is_async = True
-
-    def _new_stream(
-        self,
-        tool_call_id: str,
-        tool_name: str,
-        tool_input: dict[str, Any] | None,
-    ) -> ToolCallStream:
-        stream = ToolCallStream(tool_call_id, tool_name, tool_input)
-        stream._bind(is_async=self._is_async)
-        if self._apump_fn is not None:
-            stream._output_deltas._arequest_more = self._apump_fn
-        if self._pump_fn is not None:
-            stream._output_deltas._request_more = self._pump_fn
-        return stream
-
-    def process(self, event: ProtocolEvent) -> bool:
-        # Namespace filtering is handled by the mux via `scope_exact`.
-        if event["method"] != "tools":
-            return True
-
-        data = event["params"]["data"]
-        tool_call_id = data.get("tool_call_id")
-        if tool_call_id is None:
-            return True
-        event_type = data.get("event")
-
-        stream: ToolCallStream | None
-        if event_type == "tool-started":
-            stream = self._new_stream(
-                tool_call_id,
-                data.get("tool_name", ""),
-                data.get("input"),
-            )
-            self._active[tool_call_id] = stream
-            self._log.push(stream)
-        elif event_type == "tool-output-delta":
-            stream = self._active.get(tool_call_id)
-            if stream is not None:
-                stream._push_delta(data.get("delta"))
-        elif event_type == "tool-finished":
-            stream = self._active.pop(tool_call_id, None)
-            if stream is not None:
-                stream._finish(data.get("output"))
-        elif event_type == "tool-error":
-            stream = self._active.pop(tool_call_id, None)
-            if stream is not None:
-                stream._fail(data.get("message", ""))
-
-        # Pass-through — wire consumers subscribe to the `tools` channel
-        # directly and reconstruct handles client-side.
-        return True
-
-    def finalize(self) -> None:
-        """Close any still-active tool streams left open at run end."""
-        for stream in self._active.values():
-            if not stream.completed:
-                stream._finish(None)
-        self._active.clear()
-
-    def fail(self, err: BaseException) -> None:
-        """Fail any still-active tool streams when the run errors."""
-        message = str(err)
-        for stream in self._active.values():
-            if not stream.completed:
-                stream._fail(message)
-        self._active.clear()
@@ -82,11 +82,9 @@ 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
-from langgraph.pregel._tools import _tool_call_writer
 from langgraph.runtime import ExecutionInfo, ServerInfo  # noqa: TC002
 from langgraph.store.base import BaseStore  # noqa: TC002
 from langgraph.types import Command, Send, StreamWriter
@@ -616,7 +614,6 @@ class _InjectedArgs:
    store: str | None
    runtime: str | None
    all_injected_keys: set[str]
-    _optional_state_args: set[str]


 class ToolNode(RunnableCallable):
@@ -802,7 +799,7 @@ 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, cfg)
+            state = self._extract_state(input)
            tool_runtime = ToolRuntime(
                state=state,
                tool_call_id=call["id"],
@@ -810,7 +807,6 @@ class ToolNode(RunnableCallable):
                context=runtime.context,
                store=runtime.store,
                stream_writer=runtime.stream_writer,
-                tools=list(self.tools_by_name.values()),
                execution_info=runtime.execution_info,
                server_info=runtime.server_info,
            )
@@ -837,7 +833,7 @@ 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, cfg)
+            state = self._extract_state(input)
            tool_runtime = ToolRuntime(
                state=state,
                tool_call_id=call["id"],
@@ -845,7 +841,6 @@ class ToolNode(RunnableCallable):
                context=runtime.context,
                store=runtime.store,
                stream_writer=runtime.stream_writer,
-                tools=list(self.tools_by_name.values()),
                execution_info=runtime.execution_info,
                server_info=runtime.server_info,
            )
@@ -861,30 +856,14 @@ class ToolNode(RunnableCallable):

    def _combine_tool_outputs(
        self,
-        outputs: list[ToolMessage | Command | list[ToolMessage | Command]],
+        outputs: 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 flat_outputs):
+        if not any(isinstance(output, Command) for output in outputs):
            # TypedDict, pydantic, dataclass, etc. should all be able to load from dict
-            return (
-                flat_outputs
-                if input_type == "list"
-                else {self._messages_key: flat_outputs}
-            )
+            return outputs if input_type == "list" else {self._messages_key: outputs}

        # LangGraph will automatically handle list of Command and non-command node
        # updates
@@ -894,7 +873,7 @@ class ToolNode(RunnableCallable):

        # combine all parent commands with goto into a single parent command
        parent_command: Command | None = None
-        for output in flat_outputs:
+        for output in outputs:
            if isinstance(output, Command):
                if (
                    output.graph is Command.PARENT
@@ -924,7 +903,7 @@ class ToolNode(RunnableCallable):
        request: ToolCallRequest,
        input_type: Literal["list", "dict", "tool_calls"],
        config: RunnableConfig,
-    ) -> ToolMessage | Command | list[Command | ToolMessage]:
+    ) -> ToolMessage | Command:
        """Execute tool call with configured error handling.

        Args:
@@ -933,7 +912,7 @@ class ToolNode(RunnableCallable):
            config: Runnable configuration.

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

        Raises:
            Exception: If tool fails and handle_tool_errors is False.
@@ -965,11 +944,6 @@ 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
@@ -1011,12 +985,23 @@ 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 | list[Command | ToolMessage]:
+    ) -> ToolMessage | Command:
        """Execute single tool call with wrap_tool_call wrapper if configured.

        Args:
@@ -1071,7 +1056,7 @@ class ToolNode(RunnableCallable):
        request: ToolCallRequest,
        input_type: Literal["list", "dict", "tool_calls"],
        config: RunnableConfig,
-    ) -> ToolMessage | Command | list[Command | ToolMessage]:
+    ) -> ToolMessage | Command:
        """Execute tool call asynchronously with configured error handling.

        Args:
@@ -1080,7 +1065,7 @@ class ToolNode(RunnableCallable):
            config: Runnable configuration.

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

        Raises:
            Exception: If tool fails and handle_tool_errors is False.
@@ -1112,11 +1097,6 @@ 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
@@ -1158,12 +1138,23 @@ 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 | list[Command | ToolMessage]:
+    ) -> ToolMessage | Command:
        """Execute single tool call asynchronously with awrap_tool_call wrapper if configured.

        Args:
@@ -1279,37 +1270,18 @@ class ToolNode(RunnableCallable):
        return None

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

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

-        - `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.
+        Returns:
+            The actual state to pass to wrap_tool_call wrappers.
        """
        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(
@@ -1361,7 +1333,7 @@ class ToolNode(RunnableCallable):
            return tool_call

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

        # Inject state
        if injected.state:
@@ -1389,20 +1361,14 @@ class ToolNode(RunnableCallable):
            # Extract state values
            if isinstance(state, dict):
                for tool_arg, state_field in injected.state.items():
-                    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)
+                    injected_args[tool_arg] = (
+                        state[state_field] if state_field else state
+                    )
            else:
                for tool_arg, state_field in injected.state.items():
-                    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)
+                    injected_args[tool_arg] = (
+                        getattr(state, state_field) if state_field else state
+                    )

        # Inject store
        if injected.store:
@@ -1429,84 +1395,11 @@ 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
@@ -1556,11 +1449,7 @@ 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 (
-            require_terminator
-            and updated_command.graph is None
-            and not has_matching_tool_message
-        ):
+        if updated_command.graph is None and not has_matching_tool_message:
            example_update = (
                '`Command(update={"messages": '
                '[ToolMessage("Success", tool_call_id=tool_call_id), ...]}, ...)`'
@@ -1680,7 +1569,6 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
    - `context`: Runtime context (shared with `Runtime`)
    - `store`: `BaseStore` instance for persistent storage (shared with `Runtime`)
    - `stream_writer`: `StreamWriter` for streaming output (shared with `Runtime`)
-    - `tools`: List of all available `BaseTool` instances

    No `Annotated` wrapper is needed - just use `runtime: ToolRuntime`
    as a parameter.
@@ -1723,32 +1611,11 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
    context: ContextT
    config: RunnableConfig
    stream_writer: StreamWriter
-    tools: list[BaseTool]
    tool_call_id: str | None
    store: BaseStore | None
    execution_info: ExecutionInfo | None = None
    server_info: ServerInfo | None = None

-    def emit_output_delta(self, delta: Any) -> None:
-        """Stream a partial output chunk on the `tools` stream channel.
-
-        Reads the per-tool-call writer that `StreamToolCallHandler`
-        installs on a ContextVar at `on_tool_start` and forwards `delta`
-        through it. Silent no-op when the graph was not run with
-        `"tools"` in `stream_mode` (no writer is set), so tool authors
-        can leave `emit_output_delta` calls in place without gating
-        them on stream mode.
-
-        Args:
-            delta: Partial output chunk. Any JSON-serializable value;
-                surfaced as-is on the `tools` channel's
-                `tool-output-delta` payload under `"delta"`.
-        """
-        writer = _tool_call_writer.get()
-        if writer is None:
-            return
-        writer(delta)
-

 class InjectedState(InjectedToolArg):
    """Annotation for injecting graph state into tool arguments.
@@ -1992,7 +1859,6 @@ 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)
@@ -2007,9 +1873,6 @@ 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

@@ -2026,5 +1889,4 @@ 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 = "1.0.12"
+version = "1.0.9"
 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>=1.3.1",
+    "langchain-core>=1.0.0",
 ]

 [project.urls]
@@ -62,7 +62,6 @@ dev = [
 default-groups = ['dev']

 [tool.uv.sources]
-langchain-core = { git = "https://github.com/langchain-ai/langchain", branch = "cb/chat-model-updates", subdirectory = "libs/core" }
 langgraph = { path = "../langgraph", editable = true }
 langgraph-checkpoint = { path = "../checkpoint", editable = true }
 langgraph-checkpoint-sqlite = { path = "../checkpoint-sqlite", editable = true }
@@ -1,285 +0,0 @@
-"""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
@@ -1320,98 +1320,6 @@ 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"}
@@ -1,307 +0,0 @@
-"""Tests for ToolCallTransformer and the ToolCallStream projection."""
-
-from __future__ import annotations
-
-import time
-from typing import Annotated, Any
-
-import pytest
-from langchain_core.messages import AIMessage
-from langchain_core.tools import tool
-from langgraph.constants import END, START
-from langgraph.graph import StateGraph
-from langgraph.graph.message import add_messages
-from langgraph.stream._mux import StreamMux
-from langgraph.stream._types import ProtocolEvent
-from langgraph.stream.stream_channel import StreamChannel
-from langgraph.stream.transformers import (
-    MessagesTransformer,
-    ValuesTransformer,
-)
-from typing_extensions import TypedDict
-
-from langgraph.prebuilt import (
-    ToolCallTransformer,
-    ToolNode,
-    ToolRuntime,
-)
-from langgraph.prebuilt._tool_call_stream import ToolCallStream
-
-TS = int(time.time() * 1000)
-
-
-def _tool_event(
-    event: str,
-    tool_call_id: str,
-    *,
-    tool_name: str = "",
-    input: dict[str, Any] | None = None,
-    delta: Any = None,
-    output: Any = None,
-    message: str = "",
-    namespace: list[str] | None = None,
-) -> ProtocolEvent:
-    data: dict[str, Any] = {"event": event, "tool_call_id": tool_call_id}
-    if event == "tool-started":
-        data["tool_name"] = tool_name
-        if input is not None:
-            data["input"] = input
-    elif event == "tool-output-delta":
-        data["delta"] = delta
-    elif event == "tool-finished":
-        data["output"] = output
-    elif event == "tool-error":
-        data["message"] = message
-    return {
-        "type": "event",
-        "method": "tools",
-        "params": {
-            "namespace": namespace or [],
-            "timestamp": TS,
-            "data": data,
-        },
-    }
-
-
-def _subscribe(log: StreamChannel) -> None:
-    log._subscribed = True
-
-
-def _mux() -> tuple[StreamMux, ToolCallTransformer]:
-    transformer = ToolCallTransformer()
-    mux = StreamMux(
-        [
-            ValuesTransformer(),
-            MessagesTransformer(),
-            transformer,
-        ],
-        is_async=False,
-    )
-    _subscribe(transformer._log)
-    return mux, transformer
-
-
-class TestToolCallTransformerUnit:
-    def test_required_stream_modes_declares_tools(self) -> None:
-        assert ToolCallTransformer.required_stream_modes == ("tools",)
-
-    def test_tool_started_yields_handle(self) -> None:
-        mux, transformer = _mux()
-        mux.push(
-            _tool_event(
-                "tool-started",
-                "tc1",
-                tool_name="echo",
-                input={"text": "hi"},
-            )
-        )
-        handles = list(transformer._log._items)
-        assert len(handles) == 1
-        h = handles[0]
-        assert isinstance(h, ToolCallStream)
-        assert h.tool_call_id == "tc1"
-        assert h.tool_name == "echo"
-        assert h.input == {"text": "hi"}
-        assert h.completed is False
-
-    def test_delta_accumulates_on_active_stream(self) -> None:
-        mux, transformer = _mux()
-        mux.push(_tool_event("tool-started", "tc1", tool_name="echo"))
-        _subscribe(transformer._active["tc1"]._output_deltas)
-        mux.push(_tool_event("tool-output-delta", "tc1", delta="a"))
-        mux.push(_tool_event("tool-output-delta", "tc1", delta="b"))
-        stream = transformer._active["tc1"]
-        assert list(stream._output_deltas._items) == ["a", "b"]
-
-    def test_finish_closes_stream(self) -> None:
-        mux, transformer = _mux()
-        mux.push(_tool_event("tool-started", "tc1", tool_name="echo"))
-        stream = transformer._active["tc1"]
-        mux.push(_tool_event("tool-finished", "tc1", output="done"))
-        assert stream.completed is True
-        assert stream.output == "done"
-        assert stream.error is None
-        assert "tc1" not in transformer._active
-
-    def test_error_closes_stream(self) -> None:
-        mux, transformer = _mux()
-        mux.push(_tool_event("tool-started", "tc1", tool_name="boom"))
-        stream = transformer._active["tc1"]
-        mux.push(_tool_event("tool-error", "tc1", message="nope"))
-        assert stream.completed is True
-        assert stream.output is None
-        assert stream.error == "nope"
-        assert "tc1" not in transformer._active
-
-    def test_concurrent_tool_calls_do_not_bleed(self) -> None:
-        mux, transformer = _mux()
-        mux.push(_tool_event("tool-started", "a", tool_name="t"))
-        mux.push(_tool_event("tool-started", "b", tool_name="t"))
-        for tc in ("a", "b"):
-            _subscribe(transformer._active[tc]._output_deltas)
-        mux.push(_tool_event("tool-output-delta", "a", delta="A1"))
-        mux.push(_tool_event("tool-output-delta", "b", delta="B1"))
-        mux.push(_tool_event("tool-output-delta", "a", delta="A2"))
-        assert list(transformer._active["a"]._output_deltas._items) == ["A1", "A2"]
-        assert list(transformer._active["b"]._output_deltas._items) == ["B1"]
-
-    def test_tools_event_passes_through_main_log(self) -> None:
-        mux, transformer = _mux()
-        _subscribe(mux._events)
-        mux.push(_tool_event("tool-started", "tc1", tool_name="echo"))
-        kept = [e for e in mux._events._items if e["method"] == "tools"]
-        assert len(kept) == 1
-
-
-# ---------------------------------------------------------------------------
-# End-to-end tests with a real graph
-# ---------------------------------------------------------------------------
-
-
-class _State(TypedDict):
-    messages: Annotated[list, add_messages]
-
-
-def _build_graph(caller, tools):
-    sg = StateGraph(_State)
-    sg.add_node("caller", caller)
-    sg.add_node("tools", ToolNode(tools))
-    sg.add_edge(START, "caller")
-    sg.add_edge("caller", "tools")
-    sg.add_edge("tools", END)
-    return sg.compile()
-
-
-class TestToolCallTransformerEndToEnd:
-    def test_sync_streaming_tool_populates_tool_calls(self) -> None:
-        @tool
-        def streamer(text: str, runtime: ToolRuntime) -> str:
-            """streams chunks."""
-            for chunk in ("one", "two"):
-                runtime.emit_output_delta(chunk)
-            return text
-
-        def caller(state: _State) -> dict:
-            return {
-                "messages": [
-                    AIMessage(
-                        content="",
-                        tool_calls=[
-                            {"name": "streamer", "args": {"text": "x"}, "id": "tc1"}
-                        ],
-                    )
-                ]
-            }
-
-        graph = _build_graph(caller, [streamer])
-        run = graph.stream_v2({"messages": []}, transformers=[ToolCallTransformer])
-
-        tool_calls: list[ToolCallStream] = []
-        for tc in run.tool_calls:
-            tool_calls.append(tc)
-            deltas = list(tc.output_deltas)
-            assert deltas == ["one", "two"]
-        assert len(tool_calls) == 1
-        tc = tool_calls[0]
-        assert tc.tool_call_id == "tc1"
-        assert tc.tool_name == "streamer"
-        assert tc.completed is True
-        assert tc.error is None
-
-    def test_stream_modes_union_includes_tools(self) -> None:
-        @tool
-        def echo(text: str) -> str:
-            """echo."""
-            return text
-
-        def caller(state: _State) -> dict:
-            return {
-                "messages": [
-                    AIMessage(
-                        content="",
-                        tool_calls=[
-                            {"name": "echo", "args": {"text": "x"}, "id": "tc1"}
-                        ],
-                    )
-                ]
-            }
-
-        graph = _build_graph(caller, [echo])
-        # Without ToolCallTransformer, no tool_calls projection is
-        # exposed and no `tools` events flow through (required_stream_modes
-        # omits it).
-        run_no_tc = graph.stream_v2({"messages": []})
-        assert "tool_calls" not in run_no_tc._mux.extensions  # type: ignore[attr-defined]
-
-        # With ToolCallTransformer, the projection is present.
-        run = graph.stream_v2({"messages": []}, transformers=[ToolCallTransformer])
-        assert "tool_calls" in run._mux.extensions  # type: ignore[attr-defined]
-        # Drain so the run closes cleanly.
-        list(run.tool_calls)
-
-    @pytest.mark.anyio
-    async def test_async_streaming_tool_populates_tool_calls(self) -> None:
-        @tool
-        async def astreamer(text: str, runtime: ToolRuntime) -> str:
-            """async streams."""
-            runtime.emit_output_delta(text)
-            runtime.emit_output_delta(text + "!")
-            return text
-
-        async def caller(state: _State) -> dict:
-            return {
-                "messages": [
-                    AIMessage(
-                        content="",
-                        tool_calls=[
-                            {"name": "astreamer", "args": {"text": "hi"}, "id": "tc1"}
-                        ],
-                    )
-                ]
-            }
-
-        graph = _build_graph(caller, [astreamer])
-        run = await graph.astream_v2(
-            {"messages": []}, transformers=[ToolCallTransformer]
-        )
-
-        collected: list[ToolCallStream] = []
-        async for tc in run.tool_calls:
-            collected.append(tc)
-            deltas = [d async for d in tc.output_deltas]
-            assert deltas == ["hi", "hi!"]
-        assert len(collected) == 1
-        assert collected[0].completed is True
-        assert collected[0].error is None
-
-    def test_tool_error_populates_error_field(self) -> None:
-        @tool
-        def boom() -> str:
-            """raises."""
-            raise ValueError("nope")
-
-        def caller(state: _State) -> dict:
-            return {
-                "messages": [
-                    AIMessage(
-                        content="",
-                        tool_calls=[{"name": "boom", "args": {}, "id": "tc1"}],
-                    )
-                ]
-            }
-
-        graph = _build_graph(caller, [boom])
-        run = graph.stream_v2({"messages": []}, transformers=[ToolCallTransformer])
-
-        collected: list[ToolCallStream] = []
-        with pytest.raises(ValueError, match="nope"):
-            for tc in run.tool_calls:
-                collected.append(tc)
-                # Drain deltas so the error field is populated before we
-                # inspect it below.
-                list(tc.output_deltas)
-
-        assert len(collected) == 1
-        assert collected[0].error == "nope"
-        assert collected[0].output is None
-        assert collected[0].completed is True
@@ -2016,8 +2016,8 @@ async def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call_async()
    assert tool_message.tool_call_id == "call_dynamic_2"


-def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
-    """Test that execution_info, server_info, and tools are forwarded from Runtime to ToolRuntime."""
+def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
+    """Test that execution_info and server_info are forwarded from Runtime to ToolRuntime."""
    from langgraph.runtime import ExecutionInfo, ServerInfo

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

-    @dec_tool
-    def other_tool(y: int) -> str:
-        """Another tool available to the runtime."""
-        return str(y)
-
-    node = ToolNode([info_tool, other_tool])
+    node = ToolNode([info_tool])
    tool_call = {
        "name": "info_tool",
        "args": {"x": 1},
@@ -2060,21 +2054,17 @@ def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
    }
    msg = AIMessage("", tool_calls=[tool_call])
    config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
-    result = node.invoke({"messages": [msg]}, config=config)
+    node.invoke({"messages": [msg]}, config=config)

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


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

    exec_info = ExecutionInfo(
@@ -2100,15 +2090,9 @@ async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async(
        """Async tool that captures runtime info."""
        captured["execution_info"] = runtime.execution_info
        captured["server_info"] = runtime.server_info
-        captured["tools"] = runtime.tools
        return "ok"

-    @dec_tool
-    async def other_tool_async(y: int) -> str:
-        """Another async tool available to the runtime."""
-        return str(y)
-
-    node = ToolNode([info_tool_async, other_tool_async])
+    node = ToolNode([info_tool_async])
    tool_call = {
        "name": "info_tool_async",
        "args": {"x": 1},
@@ -2117,17 +2101,12 @@ async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async(
    }
    msg = AIMessage("", tool_calls=[tool_call])
    config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
-    result = await node.ainvoke({"messages": [msg]}, config=config)
+    await node.ainvoke({"messages": [msg]}, config=config)

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


 # --- InjectedToolArg security tests ---
@@ -2223,195 +2202,3 @@ 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
@@ -249,11 +249,10 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.3.2"
-source = { git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates#aee50839376e379891c99fcbe6d5264f66dedc68" }
+version = "1.2.25"
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
-    { name = "langchain-protocol" },
    { name = "langsmith" },
    { name = "packaging" },
    { name = "pydantic" },
@@ -262,22 +261,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-
-[[package]]
-name = "langchain-protocol"
-version = "0.0.14"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "typing-extensions" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/86/2a/d65de24fc9b7989137253da8973f850f3e39b4ce3e0377bc8200d6b3c189/langchain_core-1.2.25.tar.gz", hash = "sha256:77e032b96509d0eb1f6875042fdf97b7e2334a815314700c6894d9d078909b9c", size = 842347, upload-time = "2026-04-02T22:39:11.528Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c2/e9/06c47ecb2aff08f83dfa30058da3bf86be64862c19569043ed5331bbeecd/langchain_protocol-0.0.14-py3-none-any.whl", hash = "sha256:ffc35089779bd8ca217015180cef5e660fc3b074efdaa0f2e95df73583f1a047", size = 6984, upload-time = "2026-04-29T16:40:17.841Z" },
+    { url = "https://files.pythonhosted.org/packages/3d/0e/7b31b0249f9b9b0fc7829d5b0ee484b8f8d43c78e376e9951e2ef3eac70c/langchain_core-1.2.25-py3-none-any.whl", hash = "sha256:0c05bf395aec6d2dfa14488fd006f7bcd0540e7e89287e04f92203532a82c828", size = 506866, upload-time = "2026-04-02T22:39:10.137Z" },
 ]

 [[package]]
 name = "langgraph"
-version = "1.1.10"
+version = "1.1.6"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -290,7 +281,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=0.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "." },
    { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -302,7 +293,7 @@ requires-dist = [
 dev = [
    { name = "httpx" },
    { name = "jupyter" },
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -335,7 +326,7 @@ lint = [
 ]
 test = [
    { name = "httpx" },
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -361,7 +352,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "4.0.3"
+version = "4.0.1"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -370,7 +361,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=0.2.38" },
    { name = "ormsgpack", specifier = ">=1.12.0" },
 ]

@@ -499,7 +490,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.12"
+version = "1.0.9"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -544,14 +535,14 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

 [package.metadata.requires-dev]
 dev = [
    { name = "codespell" },
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core" },
    { name = "langgraph", editable = "../langgraph" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
@@ -571,7 +562,7 @@ lint = [
    { name = "ruff" },
 ]
 test = [
-    { name = "langchain-core", git = "https://github.com/langchain-ai/langchain?subdirectory=libs%2Fcore&branch=cb%2Fchat-model-updates" },
+    { name = "langchain-core" },
    { name = "langgraph", editable = "../langgraph" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
@@ -602,20 +593,20 @@ requires-dist = [
 dev = [
    { name = "codespell" },
    { name = "langgraph", editable = "../langgraph" },
-    { name = "mypy", specifier = "==1.20.2" },
+    { name = "mypy", specifier = "==1.19.1" },
    { name = "pydantic", specifier = ">=2.12.4" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
    { name = "pytest-watch" },
-    { name = "ruff", specifier = "==0.15.12" },
+    { name = "ruff", specifier = "==0.15.6" },
    { name = "starlette" },
    { name = "ty", specifier = "==0.0.23" },
 ]
 lint = [
    { name = "codespell" },
-    { name = "mypy", specifier = "==1.20.2" },
-    { name = "ruff", specifier = "==0.15.12" },
+    { name = "mypy", specifier = "==1.19.1" },
+    { name = "ruff", specifier = "==0.15.6" },
    { name = "starlette" },
    { name = "ty", specifier = "==0.0.23" },
 ]
@@ -628,7 +619,7 @@ test = [

 [[package]]
 name = "langsmith"
-version = "0.7.31"
+version = "0.6.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "httpx" },
@@ -638,12 +629,11 @@ dependencies = [
    { name = "requests" },
    { name = "requests-toolbelt" },
    { name = "uuid-utils" },
-    { name = "xxhash" },
    { name = "zstandard" },
 ]
-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" }
+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" }
 wheels = [
-    { 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" },
+    { url = "https://files.pythonhosted.org/packages/66/0f/09a6637a7ba777eb307b7c80852d9ee26438e2bdafbad6fcc849ff9d9192/langsmith-0.6.4-py3-none-any.whl", hash = "sha256:ac4835860160be371042c7adbba3cb267bcf8d96a5ea976c33a8a4acad6c5486", size = 283503, upload-time = "2026-01-15T20:02:26.662Z" },
 ]

 [[package]]
@@ -1192,7 +1182,7 @@ wheels = [

 [[package]]
 name = "pytest"
-version = "9.0.3"
+version = "9.0.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -1203,9 +1193,9 @@ dependencies = [
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