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
63 changed files with 6678 additions and 8818 deletions
@@ -623,7 +623,7 @@ 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'" },
@@ -634,9 +634,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
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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]]
@@ -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]
@@ -950,7 +950,7 @@ 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'" },
@@ -961,9 +961,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
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+    { url = "https://files.pythonhosted.org/packages/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]]
@@ -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 = [
    { name = "jsonpatch" },
@@ -261,9 +261,9 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
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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]]
@@ -862,7 +862,7 @@ 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'" },
@@ -873,9 +873,9 @@ dependencies = [
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    { 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" },
 ]

 [[package]]
@@ -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
@@ -56,10 +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__(
@@ -74,11 +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 = (
@@ -537,8 +530,7 @@ def _create_msgpack_ext_hook(
            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,
@@ -1117,7 +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'" },
@@ -1128,9 +1128,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
+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" }
 wheels = [
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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]]
@@ -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 "0.5.18"
-  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.18.tgz#c691ad23614f0b46eaf07d982e0ac988e1f43880"
-  integrity sha512-3zuZUWffTHQ+73EAwnodADtf534VNEZUpXr9jC12qyG8/IQuJET7PRsCpTb9wX2lmBspakwLUpqpj3tNm/0bVA==
+  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 "0.5.18"
-  resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.18.tgz#c691ad23614f0b46eaf07d982e0ac988e1f43880"
-  integrity sha512-3zuZUWffTHQ+73EAwnodADtf534VNEZUpXr9jC12qyG8/IQuJET7PRsCpTb9wX2lmBspakwLUpqpj3tNm/0bVA==
+  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==
@@ -907,7 +907,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.2.28"
+version = "1.2.27"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch", marker = "python_full_version >= '3.11'" },
@@ -919,9 +919,9 @@ dependencies = [
    { name = "typing-extensions", marker = "python_full_version >= '3.11'" },
    { name = "uuid-utils", marker = "python_full_version >= '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f8/a4/317a1a3ac1df33a64adb3670bf88bbe3b3d5baa274db6863a979db472897/langchain_core-1.2.28.tar.gz", hash = "sha256:271a3d8bd618f795fdeba112b0753980457fc90537c46a0c11998516a74dc2cb", size = 846119, upload-time = "2026-04-08T18:19:34.867Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/13/5c/56d19a252bbb26247b7a7cd20821d48804d7ca03212fec709cd8db7c2516/langchain_core-1.2.27.tar.gz", hash = "sha256:c18372e4c4c1454d49bf23a2e484431e71bd39b64173a0f621f0fc283d7183a4", size = 844935, upload-time = "2026-04-07T14:56:32.364Z" }
 wheels = [
-    { 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" },
+    { url = "https://files.pythonhosted.org/packages/c1/c3/6e0865bc130c448270eb9511b47863a3f9145cdb519b19f6e4758fa63d6f/langchain_core-1.2.27-py3-none-any.whl", hash = "sha256:9ecd6b0393b969fe88f6b9b309367134080ab095946d79e6937dd3911aa42bd5", size = 508315, upload-time = "2026-04-07T14:56:30.93Z" },
 ]

 [[package]]
@@ -2318,28 +2318,28 @@ wheels = [

 [[package]]
 name = "uv"
-version = "0.11.6"
+version = "0.11.3"
 source = { registry = "https://pypi.org/simple" }
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+sdist = { url = "https://files.pythonhosted.org/packages/88/ed/f11c558e8d2e02fba6057dacd9e92a71557359a80bd5355452310b89f40f/uv-0.11.3.tar.gz", hash = "sha256:6a6fcaf1fec28bbbdf0dfc5a0a6e34be4cea08c6287334b08c24cf187300f20d", size = 4027684, upload-time = "2026-04-01T21:47:22.096Z" }
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 ]

 [[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 GraphStreamer 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,
@@ -1,412 +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 add_handler(
-        self,
-        handler: BaseCallbackHandler,
-        inherit: bool = True,  # noqa: FBT001,FBT002
-    ) -> None:
-        if not isinstance(handler, GraphCallbackHandler):
-            raise TypeError("handlers must inherit GraphCallbackHandler")
-        super().add_handler(handler, inherit=inherit)
-
-    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 add_handler(
-        self,
-        handler: BaseCallbackHandler,
-        inherit: bool = True,  # noqa: FBT001,FBT002
-    ) -> None:
-        if not isinstance(handler, GraphCallbackHandler):
-            raise TypeError("handlers must inherit GraphCallbackHandler")
-        super().add_handler(handler, inherit=inherit)
-
-    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,
-    )
@@ -1,7 +1,5 @@
 import asyncio
 import sys
-from collections.abc import Callable
-from contextvars import ContextVar
 from typing import Any

 from langchain_core.runnables import RunnableConfig
@@ -11,18 +9,6 @@ from langgraph.store.base import BaseStore
 from langgraph._internal._constants import CONF, CONFIG_KEY_RUNTIME
 from langgraph.types import StreamWriter

-_tool_call_writer: ContextVar[Callable[[Any], None] | 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.
-Defined here (rather than alongside the handler in `pregel/_tools.py`)
-so `emit_tool_output_delta` can import it without triggering the
-pregel import chain — user tool code does
-`from langgraph.config import emit_tool_output_delta` at import time.
-"""
-

 def _no_op_stream_writer(c: Any) -> None:
    pass
@@ -208,30 +194,3 @@ def get_stream_writer() -> StreamWriter:
    """
    runtime = get_config()[CONF][CONFIG_KEY_RUNTIME]
    return runtime.stream_writer
-
-
-def emit_tool_output_delta(delta: Any) -> None:
-    """Emit a `tool-output-delta` event onto the `tools` stream mode.
-
-    Must be called from inside a tool's execution scope (sync or async).
-    While a tool is running, `StreamToolCallHandler.on_tool_start` sets a
-    writer closure on a ContextVar keyed to that call's `tool_call_id`
-    and namespace; this helper reads the ContextVar and forwards `delta`
-    through it.
-
-    When called outside any tool call, or when the graph was not
-    streamed with `"tools"` in `stream_mode`, this is a silent no-op —
-    tool authors can leave `emit_tool_output_delta` calls in place
-    without gating them on stream mode.
-
-    Args:
-        delta: The partial output chunk to stream. Shape is up to the
-            caller — strings are the common case, but any JSON-
-            serializable value is accepted and 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)
@@ -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[..., Any]] | None = None,
    ) -> CompiledStateGraph[StateT, ContextT, InputT, OutputT]:
        """Compiles the `StateGraph` into a `CompiledStateGraph` object.

@@ -1078,11 +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 zero-arg factories returning
-                `StreamTransformer` instances. Registered on the compiled
-                graph and instantiated per-run whenever `stream_v2` /
-                `astream_v2` is called. Appended after the built-in
-                `ValuesTransformer` and `MessagesTransformer`.

        Returns:
            CompiledStateGraph: The compiled `StateGraph`.
@@ -1165,7 +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

@@ -1,274 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import AsyncIterator, Callable, Iterator
-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.errors import GraphInterrupt
-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")
-
-
-_LANGGRAPH_SENTINEL_NODES = frozenset({"__start__", "__end__"})
-
-
-def _is_nested_pregel_start(
-    name: str | None,
-    metadata: dict[str, Any] | None,
-    parent_run_id: UUID | None,
-    task_run_ids: set[UUID],
-) -> bool:
-    """Recognize a nested `Pregel` invocation from its `on_chain_start` metadata.
-
-    When a compiled graph is added as a node, pregel fires two
-    `on_chain_start` callbacks at that task: first for the node chain
-    (whose `name` matches `metadata["langgraph_node"]`) and second for
-    the inner `Pregel` chain (whose `name` is the graph's `name`, not
-    the node name). Both share the same `langgraph_checkpoint_ns`.
-
-    Primary signal: a `langgraph_checkpoint_ns` is set AND `name`
-    differs from the owning task's `langgraph_node`. This covers the
-    common case where the compiled subgraph's name differs from the
-    node name it was registered under.
-
-    Fallback for name collisions (subgraph compiled with
-    `name == node_name`): the inner `Pregel` start's `parent_run_id`
-    is the run_id of the node chain's start event, which the handler
-    records in `task_run_ids` on the first start. Matching
-    `parent_run_id` to that set identifies the second start as the
-    nested `Pregel` even when names coincide.
-
-    Regular node chains are skipped; the root `Pregel` (which has no
-    `langgraph_node` metadata) isn't observed by this handler because
-    the root's start fires before the handler is attached.
-
-    Metadata-based detection is used because `on_chain_start`'s
-    `serialized` argument is `None` for compiled graphs in this
-    version of langchain-core, so class-based detection via
-    `serialized["id"]` isn't available.
-
-    Sentinel nodes (`__start__` / `__end__`) are excluded: conditional
-    edges from `START` fire an `on_chain_start` with `lg_node=__start__`
-    and the router function's name as `name`, which would otherwise
-    match the discriminator without representing an actual nested
-    `Pregel`.
-
-    Args:
-        name: The `name` kwarg from `on_chain_start`.
-        metadata: The `metadata` kwarg from `on_chain_start`.
-        parent_run_id: The `parent_run_id` kwarg from `on_chain_start`.
-        task_run_ids: The set of run_ids the handler has already seen
-            as node-chain starts (i.e. `name == langgraph_node`).
-    """
-    if not metadata:
-        return False
-    if not metadata.get("langgraph_checkpoint_ns"):
-        return False
-    lg_node = metadata.get("langgraph_node")
-    if lg_node is None or lg_node in _LANGGRAPH_SENTINEL_NODES:
-        return False
-    if name != lg_node:
-        return True
-    # Name collision fallback: the inner Pregel's parent_run_id is
-    # the node chain's run_id, which we recorded when that node
-    # chain's start fired.
-    return parent_run_id is not None and parent_run_id in task_run_ids
-
-
-class StreamLifecycleHandler(BaseCallbackHandler, _StreamingCallbackHandler):
-    """Callback handler that emits subgraph lifecycle events on the stream.
-
-    Pushes `LifecycleData`-shaped payloads onto the pregel stream under
-    the `"lifecycle"` mode, keyed by the subgraph's namespace tuple.
-    Drives the `started` → `running` → `completed` / `failed` /
-    `interrupted` state machine.
-
-    The handler is attached to `run_manager.inheritable_handlers` inside
-    a `Pregel.stream` / `astream` call, so it sees callbacks for every
-    descendant chain (nodes, nested `Pregel` subgraphs) but *not* for
-    the root `Pregel` whose start event has already fired. The root's
-    `started` event is emitted eagerly at construction; its terminal
-    state is emitted by `SubgraphTransformer.finalize` / `fail`.
-
-    `run_inline = True` keeps event ordering deterministic.
-    """
-
-    run_inline = True
-
-    def __init__(
-        self,
-        stream: Callable[[StreamChunk], None],
-        *,
-        root_graph_name: str | None = None,
-    ) -> None:
-        """Initialize the handler and emit the root graph's `started` event.
-
-        Args:
-            stream: Callable that accepts a `StreamChunk` tuple
-                `(namespace, mode, payload)` and enqueues it.
-            root_graph_name: The root `Pregel` instance's `name`, emitted
-                with the root's `started` lifecycle payload.
-        """
-        self.stream = stream
-        # Namespaces awaiting the started→running transition.
-        self._pending_running: set[tuple[str, ...]] = set()
-        # run_id → subgraph namespace; populated only for Pregel chains.
-        self._run_to_ns: dict[UUID, tuple[str, ...]] = {}
-        # run_ids of node-chain starts (name == langgraph_node); used
-        # as the parent_run_id fallback when a subgraph's name equals
-        # its node name. Cleared as each chain ends.
-        self._task_run_ids: set[UUID] = set()
-
-        root_payload: dict[str, Any] = {"event": "started"}
-        if root_graph_name is not None:
-            root_payload["graph_name"] = root_graph_name
-        self.stream(((), "lifecycle", root_payload))
-        self._pending_running.add(())
-
-    @staticmethod
-    def _subgraph_ns_from_metadata(metadata: dict[str, Any] | None) -> tuple[str, ...]:
-        """Return the running subgraph's own namespace from task metadata.
-
-        For a nested `Pregel` invoked as a node, `langgraph_checkpoint_ns`
-        ends at the node segment (no inner task appended yet), so
-        splitting on `NS_SEP` gives the subgraph's own namespace.
-        """
-        if not metadata:
-            return ()
-        nskey = metadata.get("langgraph_checkpoint_ns")
-        if not nskey:
-            return ()
-        return tuple(cast(str, nskey).split(NS_SEP))
-
-    @staticmethod
-    def _containing_ns_from_metadata(
-        metadata: dict[str, Any] | None,
-    ) -> tuple[str, ...]:
-        """Return the namespace of the subgraph that contains this task.
-
-        For an inner task with `langgraph_checkpoint_ns`
-        `"seg_a|seg_b"`, the containing subgraph is `("seg_a",)`.
-        """
-        if not metadata:
-            return ()
-        nskey = metadata.get("langgraph_checkpoint_ns")
-        if not nskey:
-            return ()
-        return tuple(cast(str, nskey).split(NS_SEP))[:-1]
-
-    def _emit(self, ns: tuple[str, ...], payload: dict[str, Any]) -> None:
-        self.stream((ns, "lifecycle", payload))
-
-    def tap_output_aiter(
-        self, run_id: UUID, output: AsyncIterator[T]
-    ) -> AsyncIterator[T]:
-        """Pass-through — required by the `_StreamingCallbackHandler` protocol.
-
-        Returns the iterator unchanged. A missing implementation lets
-        langchain's default `Protocol` body return `None`, which breaks
-        the `_consume_aiter` code path in `_runnable.py:900`.
-        """
-        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
-
-    def _fire_running_if_pending(self, ns: tuple[str, ...]) -> None:
-        if ns in self._pending_running:
-            self._pending_running.discard(ns)
-            self._emit(ns, {"event": "running"})
-
-    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:
-        # Any descendant activity transitions the containing subgraph to running.
-        containing = self._containing_ns_from_metadata(metadata)
-        self._fire_running_if_pending(containing)
-
-        name = cast(str | None, kwargs.get("name"))
-        lg_node = (metadata or {}).get("langgraph_node")
-
-        # Record node-chain starts so the name-collision fallback in
-        # `_is_nested_pregel_start` can match the inner Pregel's
-        # parent_run_id to them.
-        if (
-            lg_node is not None
-            and lg_node not in _LANGGRAPH_SENTINEL_NODES
-            and name == lg_node
-        ):
-            self._task_run_ids.add(run_id)
-
-        if not _is_nested_pregel_start(
-            name, metadata, parent_run_id, self._task_run_ids
-        ):
-            return
-
-        ns = self._subgraph_ns_from_metadata(metadata)
-        if not ns:
-            return
-
-        self._run_to_ns[run_id] = ns
-        payload: dict[str, Any] = {"event": "started"}
-        if name:
-            payload["graph_name"] = name
-        # `cause` is intentionally not populated here: pregel does not know
-        # what on the parent namespace triggered this subgraph. Product-
-        # specific stream transformers populate `cause` before events
-        # reach the wire. See LifecycleCause in the protocol definition.
-        self._emit(ns, payload)
-        self._pending_running.add(ns)
-
-    def on_chain_end(
-        self,
-        response: Any,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self._task_run_ids.discard(run_id)
-        ns = self._run_to_ns.pop(run_id, None)
-        if ns is None:
-            return
-        # Ensure started→running fired even for empty subgraphs.
-        if ns in self._pending_running:
-            self._pending_running.discard(ns)
-            self._emit(ns, {"event": "running"})
-        self._emit(ns, {"event": "completed"})
-
-    def on_chain_error(
-        self,
-        error: BaseException,
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        **kwargs: Any,
-    ) -> Any:
-        self._task_run_ids.discard(run_id)
-        ns = self._run_to_ns.pop(run_id, None)
-        if ns is None:
-            return
-        self._pending_running.discard(ns)
-        if isinstance(error, GraphInterrupt):
-            self._emit(ns, {"event": "interrupted"})
-        else:
-            self._emit(ns, {"event": "failed", "error": str(error)})
@@ -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:
@@ -830,8 +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:
@@ -932,10 +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")
@@ -962,11 +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)
@@ -1088,7 +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,
@@ -1110,7 +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:
@@ -1186,7 +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):
@@ -1287,7 +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,
@@ -1309,7 +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:
@@ -1388,7 +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):
@@ -14,7 +14,7 @@ from langchain_core.messages import BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
 from pydantic import BaseModel

-from langgraph._internal._constants import NS_END, NS_SEP
+from langgraph._internal._constants import NS_SEP
 from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
 from langgraph.pregel.protocol import StreamChunk
 from langgraph.types import Command
@@ -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]]

@@ -137,23 +132,15 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
        **kwargs: Any,
    ) -> Any:
        if metadata and (not tags or (TAG_NOSTREAM not in tags)):
-            task_checkpoint_ns = cast(str, metadata["langgraph_checkpoint_ns"])
-            checkpoint_ns = (
-                f"{task_checkpoint_ns.rsplit(NS_END, 1)[0]}{NS_END}"
-                if NS_END in task_checkpoint_ns
-                else task_checkpoint_ns
-            )
-            ns = tuple(task_checkpoint_ns.split(NS_SEP))[:-1]
+            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
-            stream_metadata = dict(metadata)
-            stream_metadata["langgraph_checkpoint_ns"] = checkpoint_ns
-            # Preserve backwards-compatible streamed checkpoint metadata shape.
-            stream_metadata["checkpoint_ns"] = checkpoint_ns
            if tags:
                if filtered_tags := [t for t in tags if not t.startswith("seq:step")]:
-                    stream_metadata["tags"] = filtered_tags
-            self.metadata[run_id] = (ns, stream_metadata)
+                    metadata["tags"] = filtered_tags
+            self.metadata[run_id] = (ns, metadata)

    def on_llm_new_token(
        self,
@@ -261,185 +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
-    `GraphStreamer` 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_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:
-        """Record metadata with the FULL checkpoint namespace for v2.
-
-        v1's ``on_chat_model_start`` (inherited) slices the ns tuple
-        with ``[:-1]`` to re-position chat model tokens onto the
-        *containing pregel's* namespace — historically convenient for
-        consumers of ``stream_mode="messages"`` who want "where did
-        this node produce its output" rather than the chat-model's
-        own task ns.
-
-        For the protocol-v2 wire shape that is wrong: the client
-        subscribes the root feed at ``namespaces=[[]]`` with
-        ``depth=1``, and any message emitted at depth ``>=1`` that
-        still carries the containing node's ns must appear at the
-        *full* path from root so that depth filtering cleanly isolates
-        subgraph chatter from the root conversation. JS's
-        ``StreamMessagesHandlerV2`` already does
-        ``metadata.langgraph_checkpoint_ns.split("|")`` (no slice); this
-        override brings the Python v2 handler to the same shape.
-
-        Without this, a chat model invoked inside a nested subgraph
-        (e.g. ``research -> researcher``, ``research`` being a root
-        node that ``.ainvoke()``s a ``researcher`` subgraph) emits at
-        ``["research:<task>"]`` — a single level deep — which slips
-        through the root-feed depth-1 filter and pollutes the main
-        conversation with subgraph tokens. With this override we emit
-        at ``["research:<task>", "researcher:<task>"]`` so the client
-        routes those tokens to the subgraph card instead.
-        """
-        if metadata and (not tags or (TAG_NOSTREAM not in tags)):
-            task_checkpoint_ns = cast(str, metadata["langgraph_checkpoint_ns"])
-            # Keep the trailing ``:<task_id>`` segment (unlike the v1
-            # handler which strips it via ``[:-1]``). The client's
-            # lifecycle events land on the same ns, so message deltas
-            # now correlate 1:1 with a ``lifecycle: started`` event —
-            # ``useMessages(stream, subgraph)`` picks them up without
-            # needing to collapse sibling namespaces.
-            ns = tuple(task_checkpoint_ns.split(NS_SEP))
-            if not self.subgraphs and len(ns) > 1 and ns != self.parent_ns:
-                return
-            stream_metadata = dict(metadata)
-            # Preserve the v1-shaped ``langgraph_checkpoint_ns`` (task
-            # id stripped, trailing ``NS_END`` retained) so downstream
-            # consumers reading checkpoint metadata off a streamed
-            # message see the same shape they did pre-v2. Only the ns
-            # tuple emitted on the wire changes.
-            checkpoint_ns = (
-                f"{task_checkpoint_ns.rsplit(NS_END, 1)[0]}{NS_END}"
-                if NS_END in task_checkpoint_ns
-                else task_checkpoint_ns
-            )
-            stream_metadata["langgraph_checkpoint_ns"] = checkpoint_ns
-            stream_metadata["checkpoint_ns"] = checkpoint_ns
-            if tags:
-                if filtered_tags := [t for t in tags if not t.startswith("seq:step")]:
-                    stream_metadata["tags"] = filtered_tags
-            self.metadata[run_id] = (ns, stream_metadata)
-
-    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:
-        """Record chain (node) metadata with the FULL checkpoint ns.
-
-        Mirror of :meth:`on_chat_model_start` for the node-start path,
-        so messages returned by ``on_chain_end`` (``Command`` updates
-        and plain state dict outputs) land at the same full-path ns as
-        any chat-model deltas from within that node. See the
-        :meth:`on_chat_model_start` docstring for why the v1 ``[:-1]``
-        slice is dropped here.
-        """
-        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))
-            if not self.subgraphs and len(ns) > 1:
-                return
-            self.metadata[run_id] = (ns, metadata)
-            for value in _state_values(inputs):
-                if isinstance(value, BaseMessage):
-                    if value.id is not None:
-                        self.seen.add(value.id)
-                elif isinstance(value, Sequence) and not isinstance(value, str):
-                    for item in value:
-                        if isinstance(item, BaseMessage):
-                            if item.id is not None:
-                                self.seen.add(item.id)
-
-    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 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":
-                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"]
@@ -1,223 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import AsyncIterator, Callable, Iterator
-from contextvars import 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.config import _tool_call_writer
-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."""
-
-
-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`. The
-    `emit_tool_output_delta` helper in `langgraph.config` 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]) -> None:
-        """Initialize the handler.
-
-        Args:
-            stream: Callable that accepts a `StreamChunk` tuple
-                `(namespace, mode, payload)` and enqueues it.
-        """
-        self.stream = stream
-        # 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]]
-        ] = {}
-
-    @staticmethod
-    def _containing_ns_from_metadata(
-        metadata: dict[str, Any] | None,
-    ) -> tuple[str, ...]:
-        """Return the namespace of the subgraph that contains this tool call.
-
-        `langgraph_checkpoint_ns` on a tool's callback metadata ends with
-        the `node_name:task_id` segment of the node that invoked the
-        tool. Dropping that segment gives the subgraph's own namespace,
-        which matches what other `tools` / `lifecycle` / `messages`
-        emitters use.
-        """
-        if not metadata:
-            return ()
-        nskey = metadata.get("langgraph_checkpoint_ns")
-        if not nskey:
-            return ()
-        return tuple(cast(str, nskey).split(NS_SEP))[:-1]
-
-    def _start(
-        self,
-        serialized: dict[str, Any] | None,
-        input_str: str,
-        *,
-        run_id: UUID,
-        metadata: dict[str, Any] | None,
-        inputs: dict[str, Any] | None,
-        kwargs: dict[str, Any],
-    ) -> None:
-        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 ""
-        )
-        ns = self._containing_ns_from_metadata(metadata)
-
-        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,
-            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
@@ -130,19 +123,18 @@ from langgraph.pregel._checkpoint import (
 )
 from langgraph.pregel._draw import draw_graph
 from langgraph.pregel._io import map_input, read_channels
-from langgraph.pregel._lifecycle import StreamLifecycleHandler
 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
@@ -346,65 +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 are registered (or none declares
-    a given mode), the graph does not stream events for that mode.
-    """
-    modes: set[str] = set()
-    for transformer in mux._transformers:
-        modes.update(transformer.required_stream_modes)
-    return cast("list[StreamMode]", list(modes))
-
-
-def _build_stream_factories(
-    compile_time: Sequence[Callable[..., Any]],
-    call_site: Sequence[Any] | None,
-) -> list[Callable[..., Any]]:
-    """Assemble the factory list handed to `StreamMux(factories=...)`.
-
-    Prepends the built-in `ValuesTransformer`, `MessagesTransformer`,
-    and `SubgraphTransformer` factories, then appends the graph's
-    compile-time `stream_transformers` followed by any call-site
-    additions. Factories flow down into subgraph mini-muxes, so
-    per-scope instances propagate automatically.
-    """
-    from langgraph.stream.transformers import (
-        MessagesTransformer,
-        SubgraphTransformer,
-        ToolLifecycleTransformer,
-        ValuesTransformer,
-    )
-
-    builtins: list[Callable[..., Any]] = [
-        ValuesTransformer,
-        ToolLifecycleTransformer,
-        MessagesTransformer,
-        SubgraphTransformer,
-    ]
-    return [*builtins, *compile_time, *(call_site or ())]
-
-
-def _merge_v2_messages_flag(
-    config: RunnableConfig | None,
-) -> RunnableConfig:
-    """Return a config with the v2 messages flag set in `configurable`.
-
-    Signals to pregel that `stream_mode="messages"` should attach
-    `StreamMessagesHandlerV2` for this call so invoke-time model runs
-    route through the v2 event generator and their protocol events
-    reach the messages channel.
-    """
-    merged: RunnableConfig = dict(config or {})  # type: ignore[assignment]
-    configurable = dict(merged.get(CONF) or {})
-    configurable[CONFIG_KEY_STREAM_MESSAGES_V2] = True
-    merged[CONF] = configurable
-    return merged
-
-
 class Pregel(
    PregelProtocol[StateT, ContextT, InputT, OutputT],
    Generic[StateT, ContextT, InputT, OutputT],
@@ -736,7 +669,6 @@ class Pregel(
        config: RunnableConfig | None = None,
        trigger_to_nodes: Mapping[str, Sequence[str]] | None = None,
        name: str = "LangGraph",
-        stream_transformers: Sequence[Callable[..., Any]] | None = None,
        **deprecated_kwargs: Unpack[DeprecatedKwargs],
    ) -> None:
        if (
@@ -783,9 +715,6 @@ class Pregel(
        self.config = config
        self.trigger_to_nodes = trigger_to_nodes or {}
        self.name = name
-        self._stream_transformers: tuple[Callable[..., Any], ...] = tuple(
-            stream_transformers or ()
-        )
        self._serde_allowlist: set[tuple[str, ...]] | None = None
        if auto_validate:
            self.validate()
@@ -876,15 +805,6 @@ class Pregel(

    def copy(self, update: dict[str, Any] | None = None) -> Self:
        attrs = {k: v for k, v in self.__dict__.items() if k != "__orig_class__"}
-        # ``__init__`` accepts ``stream_transformers`` (public parameter) but
-        # the attribute is stored as ``_stream_transformers`` (private). Map
-        # the private key back onto the public kwarg so compile-time
-        # transformers survive ``copy()`` / ``with_config()``. Without this,
-        # ``_stream_transformers`` gets captured by ``**deprecated_kwargs``
-        # and the resulting instance silently has an empty transformer
-        # pipeline.
-        if "_stream_transformers" in attrs:
-            attrs["stream_transformers"] = attrs.pop("_stream_transformers")
        attrs.update(update or {})
        return self.__class__(**attrs)

@@ -2669,10 +2589,6 @@ class Pregel(
            name=config.get("run_name", self.get_name()),
            run_id=config.get("run_id"),
        )
-        graph_callback_manager = get_sync_graph_callback_manager_for_config(
-            config,
-            run_id=run_manager.run_id,
-        )
        try:
            # assign defaults
            (
@@ -2704,34 +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))
-                messages_handler_cls = (
-                    StreamMessagesHandlerV2
-                    if config[CONF].get(CONFIG_KEY_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 lifecycle stream mode
-            if "lifecycle" in stream_modes:
-                run_manager.inheritable_handlers.append(
-                    StreamLifecycleHandler(
-                        stream.put,
-                        root_graph_name=self.name,
-                    )
-                )
-
-            # set up tools stream mode
-            if "tools" in stream_modes:
-                run_manager.inheritable_handlers.append(
-                    StreamToolCallHandler(stream.put)
-                )
-
            # set up custom stream mode
            if "custom" in stream_modes:

@@ -2777,17 +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),
@@ -2808,9 +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(
@@ -2872,11 +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,
@@ -3051,10 +2939,6 @@ class Pregel(
            name=config.get("run_name", self.get_name()),
            run_id=config.get("run_id"),
        )
-        graph_callback_manager = get_async_graph_callback_manager_for_config(
-            config,
-            run_id=run_manager.run_id,
-        )
        # if running from astream_log() run each proc with streaming
        do_stream = (
            next(
@@ -3062,7 +2946,10 @@ class Pregel(
                    True
                    for h in run_manager.handlers
                    if isinstance(h, _StreamingCallbackHandler)
-                    and not isinstance(h, StreamMessagesHandler)
+                    and not isinstance(
+                        h,
+                        (StreamMessagesHandler, StreamProtocolMessagesHandler),
+                    )
                ),
                False,
            )
@@ -3099,36 +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))
-                messages_handler_cls = (
-                    StreamMessagesHandlerV2
-                    if config[CONF].get(CONFIG_KEY_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 lifecycle stream mode
-            if "lifecycle" in stream_modes:
-                run_manager.inheritable_handlers.append(
-                    StreamLifecycleHandler(
-                        stream_put,
-                        root_graph_name=self.name,
-                    )
-                )
-
-            # set up tools stream mode
-            if "tools" in stream_modes:
-                run_manager.inheritable_handlers.append(
-                    StreamToolCallHandler(stream_put)
-                )
-
            # set up custom stream mode
            def stream_writer(c: Any) -> None:
                aioloop.call_soon_threadsafe(
@@ -3189,28 +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),
@@ -3231,9 +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(
@@ -3315,7 +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)
@@ -3324,8 +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,
@@ -3355,106 +3201,6 @@ class Pregel(
            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[Any] | None = None,
-        stream_modes: Sequence[StreamMode] | None = None,
-        output_keys: str | Sequence[str] | None = None,
-        **kwargs: Any,
-    ) -> 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.
-
-        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 instances appended after
-                compile-time `stream_transformers`.
-
-        Returns:
-            A `GraphRunStream` the caller iterates to drive the run.
-        """
-        from langgraph.stream._mux import StreamMux
-        from langgraph.stream.run_stream import GraphRunStream
-
-        factories = _build_stream_factories(self._stream_transformers, transformers)
-        mux = StreamMux(factories=factories, is_async=False)
-        requested_stream_modes = set(_collect_stream_modes(mux))
-        requested_stream_modes.update(stream_modes or ())
-        graph_iter = iter(
-            self.stream(
-                input,
-                _merge_v2_messages_flag(config),
-                stream_mode=list(requested_stream_modes),
-                subgraphs=True,
-                version="v2",
-                output_keys=output_keys,
-                interrupt_before=interrupt_before,
-                interrupt_after=interrupt_after,
-                **kwargs,
-            )
-        )
-        return GraphRunStream(graph_iter, mux)
-
-    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[Any] | None = None,
-        stream_modes: Sequence[StreamMode] | None = None,
-        output_keys: str | Sequence[str] | None = None,
-        **kwargs: Any,
-    ) -> 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.
-
-        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 instances appended after
-                compile-time `stream_transformers`.
-        """
-        from langgraph.stream._mux import StreamMux
-        from langgraph.stream.run_stream import AsyncGraphRunStream
-
-        factories = _build_stream_factories(self._stream_transformers, transformers)
-        mux = StreamMux(factories=factories, is_async=True)
-        requested_stream_modes = set(_collect_stream_modes(mux))
-        requested_stream_modes.update(stream_modes or ())
-        graph_aiter = self.astream(
-            input,
-            _merge_v2_messages_flag(config),
-            stream_mode=list(requested_stream_modes),
-            subgraphs=True,
-            version="v2",
-            output_keys=output_keys,
-            interrupt_before=interrupt_before,
-            interrupt_after=interrupt_after,
-            **kwargs,
-        ).__aiter__()
-        return AsyncGraphRunStream(graph_aiter, mux)
-
    @overload
    def invoke(
        self,
@@ -3933,14 +3679,15 @@ def _coerce_checkpoint_values(payload: Any, mapper: Callable[[Any], Any]) -> Non
 def _build_server_info(
    config: RunnableConfig, parent_runtime: Runtime[Any]
 ) -> ServerInfo | None:
-    """Build ServerInfo from config 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")
@@ -650,46 +650,22 @@ class RemoteGraph(PregelProtocol):
        """
        updated_stream_modes: list[StreamModeSDK] = []
        req_single = True
-        # `"lifecycle"` is emitted locally by the `StreamLifecycleHandler`
-        # attached inside `Pregel.stream` / `astream`. The remote graph
-        # API has no corresponding mode, so requests for it against a
-        # `RemoteGraph` are silently stripped here and a warning is
-        # logged so the caller isn't left wondering why no lifecycle
-        # events arrive.
-        dropped_lifecycle = False
        # coerce to list, or add default stream mode
        if stream_mode:
            if isinstance(stream_mode, str):
-                if stream_mode != "lifecycle":
-                    updated_stream_modes.append(cast(StreamModeSDK, stream_mode))
-                else:
-                    dropped_lifecycle = True
+                updated_stream_modes.append(stream_mode)
            else:
                req_single = False
-                for m in stream_mode:
-                    if m == "lifecycle":
-                        dropped_lifecycle = True
-                    else:
-                        updated_stream_modes.append(cast(StreamModeSDK, m))
+                updated_stream_modes.extend(stream_mode)
        else:
-            updated_stream_modes.append(default)  # type: ignore[arg-type]
+            updated_stream_modes.append(default)
        requested_stream_modes = updated_stream_modes.copy()
        # add any from parent graph
        stream: StreamProtocol | None = (
            (config or {}).get(CONF, {}).get(CONFIG_KEY_STREAM)
        )
        if stream:
-            for m in stream.modes:
-                if m == "lifecycle":
-                    dropped_lifecycle = True
-                else:
-                    updated_stream_modes.append(cast(StreamModeSDK, m))
-        if dropped_lifecycle:
-            logger.warning(
-                "Stream mode 'lifecycle' is not supported by RemoteGraph "
-                "and was stripped from the request; no lifecycle events "
-                "will be emitted for this remote run."
-            )
+            updated_stream_modes.extend(stream.modes)
        # map "messages" to "messages-tuple"
        if "messages" in updated_stream_modes:
            updated_stream_modes.remove("messages")
@@ -1,20 +1,49 @@
-"""Streaming 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.
-"""
+"""Stream protocol types and infrastructure for LangGraph."""

+from langgraph.stream._convert import STREAM_V2_MODES, convert_to_protocol_event
 from langgraph.stream._event_log import EventLog
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.run_stream import AsyncGraphRunStream, GraphRunStream
-from langgraph.stream.stream_channel import StreamChannel
+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, is_stream_channel
+from langgraph.stream.streaming_handler import StreamingHandler
+from langgraph.stream.transformers import (
+    MessagesTransformer,
+    ValuesTransformer,
+)

 __all__ = [
+    "STREAM_V2_MODES",
+    "AsyncStreamMux",
+    "AsyncChatModelStream",
    "AsyncGraphRunStream",
+    "AsyncSubgraphRunStream",
+    "ChatModelStream",
    "EventLog",
    "GraphRunStream",
+    "InterruptPayload",
+    "MessagesTransformer",
    "ProtocolEvent",
    "StreamChannel",
+    "StreamMux",
+    "SubgraphRunStream",
    "StreamTransformer",
+    "StreamingHandler",
+    "ValuesTransformer",
+    "convert_to_protocol_event",
+    "create_async_graph_run_stream",
+    "create_graph_run_stream",
+    "is_stream_channel",
 ]
@@ -1,71 +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 _is_v2_messages_payload(data: Any) -> bool:
-    return isinstance(data, dict) and isinstance(data.get("event"), str)
+def convert_to_protocol_event(
+    ns: tuple[str, ...],
+    mode: str,
+    payload: Any,
+    *,
+    node: str | None = None,
+) -> ProtocolEvent | None:
+    """Convert a ``StreamChunk`` to a ``ProtocolEvent``.

+    Returns ``None`` for unsupported or unknown modes.

-def _normalize_messages_data(data: dict[str, Any]) -> dict[str, Any]:
-    """Normalize Python Core message fields to the protocol wire shape."""
-    normalized = {**data}
-    if (
-        normalized["event"] == "message-start"
-        and "id" not in normalized
-        and isinstance(normalized.get("message_id"), str)
-    ):
-        normalized["id"] = normalized["message_id"]
-    if (
-        normalized["event"]
-        in ("content-block-start", "content-block-delta", "content-block-finish")
-        and "content" not in normalized
-        and isinstance(normalized.get("content_block"), dict)
-    ):
-        normalized["content"] = normalized["content_block"]
-    normalized.pop("message_id", None)
-    normalized.pop("content_block", None)
-    return normalized
+    The ``seq`` field is left as ``0`` here; the :class:`StreamMux` is
+    the sole seq assigner and overwrites it inside ``push()``.

-
-def convert_to_protocol_event(part: StreamPart) -> ProtocolEvent:
-    """Convert a v2 StreamPart to a ProtocolEvent.
-
-    Args:
-        part: A stream part with keys `type`, `ns`, `data`, and
-            optionally `interrupts` (present on values events).
-
-    Returns:
-        The equivalent ProtocolEvent.
+    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)
-    data = part_dict["data"]
+    if mode not in _SUPPORTED_MODES:
+        return None
+
    params: _ProtocolEventParams = {
-        "namespace": list(part_dict["ns"]),
-        "timestamp": int(time.time() * 1000),
-        "data": data,
-    }
-    if (
-        part_dict["type"] == "messages"
-        and isinstance(data, tuple)
-        and len(data) == 2
-        and _is_v2_messages_payload(data[0])
-        and isinstance(data[1], dict)
-    ):
-        payload, metadata = data
-        params["data"] = _normalize_messages_data(payload)
-        if isinstance(metadata.get("langgraph_node"), str):
-            params["node"] = metadata["langgraph_node"]
-        if isinstance(metadata.get("run_id"), str):
-            params["run_id"] = metadata["run_id"]
-    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"]
@@ -1,306 +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
-from collections import deque
-from collections.abc import AsyncIterator, Awaitable, Callable, Iterator
+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]):
-    """Single-consumer drainable queue for streaming events.
+    """Append-only event buffer with cursor-based async iteration.

-    Items are popped off the front as the consumer advances — there is
-    no retention beyond what's currently queued. A log 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.
-    The only shape where a log can accumulate meaningfully is
-    concurrent async consumers at unequal rates — a slow consumer's
-    log grows while fast consumers drive the shared pump. That's the
-    documented tradeoff for concurrent consumption; consume at similar
-    rates or use a single consumer if memory matters.
-
-    Lazy-subscribe: `push` is a no-op when no subscriber has registered.
-    Transformers still execute `process()` (so scalar state like
-    `ValuesTransformer._latest` stays current); only the log append is
-    skipped.
+    Multiple consumers can subscribe independently and each will see
+    every event from their starting offset onward.
    """

-    def __init__(self, maxlen: int | None = None) -> None:
-        """Initialize an empty, unbound log.
+    __slots__ = ("_items", "_closed", "_error", "_waiters", "_lock")

-        Args:
-            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("EventLog maxlen must be a positive int or None")
-        self._items: deque[T] = deque()
-        self._maxlen: int | None = maxlen
+    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()

-        # Binding state — None means unbound.
-        self._is_async: bool | None = None
+    # -- Producer API -------------------------------------------------------

-        # Flipped on first __iter__ / __aiter__. Pre-subscription
-        # pushes are silent no-ops.
-        self._subscribed = False
-
-        # Pump wiring set by the run stream after bind.
-        self._request_more: Callable[[], bool] | None = None
-        self._arequest_more: Callable[[], Awaitable[bool]] | None = None
-
-    # ------------------------------------------------------------------
-    # Binding
-    # ------------------------------------------------------------------
-
-    def _bind(self, *, is_async: bool) -> None:
-        """Bind this log 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 log has already been bound.
-        """
-        if self._is_async is not None:
-            raise RuntimeError("EventLog is already bound")
-        self._is_async = is_async
-
-    # ------------------------------------------------------------------
-    # Producer API
-    # ------------------------------------------------------------------
-
-    def push(self, item: T) -> None:
-        """Append an item. No-op when no subscriber is registered.
-
-        Non-blocking in both sync and async — matches v1's
-        `put_nowait` producer shape. Memory is bounded by caller pace
-        via the caller-driven pump.
-
-        Raises:
-            RuntimeError: If the log is closed (and subscribed).
-        """
-        if not self._subscribed:
-            return
-        if self._closed:
-            raise RuntimeError("Cannot push to a closed EventLog")
-        self._items.append(item)
+    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."""
-        self._closed = True
+        """Mark the log as complete.  Iterators will end gracefully."""
+        with self._lock:
+            self._closed = True
+            self._wake_all()

-    def fail(self, err: BaseException) -> None:
-        """Mark the log as errored.
+    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()

-        Args:
-            err: The exception to surface to the subscriber.
-        """
-        self._error = err
-        self._closed = True
+    # -- Consumer API -------------------------------------------------------

-    # ------------------------------------------------------------------
-    # Sync iteration (caller-driven pump)
-    # ------------------------------------------------------------------
+    def __aiter__(self) -> _Cursor[T]:
+        """Return a fresh cursor from the beginning of the log."""
+        return _Cursor(self)

-    def __iter__(self) -> Iterator[T]:
-        """Subscribe and return a sync cursor. Can be called only once.
+    # -- Inspection ---------------------------------------------------------

-        Raises:
-            TypeError: If the log is unbound or bound to async mode.
-            RuntimeError: If the log already has a subscriber.
-        """
-        if self._is_async is None:
-            raise TypeError(
-                "EventLog has not been bound yet. "
-                "Register the transformer with a StreamMux first."
-            )
-        if self._is_async:
-            raise TypeError(
-                "This EventLog is bound to async mode — use 'async for' instead."
-            )
-        if self._subscribed:
-            raise RuntimeError(
-                "EventLog already has a subscriber; use .tee(n) for fan-out."
-            )
-        self._subscribed = True
-        return self._sync_cursor()
+    def __len__(self) -> int:
+        return len(self._items)

-    def _sync_cursor(self) -> Iterator[T]:
+    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:
-            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)
-    # ------------------------------------------------------------------
-
-    def __aiter__(self) -> AsyncIterator[T]:
-        """Subscribe and return an async cursor. Can be called only once.
-
-        Raises:
-            TypeError: If the log is unbound or bound to sync mode.
-            RuntimeError: If the log already has a subscriber.
-        """
-        if self._is_async is None:
-            raise TypeError(
-                "EventLog has not been bound yet. "
-                "Register the transformer with a StreamMux first."
-            )
-        if not self._is_async:
-            raise TypeError("This EventLog is bound to sync mode — use 'for' instead.")
-        if self._subscribed:
-            raise RuntimeError(
-                "EventLog already has a subscriber; use .atee(n) for fan-out."
-            )
-        self._subscribed = True
-        return self._async_cursor()
-
-    async def _async_cursor(self) -> AsyncIterator[T]:
-        while True:
-            if self._items:
-                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
-
-    # ------------------------------------------------------------------
-    # Fan-out via tee
-    # ------------------------------------------------------------------
-
-    def tee(self, n: int = 2) -> tuple[Iterator[T], ...]:
-        """Subscribe and return `n` independent sync iterators.
-
-        Each branch has its own buffer; items pulled from the
-        underlying cursor are copied into every branch. Branches are
-        naturally bounded by caller pace since the sync pump is
-        caller-driven.
-
-        Args:
-            n: Number of branches to create. Must be >= 1.
-
-        Returns:
-            A tuple of `n` iterators over the same underlying stream.
-
-        Raises:
-            TypeError: If the log is unbound or bound to async mode.
-            RuntimeError: If the log 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:
+            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:
-                        item = next(source)
-                    except StopIteration:
-                        exhausted[0] = True
-                        return
-                    for b in buffers:
-                        b.append(item)
+                        self._log._waiters.remove(fut)
+                    except ValueError:
+                        pass  # Already removed by _wake_all
+                raise

-        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 log is unbound or bound to sync mode.
-            RuntimeError: If the log 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__ = ["EventLog"]
@@ -1,497 +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._event_log import EventLog
-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` (root or mini-mux) with the mux's scope
-— typically a subgraph's namespace or `()` for the root. Standard
-transformer classes (`ValuesTransformer`, `MessagesTransformer`,
-`SubgraphTransformer`) 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._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 discovered in transformer projections are
-    auto-wired so that every `push()` also injects a `ProtocolEvent`
-    into the main log.
+    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 EventLog and 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, ...] = (),
-    ) -> None:
-        """Initialize the mux and register transformers in order.
-
-        Callers pass either `transformers` (pre-built instances) or
-        `factories` (callables producing fresh instances per mux). A
-        factory list is preferred — mini-muxes built by `make_child()`
-        inherit the factory list, so transformers propagate naturally
-        into every subgraph's scope. `transformers` is kept for
-        back-compat tests that exercise the mux directly.
-
-        Each transformer's `init()` is called once during registration,
-        projections are merged into `extensions`, `_native` keys are
-        recorded in `native_keys`, and any EventLog / StreamChannel
-        instances are bound and wired.
-
-        Args:
-            transformers: Already-built transformer instances. Mutually
-                exclusive with `factories`.
-            is_async: True for async dispatch (`apush` / `aclose` /
-                `afail`), False for the sync path.
-            factories: Zero-or-one-argument callables producing
-                transformers. Called with this mux's `scope`.
-            scope: The namespace the mux operates within. The root mux
-                is `()`; mini-muxes for subgraphs use the subgraph's
-                namespace tuple.
-
-        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, or if
-                both `transformers` and `factories` are supplied.
-        """
-        if transformers is not None and factories is not None:
-            raise ValueError("Pass either `transformers` or `factories`, not both.")
-
-        self._is_async = is_async
-        self._factories: list[TransformerFactory] = list(factories or ())
-        self.scope: tuple[str, ...] = scope
-        self._pump_fn: Callable[[], bool] | None = None
-        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
-
-        self._events: EventLog[ProtocolEvent] = EventLog()
-        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._logs: list[EventLog[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] = {}

-        if factories is not None:
-            for factory in factories:
-                self._register(factory(scope))
-        else:
-            for transformer in transformers or ():
-                self._register(transformer)
+        # Latest values per namespace (list-of-strings key)
+        self._latest_values: dict[str, Any] = {}

-    def make_child(self, scope: tuple[str, ...]) -> StreamMux:
-        """Build a mini-mux with the same factories scoped to `scope`.
+        # Interrupt tracking
+        self._interrupts: list[InterruptPayload] = []
+        self._interrupted = False

-        Used by `SubgraphTransformer` to attach a fresh transformer
-        pipeline to each discovered subgraph handle. The child mux
-        inherits the current pump binding (so cursors on its projection
-        logs drive the root pump) and carries the same factory list
-        forward to any grandchild subgraphs.
+        # Closed state
+        self._closed = False
+        self._error: BaseException | None = None

-        Raises:
-            RuntimeError: If the mux was not built from a factory list
-                (i.e., constructed with `transformers=`). Mini-muxes
-                require factories so each scope gets its own fresh
-                transformer instances.
-        """
-        if not self._factories:
-            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,
-        )
-        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 bind_pump(self, fn: Callable[[], bool]) -> None:
-        """Wire the sync pull callback onto every EventLog in the mux.
-
-        Also propagates to transformers that expose `_bind_pump` so
-        nested handles (e.g., `ChatModelStream` instances produced by
-        `MessagesTransformer`) can drive the graph pump from their
-        projection cursors.
-        """
-        self._pump_fn = fn
-        self._events._request_more = fn
-        for value in self.extensions.values():
-            if isinstance(value, EventLog):
-                value._request_more = fn
-            elif isinstance(value, StreamChannel):
-                value._log._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 value in self.extensions.values():
-            if isinstance(value, EventLog):
-                value._arequest_more = fn
-            elif isinstance(value, StreamChannel):
-                value._log._arequest_more = fn
-        for transformer in self._transformers:
-            abind = getattr(transformer, "_bind_apump", None)
-            if abind is not None:
-                abind(fn)
-
-    def _register(self, transformer: StreamTransformer) -> None:
-        """Register a single transformer.
-
-        Calls `transformer.init()`, stores the transformer for event
-        processing, binds any EventLog or 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}"
-            )
-        self._transformers.append(transformer)
-        self._bind_and_wire(projection)
-        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 getattr(transformer, "_native", False):
-            self.native_keys.update(projection.keys())
-        on_register = getattr(transformer, "_on_register", None)
-        if on_register is not None:
-            on_register(self)
-
-    def transformer_by_key(self, key: str) -> StreamTransformer | None:
-        """Return the transformer that owns the projection at `key`, if any."""
-        return self._transformer_by_key.get(key)
-
-    def emit(self, event: ProtocolEvent) -> None:
-        """Append a protocol event directly to the main log.
-
-        Built-in transformers use this for protocol repair events that
-        must appear before the source event they are processing. Direct
-        emission intentionally bypasses the transformer pipeline, but
-        still lets this mux remain the only local sequencing authority.
-        """
-        self._seq += 1
-        event["seq"] = self._seq
-        self._events.push(event)
+    # -- 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
-        — except when the transformer has `scope_exact = True` (the
-        default) and the event's namespace differs from the mux's
-        `scope`, in which case the transformer is skipped. Transformers
-        that need to see cross-scope events opt out by setting
-        `scope_exact = False` (e.g. `SubgraphTransformer`).
-
-        If any transformer returns False, the event is suppressed from
-        the main log, but transformers that already saw it keep their
-        side effects.
-
-        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 log.
-
-        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).
        """
-        ns = tuple(event["params"]["namespace"])
-        in_scope = ns == self.scope
+        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 transformer.scope_exact and not in_scope:
-                continue
-            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:
-            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

-        EventLogs and 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 log in self._logs:
-            if not log._closed:
-                log.close()
-        for ch in self._channels:
-            if not ch._log._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()

-        EventLogs and 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 log in self._logs:
-            if not log._closed:
-                log.fail(err)
-        for ch in self._channels:
-            if not ch._log._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 — except when the transformer
-        has `scope_exact = True` and the event's namespace differs from
-        `self.scope`, in which case it is skipped. 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. Memory is bounded by caller pace via the
-        caller-driven pump; see `EventLog` 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.
        """
-        ns = tuple(event["params"]["namespace"])
-        in_scope = ns == self.scope
-        keep = True
-        for transformer in self._transformers:
-            if transformer.scope_exact and not in_scope:
-                continue
-            if not await transformer.aprocess(event):
-                keep = False
-        if keep:
-            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 logs, 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 log in self._logs:
-            if not log._closed:
-                log.close()
-        for ch in self._channels:
-            if not ch._log._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 logs, 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 log in self._logs:
-            if not log._closed:
-                log.fail(err)
-        for ch in self._channels:
-            if not ch._log._closed:
-                ch._fail(err)
-        if not self._events._closed:
-            self._events.fail(err)
-
-    def _collect_scheduled_tasks(self) -> list[asyncio.Task[Any]]:
-        """Return a snapshot of in-flight tasks scheduled via transformers."""
-        return [
-            task
-            for transformer in self._transformers
-            for task in getattr(transformer, "_stream_scheduled_tasks", ())
-            if not task.done()
-        ]
-
-    # ------------------------------------------------------------------
-    # Binding and StreamChannel auto-wiring
-    # ------------------------------------------------------------------
-
-    def _bind_and_wire(self, projection: dict[str, Any]) -> None:
-        """Bind and wire EventLog / StreamChannel instances in a projection."""
-        for value in projection.values():
-            if isinstance(value, StreamChannel):
-                value._bind(is_async=self._is_async)
-                self._channels.append(value)
-                channel_name = value.name
-
-                def _make_forward(name: str) -> Callable[[Any], None]:
+                def _make_forwarder(ch: StreamChannel[Any]) -> Any:
                    def _forward(item: Any) -> None:
-                        self._forward(name, item)
+                        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

                    return _forward

-                value._wire(_make_forward(channel_name))
-            elif isinstance(value, EventLog):
-                value._bind(is_async=self._is_async)
-                self._logs.append(value)
+                channel._wire(_make_forwarder(channel))

-    def _forward(self, channel_name: 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 the main event log but are not passed through
-        transformers' `process()` methods.
+class AsyncStreamMux(StreamMux):
+    """Async extension of :class:`StreamMux`.
+
+    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.
        """
-        event: ProtocolEvent = {
-            "type": "event",
-            "method": f"custom:{channel_name}",
-            "params": {
-                "namespace": [],
-                "timestamp": int(time.time() * 1000),
-                "data": item,
-            },
-        }
-        self.emit(event)
+        cursor = aiter(self._event_log)
+        if not path:
+            return cursor
+        return _FilteredEventIterator(cursor, path)
+
+    async def subscribe_subgraphs(
+        self, path: list[str] | None = None, offset: int = 0
+    ) -> AsyncIterator[str]:
+        """Yield top-level namespace segments as they are discovered.
+
+        Each yielded value is the first namespace segment of a newly
+        discovered subgraph (e.g. ``"agent:0"``).
+        """
+        yielded: set[str] = set()
+        while True:
+            # Yield any newly discovered namespaces
+            for ns_segment in list(self._discovered_ns):
+                if ns_segment not in yielded:
+                    # Filter by path prefix if specified
+                    if path:
+                        if not ns_segment.startswith(path[0]):
+                            continue
+                    yielded.add(ns_segment)
+                    yield ns_segment
+
+            if self._closed:
+                return
+
+            # Wait for new namespaces
+            loop = asyncio.get_running_loop()
+            fut: asyncio.Future[None] = loop.create_future()
+            self._ns_waiters.append(fut)
+            await fut
+
+    def get_output_future(self, ns: list[str] | None = None) -> asyncio.Future[Any]:
+        """Get or create an output future for a namespace.
+
+        The future resolves to the latest ``values`` event data when
+        the mux is closed.
+        """
+        ns_key = _ns_key(ns or [])
+        if ns_key not in self._output_futures:
+            loop = asyncio.get_running_loop()
+            self._output_futures[ns_key] = loop.create_future()
+
+            # If already closed, resolve immediately
+            if self._closed:
+                value = self._latest_values.get(ns_key)
+                if self._error is not None:
+                    self._output_futures[ns_key].set_exception(self._error)
+                else:
+                    self._output_futures[ns_key].set_result(value)
+
+        return self._output_futures[ns_key]
+
+    # -- Internal -----------------------------------------------------------
+
+    def _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"]
@@ -1,312 +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
-    data: Any
    node: NotRequired[str]
-    run_id: NotRequired[str]
-    interrupts: NotRequired[tuple[Any, ...]]
+    data: 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 StreamMux.
-    Consumers that need a total order across 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"]
-    event_id: 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 (EventLogs, 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.
-    EventLog and 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, a subgraph's namespace tuple inside a mini-mux.
-            Set at construction from the mux's scope (each factory is
-            called as `factory(scope)`). Transformers that only care
-            about events at their own namespace compare against
-            `self.scope`; subgraph-aware transformers can treat it as
-            a parent path.
-        scope_exact: If True (the default), the mux only calls
-            `process` / `aprocess` for events whose namespace equals
-            `self.scope` — user transformers get scope-scoped events
-            for free with no boilerplate. Set False for transformers
-            that need to see events across scopes (e.g.
-            `SubgraphTransformer` forwards deeper events into child
-            mini-muxes).
-        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.
-        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 `GraphStreamer` run requests from the
-            graph. Empty tuple means the transformer consumes only
-            synthetic events (or is purely passive).
    """

-    requires_async: ClassVar[bool] = False
-    scope_exact: ClassVar[bool] = True
-    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, the subgraph's namespace inside a
-                mini-mux. 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 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 EventLogs, resolve promises, or perform other
-        teardown. StreamChannel instances 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 EventLogs 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 EventLogs, reject promises, or perform other
-        teardown. StreamChannel instances 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`).
+    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
-    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"]
@@ -1,7 +1,21 @@
+"""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

-from collections.abc import AsyncIterator, 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

@@ -9,101 +23,54 @@ T = TypeVar("T")


 class StreamChannel(Generic[T]):
-    """A named projection channel with optional protocol auto-forwarding.
+    """A typed push-based channel that integrates with the mux.

-    Wraps an event log and declares a protocol channel name. When the
-    StreamMux detects a StreamChannel in a transformer's `init()`
-    return value, it automatically wires every `push()` to inject a
-    `ProtocolEvent` into the main event stream using the channel's
-    name as the method.
-
-    Auto-forwarded events bypass the transformer pipeline — other
-    transformers' `process()` / `aprocess()` methods do not see
-    `custom:<name>` events produced by a channel push. This prevents a
-    transformer that pushes to its own channel during `process()` from
-    re-triggering itself, but it also means filter- or tap-style
-    transformers cannot observe channel output from peer transformers.
-    Consumers that need that should iterate the main event stream.
-
-    In-process consumers iterate the channel directly (`for item in ch`
-    or `async for item in ch`). Remote SDK clients subscribe via
-    `session.subscribe("custom:<channelName>")`.
-
-    Like EventLog, a StreamChannel starts unbound. The mux calls
-    `_bind(is_async)` during registration so the correct iteration
-    protocol is available by the time user code sees it.
-
-    Lifecycle (`_close` / `_fail`) is managed by the mux — transformers
-    using only StreamChannels don't need `finalize` or `fail` hooks.
+    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, *, maxlen: int | None = None) -> None:
-        """Initialize the channel with an empty inner log.
+    __slots__ = ("channel_name", "_log", "_on_push")

-        Args:
-            name: The protocol channel name used for auto-forwarded
-                events (`custom:<name>` on the wire).
-            maxlen: Optional retention cap on the inner EventLog. See
-                `EventLog.__init__` for semantics.
-        """
-        self.name = name
-        self._log: EventLog[T] = EventLog(maxlen=maxlen)
-        self._wire_fn: Callable[[T], None] | None = None
-
-    def _bind(self, *, is_async: bool) -> None:
-        """Bind the underlying event log to sync or async mode.
-
-        Args:
-            is_async: True for async iteration, False for sync.
-        """
-        self._log._bind(is_async=is_async)
+    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 to the log and auto-forward if wired.
+        """Push an item to the channel.

-        Args:
-            item: The item to push.
+        If the mux has wired this channel, the push also injects a
+        protocol event into the main event stream.
        """
-        self._log.push(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)

-    # ------------------------------------------------------------------
-    # Mux lifecycle hooks (not called by transformers directly)
-    # ------------------------------------------------------------------
+    # -- Async iteration (in-process consumption) ---------------------------

-    def _wire(self, fn: Callable[[T], None]) -> None:
-        """Install the auto-forward callback (called by StreamMux)."""
-        self._wire_fn = fn
+    def __aiter__(self) -> AsyncIterator[T]:
+        return aiter(self._log)
+
+    # -- Internal (called by the mux) ---------------------------------------
+
+    def _wire(self, fn: Callable[[Any], None]) -> None:
+        """Wire a callback invoked on every ``push()``.  Called by the mux."""
+        self._on_push = fn

    def _close(self) -> None:
-        """Close the underlying log (called by StreamMux on run end)."""
+        """Close the underlying log.  Called by the mux on normal completion."""
        self._log.close()

    def _fail(self, err: BaseException) -> None:
-        """Fail the underlying log (called by StreamMux on run error)."""
+        """Fail the underlying log.  Called by the mux on failure."""
        self._log.fail(err)

-    # ------------------------------------------------------------------
-    # Iteration — delegates to the inner event log (multi-cursor)
-    # ------------------------------------------------------------------

-    def __iter__(self) -> Iterator[T]:
-        return iter(self._log)
+def is_stream_channel(value: object) -> bool:
+    """Check if *value* is a :class:`StreamChannel` instance."""
+    return isinstance(value, StreamChannel)

-    def __aiter__(self) -> AsyncIterator[T]:
-        return self._log.__aiter__()

-    def tee(self, n: int = 2) -> tuple[Iterator[T], ...]:
-        """Fan out the channel into `n` independent sync iterators.
-
-        Delegates to the underlying EventLog's `tee()`.
-        """
-        return self._log.tee(n)
-
-    def atee(self, n: int = 2) -> tuple[AsyncIterator[T], ...]:
-        """Fan out the channel into `n` independent async iterators.
-
-        Delegates to the underlying EventLog's `atee()`.
-        """
-        return self._log.atee(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,
+        )
@@ -1,750 +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 (
-    CheckpointRef,
-    LifecycleCause,
-    LifecycleData,
-    MessagesData,
-)
-
-from langgraph.errors import GraphInterrupt
 from langgraph.stream._event_log import EventLog
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-from langgraph.stream.run_stream import BaseRunStream
+from langgraph.stream._types import ProtocolEvent
+from langgraph.stream.chat_model_stream import ChatModelStream

-if TYPE_CHECKING:
-    from collections.abc import Awaitable, Callable
-
-    from langgraph.stream._mux import StreamMux
+# Type alias for the stream class constructor signature
+_StreamCls = type[ChatModelStream]


-logger = logging.getLogger(__name__)
+class ValuesTransformer:
+    """Extracts ``values`` events and populates a values event log.

+    Maintains the latest state per namespace and provides a separate
+    event log that :class:`AsyncGraphRunStream` / :class:`GraphRunStream` uses for ``.values``
+    iteration.

-SubgraphStatus = Literal["started", "running", "completed", "failed", "interrupted"]
-_TERMINAL_STATUSES: frozenset[SubgraphStatus] = frozenset(
-    {"completed", "failed", "interrupted"}
-)
-
-
-def _is_record(value: Any) -> bool:
-    return isinstance(value, dict)
-
-
-def _to_chat_model_stream_event(event: MessagesData) -> MessagesData:
-    """Convert wire-shaped message fields to ChatModelStream's internal shape."""
-    event_type = event.get("event")
-    converted: dict[str, Any] = dict(event)
-    if (
-        event_type == "message-start"
-        and "message_id" not in converted
-        and isinstance(converted.get("id"), str)
-    ):
-        converted["message_id"] = converted["id"]
-    if (
-        event_type in ("content-block-start", "content-block-delta", "content-block-finish")
-        and "content_block" not in converted
-        and isinstance(converted.get("content"), dict)
-    ):
-        converted["content_block"] = converted["content"]
-    return cast("MessagesData", converted)
-
-
-def _message_event_id(event: MessagesData) -> str | None:
-    raw_id = event.get("id") or event.get("message_id")
-    return str(raw_id) if raw_id is not None else None
-
-
-def _content_block_start_skeleton(content: Any) -> dict[str, Any] | None:
-    """Return a minimal content-block-start payload for a delta/finish block."""
-    if not _is_record(content) or not isinstance(content.get("type"), str):
-        return None
-
-    block_type = content["type"]
-    skeleton: dict[str, Any] = {"type": block_type}
-    if block_type == "text":
-        skeleton["text"] = ""
-    elif block_type == "reasoning":
-        skeleton["reasoning"] = ""
-    elif block_type in ("tool_call", "tool_call_chunk"):
-        skeleton["type"] = "tool_call_chunk"
-        if isinstance(content.get("id"), str):
-            skeleton["id"] = content["id"]
-        if isinstance(content.get("name"), str):
-            skeleton["name"] = content["name"]
-        skeleton["args"] = ""
-    elif block_type in ("server_tool_call", "server_tool_call_chunk"):
-        skeleton["type"] = "server_tool_call_chunk"
-        if isinstance(content.get("id"), str):
-            skeleton["id"] = content["id"]
-        if isinstance(content.get("name"), str):
-            skeleton["name"] = content["name"]
-        skeleton["args"] = ""
-    return skeleton
-
-
-def _copy_event(
-    source: ProtocolEvent,
-    *,
-    method: str,
-    namespace: list[str],
-    data: Any,
-) -> ProtocolEvent:
-    params = {**source["params"], "namespace": namespace, "data": data}
-    return {"type": "event", "method": method, "params": params}
-
-
-def _message_repair_key(event: ProtocolEvent, run_id: str) -> str:
-    namespace_key = "\x1f".join(event["params"]["namespace"])
-    return f"{namespace_key}\x1e{run_id}"
-
-
-def _extract_tool_calls_from_values(data: Any) -> dict[str, dict[str, Any]]:
-    if not _is_record(data):
-        return {}
-    messages = data.get("messages")
-    if not isinstance(messages, list):
-        return {}
-    known: dict[str, dict[str, Any]] = {}
-    for message in messages:
-        if not _is_record(message):
-            continue
-        tool_calls = message.get("tool_calls")
-        if not isinstance(tool_calls, list):
-            continue
-        for tool_call in tool_calls:
-            if not _is_record(tool_call):
-                continue
-            tool_call_id = tool_call.get("id")
-            if not isinstance(tool_call_id, str):
-                continue
-            name = tool_call.get("name")
-            args = tool_call.get("args")
-            known[tool_call_id] = {
-                "tool_name": name if isinstance(name, str) else "",
-                "input": args if _is_record(args) else {},
-            }
-    return known
-
-
-class ValuesTransformer(StreamTransformer):
-    """Capture values events as a drainable stream of state snapshots.
-
-    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.
-
-    Native transformer — projection keys are exposed as direct
-    attributes on the run stream (e.g. `run.values`).
-
-    `scope` (inherited from `StreamTransformer`) is the namespace the
-    transformer captures values for. `()` matches the root graph;
-    subgraph mini-muxes pass their subgraph's namespace, so each
-    instance sees only its own level.
+    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: EventLog[dict[str, Any]] = EventLog()
-        self._latest: dict[str, Any] | None = None
-        self._interrupted = False
-        self._interrupts: list[Any] = []
-
-    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:
-        # Namespace filtering is handled by the mux via `scope_exact`.
        if event["method"] != "values":
            return True
-        params = event["params"]
-        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 ToolLifecycleTransformer(StreamTransformer):
-    """Repair tool-start events needed for deterministic subagent discovery.
+    def fail(self, err: BaseException) -> None:
+        self._values_log.fail(err)

-    Some subagent frameworks expose a tool-caused subgraph lifecycle before
-    a LangChain tool callback has emitted the matching `tool-started`
-    frame. Core can infer the missing start from the latest values snapshot
-    (`messages[*].tool_calls`) and emit it before the lifecycle event leaves
-    the mux, keeping remote clients from guessing from values snapshots.
+
+class MessagesTransformer:
+    """Groups ``messages`` events into :class:`ChatModelStream` instances.
+
+    One ``ChatModelStream`` is created per ``message-start`` event.
+    Content-block events are routed to the active stream until
+    ``message-finish`` or ``message-error`` closes it.
+
+    Implements the :class:`StreamTransformer` protocol.
    """

-    scope_exact = False
-    required_stream_modes = ("values", "tools", "lifecycle")
+    name = "messages"

-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._known_tool_calls: dict[str, dict[str, Any]] = {}
-        self._emitted_tool_starts: set[str] = set()
-        self._mux: StreamMux | None = None
-
-    def init(self) -> dict[str, Any]:
-        return {}
-
-    def _on_register(self, mux: StreamMux) -> None:
-        self._mux = mux
-
-    def process(self, event: ProtocolEvent) -> bool:
-        method = event["method"]
-        data = event["params"]["data"]
-        if method == "values":
-            self._known_tool_calls.update(_extract_tool_calls_from_values(data))
-            return True
-        if method == "tools" and _is_record(data):
-            if (
-                data.get("event") == "tool-started"
-                and isinstance(data.get("tool_call_id"), str)
-            ):
-                tool_call_id = cast("str", data["tool_call_id"])
-                if tool_call_id in self._emitted_tool_starts:
-                    return False
-                self._emitted_tool_starts.add(tool_call_id)
-            return True
-        if method == "lifecycle":
-            self._emit_missing_tool_started(event)
-        return True
-
-    def _emit_missing_tool_started(self, event: ProtocolEvent) -> None:
-        if self._mux is None:
-            return
-        data = event["params"]["data"]
-        if not _is_record(data) or data.get("event") != "started":
-            return
-        cause = data.get("cause")
-        if not _is_record(cause) or cause.get("type") != "toolCall":
-            return
-        tool_call_id = cause.get("tool_call_id")
-        if not isinstance(tool_call_id, str):
-            return
-        if tool_call_id in self._emitted_tool_starts:
-            return
-        known = self._known_tool_calls.get(tool_call_id)
-        if known is None:
-            return
-
-        self._emitted_tool_starts.add(tool_call_id)
-        namespace = event["params"]["namespace"]
-        self._mux.emit(
-            _copy_event(
-                event,
-                method="tools",
-                namespace=namespace[:-1],
-                data={
-                    "event": "tool-started",
-                    "tool_call_id": tool_call_id,
-                    "tool_name": known["tool_name"],
-                    "input": known["input"],
-                },
-            )
-        )
-
-
-class MessagesTransformer(StreamTransformer):
-    """Capture messages events as ChatModelStream objects.
-
-    The messages projection yields one `ChatModelStream` (or
-    `AsyncChatModelStream`) per LLM call. Consumers iterate
-    `run.messages` to get stream handles, then use each handle's typed
-    projections (`.text`, `.reasoning`, `.tool_calls`, `.usage`,
-    `.output`) for per-message content.
-
-    Two input shapes are handled (via `params["data"] = (payload,
-    metadata)` from `StreamMessagesHandler`):
-
-    1. Protocol event (dict with `"event"` key) — emitted by
-       `stream_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.
-
-    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.
-
-    `scope` (inherited from `StreamTransformer`) is the namespace the
-    transformer captures messages for. `()` matches the root graph;
-    subgraph mini-muxes pass their subgraph's namespace, so each
-    instance sees only its own level.
-
-    Native transformer — the `messages` projection is exposed as a
-    direct attribute on the run stream.
-
-    `scope_exact = False`: matches events at the transformer's own
-    namespace **or** exactly one segment deeper (the chat-model /
-    node's own task ns). Mirrors JS's root-feed filter
-    (`namespaces=[[]], depth=1`) — root accepts depth-0 events plus
-    its own nodes' depth-1 tokens; subgraph mini-muxes accept their
-    own scope plus their internal nodes' tokens. Events deeper than
-    scope + 1 are dropped (the enclosing `SubgraphTransformer` has
-    already forwarded them to the matching child mini-mux).
-    """
-
-    _native = True
-    scope_exact = False
-    required_stream_modes = ("messages",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._log: EventLog[ChatModelStream] = EventLog()
-        # 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._started_blocks: dict[str, set[int]] = {}
-        self._mux: StreamMux | None = None
-        self._pump_fn: Callable[[], bool] | None = None
-        self._apump_fn: Callable[[], Awaitable[bool]] | None = None
-
-    def init(self) -> dict[str, Any]:
-        return {"messages": self._log}
-
-    def _on_register(self, mux: StreamMux) -> None:
-        self._mux = mux
-
-    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"]
-        # Accept events at our scope or exactly one segment deeper
-        # (the chat-model / node's own task ns). Deeper events belong
-        # to a subgraph and are routed by `SubgraphTransformer`.
-        ns = tuple(params["namespace"])
-        depth = len(self.scope)
-        if ns[:depth] != self.scope:
+
+        ns = event["params"].get("namespace", [])
+        node = event["params"].get("node")
+        data = event["params"]["data"]
+
+        # Apply namespace filter
+        if self._namespace is not None:
+            if ns[: len(self._namespace)] != self._namespace:
+                return True
+
+        # Apply node filter
+        if self._node_filter is not None and node != self._node_filter:
            return True

-        raw_data = params["data"]
-        metadata: dict[str, Any] = {}
-        if isinstance(raw_data, tuple) and len(raw_data) == 2:
-            payload, raw_metadata = raw_data
-            metadata = raw_metadata if isinstance(raw_metadata, dict) else {}
-        else:
-            payload = raw_data
-        node = params.get("node")
-        if not isinstance(node, str):
-            node = metadata.get("langgraph_node")
-            if not isinstance(node, str):
-                node = None
-        raw_run_id = params.get("run_id", metadata.get("run_id"))
-        run_id = str(raw_run_id) if raw_run_id is not None else ""
+        ns_key = "|".join(ns) if ns else ""
+        event_type = data.get("event") if isinstance(data, dict) else None

-        if isinstance(payload, dict) and "event" in payload:
-            self._repair_content_block_lifecycle(
-                event, cast("MessagesData", payload), run_id=run_id
-            )
-            if len(ns) > depth + 1:
-                return True
-            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:
-        stream_event = _to_chat_model_stream_event(event)
-        event_type = event.get("event")
        if event_type == "message-start":
-            message_id = _message_event_id(event)
-            stream = self._make_stream(
-                namespace=list(self.scope),
+            stream = self._stream_cls(
+                namespace=ns,
                node=node,
-                message_id=message_id,
+                message_id=data.get("message_id"),
            )
-            self._by_run[run_id or message_id or ""] = stream
-            self._log.push(stream)
-            stream.dispatch(stream_event)
-        elif run_id in self._by_run:
-            stream = self._by_run[run_id]
-            stream.dispatch(stream_event)
-            if event_type == "message-finish":
-                del self._by_run[run_id]
+            self._active[ns_key] = stream
+            self._messages_log.append(stream)
+
+        elif event_type in ("content-block-delta", "content-block-start"):
+            active = self._active.get(ns_key)
+            if active is not None and event_type == "content-block-delta":
+                active._push_content_block_delta(data)
+
+        elif event_type == "content-block-finish":
+            active = self._active.get(ns_key)
+            if active is not None:
+                active._push_content_block_finish(data)

-    def _repair_content_block_lifecycle(
-        self,
-        source: ProtocolEvent,
-        event: MessagesData,
-        *,
-        run_id: str,
-    ) -> None:
-        if self._mux is None:
-            return
-        event_type = event.get("event")
-        key = _message_repair_key(source, run_id)
-        if event_type == "message-start":
-            self._started_blocks[key] = set()
-            return
-        if event_type == "content-block-start":
-            index = event.get("index")
-            if isinstance(index, int):
-                self._started_blocks.setdefault(key, set()).add(index)
-            return
-        if event_type in ("content-block-delta", "content-block-finish"):
-            index = event.get("index")
-            if not isinstance(index, int):
-                return
-            started = self._started_blocks.setdefault(key, set())
-            if index in started:
-                return
-            skeleton = _content_block_start_skeleton(event.get("content"))
-            if skeleton is None:
-                return
-            started.add(index)
-            self._mux.emit(
-                _copy_event(
-                    source,
-                    method="messages",
-                    namespace=list(source["params"]["namespace"]),
-                    data={
-                        "event": "content-block-start",
-                        "index": index,
-                        "content": skeleton,
-                    },
-                )
-            )
        elif event_type == "message-finish":
-            self._started_blocks.pop(key, None)
+            active = self._active.pop(ns_key, None)
+            if active is not None:
+                active._finish(data)

-    def _route_whole_message(self, message: BaseMessage, *, node: str | None) -> None:
-        stream = self._make_stream(
-            namespace=list(self.scope),
-            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()
-        self._started_blocks.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()
-        self._started_blocks.clear()
-
-
-class SubgraphRunStream(BaseRunStream):
-    """Scoped view of a single nested subgraph execution.
-
-    Yielded on `run.subgraphs` (or `parent.subgraphs` for grandchildren)
-    when a nested `Pregel` spawns. Wraps a mini-`StreamMux` built with
-    the same transformer factories as the root mux, so `.values`,
-    `.messages`, `.subgraphs` are populated by the standard
-    transformers scoped to this handle's namespace — no duplicated
-    routing logic. The mini-mux borrows the root's pump via
-    `make_child`'s pump inheritance, so any cursor on a subagent
-    projection drives the whole run forward.
-
-    Lifecycle fields update in place as events arrive:
-
-    - `path`: the namespace tuple — stable for the life of the handle.
-    - `graph_name` / `cause`: set once from the `started` payload.
-      `cause` is populated by product-specific stream transformers
-      (see `LifecycleCause` in the protocol definition); pregel itself
-      emits no `cause`, so it may be `None` for subgraphs not covered
-      by a product transformer.
-    - `status`: advances `started` → `running` → `completed` /
-      `failed` / `interrupted`.
-    - `error` / `checkpoint`: set on the terminal event when present.
-
-    `.output` is a snapshot of the latest values seen at this
-    namespace — it doesn't drive the pump (unlike root's
-    `GraphRunStream.output`), because advancing a subgraph to
-    completion is only meaningful as part of advancing the whole run.
-    """
-
-    def __init__(
-        self,
-        path: tuple[str, ...],
-        mux: StreamMux,
-        *,
-        graph_name: str | None = None,
-        cause: LifecycleCause | None = None,
-    ) -> None:
-        super().__init__(mux)
-        self.path: tuple[str, ...] = path
-        self.graph_name: str | None = graph_name
-        self.cause: LifecycleCause | None = cause
-        self.status: SubgraphStatus = "started"
-        self.error: str | None = None
-        self.checkpoint: CheckpointRef | None = None
-
-    @property
-    def output(self) -> dict[str, Any] | None:
-        """Latest values snapshot at this namespace, or `None`.
-
-        Snapshot-only — iterating other projections or the root's
-        `.output` is what drives the pump.
-        """
-        values_t = self._mux.transformer_by_key("values")
-        if isinstance(values_t, ValuesTransformer):
-            return values_t._latest
-        return None
-
-
-class SubgraphTransformer(StreamTransformer):
-    """Discover subgraphs and route events into per-subgraph mini-muxes.
-
-    Thin state-machine + dispatcher. At its own `scope` (inherited
-    from `StreamTransformer`, determined by the enclosing mux), it
-    watches for `lifecycle` events at exactly one level deeper to
-    discover direct children. Each discovered child gets its own
-    `SubgraphRunStream` backed by a mini-`StreamMux` — built via
-    `parent_mux.make_child(path)`, so the same factory list produces
-    fresh transformer instances at the child's scope.
-
-    Every incoming event that falls under one of the direct children
-    (ns starts with a child's `path`) is forwarded into that child's
-    mini-mux via `push`. The standard transformers in that mini-mux
-    (`ValuesTransformer`, `MessagesTransformer`, and another
-    `SubgraphTransformer` for grandchildren) handle the rest. No
-    duplicated routing or assembly logic.
-
-    Lifecycle state for each handle (running / completed / failed /
-    interrupted) is updated in place as events fire. On terminal
-    events, the handle's mini-mux is closed so any subscribed cursors
-    unblock. `finalize` / `fail` handle dangling handles left mid-run.
-
-    Native transformer — `subgraphs` exposes the direct-children log.
-
-    `scope_exact = False`: this transformer sees events at any
-    namespace, because it forwards out-of-scope events to the matching
-    direct-child mini-mux.
-    """
-
-    _native = True
-    scope_exact = False
-    required_stream_modes = ("lifecycle",)
-
-    def __init__(self, scope: tuple[str, ...] = ()) -> None:
-        super().__init__(scope)
-        self._root_log: EventLog[SubgraphRunStream] = EventLog()
-        # Direct children only (namespace = scope + one segment).
-        self._by_ns: dict[tuple[str, ...], SubgraphRunStream] = {}
-        self._mux: StreamMux | None = None
-
-    def init(self) -> dict[str, Any]:
-        return {"subgraphs": self._root_log}
-
-    def _on_register(self, mux: StreamMux) -> None:
-        """Capture the enclosing mux so we can build child mini-muxes."""
-        self._mux = mux
-
-    def process(self, event: ProtocolEvent) -> bool:
-        ns = tuple(event["params"]["namespace"])
-        method = event["method"]
-        depth = len(self.scope)
-
-        # 1. On `started` for a direct child (ns depth = mine + 1 and
-        #    ns prefix matches mine), register the handle.
-        if method == "lifecycle" and len(ns) == depth + 1 and ns[:-1] == self.scope:
-            data = cast(LifecycleData, event["params"]["data"])
-            if data.get("event") == "started":
-                self._on_started(ns, data)
-
-        # 2. Forward the event to the matching direct-child mini-mux
-        #    before the status-change step below so that terminal events
-        #    reach the child's log and grandchild transformers *before*
-        #    the child's mini-mux is closed. Prefix-match: ns must start
-        #    with some child's path.
-        direct_child_ns = ns[: depth + 1] if len(ns) > depth else None
-        if direct_child_ns is not None and direct_child_ns in self._by_ns:
-            self._by_ns[direct_child_ns]._mux.push(event)
-
-        # 3. Status change for a direct child (ns = child's path, method
-        #    = lifecycle). Update handle fields, close mini-mux on
-        #    terminal.
-        if (
-            method == "lifecycle"
-            and ns in self._by_ns
-            and len(ns) == depth + 1
-            and ns[:-1] == self.scope
-        ):
-            data = cast(LifecycleData, event["params"]["data"])
-            event_type = data.get("event")
-            if event_type in ("running", "completed", "failed", "interrupted"):
-                self._on_status_change(ns, event_type, data)
+        elif event_type == "error":
+            active = self._active.pop(ns_key, None)
+            if active is not None:
+                msg = data.get("message", "Unknown error")
+                active._fail(RuntimeError(msg))

        return True

-    def _on_started(self, ns: tuple[str, ...], data: LifecycleData) -> None:
-        if ns in self._by_ns:
-            # Duplicate started — ignore.
-            return
-        # `_on_register` is called by the mux during registration, which
-        # happens before any event can be dispatched — so this should
-        # always be set by the time we process an event.
-        assert self._mux is not None, (
-            "SubgraphTransformer processed an event before _on_register; "
-            "transformer registration ordering is broken."
-        )
-        child_mux = self._mux.make_child(ns)
-        handle = SubgraphRunStream(
-            path=ns,
-            mux=child_mux,
-            graph_name=data.get("graph_name"),
-            cause=data.get("cause"),
-        )
-        self._by_ns[ns] = handle
-        self._root_log.push(handle)
-
-    def _on_status_change(
-        self,
-        ns: tuple[str, ...],
-        event_type: SubgraphStatus,
-        data: LifecycleData,
-    ) -> None:
-        handle = self._by_ns[ns]
-        handle.status = event_type
-        err = data.get("error")
-        if err is not None:
-            handle.error = err
-        checkpoint = data.get("checkpoint")
-        if checkpoint is not None:
-            handle.checkpoint = checkpoint
-        if event_type in _TERMINAL_STATUSES:
-            self._close_handle_mux(handle)
-
-    @staticmethod
-    def _close_handle_mux(handle: SubgraphRunStream) -> None:
-        # Idempotent close — mux.close() runs finalize on its transformers
-        # (which cascades through grandchildren) and closes projection logs.
-        if not handle._mux._events._closed:
-            try:
-                handle._mux.close()
-            except Exception:
-                logger.warning(
-                    "Error closing subgraph mini-mux at %s; subscribers "
-                    "may not see a clean close.",
-                    handle.path,
-                    exc_info=True,
-                )
-
    def finalize(self) -> None:
-        """Transition any still-open direct children to `completed`."""
-        for handle in self._by_ns.values():
-            if handle.status not in _TERMINAL_STATUSES:
-                handle.status = "completed"
-            self._close_handle_mux(handle)
+        # 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:
-        """Transition any still-open direct children to `failed` / `interrupted`."""
-        is_interrupt = isinstance(err, GraphInterrupt)
-        terminal: SubgraphStatus = "interrupted" if is_interrupt else "failed"
-        error_str = None if is_interrupt else str(err)
-        for handle in self._by_ns.values():
-            if handle.status not in _TERMINAL_STATUSES:
-                handle.status = terminal
-                if error_str is not None and handle.error is None:
-                    handle.error = error_str
-            if 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)
+
+
+__all__ = [
+    "MessagesTransformer",
+    "ValuesTransformer",
+]
@@ -116,15 +116,7 @@ def ensure_valid_checkpointer(checkpointer: Checkpointer) -> Checkpointer:


 StreamMode = Literal[
-    "values",
-    "updates",
-    "checkpoints",
-    "tasks",
-    "debug",
-    "messages",
-    "custom",
-    "lifecycle",
-    "tools",
+    "values", "updates", "checkpoints", "tasks", "debug", "messages", "custom"
 ]
 """How the stream method should emit outputs.

@@ -137,8 +129,6 @@ StreamMode = Literal[
 - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by `get_state()`.
 - `"tasks"`: Emit events when tasks start and finish, including their results and errors.
 - `"debug"`: Emit `"checkpoints"` and `"tasks"` events for debugging purposes.
- `"lifecycle"`: Emit subgraph lifecycle events (`started`, `running`, `completed`, `failed`, `interrupted`) with payloads matching `LifecycleData`.
- `"tools"`: Emit tool-call lifecycle events (`tool-started`, `tool-output-delta`, `tool-finished`, `tool-error`) keyed by `tool_call_id`.
 """

 StreamWriter = Callable[[Any], None]
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph"
-version = "1.1.7a2"
+version = "1.1.6"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -24,7 +24,7 @@ classifiers = [
    'Programming Language :: Python :: 3.13',
 ]
 dependencies = [
-    "langchain-core>=1.3.2",
+    "langchain-core>=0.1",
    "langgraph-checkpoint>=2.1.0,<5.0.0",
    "langgraph-sdk>=0.3.0,<0.4.0",
    "langgraph-prebuilt>=1.0.9,<1.1.0",
@@ -1,277 +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
@@ -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"
@@ -6271,7 +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:
@@ -6284,7 +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]
@@ -6893,6 +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",
@@ -6902,60 +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
@@ -7542,6 +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",
@@ -7551,67 +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."
+    )
@@ -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
@@ -1,628 +0,0 @@
-"""Tests for subgraph lifecycle events and the SubgraphTransformer."""
-
-from __future__ import annotations
-
-import operator
-import time
-from typing import Annotated, Any
-
-import pytest
-from langgraph.checkpoint.memory import InMemorySaver
-from typing_extensions import TypedDict
-
-from langgraph.constants import END, START
-from langgraph.errors import GraphInterrupt
-from langgraph.graph import StateGraph
-from langgraph.stream._event_log import EventLog
-from langgraph.stream._mux import StreamMux
-from langgraph.stream._types import ProtocolEvent
-from langgraph.stream.transformers import (
-    MessagesTransformer,
-    SubgraphRunStream,
-    SubgraphTransformer,
-    ToolLifecycleTransformer,
-    ValuesTransformer,
-)
-from langgraph.types import interrupt
-
-TS = int(time.time() * 1000)
-
-
-def _lifecycle(
-    event: str,
-    *,
-    namespace: list[str] | None = None,
-    graph_name: str | None = None,
-    cause: dict[str, Any] | None = None,
-    error: str | None = None,
-) -> ProtocolEvent:
-    data: dict[str, Any] = {"event": event}
-    if graph_name is not None:
-        data["graph_name"] = graph_name
-    if cause is not None:
-        data["cause"] = cause
-    if error is not None:
-        data["error"] = error
-    return {
-        "type": "event",
-        "method": "lifecycle",
-        "params": {
-            "namespace": namespace or [],
-            "timestamp": TS,
-            "data": data,
-        },
-    }
-
-
-def _values(payload: dict[str, Any], *, namespace: list[str]) -> ProtocolEvent:
-    return {
-        "type": "event",
-        "method": "values",
-        "params": {
-            "namespace": namespace,
-            "timestamp": TS,
-            "data": payload,
-        },
-    }
-
-
-def _subscribe(log: EventLog) -> None:
-    """Flip `_subscribed = True` so pushes retain items for test inspection."""
-    log._subscribed = True
-
-
-# ---------------------------------------------------------------------------
-# Unit tests: feed events directly into the transformer
-# ---------------------------------------------------------------------------
-
-
-_FACTORIES = [
-    ValuesTransformer,
-    ToolLifecycleTransformer,
-    MessagesTransformer,
-    SubgraphTransformer,
-]
-
-
-def _handle_values_items(handle: SubgraphRunStream) -> list:
-    return list(handle._mux.extensions["values"]._items)  # type: ignore[attr-defined]
-
-
-def _handle_subgraphs_items(handle: SubgraphRunStream) -> list:
-    return list(handle._mux.extensions["subgraphs"]._items)  # type: ignore[attr-defined]
-
-
-def _pre_subscribe_handle(handle: SubgraphRunStream) -> None:
-    """Flip `_subscribed` on every EventLog inside the handle's mini-mux.
-
-    The mini-mux is built via `make_child` with the full factory list,
-    so values / messages / subgraphs logs all exist as projections.
-    Tests that feed events directly need them subscribed so pushes
-    retain items in the deque for `_items` inspection.
-    """
-    for value in handle._mux.extensions.values():
-        if isinstance(value, EventLog):
-            _subscribe(value)
-
-
-class TestSubgraphTransformerUnit:
-    def _mux(self) -> tuple[StreamMux, SubgraphTransformer]:
-        mux = StreamMux(factories=_FACTORIES, is_async=False)
-        transformer = mux.transformer_by_key("subgraphs")
-        assert isinstance(transformer, SubgraphTransformer)
-        _subscribe(transformer._root_log)
-        return mux, transformer
-
-    def _handle(self, transformer: SubgraphTransformer) -> SubgraphRunStream:
-        """Return the single root handle after pushing one lifecycle started."""
-        (handle,) = list(transformer._root_log._items)
-        return handle
-
-    def test_root_started_is_ignored(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", graph_name="root"))
-        assert list(transformer._root_log._items) == []
-        assert transformer._by_ns == {}
-
-    def test_child_started_yields_handle(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(
-            _lifecycle(
-                "started",
-                namespace=["task_a:child"],
-                graph_name="child",
-                cause={"type": "toolCall", "tool_call_id": "call_abc"},
-            )
-        )
-
-        handle = self._handle(transformer)
-        assert handle.path == ("task_a:child",)
-        assert handle.graph_name == "child"
-        assert handle.cause == {"type": "toolCall", "tool_call_id": "call_abc"}
-        assert handle.status == "started"
-
-    def test_tool_started_is_synthesized_before_tool_caused_lifecycle(self) -> None:
-        mux, transformer = self._mux()
-        events = iter(mux._events)
-        mux.push(
-            _values(
-                {
-                    "messages": [
-                        {
-                            "tool_calls": [
-                                {
-                                    "id": "call_abc",
-                                    "name": "task",
-                                    "args": {"subagent_type": "researcher"},
-                                }
-                            ]
-                        }
-                    ]
-                },
-                namespace=[],
-            )
-        )
-        mux.push(
-            _lifecycle(
-                "started",
-                namespace=["task:child"],
-                graph_name="child",
-                cause={"type": "toolCall", "tool_call_id": "call_abc"},
-            )
-        )
-
-        mux.close()
-        tool_started, lifecycle_started = list(events)[1:3]
-        assert tool_started["method"] == "tools"
-        assert tool_started["params"]["namespace"] == []
-        assert tool_started["params"]["data"] == {
-            "event": "tool-started",
-            "tool_call_id": "call_abc",
-            "tool_name": "task",
-            "input": {"subagent_type": "researcher"},
-        }
-        assert lifecycle_started["method"] == "lifecycle"
-        assert tool_started["seq"] < lifecycle_started["seq"]
-        assert self._handle(transformer).path == ("task:child",)
-
-    def test_core_golden_trace_uses_js_wire_shape_and_ordering(self) -> None:
-        mux, _transformer = self._mux()
-        events = iter(mux._events)
-        mux.push(
-            _values(
-                {
-                    "messages": [
-                        {
-                            "tool_calls": [
-                                {
-                                    "id": "call_abc",
-                                    "name": "task",
-                                    "args": {"subagent_type": "researcher"},
-                                }
-                            ]
-                        }
-                    ]
-                },
-                namespace=[],
-            )
-        )
-        for data in (
-            {"event": "message-start", "id": "msg-1", "role": "ai"},
-            {
-                "event": "content-block-delta",
-                "index": 0,
-                "content": {"type": "text", "text": "hi"},
-            },
-        ):
-            mux.push(
-                {
-                    "type": "event",
-                    "method": "messages",
-                    "params": {
-                        "namespace": ["call_model:task-1"],
-                        "timestamp": TS,
-                        "data": data,
-                        "run_id": "run-1",
-                    },
-                }
-            )
-        mux.push(
-            _lifecycle(
-                "started",
-                namespace=["task:child"],
-                graph_name="child",
-                cause={"type": "toolCall", "tool_call_id": "call_abc"},
-            )
-        )
-        mux.close()
-
-        trace = [
-            (event["method"], event["params"]["namespace"], event["params"]["data"])
-            for event in events
-        ]
-        assert trace == [
-            (
-                "values",
-                [],
-                {
-                    "messages": [
-                        {
-                            "tool_calls": [
-                                {
-                                    "id": "call_abc",
-                                    "name": "task",
-                                    "args": {"subagent_type": "researcher"},
-                                }
-                            ]
-                        }
-                    ]
-                },
-            ),
-            (
-                "messages",
-                ["call_model:task-1"],
-                {"event": "message-start", "id": "msg-1", "role": "ai"},
-            ),
-            (
-                "messages",
-                ["call_model:task-1"],
-                {
-                    "event": "content-block-start",
-                    "index": 0,
-                    "content": {"type": "text", "text": ""},
-                },
-            ),
-            (
-                "messages",
-                ["call_model:task-1"],
-                {
-                    "event": "content-block-delta",
-                    "index": 0,
-                    "content": {"type": "text", "text": "hi"},
-                },
-            ),
-            (
-                "tools",
-                [],
-                {
-                    "event": "tool-started",
-                    "tool_call_id": "call_abc",
-                    "tool_name": "task",
-                    "input": {"subagent_type": "researcher"},
-                },
-            ),
-            (
-                "lifecycle",
-                ["task:child"],
-                {
-                    "event": "started",
-                    "graph_name": "child",
-                    "cause": {"type": "toolCall", "tool_call_id": "call_abc"},
-                },
-            ),
-        ]
-
-    def test_status_transitions(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        mux.push(_lifecycle("running", namespace=["t:c"]))
-        mux.push(_lifecycle("completed", namespace=["t:c"]))
-
-        handle = self._handle(transformer)
-        assert handle.status == "completed"
-
-    def test_grandchild_surfaces_under_child(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:child"], graph_name="child"))
-
-        child = self._handle(transformer)
-        _pre_subscribe_handle(child)
-
-        mux.push(
-            _lifecycle(
-                "started",
-                namespace=["t:child", "u:grand"],
-                graph_name="grand",
-            )
-        )
-
-        (grand,) = _handle_subgraphs_items(child)
-        assert grand.path == ("t:child", "u:grand")
-        assert grand.graph_name == "grand"
-
-    def test_failed_stores_error(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        mux.push(_lifecycle("failed", namespace=["t:c"], error="boom"))
-
-        handle = self._handle(transformer)
-        assert handle.status == "failed"
-        assert handle.error == "boom"
-
-    def test_values_routed_into_handle(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-
-        handle = self._handle(transformer)
-        _pre_subscribe_handle(handle)
-
-        mux.push(_values({"value": 1}, namespace=["t:c"]))
-        mux.push(_values({"value": 2}, namespace=["t:c"]))
-
-        assert _handle_values_items(handle) == [{"value": 1}, {"value": 2}]
-        assert handle.output == {"value": 2}
-
-    def test_root_values_not_routed(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        handle = self._handle(transformer)
-        _pre_subscribe_handle(handle)
-
-        # Values event at root namespace — must not leak into child handle.
-        mux.push(_values({"value": "root"}, namespace=[]))
-        assert _handle_values_items(handle) == []
-
-    def test_finalize_closes_dangling(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        handle = self._handle(transformer)
-
-        mux.close()
-        assert handle.status == "completed"
-        assert handle._mux.extensions["values"]._closed
-        assert handle._mux.extensions["subgraphs"]._closed
-
-    def test_fail_with_graph_interrupt_marks_interrupted(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        handle = self._handle(transformer)
-
-        mux.fail(GraphInterrupt())
-        assert handle.status == "interrupted"
-
-    def test_fail_with_generic_error_marks_failed(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        handle = self._handle(transformer)
-
-        mux.fail(RuntimeError("explode"))
-        assert handle.status == "failed"
-        assert handle.error == "explode"
-
-    def test_duplicate_started_ignored(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
-        mux.push(_lifecycle("started", namespace=["t:c"], graph_name="other"))
-
-        handles = list(transformer._root_log._items)
-        assert len(handles) == 1
-        assert handles[0].graph_name == "c"
-
-    def test_non_lifecycle_non_values_passthrough(self) -> None:
-        mux, transformer = self._mux()
-        mux.push(
-            {
-                "type": "event",
-                "method": "messages",
-                "params": {
-                    "namespace": ["t:c"],
-                    "timestamp": TS,
-                    "data": (
-                        {"event": "message-start", "message_id": "m1"},
-                        {"run_id": "m1"},
-                    ),
-                },
-            }
-        )
-        assert list(transformer._root_log._items) == []
-
-
-# ---------------------------------------------------------------------------
-# End-to-end tests via stream_v2 on real graphs
-# ---------------------------------------------------------------------------
-
-
-class SimpleState(TypedDict):
-    value: str
-    items: Annotated[list[str], operator.add]
-
-
-def _build_nested_graph():
-    """Parent graph with a compiled subgraph node."""
-
-    def inner_node(state: SimpleState) -> dict:
-        return {"value": state["value"] + "X", "items": ["x"]}
-
-    inner_builder = StateGraph(SimpleState)
-    inner_builder.add_node("inner_node", inner_node)
-    inner_builder.add_edge(START, "inner_node")
-    inner_builder.add_edge("inner_node", END)
-    inner = inner_builder.compile()
-
-    def outer_node(state: SimpleState) -> dict:
-        return {"value": state["value"] + "Y", "items": ["y"]}
-
-    outer_builder = StateGraph(SimpleState)
-    outer_builder.add_node("outer_node", outer_node)
-    outer_builder.add_node("sub", inner)
-    outer_builder.add_edge(START, "outer_node")
-    outer_builder.add_edge("outer_node", "sub")
-    outer_builder.add_edge("sub", END)
-    return outer_builder.compile()
-
-
-class TestSubgraphTransformerEndToEnd:
-    def test_flat_graph_yields_no_subgraphs(self) -> None:
-        builder = StateGraph(SimpleState)
-        builder.add_node("n", lambda s: {"value": s["value"] + "!", "items": ["!"]})
-        builder.add_edge(START, "n")
-        builder.add_edge("n", END)
-        graph = builder.compile()
-
-        run = graph.stream_v2({"value": "", "items": []})
-
-        collected: list[SubgraphRunStream] = []
-        for sub in run.subgraphs:
-            collected.append(sub)
-        assert collected == []
-        # Output still resolves.
-        assert run.output is not None
-
-    def test_nested_graph_yields_one_child(self) -> None:
-        graph = _build_nested_graph()
-        run = graph.stream_v2({"value": "", "items": []})
-
-        collected: list[SubgraphRunStream] = []
-        for sub in run.subgraphs:
-            collected.append(sub)
-
-        assert len(collected) == 1
-        child = collected[0]
-        assert len(child.path) == 1
-        assert child.path[0].startswith("sub:")
-        assert child.status == "completed"
-
-    def test_error_in_subgraph_fails_child(self) -> None:
-        def boom(state: SimpleState) -> dict:
-            raise RuntimeError("subgraph_failed")
-
-        inner_builder = StateGraph(SimpleState)
-        inner_builder.add_node("inner", boom)
-        inner_builder.add_edge(START, "inner")
-        inner_builder.add_edge("inner", END)
-        inner = inner_builder.compile()
-
-        outer_builder = StateGraph(SimpleState)
-        outer_builder.add_node("sub", inner)
-        outer_builder.add_edge(START, "sub")
-        outer_builder.add_edge("sub", END)
-        graph = outer_builder.compile()
-
-        run = graph.stream_v2({"value": "", "items": []})
-
-        collected: list[SubgraphRunStream] = []
-        with pytest.raises(RuntimeError):
-            for sub in run.subgraphs:
-                collected.append(sub)
-
-        assert len(collected) == 1
-        assert collected[0].status == "failed"
-
-
-class TestSubgraphTransformerAsyncEndToEnd:
-    @pytest.mark.anyio
-    async def test_nested_graph_yields_one_child(self) -> None:
-        async def inner(state: SimpleState) -> dict:
-            return {"value": state["value"] + "X", "items": ["x"]}
-
-        inner_builder = StateGraph(SimpleState)
-        inner_builder.add_node("inner", inner)
-        inner_builder.add_edge(START, "inner")
-        inner_builder.add_edge("inner", END)
-        inner_graph = inner_builder.compile()
-
-        outer_builder = StateGraph(SimpleState)
-        outer_builder.add_node("sub", inner_graph)
-        outer_builder.add_edge(START, "sub")
-        outer_builder.add_edge("sub", END)
-        graph = outer_builder.compile()
-
-        run = await graph.astream_v2({"value": "", "items": []})
-
-        collected: list[SubgraphRunStream] = []
-        async for sub in run.subgraphs:
-            collected.append(sub)
-
-        assert len(collected) == 1
-        child = collected[0]
-        assert child.status == "completed"
-
-
-class TestSubgraphCause:
-    """Pregel core emits no `cause`; product transformers populate it."""
-
-    def test_cause_not_populated_by_pregel(self) -> None:
-        graph = _build_nested_graph()
-        run = graph.stream_v2({"value": "", "items": []})
-
-        collected: list[SubgraphRunStream] = list(run.subgraphs)
-        assert len(collected) == 1
-        child = collected[0]
-
-        # The child's single-segment path still encodes `node_name:task_id`
-        # (that's pregel's internal namespace format), but `cause` is now
-        # product-agnostic and must be populated by a stream transformer,
-        # not by pregel itself.
-        assert ":" in child.path[0]
-        node_name, _, task_id = child.path[0].partition(":")
-        assert node_name == "sub"
-        assert task_id  # non-empty
-        assert child.cause is None
-
-
-class TestSubgraphInterrupt:
-    """Interrupts raised inside a subgraph surface as status=interrupted."""
-
-    def _build_interrupt_subgraph(self):
-        def inner_node(state: SimpleState) -> dict:
-            interrupt("need approval")
-            return {"value": state["value"] + "X", "items": ["x"]}
-
-        inner_builder = StateGraph(SimpleState)
-        inner_builder.add_node("inner_node", inner_node)
-        inner_builder.add_edge(START, "inner_node")
-        inner_builder.add_edge("inner_node", END)
-        inner = inner_builder.compile()
-
-        outer_builder = StateGraph(SimpleState)
-        outer_builder.add_node("sub", inner)
-        outer_builder.add_edge(START, "sub")
-        outer_builder.add_edge("sub", END)
-        return outer_builder.compile(checkpointer=InMemorySaver())
-
-    def test_interrupt_in_subgraph_marks_handle_interrupted(self) -> None:
-        graph = self._build_interrupt_subgraph()
-        run = graph.stream_v2(
-            {"value": "", "items": []},
-            config={"configurable": {"thread_id": "t1"}},
-        )
-
-        collected: list[SubgraphRunStream] = list(run.subgraphs)
-
-        assert run.interrupted is True
-        assert len(collected) == 1
-        assert collected[0].status == "interrupted"
-
-
-class TestSubgraphNameCollision:
-    """The subgraph's compiled `name` equaling its node name is detected.
-
-    Primary detector `name != langgraph_node` fails here; the
-    parent_run_id fallback in `_is_nested_pregel_start` is what keeps
-    the subgraph visible.
-    """
-
-    def test_name_equals_node_name_still_detected(self) -> None:
-        def inner_node(state: SimpleState) -> dict:
-            return {"value": state["value"] + "X", "items": ["x"]}
-
-        inner_builder = StateGraph(SimpleState)
-        inner_builder.add_node("inner_node", inner_node)
-        inner_builder.add_edge(START, "inner_node")
-        inner_builder.add_edge("inner_node", END)
-        # Compile with the same name as the node it will be registered as.
-        inner = inner_builder.compile(name="sub")
-
-        outer_builder = StateGraph(SimpleState)
-        outer_builder.add_node("sub", inner)
-        outer_builder.add_edge(START, "sub")
-        outer_builder.add_edge("sub", END)
-        graph = outer_builder.compile()
-
-        run = graph.stream_v2({"value": "", "items": []})
-
-        collected: list[SubgraphRunStream] = list(run.subgraphs)
-        assert len(collected) == 1
-        child = collected[0]
-        assert child.graph_name == "sub"
-        assert child.status == "completed"
@@ -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
@@ -1,290 +0,0 @@
-"""Tests for StreamToolCallHandler and emit_tool_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
-from typing_extensions import TypedDict
-
-from langgraph.config import emit_tool_output_delta
-from langgraph.constants import END, START
-from langgraph.graph import StateGraph
-from langgraph.graph.message import add_messages
-
-
-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_tool_output_delta_produces_delta_events(self) -> None:
-        @tool
-        def streaming_echo(text: str) -> str:
-            """stream chunks."""
-            for chunk in ("a", "b", "c"):
-                emit_tool_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_emit_outside_tool_is_noop(self) -> None:
-        # Called at import time (outside any tool body) — must not raise.
-        emit_tool_output_delta("ignored")
-        emit_tool_output_delta({"any": "payload"})
-
-    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) -> str:
-            """async echo."""
-            emit_tool_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) -> str:
-            """emits marker twice."""
-            emit_tool_output_delta(f"{marker}-1")
-            emit_tool_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"
+version = "1.2.22"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
-    { name = "langchain-protocol" },
    { name = "langsmith" },
    { name = "packaging" },
    { name = "pydantic" },
@@ -1361,26 +1360,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a8/03/7219502e8ca728d65eb44d7a3eb60239230742a70dbfc9241b9bfd61c4ab/langchain_core-1.3.2.tar.gz", hash = "sha256:fd7a50b2f28ba561fd9d7f5d2760bc9e06cf00cdf820a3ccafe88a94ffa8d5b7", size = 911813, upload-time = "2026-04-24T15:49:23.699Z" }
+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 = [
-    { url = "https://files.pythonhosted.org/packages/7d/d5/8fa4431007cbb7cfed7590f4d6a5dea3ad724f4174d248f6642ef5ce7d05/langchain_core-1.3.2-py3-none-any.whl", hash = "sha256:d44a66127f9f8db735bdfd0ab9661bccb47a97113cfd3f2d89c74864422b7274", size = 542390, upload-time = "2026-04-24T15:49:21.991Z" },
-]
-
-[[package]]
-name = "langchain-protocol"
-version = "0.0.12"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "typing-extensions" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/5c/51/1157009b6f94e6e58be58fa8b620187d657909a8b36a6bf5b0c52a2711f6/langchain_protocol-0.0.12.tar.gz", hash = "sha256:5e14c434290a705c9510fdb1a83ecf7561a5e6e0dfd053930ade80dba069269f", size = 6408, upload-time = "2026-04-25T01:05:01.489Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/95/82/3431e3061c917439589fa88a6b23c9bc0e154cba0f05d2e895a68c76ff74/langchain_protocol-0.0.12-py3-none-any.whl", hash = "sha256:402b61f42d4139692528cf37226c367bb6efc8ff8165b29380accb0abfece7b2", size = 6639, upload-time = "2026-04-25T01:05:00.487Z" },
+    { 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 = "1.1.7a2"
+version = "1.1.6"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -1452,7 +1439,7 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=1.3.2" },
+    { name = "langchain-core", specifier = ">=0.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "../prebuilt" },
    { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -2918,7 +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'" },
@@ -2929,9 +2916,9 @@ dependencies = [
    { name = "pygments" },
    { name = "tomli", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" }
+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" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
+    { 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" },
 ]

 [[package]]
@@ -1,7 +1,5 @@
 """langgraph.prebuilt exposes a higher-level API for creating and executing agents and tools."""

-from langgraph.prebuilt._tool_call_stream import ToolCallStream
-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,
@@ -15,8 +13,6 @@ from langgraph.prebuilt.tool_validator import ValidationNode
 __all__ = [
    "create_react_agent",
    "ToolNode",
-    "ToolCallStream",
-    "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._event_log import EventLog
-
-
-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`: an `EventLog` 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: EventLog[Any] = EventLog()
-        self.output: Any = None
-        self.error: str | None = None
-        self.completed = False
-
-    @property
-    def output_deltas(self) -> EventLog[Any]:
-        """The EventLog 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})"
-        )
@@ -1,128 +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._event_log import EventLog
-from langgraph.stream._types import ProtocolEvent, StreamTransformer
-
-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.
-
-    `EventLog[ToolCallStream]` is used (not `StreamChannel`) because the
-    live handles are not serializable and should not be auto-forwarded
-    onto 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: EventLog[ToolCallStream] = EventLog()
-        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()
@@ -1,306 +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.config import emit_tool_output_delta
-from langgraph.constants import END, START
-from langgraph.graph import StateGraph
-from langgraph.graph.message import add_messages
-from langgraph.stream._event_log import EventLog
-from langgraph.stream._mux import StreamMux
-from langgraph.stream._types import ProtocolEvent
-from langgraph.stream.transformers import (
-    MessagesTransformer,
-    SubgraphTransformer,
-    ValuesTransformer,
-)
-from typing_extensions import TypedDict
-
-from langgraph.prebuilt import ToolCallStream, ToolCallTransformer, ToolNode
-
-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: EventLog) -> None:
-    log._subscribed = True
-
-
-def _mux() -> tuple[StreamMux, ToolCallTransformer]:
-    mux = StreamMux(
-        factories=[
-            ValuesTransformer,
-            MessagesTransformer,
-            SubgraphTransformer,
-            ToolCallTransformer,
-        ],
-        is_async=False,
-    )
-    transformer = mux.transformer_by_key("tool_calls")
-    assert isinstance(transformer, ToolCallTransformer)
-    _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) -> str:
-            """streams chunks."""
-            for chunk in ("one", "two"):
-                emit_tool_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) -> str:
-            """async streams."""
-            emit_tool_output_delta(text)
-            emit_tool_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
@@ -249,7 +249,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.3.0a2"
+version = "1.2.25"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -261,14 +261,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/af/bc/0bff31fcaff174d86031cc713471a3e85ed4ec8e5cd95ad0217f2aced20e/langchain_core-1.3.0a2.tar.gz", hash = "sha256:52d978c84552b74b9a3f16c1fced84f9e27cc96d7a67c601925ce6cbc4ea3cf9", size = 854580, upload-time = "2026-04-13T14:37:55.745Z" }
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+    { url = "https://files.pythonhosted.org/packages/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 = "1.1.7a2"
+version = "1.1.6"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -281,7 +281,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = "==1.3.0a2" },
+    { name = "langchain-core", specifier = ">=0.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "." },
    { name = "langgraph-sdk", editable = "../sdk-py" },
@@ -1182,7 +1182,7 @@ wheels = [

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 name = "pytest"
-version = "9.0.3"
+version = "9.0.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "colorama", marker = "sys_platform == 'win32'" },
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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]]
@@ -262,7 +262,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.3.0a2"
+version = "1.2.28"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -274,14 +274,14 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/af/bc/0bff31fcaff174d86031cc713471a3e85ed4ec8e5cd95ad0217f2aced20e/langchain_core-1.3.0a2.tar.gz", hash = "sha256:52d978c84552b74b9a3f16c1fced84f9e27cc96d7a67c601925ce6cbc4ea3cf9", size = 854580, upload-time = "2026-04-13T14:37:55.745Z" }
+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"
-version = "1.1.7a2"
+version = "1.1.6"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -294,7 +294,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = "==1.3.0a2" },
+    { name = "langchain-core", specifier = ">=0.1" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-prebuilt", editable = "../prebuilt" },
    { name = "langgraph-sdk", editable = "." },
@@ -1000,7 +1000,7 @@ wheels = [

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-version = "9.0.3"
+version = "9.0.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "colorama", marker = "sys_platform == 'win32'" },
@@ -1011,9 +1011,9 @@ dependencies = [
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 [[package]]