chore: use bounded queue for checkpointing

fix: handle non-deterministic ordering in test_imp_nested
Nested tasks run concurrently so output order is non-deterministic. Sort intermediate results before comparison, matching the pattern already used by test_imp_task. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-08-27 01:52:25 +02:00 · 2026-04-09 17:33:50 -07:00 · 2026-04-08 18:04:55 -07:00 · 2026-04-08 16:02:42 -07:00
54 changed files with 823 additions and 8589 deletions
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@@ -6,11 +6,6 @@ Implementation of LangGraph CheckpointSaver that uses Postgres.

 By default `langgraph-checkpoint-postgres` installs `psycopg` (Psycopg 3) without any extras. However, you can choose a specific installation that best suits your needs [here](https://www.psycopg.org/psycopg3/docs/basic/install.html) (for example, `psycopg[binary]`).

-## Security
-
-> [!IMPORTANT]
-> Set `LANGGRAPH_STRICT_MSGPACK=true` or pass an explicit `allowed_msgpack_modules` list when creating your checkpointer. This restricts checkpoint deserialization to known-safe types, preventing code execution if the database is compromised. See the [langgraph-checkpoint README](https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint#serde) for details.
-
 ## Usage

 > [!IMPORTANT]
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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
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 [[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,
@@ -267,7 +267,7 @@ wheels = [

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@@ -1086,6 +1086,11 @@
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+"@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==
+
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@@ -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==
@@ -215,7 +215,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.2.28"
+version = "1.2.27"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -227,9 +227,9 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-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]]
@@ -191,7 +191,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.2.28"
+version = "1.2.27"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -203,9 +203,9 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "uuid-utils" },
 ]
-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]]
@@ -413,62 +413,62 @@ wheels = [

 [[package]]
 name = "cryptography"
-version = "46.0.7"
+version = "46.0.6"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
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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

@@ -0,0 +1,215 @@
+from __future__ import annotations
+
+import asyncio
+import os
+import queue
+import threading
+from collections.abc import Callable
+from contextlib import AbstractAsyncContextManager, AbstractContextManager
+from dataclasses import dataclass
+from types import TracebackType
+from typing import Any
+
+from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import (
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+)
+
+QUEUE_PUT_TIMEOUT = 0.05
+CHECKPOINT_BACKLOG_ENV_VAR = "LANGGRAPH_CHECKPOINT_BACKLOG"
+DEFAULT_CHECKPOINT_BACKLOG = 10
+
+
+@dataclass(frozen=True)
+class CheckpointRequest:
+    config: RunnableConfig
+    checkpoint: Checkpoint
+    metadata: CheckpointMetadata
+    new_versions: ChannelVersions
+
+
+def _raise(error: BaseException) -> None:
+    raise error
+
+
+def resolve_checkpoint_backlog() -> int:
+    if raw := os.getenv(CHECKPOINT_BACKLOG_ENV_VAR):
+        try:
+            backlog = int(raw)
+        except ValueError:
+            return DEFAULT_CHECKPOINT_BACKLOG
+        if backlog > 0:
+            return backlog
+    return DEFAULT_CHECKPOINT_BACKLOG
+
+
+class SyncCheckpointWriter(AbstractContextManager):
+    def __init__(
+        self,
+        put: Callable[
+            [RunnableConfig, Checkpoint, CheckpointMetadata, ChannelVersions], Any
+        ],
+        *,
+        max_pending: int | None = None,
+    ) -> None:
+        self.put = put
+        max_pending = (
+            resolve_checkpoint_backlog() if max_pending is None else max_pending
+        )
+        self.queue: queue.Queue[CheckpointRequest | None] = queue.Queue(max_pending)
+        self.error: BaseException | None = None
+        self.closed = False
+        self.thread = threading.Thread(
+            target=self._run,
+            name="langgraph-checkpoint-writer",
+            daemon=True,
+        )
+
+    def __enter__(self) -> SyncCheckpointWriter:
+        self.thread.start()
+        return self
+
+    def submit(self, request: CheckpointRequest) -> None:
+        self._ensure_open()
+        while True:
+            self._raise_if_broken()
+            try:
+                self.queue.put(request, timeout=QUEUE_PUT_TIMEOUT)
+            except queue.Full:
+                continue
+            else:
+                self._raise_if_broken()
+                return
+
+    def _run(self) -> None:
+        while True:
+            item = self.queue.get()
+            if item is None:
+                return
+            try:
+                self.put(
+                    item.config,
+                    item.checkpoint,
+                    item.metadata,
+                    item.new_versions,
+                )
+            except BaseException as exc:
+                self.error = exc
+                return
+
+    def _ensure_open(self) -> None:
+        if self.closed:
+            raise RuntimeError("Checkpoint writer is closed")
+
+    def _raise_if_broken(self) -> None:
+        if self.error is not None:
+            _raise(self.error)
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_value: BaseException | None,
+        traceback: TracebackType | None,
+    ) -> bool | None:
+        self.closed = True
+        while self.thread.is_alive():
+            if self.error is not None:
+                break
+            try:
+                self.queue.put(None, timeout=QUEUE_PUT_TIMEOUT)
+            except queue.Full:
+                continue
+            else:
+                break
+        self.thread.join()
+        if exc_type is None and self.error is not None:
+            _raise(self.error)
+        return None
+
+
+class AsyncCheckpointWriter(AbstractAsyncContextManager):
+    def __init__(
+        self,
+        put: Callable[
+            [RunnableConfig, Checkpoint, CheckpointMetadata, ChannelVersions], Any
+        ],
+        *,
+        max_pending: int | None = None,
+    ) -> None:
+        self.put = put
+        max_pending = (
+            resolve_checkpoint_backlog() if max_pending is None else max_pending
+        )
+        self.queue: asyncio.Queue[CheckpointRequest | None] = asyncio.Queue(max_pending)
+        self.error: BaseException | None = None
+        self.closed = False
+        self.task: asyncio.Task[None] | None = None
+
+    async def __aenter__(self) -> AsyncCheckpointWriter:
+        self.task = asyncio.create_task(self._run(), name="langgraph-checkpoint-writer")
+        return self
+
+    async def submit(self, request: CheckpointRequest) -> None:
+        self._ensure_open()
+        while True:
+            self._raise_if_broken()
+            try:
+                await asyncio.wait_for(
+                    self.queue.put(request),
+                    timeout=QUEUE_PUT_TIMEOUT,
+                )
+            except asyncio.TimeoutError:
+                continue
+            else:
+                self._raise_if_broken()
+                return
+
+    async def _run(self) -> None:
+        while True:
+            item = await self.queue.get()
+            if item is None:
+                return
+            try:
+                await self.put(
+                    item.config,
+                    item.checkpoint,
+                    item.metadata,
+                    item.new_versions,
+                )
+            except BaseException as exc:
+                self.error = exc
+                return
+
+    def _ensure_open(self) -> None:
+        if self.closed:
+            raise RuntimeError("Checkpoint writer is closed")
+
+    def _raise_if_broken(self) -> None:
+        if self.error is not None:
+            _raise(self.error)
+
+    async def __aexit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_value: BaseException | None,
+        traceback: TracebackType | None,
+    ) -> None:
+        self.closed = True
+        while self.task is not None and not self.task.done():
+            if self.error is not None:
+                break
+            try:
+                await asyncio.wait_for(
+                    self.queue.put(None),
+                    timeout=QUEUE_PUT_TIMEOUT,
+                )
+            except asyncio.TimeoutError:
+                continue
+            else:
+                break
+        if self.task is not None:
+            await self.task
+        if exc_type is None and self.error is not None:
+            _raise(self.error)
@@ -1,291 +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]
-
-    @staticmethod
-    def _trigger_call_id(metadata: dict[str, Any] | None) -> str | None:
-        """Extract `trigger_call_id` from task metadata if present.
-
-        The task that spawned a nested `Pregel` has its task id encoded
-        in `langgraph_checkpoint_ns`'s last segment as
-        `node_name:task_id`. Returns the `task_id` portion, which
-        parents can correlate with their `tools` / `tasks` events.
-        """
-        if not metadata:
-            return None
-        nskey = cast(str | None, metadata.get("langgraph_checkpoint_ns"))
-        if not nskey:
-            return None
-        last = nskey.split(NS_SEP)[-1]
-        _, sep, task_id = last.rpartition(":")
-        return task_id if sep else None
-
-    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
-        trigger_call_id = self._trigger_call_id(metadata)
-        if trigger_call_id:
-            payload["trigger_call_id"] = trigger_call_id
-        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)})
@@ -2,7 +2,6 @@ from __future__ import annotations

 import asyncio
 import binascii
-import concurrent.futures
 from collections import defaultdict, deque
 from collections.abc import Callable, Iterator, Mapping, Sequence
 from contextlib import (
@@ -27,7 +26,6 @@ from langgraph.cache.base import BaseCache
 from langgraph.checkpoint.base import (
    WRITES_IDX_MAP,
    BaseCheckpointSaver,
-    ChannelVersions,
    Checkpoint,
    CheckpointMetadata,
    CheckpointTuple,
@@ -62,11 +60,6 @@ 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
@@ -97,6 +90,11 @@ from langgraph.pregel._checkpoint import (
    create_checkpoint,
    empty_checkpoint,
 )
+from langgraph.pregel._checkpoint_writer import (
+    AsyncCheckpointWriter,
+    CheckpointRequest,
+    SyncCheckpointWriter,
+)
 from langgraph.pregel._executor import (
    AsyncBackgroundExecutor,
    BackgroundExecutor,
@@ -122,7 +120,6 @@ from langgraph.types import (
    CachePolicy,
    Command,
    Durability,
-    Interrupt,
    PregelExecutableTask,
    RetryPolicy,
    Send,
@@ -172,19 +169,6 @@ class PregelLoop:
    checkpointer_get_next_version: GetNextVersion
    checkpointer_put_writes: Callable[[RunnableConfig, WritesT, str], Any] | None
    checkpointer_put_writes_accepts_task_path: bool
-    _checkpointer_put_after_previous: (
-        Callable[
-            [
-                concurrent.futures.Future | None,
-                RunnableConfig,
-                Checkpoint,
-                str,
-                ChannelVersions,
-            ],
-            Any,
-        ]
-        | None
-    )
    _migrate_checkpoint: Callable[[Checkpoint], None] | None
    submit: Submit
    channels: Mapping[str, BaseChannel]
@@ -209,8 +193,6 @@ 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 +218,6 @@ 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 +242,6 @@ 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 +293,6 @@ 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:
@@ -536,7 +481,7 @@ class PregelLoop:
        )

        # produce debug output
-        if self._checkpointer_put_after_previous is not None:
+        if self.checkpointer is not None:
            self._emit(
                "checkpoints",
                map_debug_checkpoint,
@@ -582,7 +527,7 @@ class PregelLoop:

        return True

-    def after_tick(self) -> None:
+    def _after_tick(self) -> CheckpointRequest | None:
        # finish superstep
        writes = [w for t in self.tasks.values() for w in t.writes]
        # all tasks have finished
@@ -607,14 +552,14 @@ class PregelLoop:
        # only replay (re-execute) done tasks on the first tick
        self.is_replaying = False
        # save checkpoint
-        self._put_checkpoint({"source": "loop"})
-        # after execution, check if we should interrupt
+        return self._prepare_checkpoint({"source": "loop"})
+
+    def _finish_after_tick(self) -> None:
        if self.interrupt_after and should_interrupt(
            self.checkpoint, self.interrupt_after, self.tasks.values()
        ):
            self.status = "interrupt_after"
            raise GraphInterrupt()
-        # unset resuming flag
        self.config[CONF].pop(CONFIG_KEY_RESUMING, None)

    def match_cached_writes(self) -> Sequence[PregelExecutableTask]:
@@ -664,7 +609,7 @@ class PregelLoop:

    def _first(
        self, *, input_keys: str | Sequence[str], updated_channels: set[str] | None
-    ) -> set[str] | None:
+    ) -> tuple[set[str] | None, CheckpointRequest | None]:
        # Resuming from a previous checkpoint requires two things:
        # 1. A prior checkpoint exists (channel_versions is non-empty)
        # 2. The input signals continuation (not a fresh run with new input)
@@ -758,6 +703,7 @@ class PregelLoop:
            )
            if updated_channels is not None:
                updated_channels.update(null_updated_channels)
+        checkpoint_request = None
        # proceed past previous checkpoint
        if is_resuming:
            self.checkpoint["versions_seen"].setdefault(INTERRUPT, {})
@@ -800,7 +746,7 @@ class PregelLoop:
            )
            # save input checkpoint
            self.updated_channels = updated_channels
-            self._put_checkpoint({"source": "input"})
+            checkpoint_request = self._prepare_checkpoint({"source": "input"})
        elif CONFIG_KEY_RESUMING not in configurable:
            raise EmptyInputError(f"Received no input for {input_keys}")
        # Propagate resuming and replaying flags to subgraphs.
@@ -830,11 +776,11 @@ class PregelLoop:
            )
        # set flag
        self.status = "pending"
-        if is_resuming:
-            self._push_graph_lifecycle_event("resume")
-        return updated_channels
+        return updated_channels, checkpoint_request

-    def _put_checkpoint(self, metadata: CheckpointMetadata) -> None:
+    def _prepare_checkpoint(
+        self, metadata: CheckpointMetadata
+    ) -> CheckpointRequest | None:
        # assign step and parents
        exiting = metadata is self.checkpoint_metadata
        if exiting and self.checkpoint["id"] == self.checkpoint_id_saved:
@@ -844,8 +790,7 @@ class PregelLoop:
            metadata["step"] = self.step
            metadata["parents"] = self.config[CONF].get(CONFIG_KEY_CHECKPOINT_MAP, {})
            self.checkpoint_metadata = metadata
-        # do checkpoint?
-        do_checkpoint = self._checkpointer_put_after_previous is not None and (
+        do_checkpoint = self.checkpointer is not None and (
            exiting or self.durability != "exit"
        )
        # create new checkpoint
@@ -867,9 +812,8 @@ class PregelLoop:
                for value in self.checkpoint["channel_values"][TASKS]
            ]
            self.checkpoint["channel_values"][TASKS] = sanitized_tasks
-        # bail if no checkpointer
-
-        if do_checkpoint and self._checkpointer_put_after_previous is not None:
+        request = None
+        if do_checkpoint:
            self.prev_checkpoint_config = (
                self.checkpoint_config
                if CONFIG_KEY_CHECKPOINT_ID in self.checkpoint_config[CONF]
@@ -891,17 +835,11 @@ class PregelLoop:
                self.checkpoint_previous_versions, channel_versions
            )
            self.checkpoint_previous_versions = channel_versions
-
-            # save it, without blocking
-            # if there's a previous checkpoint save in progress, wait for it
-            # ensuring checkpointers receive checkpoints in order
-            self._put_checkpoint_fut = self.submit(
-                self._checkpointer_put_after_previous,
-                getattr(self, "_put_checkpoint_fut", None),
-                self.checkpoint_config,
-                copy_checkpoint(self.checkpoint),
-                self.checkpoint_metadata,
-                new_versions,
+            request = CheckpointRequest(
+                config=self.checkpoint_config,
+                checkpoint=copy_checkpoint(self.checkpoint),
+                metadata=self.checkpoint_metadata,
+                new_versions=new_versions,
            )
            self.checkpoint_config = {
                **self.checkpoint_config,
@@ -913,30 +851,18 @@ class PregelLoop:
        if not exiting:
            # increment step
            self.step += 1
+        return request

-    def _suppress_interrupt(
+    def _put_checkpoint(self, metadata: CheckpointMetadata) -> None:
+        raise NotImplementedError
+
+    def _finalize_suppress(
        self,
        exc_type: type[BaseException] | None,
        exc_value: BaseException | None,
-        traceback: TracebackType | None,
    ) -> bool | None:
-        # persist current checkpoint and writes
-        if self.durability == "exit" and (
-            # if it's a top graph
-            not self.is_nested
-            # or a nested graph with error or interrupt
-            or exc_value is not None
-            # or a nested graph with checkpointer=True
-            or all(NS_END not in part for part in self.checkpoint_ns)
-        ):
-            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)
-            # emit one last "values" event, with pending writes applied
+        suppress = isinstance(exc_value, GraphInterrupt) and not self.is_nested
+        if suppress:
            if (
                hasattr(self, "tasks")
                and self.checkpoint_pending_writes
@@ -961,20 +887,33 @@ class PregelLoop:
                        [w for t in self.tasks.values() for w in t.writes],
                        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)
-            # suppress interrupt
            return True
        elif exc_type is None:
-            # save final output
            self.output = read_channels(self.channels, self.output_keys)
+        return None
+
+    def _suppress_interrupt(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_value: BaseException | None,
+        traceback: TracebackType | None,
+    ) -> bool | None:
+        if self.durability == "exit" and (
+            not self.is_nested
+            or exc_value is not None
+            or all(NS_END not in part for part in self.checkpoint_ns)
+        ):
+            self._put_checkpoint(self.checkpoint_metadata)
+            self._put_pending_writes()
+        return self._finalize_suppress(exc_type, exc_value)

    def _emit(
        self,
@@ -1088,7 +1027,6 @@ 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 +1048,6 @@ 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:
@@ -1122,26 +1059,30 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
            )
        else:
            self.checkpointer_get_next_version = increment
-            self._checkpointer_put_after_previous = None  # type: ignore[assignment]
            self.checkpointer_put_writes = None
            self.checkpointer_put_writes_accepts_task_path = False
+        self._checkpoint_writer: SyncCheckpointWriter | None = None

-    def _checkpointer_put_after_previous(
-        self,
-        prev: concurrent.futures.Future | None,
-        config: RunnableConfig,
-        checkpoint: Checkpoint,
-        metadata: CheckpointMetadata,
-        new_versions: ChannelVersions,
-    ) -> RunnableConfig:
-        try:
-            if prev is not None:
-                prev.result()
-        finally:
+    def _dispatch_checkpoint_request(self, request: CheckpointRequest) -> None:
+        if self.durability == "async" and self._checkpoint_writer is not None:
+            self._checkpoint_writer.submit(request)
+        else:
            cast(BaseCheckpointSaver, self.checkpointer).put(
-                config, checkpoint, metadata, new_versions
+                request.config,
+                request.checkpoint,
+                request.metadata,
+                request.new_versions,
            )

+    def _put_checkpoint(self, metadata: CheckpointMetadata) -> None:
+        if request := self._prepare_checkpoint(metadata):
+            self._dispatch_checkpoint_request(request)
+
+    def after_tick(self) -> None:
+        if request := self._after_tick():
+            self._dispatch_checkpoint_request(request)
+        self._finish_after_tick()
+
    def match_cached_writes(self) -> Sequence[PregelExecutableTask]:
        if self.cache is None:
            return ()
@@ -1186,7 +1127,6 @@ 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):
@@ -1237,6 +1177,10 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
            else []
        )
        self.submit = self.stack.enter_context(BackgroundExecutor(self.config))
+        if self.checkpointer is not None and self.durability == "async":
+            self._checkpoint_writer = self.stack.enter_context(
+                SyncCheckpointWriter(self.checkpointer.put)
+            )
        self.channels, self.managed = channels_from_checkpoint(
            self.specs, self.checkpoint
        )
@@ -1245,12 +1189,14 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
        self.step = self.checkpoint_metadata["step"] + 1
        self.stop = self.step + self.config["recursion_limit"] + 1
        self.checkpoint_previous_versions = self.checkpoint["channel_versions"].copy()
-        self.updated_channels = self._first(
+        self.updated_channels, checkpoint_request = self._first(
            input_keys=self.input_keys,
            updated_channels=set(self.checkpoint.get("updated_channels"))  # type: ignore[arg-type]
            if self.checkpoint.get("updated_channels")
            else None,
        )
+        if checkpoint_request is not None:
+            self._dispatch_checkpoint_request(checkpoint_request)

        return self

@@ -1287,7 +1233,6 @@ 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 +1254,6 @@ 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:
@@ -1321,26 +1265,26 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
            )
        else:
            self.checkpointer_get_next_version = increment
-            self._checkpointer_put_after_previous = None  # type: ignore[assignment]
            self.checkpointer_put_writes = None
            self.checkpointer_put_writes_accepts_task_path = False
+        self._checkpoint_writer: AsyncCheckpointWriter | None = None

-    async def _checkpointer_put_after_previous(
-        self,
-        prev: asyncio.Task | None,
-        config: RunnableConfig,
-        checkpoint: Checkpoint,
-        metadata: CheckpointMetadata,
-        new_versions: ChannelVersions,
-    ) -> RunnableConfig:
-        try:
-            if prev is not None:
-                await prev
-        finally:
+    async def _dispatch_checkpoint_request(self, request: CheckpointRequest) -> None:
+        if self.durability == "async" and self._checkpoint_writer is not None:
+            await self._checkpoint_writer.submit(request)
+        else:
            await cast(BaseCheckpointSaver, self.checkpointer).aput(
-                config, checkpoint, metadata, new_versions
+                request.config,
+                request.checkpoint,
+                request.metadata,
+                request.new_versions,
            )

+    async def aafter_tick(self) -> None:
+        if request := self._after_tick():
+            await self._dispatch_checkpoint_request(request)
+        self._finish_after_tick()
+
    async def amatch_cached_writes(self) -> Sequence[PregelExecutableTask]:
        if self.cache is None:
            return []
@@ -1385,10 +1329,25 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
            },
        )

+    async def _asuppress_interrupt(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_value: BaseException | None,
+        traceback: TracebackType | None,
+    ) -> bool | None:
+        if self.durability == "exit" and (
+            not self.is_nested
+            or exc_value is not None
+            or all(NS_END not in part for part in self.checkpoint_ns)
+        ):
+            if request := self._prepare_checkpoint(self.checkpoint_metadata):
+                await self._dispatch_checkpoint_request(request)
+            self._put_pending_writes()
+        return self._finalize_suppress(exc_type, exc_value)
+
    # 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):
@@ -1441,20 +1400,26 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
        self.submit = await self.stack.enter_async_context(
            AsyncBackgroundExecutor(self.config)
        )
+        if self.checkpointer is not None and self.durability == "async":
+            self._checkpoint_writer = await self.stack.enter_async_context(
+                AsyncCheckpointWriter(self.checkpointer.aput)
+            )
        self.channels, self.managed = channels_from_checkpoint(
            self.specs, self.checkpoint
        )
-        self.stack.push(self._suppress_interrupt)
+        self.stack.push_async_exit(self._asuppress_interrupt)
        self.status = "input"
        self.step = self.checkpoint_metadata["step"] + 1
        self.stop = self.step + self.config["recursion_limit"] + 1
        self.checkpoint_previous_versions = self.checkpoint["channel_versions"].copy()
-        self.updated_channels = self._first(
+        self.updated_channels, checkpoint_request = self._first(
            input_keys=self.input_keys,
            updated_channels=set(self.checkpoint.get("updated_channels"))  # type: ignore[arg-type]
            if self.checkpoint.get("updated_channels")
            else None,
        )
+        if checkpoint_request is not None:
+            await self._dispatch_checkpoint_request(checkpoint_request)

        return self

@@ -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,
@@ -261,78 +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_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)))
@@ -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 +123,14 @@ 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._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
@@ -346,63 +334,6 @@ 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,
-        ValuesTransformer,
-    )
-
-    builtins: list[Callable[..., Any]] = [
-        ValuesTransformer,
-        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],
@@ -734,7 +665,6 @@ 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 (
@@ -781,9 +711,6 @@ 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()
@@ -2658,10 +2585,6 @@ 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
            (
@@ -2693,34 +2616,14 @@ 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)
-                    else StreamMessagesHandler
-                )
                run_manager.inheritable_handlers.append(
-                    messages_handler_cls(
+                    StreamMessagesHandler(
                        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:

@@ -2766,17 +2669,6 @@ 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),
@@ -2797,9 +2689,7 @@ 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(
@@ -2861,11 +2751,6 @@ 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,
@@ -3040,10 +2925,6 @@ 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(
@@ -3090,34 +2971,14 @@ class Pregel(
            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)
-                    else StreamMessagesHandler
-                )
                run_manager.inheritable_handlers.append(
-                    messages_handler_cls(
+                    StreamMessagesHandler(
                        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(
@@ -3178,28 +3039,6 @@ 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),
@@ -3220,9 +3059,7 @@ 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(
@@ -3303,18 +3140,12 @@ class Pregel(
                                _state_mapper,
                            ):
                                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)
+                        await loop.aafter_tick()
                finally:
                    # ensure waiter doesn't remain pending on cancel/shutdown
                    if _cleanup_waiter is not None:
                        await _cleanup_waiter()

-            await aemit_graph_lifecycle_events(loop)
-
            # emit output
            for o in _output(
                stream_mode,
@@ -3344,94 +3175,6 @@ 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,
-    ) -> 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)
-        stream_modes = _collect_stream_modes(mux)
-        graph_iter = iter(
-            self.stream(
-                input,
-                _merge_v2_messages_flag(config),
-                stream_mode=stream_modes,
-                subgraphs=True,
-                version="v2",
-                interrupt_before=interrupt_before,
-                interrupt_after=interrupt_after,
-            )
-        )
-        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,
-    ) -> 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)
-        stream_modes = _collect_stream_modes(mux)
-        graph_aiter = self.astream(
-            input,
-            _merge_v2_messages_flag(config),
-            stream_mode=stream_modes,
-            subgraphs=True,
-            version="v2",
-            interrupt_before=interrupt_before,
-            interrupt_after=interrupt_after,
-        ).__aiter__()
-        return AsyncGraphRunStream(graph_aiter, mux)
-
    @overload
    def invoke(
        self,
@@ -3910,14 +3653,15 @@ 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 +0,0 @@
-"""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.
-"""
-
-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
-
-__all__ = [
-    "AsyncGraphRunStream",
-    "EventLog",
-    "GraphRunStream",
-    "ProtocolEvent",
-    "StreamChannel",
-    "StreamTransformer",
-]
@@ -1,32 +0,0 @@
-from __future__ import annotations
-
-import time
-from typing import Any, cast
-
-from langgraph.stream._types import ProtocolEvent, _ProtocolEventParams
-from langgraph.types import StreamPart
-
-
-def convert_to_protocol_event(part: StreamPart) -> ProtocolEvent:
-    """Convert a v2 StreamPart to a ProtocolEvent.
-
-    Args:
-        part: A stream part with keys `type`, `ns`, `data`, and
-            optionally `interrupts` (present on values events).
-
-    Returns:
-        The equivalent ProtocolEvent.
-    """
-    part_dict = cast(dict[str, Any], part)
-    params: _ProtocolEventParams = {
-        "namespace": list(part_dict["ns"]),
-        "timestamp": int(time.time() * 1000),
-        "data": part_dict["data"],
-    }
-    if "interrupts" in part_dict:
-        params["interrupts"] = part_dict["interrupts"]
-    return {
-        "type": "event",
-        "method": part_dict["type"],
-        "params": params,
-    }
@@ -1,306 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-from collections import deque
-from collections.abc import AsyncIterator, Awaitable, Callable, Iterator
-from typing import Generic, TypeVar
-
-T = TypeVar("T")
-
-
-class EventLog(Generic[T]):
-    """Single-consumer drainable queue for streaming events.
-
-    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.
-    """
-
-    def __init__(self, maxlen: int | None = None) -> None:
-        """Initialize an empty, unbound log.
-
-        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
-        self._closed = False
-        self._error: BaseException | None = None
-
-        # Binding state — None means unbound.
-        self._is_async: bool | None = None
-
-        # 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 close(self) -> None:
-        """Mark the log as complete."""
-        self._closed = True
-
-    def fail(self, err: BaseException) -> None:
-        """Mark the log as errored.
-
-        Args:
-            err: The exception to surface to the subscriber.
-        """
-        self._error = err
-        self._closed = True
-
-    # ------------------------------------------------------------------
-    # Sync iteration (caller-driven pump)
-    # ------------------------------------------------------------------
-
-    def __iter__(self) -> Iterator[T]:
-        """Subscribe and return a sync cursor. Can be called only once.
-
-        Raises:
-            TypeError: If the 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 _sync_cursor(self) -> Iterator[T]:
-        while True:
-            if self._items:
-                yield self._items.popleft()
-            elif self._closed:
-                if self._error is not None:
-                    raise self._error
-                return
-            elif self._request_more is not None:
-                if not self._request_more():
-                    if not self._items and not self._closed:
-                        return
-            else:
-                return
-
-    # ------------------------------------------------------------------
-    # Async iteration (caller-driven pump)
-    # ------------------------------------------------------------------
-
-    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:
-                    try:
-                        item = next(source)
-                    except StopIteration:
-                        exhausted[0] = True
-                        return
-                    for b in buffers:
-                        b.append(item)
-
-        return tuple(branch(i) for i in range(n))
-
-    def atee(self, n: int = 2) -> tuple[AsyncIterator[T], ...]:
-        """Subscribe and return `n` independent async iterators.
-
-        Caller-driven fan-out: each branch's `__anext__` either pops
-        from its own buffer or, under a shared `asyncio.Lock`, pulls
-        one item from the underlying cursor and distributes it to
-        every branch's buffer.
-
-        Args:
-            n: Number of branches to create. Must be >= 1.
-
-        Returns:
-            A tuple of `n` async iterators over the same underlying
-            stream.
-
-        Raises:
-            TypeError: If the 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))
@@ -1,487 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import time
-from collections.abc import Awaitable, Callable
-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=...)`.
-"""
-
-
-class StreamMux:
-    """Central event dispatcher for the streaming 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.
-
-    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`.
-    """
-
-    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] = []
-        self._channels: list[StreamChannel[Any]] = []
-        self._logs: list[EventLog[Any]] = []
-        self._seq = 0
-
-        self.extensions: dict[str, Any] = {}
-        self.native_keys: set[str] = set()
-        self._projection_owners: dict[str, str] = {}
-        self._transformer_by_key: dict[str, StreamTransformer] = {}
-
-        if factories is not None:
-            for factory in factories:
-                self._register(factory(scope))
-        else:
-            for transformer in transformers or ():
-                self._register(transformer)
-
-    def make_child(self, scope: tuple[str, ...]) -> StreamMux:
-        """Build a mini-mux with the same factories scoped to `scope`.
-
-        Used by `SubgraphTransformer` to attach a fresh transformer
-        pipeline to each discovered subgraph handle. The child mux
-        inherits the current pump binding (so cursors on its projection
-        logs drive the root pump) and carries the same factory list
-        forward to any grandchild subgraphs.
-
-        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 push(self, event: ProtocolEvent) -> None:
-        """Route an event through all transformers, then append to the main log.
-
-        Each transformer's `process()` is called in registration order
-        — 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.
-        """
-        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 transformer.process(event):
-                keep = False
-        if keep:
-            self._seq += 1
-            event["seq"] = self._seq
-            self._events.push(event)
-
-    def close(self) -> None:
-        """Finalize all transformers, close all projections and the main log.
-
-        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
-        for transformer in self._transformers:
-            try:
-                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.
-
-        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.
-
-        Args:
-            err: The exception that ended the run.
-        """
-        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)
-
-    # ------------------------------------------------------------------
-    # Async dispatch
-    # ------------------------------------------------------------------
-
-    async def apush(self, event: ProtocolEvent) -> None:
-        """Dispatch an event on the async lane.
-
-        Awaits each transformer's `aprocess` in registration order
-        before appending to the main log — 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.
-
-        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.
-
-        Args:
-            event: The protocol event to dispatch.
-        """
-        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.
-
-        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.
-
-        If any scheduled task raised under `on_error="raise"`, or any
-        transformer's `afinalize` raises, the exception propagates.
-        The caller (the pump) handles it by routing into `afail`.
-
-        Raises:
-            BaseException: The first scheduled-task or `afinalize`
-                error, re-raised after cleanup.
-        """
-        pending = self._collect_scheduled_tasks()
-        if pending:
-            results = await asyncio.gather(*pending, return_exceptions=True)
-            first_err = next(
-                (
-                    r
-                    for r in results
-                    if isinstance(r, BaseException)
-                    and not isinstance(r, asyncio.CancelledError)
-                ),
-                None,
-            )
-            if first_err is not None:
-                raise first_err
-
-        first_error: BaseException | None = None
-        for transformer in self._transformers:
-            try:
-                await transformer.afinalize()
-            except BaseException as e:
-                if first_error is None:
-                    first_error = e
-        for 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
-
-    async def afail(self, err: BaseException) -> None:
-        """Fail on the async lane.
-
-        Cancels every scheduled task across all transformers, awaits
-        them to completion, then runs each transformer's `afail` hook
-        and auto-fails logs, channels, and the main event log.
-
-        Args:
-            err: The exception that ended the run.
-        """
-        pending = self._collect_scheduled_tasks()
-        for task in pending:
-            task.cancel()
-        if pending:
-            await asyncio.gather(*pending, return_exceptions=True)
-
-        for transformer in self._transformers:
-            try:
-                await transformer.afail(err)
-            except BaseException:
-                pass
-        for 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 _forward(item: Any) -> None:
-                        self._forward(name, item)
-
-                    return _forward
-
-                value._wire(_make_forward(channel_name))
-            elif isinstance(value, EventLog):
-                value._bind(is_async=self._is_async)
-                self._logs.append(value)
-
-    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.
-        """
-        self._seq += 1
-        event: ProtocolEvent = {
-            "type": "event",
-            "seq": self._seq,
-            "method": f"custom:{channel_name}",
-            "params": {
-                "namespace": [],
-                "timestamp": int(time.time() * 1000),
-                "data": item,
-            },
-        }
-        self._events.push(event)
@@ -1,310 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import logging
-from abc import ABC, abstractmethod
-from collections.abc import Coroutine
-from typing import Any, ClassVar, Literal
-
-from typing_extensions import NotRequired, TypedDict
-
-_logger = logging.getLogger(__name__)
-
-
-class _ProtocolEventParams(TypedDict):
-    """Parameters for a protocol event.
-
-    `timestamp` is wall-clock milliseconds since the epoch and can go
-    backwards across NTP adjustments — use `ProtocolEvent.seq` for
-    ordering.
-    """
-
-    namespace: list[str]
-    timestamp: int
-    data: Any
-    interrupts: NotRequired[tuple[Any, ...]]
-
-
-class ProtocolEvent(TypedDict):
-    """A protocol event emitted by the streaming infrastructure.
-
-    Wraps a raw stream part (values, messages, custom, etc.) in a uniform
-    envelope with a monotonic sequence number assigned by the StreamMux.
-    Consumers that need a total order across events should use `seq`, not
-    `params.timestamp` (which is wall-clock and not monotonic).
-    """
-
-    type: Literal["event"]
-    eventId: NotRequired[str]
-    seq: NotRequired[int]
-    method: str  # StreamMode value: "values", "messages", "custom", etc.
-    params: _ProtocolEventParams
-
-
-class StreamTransformer(ABC):
-    """Extension point for custom stream projections.
-
-    Transformers observe protocol events flowing through the StreamMux and
-    build typed derived projections (EventLogs, StreamChannels, promises,
-    etc.).
-
-    Set `_native = True` on a transformer to have its projection keys
-    exposed as direct attributes on the run stream (in addition to
-    appearing in `run.extensions`).
-
-    Subclasses must implement `init` and override at least one of
-    `process` / `aprocess`. The `finalize` / `afinalize` and `fail` /
-    `afail` hooks are optional — the default implementations are no-ops.
-    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, 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.
-        """
-        ...
-
-    def process(self, event: ProtocolEvent) -> bool:
-        """Handle an event on the sync lane.
-
-        Called for every event before it is appended to the main event
-        log. Subclasses must override either `process` or `aprocess`.
-        The default raises so a missing override fails loudly rather
-        than silently passing every event through.
-
-        Args:
-            event: The protocol event to observe.
-
-        Returns:
-            True to keep the event in the main log, False to suppress it.
-        """
-        raise NotImplementedError(
-            f"{type(self).__name__} must override process() or aprocess()"
-        )
-
-    async def aprocess(self, event: ProtocolEvent) -> bool:
-        """Handle an event on the async lane.
-
-        The mux awaits this before dispatching to the next transformer,
-        so a slow `aprocess` serializes the pipeline. Use it only when
-        a later transformer — or a consumer reading the event
-        synchronously — must see the result of the async work (e.g.
-        PII redaction that mutates `event` in place).
-
-        The default delegates to `process`, so purely-sync transformers
-        run unchanged under `astream()`.
-
-        Args:
-            event: The protocol event to observe.
-
-        Returns:
-            True to keep the event in the main log, False to suppress it.
-        """
-        return self.process(event)
-
-    def finalize(self) -> None:
-        """Called when the run ends normally (sync lane).
-
-        Override to close EventLogs, resolve promises, or perform other
-        teardown. StreamChannel instances are auto-closed by the mux.
-        """
-
-    async def afinalize(self) -> None:
-        """Called when the run ends normally (async lane).
-
-        By the time this runs, the mux has already awaited every task
-        started via `schedule()`, so 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).
-
-        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.
-        """
-
-    async def afail(self, err: BaseException) -> None:
-        """Called when the run ends with an error (async lane).
-
-        The mux cancels and awaits every task started via `schedule()`
-        before calling this, so cleanup doesn't race with in-flight work.
-
-        The default delegates to `fail`.
-
-        Args:
-            err: The exception that ended the run.
-        """
-        self.fail(err)
-
-    # ------------------------------------------------------------------
-    # Scheduled async work
-    # ------------------------------------------------------------------
-
-    def schedule(
-        self,
-        coro: Coroutine[Any, Any, Any],
-        *,
-        on_error: Literal["log", "raise"] = "log",
-    ) -> asyncio.Task[Any]:
-        """Schedule a coroutine tied to this transformer's lifecycle.
-
-        The mux holds the task reference, awaits all scheduled tasks
-        during `aclose()` before calling `afinalize()`, and cancels
-        them on `afail()`. Authors don't need to track tasks or
-        implement the last-task-closes-the-log dance.
-
-        Requires a running event loop — call only under `astream()`.
-        Set `requires_async = True` on the class so registration under
-        sync `stream()` fails fast with a clear message.
-
-        Args:
-            coro: The coroutine to run. Its lifecycle is owned by the
-                mux from this point on.
-            on_error: `"log"` (default) catches and logs any exception
-                the coroutine raises, so a single failure doesn't tear
-                down the run. `"raise"` lets the exception propagate
-                when the mux joins pendings, converting the close path
-                into the fail path.
-
-        Returns:
-            The asyncio Task. Authors rarely need to await it directly
-            — consumers read results from whatever projection the
-            coroutine pushes into.
-
-        Raises:
-            RuntimeError: If called without a running event loop (i.e.
-                under sync `stream()` rather than `astream()`).
-        """
-        try:
-            asyncio.get_running_loop()
-        except RuntimeError:
-            raise RuntimeError(
-                f"{type(self).__name__}.schedule() requires a running "
-                "event loop; this transformer must run under astream(), "
-                "not stream(). Set requires_async=True on the class so "
-                "this fails at registration rather than at first event."
-            ) from None
-
-        wrapped = self._wrap_scheduled(coro) if on_error == "log" else coro
-        task = asyncio.create_task(wrapped)
-        tasks = self._scheduled_task_set()
-        tasks.add(task)
-        task.add_done_callback(tasks.discard)
-        return task
-
-    @staticmethod
-    async def _wrap_scheduled(coro: Coroutine[Any, Any, Any]) -> Any:
-        try:
-            return await coro
-        except asyncio.CancelledError:
-            raise
-        except BaseException:
-            _logger.exception("Scheduled StreamTransformer task failed")
-
-    def _scheduled_task_set(self) -> set[asyncio.Task[Any]]:
-        """Return the lazily-allocated task set.
-
-        Avoids requiring subclasses to call `super().__init__()`.
-        """
-        tasks: set[asyncio.Task[Any]] | None = getattr(
-            self, "_stream_scheduled_tasks", None
-        )
-        if tasks is None:
-            tasks = set()
-            self._stream_scheduled_tasks = tasks
-        return tasks
-
-
-def transformer_requires_async(transformer: StreamTransformer) -> bool:
-    """Return True if the transformer needs a running event loop.
-
-    A transformer requires async if it explicitly opts in
-    (`requires_async = True`) or overrides any of the async-lane methods
-    (`aprocess`, `afinalize`, `afail`).
-
-    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
@@ -1,412 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-from collections.abc import AsyncIterator, Awaitable, Callable, Iterator, Mapping
-from types import MappingProxyType, TracebackType
-from typing import TYPE_CHECKING, Any
-
-from langgraph.stream._convert import convert_to_protocol_event
-from langgraph.stream._mux import StreamMux
-from langgraph.stream._types import ProtocolEvent
-
-if TYPE_CHECKING:
-    from langgraph.stream.transformers import ValuesTransformer
-
-
-def _drive_until_done(pump: Callable[[], bool]) -> None:
-    """Call the sync pump until it returns False."""
-    while pump():
-        pass
-
-
-async def _adrive_until_done(pump: Callable[[], Awaitable[bool]]) -> None:
-    """Call the async pump until it returns False."""
-    while await pump():
-        pass
-
-
-class BaseRunStream:
-    """Shared shape for any object that wraps a `StreamMux`.
-
-    Root (`GraphRunStream` / `AsyncGraphRunStream`) and scoped
-    (`SubgraphRunStream`) streams both compose a `StreamMux`. The mux
-    owns the projections — `values`, `messages`, `subgraphs`, and any
-    user-registered keys — all exposed via `extensions`. Native
-    projections (`_native = True`) are also bound as direct attributes
-    (`run.values`, `run.messages`, …) for ergonomics.
-
-    Raw iteration (`for event in run` / `async for event in run`) and
-    the `interleave(...)` helper both live here so every subclass
-    behaves consistently. Subclasses only add pump ownership, scope
-    metadata, or sync/async flavor.
-    """
-
-    def __init__(self, mux: StreamMux) -> None:
-        self._mux = mux
-        self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
-        for key in mux.native_keys:
-            setattr(self, key, mux.extensions[key])
-
-    @property
-    def _values_transformer(self) -> ValuesTransformer:
-        """Look up the `ValuesTransformer` backing `output` / `interrupted`.
-
-        Resolved lazily off the mux so subclasses don't have to thread
-        it through their constructors. Raises if no `ValuesTransformer`
-        is registered — `output` / `interrupted` / `interrupts` have
-        nothing to return in that case, so failing loudly is better
-        than returning `None` silently.
-        """
-        from langgraph.stream.transformers import ValuesTransformer
-
-        vt = self._mux.transformer_by_key("values")
-        if not isinstance(vt, ValuesTransformer):
-            raise RuntimeError(
-                "No ValuesTransformer is registered on this mux — "
-                "`output`, `interrupted`, and `interrupts` require one. "
-                "Add it to your GraphStreamer subclass's "
-                "`builtin_factories` or pass it via `transformers=`."
-            )
-        return vt
-
-    def __iter__(self) -> Iterator[ProtocolEvent]:
-        """Sync iteration of protocol events on this mux's main log.
-
-        Raises at the EventLog level if the mux is async-bound.
-        """
-        return iter(self._mux._events)
-
-    def __aiter__(self) -> AsyncIterator[ProtocolEvent]:
-        """Async iteration of protocol events on this mux's main log.
-
-        Raises at the EventLog level if the mux is sync-bound.
-        """
-        return self._mux._events.__aiter__()
-
-    def interleave(self, *names: str) -> Iterator[tuple[str, Any]]:
-        """Iterate multiple projections round-robin, yielding ``(name, item)``.
-
-        Each turn advances one projection's cursor; when a cursor's
-        buffer is empty, pulling from it drives the pump once, which
-        fans out to every subscribed projection log. Projections whose
-        items aren't consumed on this turn sit in their own buffers
-        only until the next turn reaches them, bounding memory by the
-        skew between projection rates rather than letting any single
-        log grow to the full run length.
-
-        Projections are exhausted independently; a projection that
-        finishes early drops out of the rotation while others
-        continue. The overall iterator ends once all named projections
-        are done.
-
-        Args:
-            *names: Projection keys to interleave. Must match keys in
-                `extensions`.
-
-        Yields:
-            `(name, item)` tuples in round-robin order across the named
-            projections.
-
-        Raises:
-            KeyError: If a name doesn't match a registered projection.
-
-        Example:
-            ```python
-            for name, item in run.interleave("messages", "values"):
-                if name == "messages":
-                    print("msg:", item)
-                else:
-                    print("val:", item)
-            ```
-        """
-        cursors: dict[str, Iterator[Any]] = {
-            name: iter(self.extensions[name]) for name in names
-        }
-        done: set[str] = set()
-        while len(done) < len(cursors):
-            for name, cursor in cursors.items():
-                if name in done:
-                    continue
-                try:
-                    item = next(cursor)
-                except StopIteration:
-                    done.add(name)
-                    continue
-                yield (name, item)
-
-
-class GraphRunStream(BaseRunStream):
-    """Sync run stream with caller-driven pumping.
-
-    The caller's iteration on any projection (`values`, `messages`,
-    raw events, or `output`) drives the graph forward. No background
-    thread is used — the caller's `for` loop is the pump.
-
-    Projections are single-consumer — iterating `run.values` twice
-    raises. Use `projection.tee(n)` if you genuinely need fan-out.
-    """
-
-    def __init__(
-        self,
-        graph_iter: Iterator[Any],
-        mux: StreamMux,
-    ) -> None:
-        """Initialize the run stream.
-
-        Args:
-            graph_iter: Pull-based iterator over the graph's stream.
-            mux: The StreamMux owning projections and the main log.
-                Must have a `ValuesTransformer` registered under the
-                `"values"` key — `output` / `interrupted` / `interrupts`
-                read from it lazily.
-        """
-        super().__init__(mux)
-        self._graph_iter = graph_iter
-        self._exhausted = False
-        mux.bind_pump(self._pump_next)
-
-    def _pump_next(self) -> bool:
-        """Pull one event from the graph and push it through the mux.
-
-        Returns:
-            True if an event was pulled, False if the graph is
-            exhausted or has raised.
-        """
-        if self._exhausted:
-            return False
-        try:
-            part = next(self._graph_iter)
-        except StopIteration:
-            self._mux.close()
-            self._exhausted = True
-            return False
-        except Exception as e:
-            self._mux.fail(e)
-            self._exhausted = True
-            return False
-        self._mux.push(convert_to_protocol_event(part))
-        return True
-
-    def abort(self) -> None:
-        """Stop the run early.
-
-        Closes the mux and marks the stream exhausted. The graph
-        iterator is dropped; any in-flight nodes see the closure on
-        their next yield point. Idempotent.
-        """
-        if self._exhausted:
-            return
-        self._exhausted = True
-        try:
-            self._mux.close()
-        except Exception:
-            pass
-
-    def __enter__(self) -> GraphRunStream:
-        return self
-
-    def __exit__(
-        self,
-        exc_type: type[BaseException] | None,
-        exc: BaseException | None,
-        tb: TracebackType | None,
-    ) -> None:
-        self.abort()
-
-    @property
-    def output(self) -> dict[str, Any] | None:
-        """Drive the run to completion and return the final state."""
-        _drive_until_done(self._pump_next)
-        vt = self._values_transformer
-        if vt.error is not None:
-            raise vt.error
-        return vt._latest
-
-    @property
-    def interrupted(self) -> bool:
-        """Drive the run to completion, then return whether it was interrupted.
-
-        Raises:
-            BaseException: If the run ended with an error.
-        """
-        _drive_until_done(self._pump_next)
-        vt = self._values_transformer
-        if vt.error is not None:
-            raise vt.error
-        return vt._interrupted
-
-    @property
-    def interrupts(self) -> list[Any]:
-        """Drive the run to completion, then return interrupt payloads.
-
-        Raises:
-            BaseException: If the run ended with an error.
-        """
-        _drive_until_done(self._pump_next)
-        vt = self._values_transformer
-        if vt.error is not None:
-            raise vt.error
-        return vt._interrupts
-
-
-class AsyncGraphRunStream(BaseRunStream):
-    """Async run stream with caller-driven pumping.
-
-    Async iteration on any projection drives the graph forward — there
-    is no background task. Concurrent consumers share a single-flight
-    pump via an `asyncio.Lock`, so each awaiting cursor contributes
-    one event per acquisition. Backpressure comes from the logs: when
-    a subscribed log's buffer reaches `maxlen`, `apush` awaits the
-    subscriber to drain, which holds back the pump and paces the
-    graph.
-
-    Projections are single-consumer — a second `aiter(run.values)`
-    raises. Use `projection.tee(n)` for fan-out.
-
-    Use as an async context manager to guarantee clean shutdown on
-    early exit:
-
-    ```python
-    async with await handler.astream(input) as run:
-        async for msg in run.messages:
-            ...
-    ```
-    """
-
-    def __init__(
-        self,
-        graph_aiter: AsyncIterator[Any],
-        mux: StreamMux,
-    ) -> None:
-        """Initialize the async run stream.
-
-        Args:
-            graph_aiter: Async iterator over the graph's stream.
-            mux: The StreamMux owning projections and the main log.
-                Must have a `ValuesTransformer` registered under the
-                `"values"` key — `output` / `interrupted` / `interrupts`
-                read from it lazily.
-        """
-        super().__init__(mux)
-        self._graph_aiter = graph_aiter
-        self._exhausted = False
-        self._pump_cond = asyncio.Condition()
-        self._pumping = False
-        mux.bind_apump(self._apump_next)
-
-    async def _apump_next(self) -> bool:
-        """Drive one pump step, or wait for the active pumper to drive one.
-
-        "Take-a-number" semantics: at most one task at a time calls
-        `graph_aiter.__anext__()` (asyncio iterators can't be advanced
-        concurrently). Other callers wait on a Condition that the
-        active pumper notifies after each step. This lets a "passive"
-        consumer — one whose projection's buffer is being filled by the
-        active pumper's push — wake up as soon as its data lands,
-        instead of queueing on the pump and only observing its data one
-        graph event late.
-
-        `except Exception` is intentional — `CancelledError` and other
-        `BaseException` subclasses propagate, matching asyncio's
-        cancellation contract.
-
-        Returns:
-            True if a pump step completed (by this task or another),
-            False if the graph is exhausted.
-        """
-        async with self._pump_cond:
-            if self._exhausted:
-                return False
-            if self._pumping:
-                # Another task is pumping; wait for its progress signal.
-                await self._pump_cond.wait()
-                return not self._exhausted
-            self._pumping = True
-
-        try:
-            try:
-                part = await self._graph_aiter.__anext__()
-            except StopAsyncIteration:
-                self._exhausted = True
-                await self._mux.aclose()
-                return False
-            except Exception as e:
-                self._exhausted = True
-                await self._mux.afail(e)
-                return False
-            await self._mux.apush(convert_to_protocol_event(part))
-            return True
-        finally:
-            async with self._pump_cond:
-                self._pumping = False
-                self._pump_cond.notify_all()
-
-    async def abort(self) -> None:
-        """Stop the run early.
-
-        Marks the stream exhausted, wakes any pump-waiters, and closes
-        the mux. Any `apush` blocked on backpressure wakes and returns
-        without appending. Idempotent.
-        """
-        async with self._pump_cond:
-            if self._exhausted:
-                return
-            self._exhausted = True
-            self._pump_cond.notify_all()
-        try:
-            await self._mux.aclose()
-        except Exception:
-            pass
-
-    async def __aenter__(self) -> AsyncGraphRunStream:
-        return self
-
-    async def __aexit__(
-        self,
-        exc_type: type[BaseException] | None,
-        exc: BaseException | None,
-        tb: TracebackType | None,
-    ) -> None:
-        await self.abort()
-
-    async def output(self) -> dict[str, Any] | None:
-        """Drive the run to completion and return the final state.
-
-        Methods (not properties) on the async lane so `run.output`
-        without `await` raises at type-check time instead of silently
-        yielding a coroutine object.
-
-        Example:
-            ```python
-            output = await run.output()
-            ```
-
-        Raises:
-            BaseException: If the run ended with an error.
-        """
-        await _adrive_until_done(self._apump_next)
-        if (err := self._values_transformer.error) is not None:
-            raise err
-        return self._values_transformer._latest
-
-    async def interrupted(self) -> bool:
-        """Drive the run to completion and return whether it was interrupted.
-
-        Raises:
-            BaseException: If the run ended with an error.
-        """
-        await _adrive_until_done(self._apump_next)
-        if (err := self._values_transformer.error) is not None:
-            raise err
-        return self._values_transformer._interrupted
-
-    async def interrupts(self) -> list[Any]:
-        """Drive the run to completion and return interrupt payloads.
-
-        Raises:
-            BaseException: If the run ended with an error.
-        """
-        await _adrive_until_done(self._apump_next)
-        if (err := self._values_transformer.error) is not None:
-            raise err
-        return self._values_transformer._interrupts
@@ -1,109 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import AsyncIterator, Callable, Iterator
-from typing import Generic, TypeVar
-
-from langgraph.stream._event_log import EventLog
-
-T = TypeVar("T")
-
-
-class StreamChannel(Generic[T]):
-    """A named projection channel with optional protocol auto-forwarding.
-
-    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.
-    """
-
-    def __init__(self, name: str, *, maxlen: int | None = None) -> None:
-        """Initialize the channel with an empty inner log.
-
-        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 push(self, item: T) -> None:
-        """Append an item to the log and auto-forward if wired.
-
-        Args:
-            item: The item to push.
-        """
-        self._log.push(item)
-        if self._wire_fn is not None:
-            self._wire_fn(item)
-
-    # ------------------------------------------------------------------
-    # Mux lifecycle hooks (not called by transformers directly)
-    # ------------------------------------------------------------------
-
-    def _wire(self, fn: Callable[[T], None]) -> None:
-        """Install the auto-forward callback (called by StreamMux)."""
-        self._wire_fn = fn
-
-    def _close(self) -> None:
-        """Close the underlying log (called by StreamMux on run end)."""
-        self._log.close()
-
-    def _fail(self, err: BaseException) -> None:
-        """Fail the underlying log (called by StreamMux on run error)."""
-        self._log.fail(err)
-
-    # ------------------------------------------------------------------
-    # Iteration — delegates to the inner event log (multi-cursor)
-    # ------------------------------------------------------------------
-
-    def __iter__(self) -> Iterator[T]:
-        return iter(self._log)
-
-    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)
@@ -1,477 +0,0 @@
-from __future__ import annotations
-
-import logging
-from typing import TYPE_CHECKING, Any, Literal, cast
-
-from langchain_core.language_models._compat_bridge import message_to_events
-from langchain_core.language_models.chat_model_stream import (
-    AsyncChatModelStream,
-    ChatModelStream,
-)
-from langchain_core.messages import AIMessageChunk, BaseMessage
-from langchain_protocol.protocol import CheckpointRef, 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
-
-if TYPE_CHECKING:
-    from collections.abc import Awaitable, Callable
-
-    from langgraph.stream._mux import StreamMux
-
-
-logger = logging.getLogger(__name__)
-
-
-SubgraphStatus = Literal["started", "running", "completed", "failed", "interrupted"]
-_TERMINAL_STATUSES: frozenset[SubgraphStatus] = frozenset(
-    {"completed", "failed", "interrupted"}
-)
-
-
-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.
-    """
-
-    _native = True
-    required_stream_modes = ("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}
-
-    @property
-    def error(self) -> BaseException | None:
-        """The error that ended the run, or `None` if it succeeded.
-
-        Set by the mux when it auto-fails the projection log.
-        """
-        return self._log._error
-
-    def process(self, event: ProtocolEvent) -> bool:
-        # 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"])
-        return True
-
-
-class MessagesTransformer(StreamTransformer):
-    """Capture messages events as ChatModelStream objects.
-
-    The messages projection yields one `ChatModelStream` (or
-    `AsyncChatModelStream`) per LLM call. Consumers iterate
-    `run.messages` to get stream handles, then use each handle's typed
-    projections (`.text`, `.reasoning`, `.tool_calls`, `.usage`,
-    `.output`) for per-message content.
-
-    Two input shapes are handled (via `params["data"] = (payload,
-    metadata)` from `StreamMessagesHandler`):
-
-    1. Protocol event (dict with `"event"` key) — emitted by
-       `stream_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.
-    """
-
-    _native = True
-    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._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 _bind_pump(self, fn: Callable[[], bool]) -> None:
-        """Wire the sync pull callback. Called by GraphRunStream._wire_request_more."""
-        self._pump_fn = fn
-
-    def _bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
-        """Wire the async pull callback.
-
-        Called by `AsyncGraphRunStream._wire_arequest_more` so each
-        `AsyncChatModelStream` this transformer creates can drive the
-        shared graph pump from its projection cursors.
-        """
-        self._apump_fn = fn
-
-    def _make_stream(
-        self,
-        *,
-        namespace: list[str],
-        node: str | None,
-        message_id: str | None,
-    ) -> ChatModelStream:
-        """Create a ChatModelStream (sync) or AsyncChatModelStream (async).
-
-        Wires whichever pump is bound. Prefers the async pump so nested
-        iteration under `AsyncGraphRunStream` drives the graph forward
-        without a background task. The unwired fallback (no pump bound)
-        is used by unit tests that dispatch events manually.
-        """
-        if self._apump_fn is not None:
-            astream = AsyncChatModelStream(
-                namespace=namespace,
-                node=node,
-                message_id=message_id,
-            )
-            astream.set_arequest_more(self._apump_fn)
-            return astream
-        if self._pump_fn is not None:
-            stream: ChatModelStream = ChatModelStream(
-                namespace=namespace,
-                node=node,
-                message_id=message_id,
-            )
-            stream.set_request_more(self._pump_fn)
-            return stream
-        return AsyncChatModelStream(
-            namespace=namespace,
-            node=node,
-            message_id=message_id,
-        )
-
-    def process(self, event: ProtocolEvent) -> bool:
-        # Namespace filtering is handled by the mux via `scope_exact`.
-        if event["method"] != "messages":
-            return True
-        params = event["params"]
-
-        payload, metadata = params["data"]
-        node: str | None = metadata.get("langgraph_node")
-        run_id = str(metadata.get("run_id", "")) if metadata else ""
-
-        if isinstance(payload, dict) and "event" in payload:
-            self._route_protocol_event(
-                cast("MessagesData", payload), run_id=run_id, node=node
-            )
-        elif isinstance(payload, BaseMessage) and not isinstance(
-            payload, AIMessageChunk
-        ):
-            self._route_whole_message(payload, node=node)
-        # Legacy AIMessageChunk tuples (from on_llm_new_token) are ignored;
-        # v1 streaming callers must switch to stream_v2() to populate this
-        # projection.
-
-        return True
-
-    def _route_protocol_event(
-        self,
-        event: MessagesData,
-        *,
-        run_id: str,
-        node: str | None,
-    ) -> None:
-        event_type = event.get("event")
-        if event_type == "message-start":
-            message_id = event.get("message_id")
-            stream = self._make_stream(
-                namespace=list(self.scope),
-                node=node,
-                message_id=str(message_id) if message_id is not None else None,
-            )
-            self._by_run[run_id] = stream
-            self._log.push(stream)
-            stream.dispatch(event)
-        elif run_id in self._by_run:
-            stream = self._by_run[run_id]
-            stream.dispatch(event)
-            if event_type == "message-finish":
-                del self._by_run[run_id]
-
-    def _route_whole_message(self, message: BaseMessage, *, node: str | None) -> None:
-        stream = self._make_stream(
-            namespace=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()
-
-    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()
-
-
-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` / `trigger_call_id`: set once from the `started`
-      payload.
-    - `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,
-        trigger_call_id: str | None = None,
-    ) -> None:
-        super().__init__(mux)
-        self.path: tuple[str, ...] = path
-        self.graph_name: str | None = graph_name
-        self.trigger_call_id: str | None = trigger_call_id
-        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)
-
-        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"),
-            trigger_call_id=data.get("trigger_call_id"),
-        )
-        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)
-
-    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,
-                    )
@@ -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==1.3.0a2",
+    "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
@@ -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",
@@ -54,6 +54,13 @@ from langgraph.pregel import (
    NodeBuilder,
    Pregel,
 )
+from langgraph.pregel._checkpoint_writer import (
+    CHECKPOINT_BACKLOG_ENV_VAR,
+    DEFAULT_CHECKPOINT_BACKLOG,
+    AsyncCheckpointWriter,
+    SyncCheckpointWriter,
+    resolve_checkpoint_backlog,
+)
 from langgraph.pregel._loop import SyncPregelLoop
 from langgraph.pregel._runner import PregelRunner
 from langgraph.types import (
@@ -3726,6 +3733,7 @@ def test_repeat_condition(snapshot: SnapshotAssertion) -> None:
            "end": END,
        },
    )
+
    workflow.add_conditional_edges(
        "Chart Generator",
        router,
@@ -3749,6 +3757,93 @@ def test_repeat_condition(snapshot: SnapshotAssertion) -> None:
    assert app.get_graph().draw_mermaid(with_styles=False) == snapshot


+def test_sync_durability_applies_checkpoint_backpressure() -> None:
+    first_put_started = threading.Event()
+    release_first_put = threading.Event()
+    put_calls = 0
+    visited: list[int] = []
+    result: dict[str, Any] = {}
+    error: dict[str, BaseException] = {}
+
+    class SlowFirstPutCheckpointer(InMemorySaver):
+        def put(
+            self,
+            config: RunnableConfig,
+            checkpoint: Checkpoint,
+            metadata: CheckpointMetadata,
+            new_versions: Any,
+        ) -> RunnableConfig:
+            nonlocal put_calls
+            put_calls += 1
+            if put_calls == 1:
+                first_put_started.set()
+                release_first_put.wait()
+            return super().put(config, checkpoint, metadata, new_versions)
+
+    class State(TypedDict):
+        counter: int
+
+    def increment(state: State) -> State:
+        visited.append(state["counter"])
+        return {"counter": state["counter"] + 1}
+
+    def should_continue(state: State) -> str:
+        return "loop" if state["counter"] < 4 else "done"
+
+    builder = StateGraph(State)
+    builder.add_node("increment", increment)
+    builder.add_edge(START, "increment")
+    builder.add_conditional_edges(
+        "increment", should_continue, {"loop": "increment", "done": END}
+    )
+
+    graph = builder.compile(checkpointer=SlowFirstPutCheckpointer())
+
+    def invoke() -> None:
+        try:
+            result["value"] = graph.invoke(
+                {"counter": 0},
+                {"configurable": {"thread_id": "1"}},
+                durability="async",
+            )
+        except BaseException as exc:
+            error["value"] = exc
+
+    thread = threading.Thread(target=invoke)
+    thread.start()
+
+    assert first_put_started.wait(timeout=1)
+    time.sleep(0.05)
+
+    assert thread.is_alive()
+    assert len(visited) <= DEFAULT_CHECKPOINT_BACKLOG + 1
+
+    release_first_put.set()
+    thread.join(timeout=1)
+
+    assert not thread.is_alive()
+    assert "value" not in error
+    assert result["value"] == {"counter": 4}
+
+
+def test_checkpoint_backlog_uses_env_override(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv(CHECKPOINT_BACKLOG_ENV_VAR, "7")
+
+    assert resolve_checkpoint_backlog() == 7
+    assert SyncCheckpointWriter(lambda *_args: None).queue.maxsize == 7
+    assert AsyncCheckpointWriter(lambda *_args: None).queue.maxsize == 7
+
+
+def test_checkpoint_backlog_invalid_env_uses_default(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    monkeypatch.setenv(CHECKPOINT_BACKLOG_ENV_VAR, "not-an-int")
+    assert resolve_checkpoint_backlog() == DEFAULT_CHECKPOINT_BACKLOG
+
+    monkeypatch.setenv(CHECKPOINT_BACKLOG_ENV_VAR, "0")
+    assert resolve_checkpoint_backlog() == DEFAULT_CHECKPOINT_BACKLOG
+
+
 def test_checkpoint_metadata(sync_checkpointer: BaseCheckpointSaver) -> None:
    """This test verifies that a run's configurable fields are merged with the
    previous checkpoint config for each step in the run.
@@ -6271,7 +6366,7 @@ 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 +6379,7 @@ 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 +6988,7 @@ 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 +6998,6 @@ 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
@@ -54,6 +53,7 @@ from langgraph.func import entrypoint, task
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import MessagesState, add_messages
 from langgraph.pregel import NodeBuilder, Pregel
+from langgraph.pregel._checkpoint_writer import DEFAULT_CHECKPOINT_BACKLOG
 from langgraph.pregel._loop import AsyncPregelLoop
 from langgraph.pregel._runner import PregelRunner
 from langgraph.types import (
@@ -485,6 +485,61 @@ async def test_checkpoint_put_after_cancellation_stream_events_anext() -> None:
        assert False, "Task should be cancelled"


+async def test_async_durability_applies_checkpoint_backpressure() -> None:
+    first_put_started = asyncio.Event()
+    release_first_put = asyncio.Event()
+    put_calls = 0
+    visited: list[int] = []
+
+    class SlowFirstPutCheckpointer(InMemorySaver):
+        async def aput(
+            self,
+            config: RunnableConfig,
+            checkpoint: Checkpoint,
+            metadata: CheckpointMetadata,
+            new_versions: ChannelVersions,
+        ) -> RunnableConfig:
+            nonlocal put_calls
+            put_calls += 1
+            if put_calls == 1:
+                first_put_started.set()
+                await release_first_put.wait()
+            return await super().aput(config, checkpoint, metadata, new_versions)
+
+    class State(TypedDict):
+        counter: int
+
+    def increment(state: State) -> State:
+        visited.append(state["counter"])
+        return {"counter": state["counter"] + 1}
+
+    def should_continue(state: State) -> str:
+        return "loop" if state["counter"] < 4 else "done"
+
+    builder = StateGraph(State)
+    builder.add_node("increment", increment)
+    builder.add_edge(START, "increment")
+    builder.add_conditional_edges(
+        "increment", should_continue, {"loop": "increment", "done": END}
+    )
+
+    graph = builder.compile(checkpointer=SlowFirstPutCheckpointer())
+    task = asyncio.create_task(
+        graph.ainvoke(
+            {"counter": 0}, {"configurable": {"thread_id": "1"}}, durability="async"
+        )
+    )
+
+    await first_put_started.wait()
+    await asyncio.sleep(0.05)
+
+    assert not task.done()
+    assert len(visited) <= DEFAULT_CHECKPOINT_BACKLOG + 1
+
+    release_first_put.set()
+    assert await task == {"counter": 4}
+
+
 async def test_node_cancellation_on_external_cancel() -> None:
    inner_task_cancelled = False

@@ -7542,6 +7597,7 @@ 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 +7607,6 @@ 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"]
@@ -1,907 +0,0 @@
-"""Tests for the MessagesTransformer content-block upgrade (B2).
-
-Verifies that `MessagesTransformer` routes protocol events (emitted by
-`stream_v2` via `on_stream_event`) to `ChatModelStream` objects keyed by
-run_id, and replays whole `AIMessage` payloads via `message_to_events`.
-Legacy v1 `AIMessageChunk` tuples (from `on_llm_new_token`) are ignored.
-"""
-
-from __future__ import annotations
-
-import time
-from typing import Any
-
-import pytest
-from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.language_models.chat_model_stream import (
-    AsyncChatModelStream,
-    ChatModelStream,
-)
-from langchain_core.messages import AIMessage, AIMessageChunk
-
-from langgraph.constants import END, START
-from langgraph.graph import MessagesState, StateGraph
-from langgraph.stream._event_log import EventLog
-from langgraph.stream._mux import StreamMux
-from langgraph.stream.run_stream import GraphRunStream
-from langgraph.stream.transformers import MessagesTransformer, ValuesTransformer
-
-TS = int(time.time() * 1000)
-
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-
-def _proto_event(
-    event: dict[str, Any],
-    *,
-    run_id: str = "run-1",
-    node: str = "llm",
-) -> dict[str, Any]:
-    """Build a messages ProtocolEvent carrying a protocol event dict (v2 path)."""
-    metadata: dict[str, Any] = {"langgraph_node": node, "run_id": run_id}
-    return {
-        "type": "event",
-        "method": "messages",
-        "params": {
-            "namespace": [],
-            "timestamp": TS,
-            "data": (event, metadata),
-        },
-    }
-
-
-def _v1_chunk(
-    text: str,
-    msg_id: str = "msg-1",
-    *,
-    finish: bool = False,
-    node: str = "llm",
-) -> dict[str, Any]:
-    """Build a messages ProtocolEvent carrying a v1 AIMessageChunk tuple."""
-    rm: dict[str, Any] = {}
-    if finish:
-        rm["finish_reason"] = "stop"
-    message = AIMessageChunk(content=text, id=msg_id, response_metadata=rm)
-    metadata: dict[str, Any] = {"langgraph_node": node}
-    return {
-        "type": "event",
-        "method": "messages",
-        "params": {
-            "namespace": [],
-            "timestamp": TS,
-            "data": (message, metadata),
-        },
-    }
-
-
-def _whole_msg(
-    text: str,
-    msg_id: str = "msg-10",
-    *,
-    node: str = "node",
-) -> dict[str, Any]:
-    """Build a messages ProtocolEvent carrying a completed AIMessage."""
-    message = AIMessage(content=text, id=msg_id)
-    metadata: dict[str, Any] = {"langgraph_node": node}
-    return {
-        "type": "event",
-        "method": "messages",
-        "params": {
-            "namespace": [],
-            "timestamp": TS,
-            "data": (message, metadata),
-        },
-    }
-
-
-def _make_sync_transformer() -> tuple[MessagesTransformer, EventLog[ChatModelStream]]:
-    t = MessagesTransformer()
-    proj = t.init()
-    log: EventLog[ChatModelStream] = proj["messages"]
-    log._bind(is_async=False)
-    # Production subscribes via `iter(log)` from the graph consumer — do that
-    # up front so `push` during `process` isn't a no-op. Tests read buffered
-    # items via `log._items` directly rather than re-iterating.
-    log._subscribed = True
-    t._bind_pump(lambda: False)
-    return t, log
-
-
-def _make_async_transformer() -> tuple[MessagesTransformer, EventLog[ChatModelStream]]:
-    t = MessagesTransformer()
-    proj = t.init()
-    log: EventLog[ChatModelStream] = proj["messages"]
-    log._bind(is_async=True)
-    log._subscribed = True
-    return t, log
-
-
-# Standard lifecycle events for one streaming LLM call.
-def _lifecycle(
-    *,
-    text: str = "hello world",
-    message_id: str = "run-1",
-) -> list[dict[str, Any]]:
-    """Produce a valid protocol event lifecycle: start, delta, finish, end."""
-    # Split text into two deltas to exercise delta accumulation.
-    half = len(text) // 2
-    first, second = text[:half], text[half:]
-    return [
-        {"event": "message-start", "role": "ai", "message_id": message_id},
-        {
-            "event": "content-block-start",
-            "index": 0,
-            "content_block": {"type": "text", "text": ""},
-        },
-        {
-            "event": "content-block-delta",
-            "index": 0,
-            "content_block": {"type": "text", "text": first},
-        },
-        {
-            "event": "content-block-delta",
-            "index": 0,
-            "content_block": {"type": "text", "text": second},
-        },
-        {
-            "event": "content-block-finish",
-            "index": 0,
-            "content_block": {"type": "text", "text": text},
-        },
-        {"event": "message-finish", "reason": "stop"},
-    ]
-
-
-# ---------------------------------------------------------------------------
-# Primary path: protocol event routing
-# ---------------------------------------------------------------------------
-
-
-class TestProtocolEventRouting:
-    def test_message_start_creates_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "role": "ai", "message_id": "run-1"},
-                run_id="run-1",
-            )
-        )
-        # Stream is in the log immediately.
-        log.close()
-        streams = list(log._items)
-        assert len(streams) == 1
-        assert isinstance(streams[0], ChatModelStream)
-        assert streams[0].message_id == "run-1"
-
-    def test_full_lifecycle_yields_done_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        for evt in _lifecycle(text="hello world"):
-            t.process(_proto_event(evt, run_id="run-1"))
-        log.close()
-        (stream,) = list(log._items)
-        assert stream.done
-        assert stream.output.content == "hello world"
-
-    def test_message_finish_cleans_up_routing(self) -> None:
-        t, log = _make_sync_transformer()
-        for evt in _lifecycle():
-            t.process(_proto_event(evt, run_id="run-1"))
-        assert t._by_run == {}
-
-    def test_events_without_prior_start_are_ignored(self) -> None:
-        """Orphan delta events (no preceding message-start) are dropped silently."""
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {
-                    "event": "content-block-delta",
-                    "index": 0,
-                    "content_block": {"type": "text", "text": "orphan"},
-                },
-                run_id="unknown",
-            )
-        )
-        log.close()
-        assert list(log._items) == []
-
-    def test_concurrent_streams_routed_by_run_id(self) -> None:
-        """Two interleaved LLM calls each produce their own stream."""
-        t, log = _make_sync_transformer()
-        # Interleave events from two different run_ids.
-        life_a = _lifecycle(text="aaaa", message_id="run-a")
-        life_b = _lifecycle(text="bbbb", message_id="run-b")
-        for a, b in zip(life_a, life_b):
-            t.process(_proto_event(a, run_id="run-a"))
-            t.process(_proto_event(b, run_id="run-b"))
-        log.close()
-        streams = list(log._items)
-        assert len(streams) == 2
-        by_id = {s.message_id: s for s in streams}
-        assert by_id["run-a"].output.content == "aaaa"
-        assert by_id["run-b"].output.content == "bbbb"
-
-    def test_text_deltas_accumulated_on_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        for evt in _lifecycle(text="abcdef"):
-            t.process(_proto_event(evt))
-        log.close()
-        (stream,) = list(log._items)
-        deltas = list(stream._text_proj._deltas)
-        assert "".join(deltas) == "abcdef"
-
-    def test_stream_pushed_on_message_start_not_finish(self) -> None:
-        """Consumer can see the stream before it finishes."""
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "role": "ai", "message_id": "run-1"},
-                run_id="run-1",
-            )
-        )
-        # The log has the stream immediately — even though message-finish
-        # hasn't arrived yet.
-        assert len(log._items) == 1
-
-    def test_node_metadata_set_on_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "role": "ai", "message_id": "run-1"},
-                run_id="run-1",
-                node="my_llm",
-            )
-        )
-        (stream,) = [*log._items]
-        assert stream.node == "my_llm"
-
-
-# ---------------------------------------------------------------------------
-# Non-streaming (whole AIMessage) fallback
-# ---------------------------------------------------------------------------
-
-
-class TestWholeMessageFallback:
-    def test_whole_ai_message_produces_complete_stream(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(_whole_msg("the full answer"))
-        log.close()
-        (stream,) = list(log._items)
-        assert stream.done
-        assert stream.output.content == "the full answer"
-
-    def test_whole_message_has_full_lifecycle(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(_whole_msg("full"))
-        log.close()
-        (stream,) = list(log._items)
-        event_types = [e["event"] for e in stream._events]
-        assert event_types == [
-            "message-start",
-            "content-block-start",
-            "content-block-delta",
-            "content-block-finish",
-            "message-finish",
-        ]
-
-
-# ---------------------------------------------------------------------------
-# Legacy v1 chunks are ignored (users must migrate to stream_v2)
-# ---------------------------------------------------------------------------
-
-
-class TestLegacyChunksIgnored:
-    def test_aimessage_chunk_tuple_is_dropped(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(_v1_chunk("hello"))
-        t.process(_v1_chunk(" world", finish=True))
-        log.close()
-        assert list(log._items) == []
-
-
-# ---------------------------------------------------------------------------
-# Filtering behaviors
-# ---------------------------------------------------------------------------
-
-
-class TestFiltering:
-    def test_non_messages_events_pass_through(self) -> None:
-        t, _ = _make_sync_transformer()
-        values_event = {
-            "type": "event",
-            "method": "values",
-            "params": {"namespace": [], "timestamp": TS, "data": {"x": 1}},
-        }
-        assert t.process(values_event) is True
-
-    def test_subgraph_namespace_dropped(self) -> None:
-        """Root MessagesTransformer (via the mux) ignores non-root events."""
-        from langgraph.stream._mux import StreamMux
-
-        mux = StreamMux([MessagesTransformer()], is_async=False)
-        t = mux.transformer_by_key("messages")
-        assert isinstance(t, MessagesTransformer)
-        t._log._subscribed = True
-        t._bind_pump(lambda: False)
-
-        mux.push(
-            {
-                "type": "event",
-                "method": "messages",
-                "params": {
-                    "namespace": ["subgraph"],
-                    "timestamp": TS,
-                    "data": (
-                        {"event": "message-start", "message_id": "run-x"},
-                        {"run_id": "run-x"},
-                    ),
-                },
-            }
-        )
-        t._log.close()
-        assert list(t._log._items) == []
-
-
-# ---------------------------------------------------------------------------
-# Lifecycle: finalize / fail
-# ---------------------------------------------------------------------------
-
-
-class TestLifecycle:
-    def test_fail_propagates_to_open_streams(self) -> None:
-        t, log = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "message_id": "run-1"},
-                run_id="run-1",
-            )
-        )
-        streams = list(log._items)
-        err = RuntimeError("graph died")
-        t.fail(err)
-        assert t._by_run == {}
-        assert streams[0]._error is err
-
-    def test_finalize_clears_routing_state(self) -> None:
-        t, _ = _make_sync_transformer()
-        t.process(
-            _proto_event(
-                {"event": "message-start", "message_id": "run-1"},
-                run_id="run-1",
-            )
-        )
-        assert "run-1" in t._by_run
-        t.finalize()
-        assert t._by_run == {}
-
-
-# ---------------------------------------------------------------------------
-# Async mode (AsyncChatModelStream)
-# ---------------------------------------------------------------------------
-
-
-class TestAsyncMode:
-    def test_async_mode_creates_async_stream(self) -> None:
-        t, log = _make_async_transformer()
-        for evt in _lifecycle(text="async stream"):
-            t.process(_proto_event(evt))
-        streams = list(log._items)
-        assert len(streams) == 1
-        assert isinstance(streams[0], AsyncChatModelStream)
-
-    @pytest.mark.anyio
-    async def test_async_text_projection_yields_deltas(self) -> None:
-        t, log = _make_async_transformer()
-        for evt in _lifecycle(text="hello world"):
-            t.process(_proto_event(evt))
-        (stream,) = list(log._items)
-        assert isinstance(stream, AsyncChatModelStream)
-        collected = []
-        async for delta in stream.text:
-            collected.append(delta)
-        assert "".join(collected) == "hello world"
-
-    @pytest.mark.anyio
-    async def test_async_output_awaitable(self) -> None:
-        t, log = _make_async_transformer()
-        for evt in _lifecycle(text="async"):
-            t.process(_proto_event(evt))
-        (stream,) = list(log._items)
-        msg = await stream.output
-        assert msg.content == "async"
-
-
-# ---------------------------------------------------------------------------
-# GraphRunStream integration
-# ---------------------------------------------------------------------------
-
-
-class TestWireRequestMore:
-    def test_bind_pump_called_on_wire(self) -> None:
-        values_t = ValuesTransformer()
-        messages_t = MessagesTransformer()
-        mux = StreamMux([values_t, messages_t], is_async=False)
-
-        assert messages_t._pump_fn is None
-        run = GraphRunStream(iter([]), mux)
-        # After wire, the transformer's pump callback is set.
-        assert messages_t._pump_fn is not None
-        # And calling it invokes GraphRunStream._pump_next (drains an empty
-        # graph_iter, returns False).
-        assert messages_t._pump_fn() is False
-        assert run._exhausted
-
-    def test_created_streams_have_request_more(self) -> None:
-        values_t = ValuesTransformer()
-        messages_t = MessagesTransformer()
-        mux = StreamMux([values_t, messages_t], is_async=False)
-
-        GraphRunStream(iter([]), mux)
-        log: EventLog[ChatModelStream] = mux.extensions["messages"]
-        log._subscribed = True
-
-        for evt in _lifecycle():
-            messages_t.process(_proto_event(evt))
-
-        (stream,) = list(log._items)
-        # Pump was threaded through: the stream's _request_more points at
-        # the same callable the transformer was bound with.
-        assert stream._request_more is messages_t._pump_fn
-
-
-# ---------------------------------------------------------------------------
-# End-to-end via StreamMux
-# ---------------------------------------------------------------------------
-
-
-class TestViaMux:
-    def test_streaming_via_mux(self) -> None:
-        t = MessagesTransformer()
-        v = ValuesTransformer()
-        mux = StreamMux([v, t], is_async=False)
-        t._bind_pump(lambda: False)
-        log: EventLog[ChatModelStream] = mux.extensions["messages"]
-        # Simulate a consumer subscribing (as `run.messages` iteration would).
-        log._subscribed = True
-
-        for evt in _lifecycle(text="mux stream"):
-            mux.push(_proto_event(evt))
-        mux.close()
-
-        (stream,) = list(log._items)
-        assert stream.output.content == "mux stream"
-
-    def test_whole_message_via_mux(self) -> None:
-        t = MessagesTransformer()
-        v = ValuesTransformer()
-        mux = StreamMux([v, t], is_async=False)
-        t._bind_pump(lambda: False)
-        log: EventLog[ChatModelStream] = mux.extensions["messages"]
-        log._subscribed = True
-
-        mux.push(_whole_msg("result"))
-        mux.close()
-
-        (stream,) = list(log._items)
-        assert stream.output.content == "result"
-
-    @pytest.mark.anyio
-    async def test_async_streaming_via_mux(self) -> None:
-        t = MessagesTransformer()
-        v = ValuesTransformer()
-        mux = StreamMux([v, t], is_async=True)
-        log: EventLog[ChatModelStream] = mux.extensions["messages"]
-        log._subscribed = True
-
-        for evt in _lifecycle(text="async mux"):
-            await mux.apush(_proto_event(evt))
-
-        streams = list(log._items)
-        assert len(streams) == 1
-        msg = await streams[0].output
-        assert msg.content == "async mux"
-        await mux.aclose()
-
-
-# ---------------------------------------------------------------------------
-# End-to-end: full graph → stream_v2 → run.messages
-# ---------------------------------------------------------------------------
-
-
-class TestEndToEnd:
-    """Prove the full pipeline works when a node calls `model.stream_v2()`.
-
-    These tests exercise the path that the new messages projection is
-    designed for: a user node invokes `stream_v2` on a chat model,
-    `on_stream_event` fires on `StreamMessagesHandler`, the handler
-    forwards to the mux, and the transformer routes events into a
-    `ChatModelStream` exposed on `run.messages`.
-
-    Nothing in Pregel calls `stream_v2` automatically yet; the planned
-    `graph.stream_v2()` API (B4) and the `create_react_agent`
-    integration (C2) will wire that up. Until then, populating the
-    messages projection is opt-in at the node level.
-    """
-
-    def test_node_calling_stream_v2_populates_messages(self) -> None:
-        model = GenericFakeChatModel(messages=iter(["hello world"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = model.stream_v2(state["messages"])
-            return {"messages": stream.output}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-
-        assert len(streams) == 1
-        assert isinstance(streams[0], ChatModelStream)
-        assert streams[0].output.content == "hello world"
-
-    def test_node_stream_v2_text_deltas_iterate(self) -> None:
-        """Consumer can iterate `.text` on the streamed message in real time."""
-        model = GenericFakeChatModel(messages=iter(["streamed answer"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = model.stream_v2(state["messages"])
-            return {"messages": stream.output}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "go"})
-
-        # Pull the stream handle out, then iterate its text deltas.
-        (stream,) = list(run.messages)
-        text = "".join(stream.text)
-        assert text == "streamed answer"
-
-    def test_non_llm_message_returned_from_node(self) -> None:
-        """Node returns a finalized AIMessage directly — whole-message fallback."""
-
-        def return_message(state: MessagesState) -> dict[str, Any]:
-            return {"messages": AIMessage(content="hardcoded", id="msg-abc")}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("return_message", return_message)
-            .add_edge(START, "return_message")
-            .add_edge("return_message", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-
-        assert len(streams) == 1
-        assert streams[0].output.content == "hardcoded"
-
-    @pytest.mark.anyio
-    async def test_async_node_calling_astream_v2(self) -> None:
-        model = GenericFakeChatModel(messages=iter(["async answer"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = await model.astream_v2(state["messages"])
-            msg = await stream
-            return {"messages": msg}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-
-        streams = []
-        async for stream in run.messages:
-            streams.append(stream)
-
-        assert len(streams) == 1
-        assert isinstance(streams[0], AsyncChatModelStream)
-        msg = await streams[0].output
-        assert msg.content == "async answer"
-
-    @pytest.mark.anyio
-    async def test_nested_async_iteration_yields_text_deltas(self) -> None:
-        """Iterate `stream.text` inside `async for stream in run.messages`.
-
-        The inner `stream.text` cursor drives the shared graph pump via
-        `AsyncProjection._arequest_more`, wired by
-        `MessagesTransformer._bind_apump` and
-        `AsyncGraphRunStream._wire_arequest_more`.
-        """
-        import asyncio
-
-        model = GenericFakeChatModel(messages=iter(["hello world"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            stream = await model.astream_v2(state["messages"])
-            msg = await stream
-            return {"messages": msg}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-
-        async def consume_nested() -> list[str]:
-            collected: list[str] = []
-            async for stream in run.messages:
-                async for delta in stream.text:
-                    collected.append(delta)
-            return collected
-
-        deltas = await asyncio.wait_for(consume_nested(), timeout=2.0)
-        assert "".join(deltas) == "hello world"
-
-
-class TestEndToEndV2Invoke:
-    """Nodes call `model.invoke()`; `stream_v2` routes through v2.
-
-    Exercises the auto-routing path added in
-    `feat(core): route invoke through v2 event path for
-    _V2StreamingCallbackHandler`: `stream_v2` injects
-    `CONFIG_KEY_STREAM_MESSAGES_V2` into the config, pregel attaches
-    `StreamMessagesHandlerV2`, `BaseChatModel._should_stream_v2` sees the
-    v2 marker and drives the protocol event generator, and
-    `on_stream_event` forwards each event onto the messages channel.
-    """
-
-    def test_invoke_with_v2_marker_populates_messages(self) -> None:
-        """Node calling `model.invoke()` produces one ChatModelStream with v2 events."""
-        model = GenericFakeChatModel(messages=iter(["hello world"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-
-        assert len(streams) == 1, (
-            "Expected exactly one ChatModelStream — the streamed invoke and "
-            "the node's return of the same AIMessage must dedupe."
-        )
-        stream = streams[0]
-        assert isinstance(stream, ChatModelStream)
-        assert stream.output.content == "hello world"
-
-    def test_invoke_v2_emits_protocol_events(self) -> None:
-        """Iterating the stream yields the full v2 lifecycle (not v1 chunks)."""
-        model = GenericFakeChatModel(messages=iter(["streamed answer"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "go"})
-        (stream,) = list(run.messages)
-
-        events = list(stream)
-        event_types = [e.get("event") for e in events]
-        assert "message-start" in event_types
-        assert "content-block-start" in event_types
-        assert "content-block-delta" in event_types
-        assert "content-block-finish" in event_types
-        assert "message-finish" in event_types
-        # Sanity: every event is a dict carrying an "event" key — not an
-        # AIMessageChunk tuple from the v1 path.
-        for event in events:
-            assert isinstance(event, dict)
-            assert "event" in event
-        # Typed projection still assembles the final text.
-        assert stream.output.content == "streamed answer"
-
-    def test_invoke_text_deltas_iterate_live(self) -> None:
-        """`.text` projection yields deltas in order."""
-        model = GenericFakeChatModel(messages=iter(["delta streaming works"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        (stream,) = list(run.messages)
-
-        assembled = "".join(stream.text)
-        assert assembled == "delta streaming works"
-
-    def test_invoke_dedupe_survives_multi_node_graph(self) -> None:
-        """Two model-invoking nodes produce exactly two streams, each once."""
-        model_a = GenericFakeChatModel(messages=iter(["alpha"]))
-        model_b = GenericFakeChatModel(messages=iter(["beta"]))
-
-        def node_a(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model_a.invoke(state["messages"])}
-
-        def node_b(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model_b.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("node_a", node_a)
-            .add_node("node_b", node_b)
-            .add_edge(START, "node_a")
-            .add_edge("node_a", "node_b")
-            .add_edge("node_b", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-
-        assert len(streams) == 2
-        contents = {s.output.content for s in streams}
-        assert contents == {"alpha", "beta"}
-
-    def test_invoke_plus_constructed_message_two_streams(self) -> None:
-        """A v2-streamed node + a node that returns a constructed AIMessage
-        produces two ChatModelStreams — one from the live event lifecycle,
-        one synthesized from the constructed message via `message_to_events`.
-        """
-        model = GenericFakeChatModel(messages=iter(["live stream"]))
-
-        def streaming_node(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        def constructed_node(state: MessagesState) -> dict[str, Any]:
-            return {"messages": [AIMessage(content="hardcoded", id="constructed-1")]}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("streaming_node", streaming_node)
-            .add_node("constructed_node", constructed_node)
-            .add_edge(START, "streaming_node")
-            .add_edge("streaming_node", "constructed_node")
-            .add_edge("constructed_node", END)
-            .compile()
-        )
-
-        run = graph.stream_v2({"messages": "hi"})
-        streams = list(run.messages)
-
-        assert len(streams) == 2
-        assert streams[0].node == "streaming_node"
-        assert streams[0].output.content == "live stream"
-        assert streams[1].node == "constructed_node"
-        assert streams[1].output.content == "hardcoded"
-        assert streams[1].message_id == "constructed-1"
-
-    @pytest.mark.anyio
-    async def test_ainvoke_with_v2_marker_populates_messages(self) -> None:
-        """Async mirror: `model.ainvoke()` + `astream_v2`."""
-        model = GenericFakeChatModel(messages=iter(["async invoke"]))
-
-        async def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": await model.ainvoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        run = await graph.astream_v2({"messages": "hi"})
-
-        streams = []
-        async for stream in run.messages:
-            streams.append(stream)
-
-        assert len(streams) == 1
-        assert isinstance(streams[0], AsyncChatModelStream)
-        msg = await streams[0].output
-        assert msg.content == "async invoke"
-
-
-class TestDirectMessagesModeStaysV1:
-    """Regression guard: direct `graph.stream(stream_mode="messages")`
-    (no `stream_v2`) must keep the v1 `(AIMessageChunk, metadata)`
-    tuple shape. The v2 flag is only injected by `stream_v2` / `astream_v2`.
-    """
-
-    def test_direct_graph_stream_messages_yields_ai_message_chunks(self) -> None:
-        model = GenericFakeChatModel(messages=iter(["legacy path"]))
-
-        def call_model(state: MessagesState) -> dict[str, Any]:
-            return {"messages": model.invoke(state["messages"])}
-
-        graph = (
-            StateGraph(MessagesState)
-            .add_node("call_model", call_model)
-            .add_edge(START, "call_model")
-            .add_edge("call_model", END)
-            .compile()
-        )
-
-        parts = list(graph.stream({"messages": "hi"}, stream_mode="messages"))
-        # Should have at least one streamed chunk; each part is
-        # (AIMessageChunk, metadata) — not a v2 event dict.
-        assert parts, "expected stream_mode='messages' to emit tuples"
-        for part in parts:
-            payload, _metadata = part
-            assert isinstance(payload, AIMessageChunk), (
-                "direct graph.stream(stream_mode='messages') leaked v2 "
-                "event dicts — stream_v2 flag bled through."
-            )
-        assembled = "".join(
-            p[0].content for p in parts if isinstance(p[0].content, str)
-        )
-        assert assembled == "legacy path"
-
-
-class TestStreamMessagesHandlerV2Unit:
-    """Unit tests on the handler class itself."""
-
-    def test_on_llm_new_token_is_noop(self) -> None:
-        """v2 handler must not emit v1 chunks even if `on_llm_new_token` fires
-        (e.g. from a node calling `model.stream()` directly on a v2-flagged run).
-        """
-        from uuid import uuid4
-
-        from langchain_core.outputs import ChatGenerationChunk
-
-        from langgraph.pregel._messages import StreamMessagesHandlerV2
-
-        emitted: list[Any] = []
-        handler = StreamMessagesHandlerV2(emitted.append, subgraphs=False)
-        run_id = uuid4()
-        # Register a fake run so `self.metadata.get(run_id)` would succeed for
-        # other callbacks — this makes sure the no-op is unconditional, not a
-        # side effect of missing metadata.
-        handler.metadata[run_id] = ((), {"langgraph_node": "x"})
-
-        handler.on_llm_new_token(
-            "hello",
-            chunk=ChatGenerationChunk(message=AIMessageChunk(content="hello")),
-            run_id=run_id,
-        )
-
-        assert emitted == [], (
-            "StreamMessagesHandlerV2.on_llm_new_token must not push to the "
-            "messages stream — it's the v2 marker's guarantee."
-        )
@@ -1,453 +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,
-    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,
-    trigger_call_id: str | 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 trigger_call_id is not None:
-        data["trigger_call_id"] = trigger_call_id
-    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, 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",
-                trigger_call_id="task_a",
-            )
-        )
-
-        handle = self._handle(transformer)
-        assert handle.path == ("task_a:child",)
-        assert handle.graph_name == "child"
-        assert handle.trigger_call_id == "task_a"
-        assert handle.status == "started"
-
-    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": "x"},
-            }
-        )
-        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 TestSubgraphTriggerCallId:
-    """Confirm `trigger_call_id` flows from real pregel metadata."""
-
-    def test_trigger_call_id_populated_end_to_end(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 encodes `node_name:task_id`.
-        # Both the parsed task_id (`trigger_call_id`) and the segment
-        # should match the same task_id suffix.
-        assert ":" in child.path[0]
-        node_name, _, task_id = child.path[0].partition(":")
-        assert node_name == "sub"
-        assert task_id  # non-empty
-        assert child.trigger_call_id == task_id
-
-
-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"
@@ -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",
-    }
@@ -524,61 +524,61 @@ toml = [

 [[package]]
 name = "cryptography"
-version = "46.0.7"
+version = "46.0.6"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "cffi", marker = "python_full_version >= '3.11' and python_full_version < '3.14' and platform_python_implementation != 'PyPy'" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/a4/ba/04b1bd4218cbc58dc90ce967106d51582371b898690f3ae0402876cc4f34/cryptography-46.0.6.tar.gz", hash = "sha256:27550628a518c5c6c903d84f637fbecf287f6cb9ced3804838a1295dc1fd0759", size = 750542, upload-time = "2026-03-25T23:34:53.396Z" }
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-    { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" },
+    { 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" }
+sdist = { url = "https://files.pythonhosted.org/packages/86/2a/d65de24fc9b7989137253da8973f850f3e39b4ce3e0377bc8200d6b3c189/langchain_core-1.2.25.tar.gz", hash = "sha256:77e032b96509d0eb1f6875042fdf97b7e2334a815314700c6894d9d078909b9c", size = 842347, upload-time = "2026-04-02T22:39:11.528Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0e/14/03c09686602567059f26af29de0c44546a83af2f2aa29925e61040e43ea2/langchain_core-1.3.0a2-py3-none-any.whl", hash = "sha256:9e929a34f0b0c6c1255e395a1de34f8626893ceb4cdae550a22a0bd18c87be54", size = 510233, upload-time = "2026-04-13T14:37:54.277Z" },
+    { 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"
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 [[package]]
Author	SHA1	Message	Date
Will Fu-Hinthorn	685a755baf	chore: use bounded queue for checkpointing	2026-04-09 17:33:50 -07:00
Will Fu-HinthornandClaude Opus 4.6	bde0c47cd9	fix: handle non-deterministic ordering in test_imp_nested Nested tasks run concurrently so output order is non-deterministic. Sort intermediate results before comparison, matching the pattern already used by test_imp_task. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-08 18:04:55 -07:00
Will Fu-Hinthorn	7b034c2d25	chore: update conformance lint	2026-04-08 16:02:42 -07:00