mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-08-19 22:25:44 +02:00
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27
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25470ea435 |
Generated
+3
-3
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||||
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||||
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[[package]]
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Generated
+123
-4
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[[package]]
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{ url = "https://files.pythonhosted.org/packages/7b/d9/8d95e906764a386a3d3b596f3c68bb63687dfca806373509f51ce8eea81f/xxhash-3.6.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:15e0dac10eb9309508bfc41f7f9deaa7755c69e35af835db9cb10751adebc35d", size = 31565, upload-time = "2025-10-02T14:37:06.966Z" },
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|
||||
[[package]]
|
||||
name = "zstandard"
|
||||
version = "0.25.0"
|
||||
|
||||
@@ -46,6 +46,23 @@ LC_REVIVER = Reviver()
|
||||
EMPTY_BYTES = b""
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Dedup log warnings across process lifetime; cap bounds state if types are
|
||||
# dynamically generated (also acts as a circuit breaker on warning volume).
|
||||
# Dedup is best-effort: racing threads may each emit once for the same key,
|
||||
# and warnings are silently dropped once _MAX_WARNED_TYPES is reached.
|
||||
_MAX_WARNED_TYPES = 1000
|
||||
_warned_unregistered_types: set[tuple[str, str]] = set()
|
||||
_warned_blocked_types: set[tuple[str, str]] = set()
|
||||
|
||||
|
||||
def _warn_once(
|
||||
seen: set[tuple[str, str]], key: tuple[str, str], msg: str, *args: object
|
||||
) -> None:
|
||||
if key in seen or len(seen) >= _MAX_WARNED_TYPES:
|
||||
return
|
||||
seen.add(key)
|
||||
logger.warning(msg, *args)
|
||||
|
||||
|
||||
class JsonPlusSerializer(SerializerProtocol):
|
||||
"""Serializer that uses ormsgpack, with optional fallbacks.
|
||||
@@ -534,7 +551,9 @@ def _create_msgpack_ext_hook(
|
||||
"name": name,
|
||||
}
|
||||
)
|
||||
logger.warning(
|
||||
_warn_once(
|
||||
_warned_unregistered_types,
|
||||
key,
|
||||
"Deserializing unregistered type %s.%s from checkpoint. "
|
||||
"This will be blocked in a future version. "
|
||||
"Set LANGGRAPH_STRICT_MSGPACK=true to block now, or add "
|
||||
@@ -556,7 +575,9 @@ def _create_msgpack_ext_hook(
|
||||
"name": name,
|
||||
}
|
||||
)
|
||||
logger.warning(
|
||||
_warn_once(
|
||||
_warned_blocked_types,
|
||||
key,
|
||||
"Blocked deserialization of %s.%s - not in allowed_msgpack_modules. "
|
||||
"Add to allowed_msgpack_modules to allow: [(%r, %r)]",
|
||||
module,
|
||||
|
||||
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
|
||||
|
||||
[project]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.0.1"
|
||||
version = "4.0.2"
|
||||
description = "Library with base interfaces for LangGraph checkpoint savers."
|
||||
authors = []
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@@ -29,6 +29,8 @@ from langgraph.checkpoint.serde.jsonplus import (
|
||||
EXT_METHOD_SINGLE_ARG,
|
||||
JsonPlusSerializer,
|
||||
_msgpack_enc,
|
||||
_warned_blocked_types,
|
||||
_warned_unregistered_types,
|
||||
)
|
||||
|
||||
|
||||
@@ -102,6 +104,13 @@ def test_msgpack_method_pathlib_blocked_encrypted_strict(
|
||||
class TestEncryptedSerializerMsgpackAllowlist:
|
||||
"""Test msgpack allowlist behavior through EncryptedSerializer."""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_warned_types(self) -> None:
|
||||
# Warning dedup state is process-global; reset per-test so each case
|
||||
# sees a fresh slate and assertions about warning emission are stable.
|
||||
_warned_unregistered_types.clear()
|
||||
_warned_blocked_types.clear()
|
||||
|
||||
def test_safe_types_no_warning(self, caplog: pytest.LogCaptureFixture) -> None:
|
||||
"""Test safe types deserialize without warnings through encryption."""
|
||||
serde = _make_encrypted_serde()
|
||||
|
||||
@@ -35,6 +35,8 @@ from langgraph.checkpoint.serde.jsonplus import (
|
||||
JsonPlusSerializer,
|
||||
_msgpack_enc,
|
||||
_msgpack_ext_hook_to_json,
|
||||
_warned_blocked_types,
|
||||
_warned_unregistered_types,
|
||||
)
|
||||
from langgraph.store.base import Item
|
||||
|
||||
@@ -580,6 +582,14 @@ def test_msgpack_safe_types_no_warning(caplog: pytest.LogCaptureFixture) -> None
|
||||
assert result is not None
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_warned_types() -> None:
|
||||
# Warning dedup state is process-global; reset per-test so each case sees
|
||||
# a fresh slate and assertions about warning emission are stable.
|
||||
_warned_unregistered_types.clear()
|
||||
_warned_blocked_types.clear()
|
||||
|
||||
|
||||
def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) -> None:
|
||||
"""Pydantic models not in allowlist should log warning but still deserialize."""
|
||||
current = _lg_msgpack.STRICT_MSGPACK_ENABLED
|
||||
@@ -595,6 +605,12 @@ def test_msgpack_pydantic_warns_by_default(caplog: pytest.LogCaptureFixture) ->
|
||||
assert "unregistered type" in caplog.text.lower()
|
||||
assert "allowed_msgpack_modules" in caplog.text
|
||||
assert result == obj
|
||||
|
||||
# Second deserialization of the same type should NOT produce another warning
|
||||
caplog.clear()
|
||||
result2 = serde.loads_typed(dumped)
|
||||
assert "unregistered type" not in caplog.text.lower()
|
||||
assert result2 == obj
|
||||
_lg_msgpack.STRICT_MSGPACK_ENABLED = current
|
||||
|
||||
|
||||
@@ -639,7 +655,6 @@ def test_msgpack_allowlist_silences_warning(caplog: pytest.LogCaptureFixture) ->
|
||||
|
||||
def test_msgpack_none_blocks_unregistered(caplog: pytest.LogCaptureFixture) -> None:
|
||||
"""allowed_msgpack_modules=None should block unregistered types."""
|
||||
|
||||
serde = JsonPlusSerializer(allowed_msgpack_modules=None)
|
||||
|
||||
obj = MyPydantic(foo="test", bar=42, inner=InnerPydantic(hello="world"))
|
||||
@@ -657,7 +672,6 @@ def test_msgpack_allowlist_blocks_non_listed(
|
||||
caplog: pytest.LogCaptureFixture,
|
||||
) -> None:
|
||||
"""Allowlists should block unregistered types even if msgpack is enabled."""
|
||||
|
||||
serde = JsonPlusSerializer(
|
||||
allowed_msgpack_modules=[("tests.test_jsonplus", "MyPydantic")]
|
||||
)
|
||||
|
||||
@@ -12,13 +12,25 @@ from langgraph.checkpoint.base import (
|
||||
empty_checkpoint,
|
||||
)
|
||||
from langgraph.checkpoint.memory import InMemorySaver
|
||||
from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
|
||||
from langgraph.checkpoint.serde.jsonplus import (
|
||||
JsonPlusSerializer,
|
||||
_warned_blocked_types,
|
||||
_warned_unregistered_types,
|
||||
)
|
||||
|
||||
|
||||
class MemoryPydantic(BaseModel):
|
||||
foo: str
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_warned_types() -> None:
|
||||
# Warning dedup state is process-global; reset per-test so each case sees
|
||||
# a fresh slate and assertions about warning emission are stable.
|
||||
_warned_unregistered_types.clear()
|
||||
_warned_blocked_types.clear()
|
||||
|
||||
|
||||
class TestMemorySaver:
|
||||
@pytest.fixture(autouse=True)
|
||||
def setup(self) -> None:
|
||||
|
||||
Generated
+123
-4
@@ -286,7 +286,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.0.1"
|
||||
version = "4.0.2"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -369,7 +369,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.6.4"
|
||||
version = "0.7.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
@@ -379,11 +379,12 @@ dependencies = [
|
||||
{ name = "requests" },
|
||||
{ name = "requests-toolbelt" },
|
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{ name = "uuid-utils" },
|
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{ name = "xxhash" },
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{ name = "zstandard" },
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wheels = [
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[[package]]
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@@ -1515,6 +1516,124 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/33/e8/e40370e6d74ddba47f002a32919d91310d6074130fe4e17dabcafc15cbf1/watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f", size = 79067, upload-time = "2024-11-01T14:07:11.845Z" },
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[[package]]
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name = "xxhash"
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wheels = [
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||||
{ url = "https://files.pythonhosted.org/packages/4b/77/07f0e7a3edd11a6097e990f6e5b815b6592459cb16dae990d967693e6ea9/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:b465afd7909db30168ab62afe40b2fcf79eedc0b89a6c0ab3123515dc0df8b99", size = 213007, upload-time = "2025-10-02T14:36:07.733Z" },
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{ url = "https://files.pythonhosted.org/packages/ae/d8/bc5fa0d152837117eb0bef6f83f956c509332ce133c91c63ce07ee7c4873/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:a881851cf38b0a70e7c4d3ce81fc7afd86fbc2a024f4cfb2a97cf49ce04b75d3", size = 200956, upload-time = "2025-10-02T14:36:09.106Z" },
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{ url = "https://files.pythonhosted.org/packages/26/a5/d749334130de9411783873e9b98ecc46688dad5db64ca6e04b02acc8b473/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:9b3222c686a919a0f3253cfc12bb118b8b103506612253b5baeaac10d8027cf6", size = 213401, upload-time = "2025-10-02T14:36:10.585Z" },
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||||
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||||
{ url = "https://files.pythonhosted.org/packages/0c/b3/62fd2b586283b7d7d665fb98e266decadf31f058f1cf6c478741f68af0cb/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5c1343d49ac102799905e115aee590183c3921d475356cb24b4de29a4bc56518", size = 193913, upload-time = "2025-10-02T14:36:14.025Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/9a/9a/c19c42c5b3f5a4aad748a6d5b4f23df3bed7ee5445accc65a0fb3ff03953/xxhash-3.6.0-cp314-cp314t-win32.whl", hash = "sha256:5851f033c3030dd95c086b4a36a2683c2ff4a799b23af60977188b057e467119", size = 31586, upload-time = "2025-10-02T14:36:15.603Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/03/d6/4cc450345be9924fd5dc8c590ceda1db5b43a0a889587b0ae81a95511360/xxhash-3.6.0-cp314-cp314t-win_amd64.whl", hash = "sha256:0444e7967dac37569052d2409b00a8860c2135cff05502df4da80267d384849f", size = 32526, upload-time = "2025-10-02T14:36:16.708Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/0f/c9/7243eb3f9eaabd1a88a5a5acadf06df2d83b100c62684b7425c6a11bcaa8/xxhash-3.6.0-cp314-cp314t-win_arm64.whl", hash = "sha256:bb79b1e63f6fd84ec778a4b1916dfe0a7c3fdb986c06addd5db3a0d413819d95", size = 28898, upload-time = "2025-10-02T14:36:17.843Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/93/1e/8aec23647a34a249f62e2398c42955acd9b4c6ed5cf08cbea94dc46f78d2/xxhash-3.6.0-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0f7b7e2ec26c1666ad5fc9dbfa426a6a3367ceaf79db5dd76264659d509d73b0", size = 30662, upload-time = "2025-10-02T14:37:01.743Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b8/0b/b14510b38ba91caf43006209db846a696ceea6a847a0c9ba0a5b1adc53d6/xxhash-3.6.0-pp311-pypy311_pp73-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:5dc1e14d14fa0f5789ec29a7062004b5933964bb9b02aae6622b8f530dc40296", size = 41056, upload-time = "2025-10-02T14:37:02.879Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/50/55/15a7b8a56590e66ccd374bbfa3f9ffc45b810886c8c3b614e3f90bd2367c/xxhash-3.6.0-pp311-pypy311_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:881b47fc47e051b37d94d13e7455131054b56749b91b508b0907eb07900d1c13", size = 36251, upload-time = "2025-10-02T14:37:04.44Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/62/b2/5ac99a041a29e58e95f907876b04f7067a0242cb85b5f39e726153981503/xxhash-3.6.0-pp311-pypy311_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c6dc31591899f5e5666f04cc2e529e69b4072827085c1ef15294d91a004bc1bd", size = 32481, upload-time = "2025-10-02T14:37:05.869Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/7b/d9/8d95e906764a386a3d3b596f3c68bb63687dfca806373509f51ce8eea81f/xxhash-3.6.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:15e0dac10eb9309508bfc41f7f9deaa7755c69e35af835db9cb10751adebc35d", size = 31565, upload-time = "2025-10-02T14:37:06.966Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zstandard"
|
||||
version = "0.25.0"
|
||||
|
||||
@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
dependencies = [
|
||||
"langchain-openai==1.0.1"
|
||||
"langchain-openai==1.1.14"
|
||||
]
|
||||
@@ -5,7 +5,7 @@ description = "Test for prerelease stuff"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
dependencies = [
|
||||
"langchain-openai==1.0.0a2",
|
||||
"langchain-openai==1.1.14",
|
||||
"langchain-anthropic==1.0.0a5",
|
||||
"langgraph==1.1.5"
|
||||
]
|
||||
|
||||
@@ -5,7 +5,7 @@ description = "Test for prerelease stuff"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
dependencies = [
|
||||
"langchain-openai==1.0.0a2",
|
||||
"langchain-openai==1.1.14",
|
||||
"langgraph==1.1.2",
|
||||
"langchain_community>=0.3.0",
|
||||
]
|
||||
@@ -3676,9 +3676,9 @@ 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 "0.5.20"
|
||||
resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.20.tgz#4021847d2ccd5a86c5eb96060f9bb5f19f80eca5"
|
||||
integrity sha512-ULhLM8RswvQDXufLtNtvclHrWCBx8Cb5UPI6lAZC+8Dq59iHsVPz/3Ac9khWNm1VIvChRsuykixD/WrmzuuA3Q==
|
||||
dependencies:
|
||||
p-queue "6.6.2"
|
||||
uuid "10.0.0"
|
||||
|
||||
@@ -1328,9 +1328,9 @@ 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 "0.5.20"
|
||||
resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.5.20.tgz#4021847d2ccd5a86c5eb96060f9bb5f19f80eca5"
|
||||
integrity sha512-ULhLM8RswvQDXufLtNtvclHrWCBx8Cb5UPI6lAZC+8Dq59iHsVPz/3Ac9khWNm1VIvChRsuykixD/WrmzuuA3Q==
|
||||
dependencies:
|
||||
p-queue "6.6.2"
|
||||
uuid "10.0.0"
|
||||
|
||||
@@ -1 +1 @@
|
||||
__version__ = "0.4.21"
|
||||
__version__ = "0.4.23"
|
||||
|
||||
@@ -26,8 +26,15 @@ class LogData(TypedDict):
|
||||
params: dict[str, Any]
|
||||
|
||||
|
||||
def get_anonymized_params(kwargs: dict[str, Any]) -> dict[str, bool]:
|
||||
params = {}
|
||||
def get_anonymized_params(
|
||||
kwargs: dict[str, Any], *, cli_command: str
|
||||
) -> dict[str, bool | str]:
|
||||
params: dict[str, bool | str] = {}
|
||||
|
||||
if cli_command == "deploy" and (
|
||||
analytics_source := os.getenv("LANGGRAPH_CLI_ANALYTICS_SOURCE")
|
||||
):
|
||||
params["source"] = analytics_source
|
||||
|
||||
# anonymize params with values
|
||||
if config := kwargs.get("config"):
|
||||
@@ -88,7 +95,7 @@ def log_command(func):
|
||||
"python_version": platform.python_version(),
|
||||
"cli_version": __version__,
|
||||
"cli_command": func.__name__,
|
||||
"params": get_anonymized_params(kwargs),
|
||||
"params": get_anonymized_params(kwargs, cli_command=func.__name__),
|
||||
}
|
||||
|
||||
background_thread = threading.Thread(target=log_data, args=(data,))
|
||||
|
||||
@@ -23,7 +23,7 @@ dependencies = [
|
||||
path = "langgraph_cli/__init__.py"
|
||||
[project.optional-dependencies]
|
||||
inmem = [
|
||||
"langgraph-api>=0.5.35,<0.8.0 ; python_version >= '3.11'",
|
||||
"langgraph-api>=0.5.35,<0.9.0 ; python_version >= '3.11'",
|
||||
"langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
|
||||
]
|
||||
|
||||
|
||||
Generated
+3
-3
@@ -290,7 +290,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.7.26"
|
||||
version = "0.7.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
@@ -303,9 +303,9 @@ dependencies = [
|
||||
{ name = "xxhash" },
|
||||
{ name = "zstandard" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/76/86/6de4f6f0451a9658f26f633e0bb090552a4dafd7df3f1ae7f0d40558e67e/langsmith-0.7.26.tar.gz", hash = "sha256:a3e06f3d689ce7195717aa6b8f91082319819ec7ea9b9a62cdcd3d9dc25bfc7b", size = 1146118, upload-time = "2026-04-06T15:01:03.336Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/81/8e/7eb7d65ce62e98e74b9f18f193ea7ac3996d4fbd71fffcc67d0f7ba3103e/langsmith-0.7.26-py3-none-any.whl", hash = "sha256:fe5c877972cea450c1c48251c8fae0f18543c8d19dfdb9ff9a9c4263763dde4e", size = 360160, upload-time = "2026-04-06T15:01:01.516Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+3
-3
@@ -266,7 +266,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.7.26"
|
||||
version = "0.7.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
@@ -279,9 +279,9 @@ dependencies = [
|
||||
{ name = "xxhash" },
|
||||
{ name = "zstandard" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/76/86/6de4f6f0451a9658f26f633e0bb090552a4dafd7df3f1ae7f0d40558e67e/langsmith-0.7.26.tar.gz", hash = "sha256:a3e06f3d689ce7195717aa6b8f91082319819ec7ea9b9a62cdcd3d9dc25bfc7b", size = 1146118, upload-time = "2026-04-06T15:01:03.336Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/81/8e/7eb7d65ce62e98e74b9f18f193ea7ac3996d4fbd71fffcc67d0f7ba3103e/langsmith-0.7.26-py3-none-any.whl", hash = "sha256:fe5c877972cea450c1c48251c8fae0f18543c8d19dfdb9ff9a9c4263763dde4e", size = 360160, upload-time = "2026-04-06T15:01:01.516Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+465
-383
File diff suppressed because it is too large
Load Diff
@@ -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,
|
||||
|
||||
@@ -245,15 +245,6 @@ class _GraphCallbackManager(BaseCallbackManager):
|
||||
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,
|
||||
*,
|
||||
@@ -321,15 +312,6 @@ class _AsyncGraphCallbackManager(BaseCallbackManager):
|
||||
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,
|
||||
*,
|
||||
|
||||
@@ -1,7 +1,5 @@
|
||||
import asyncio
|
||||
import sys
|
||||
from collections.abc import Callable
|
||||
from contextvars import ContextVar
|
||||
from typing import Any
|
||||
|
||||
from langchain_core.runnables import RunnableConfig
|
||||
@@ -11,18 +9,6 @@ from langgraph.store.base import BaseStore
|
||||
from langgraph._internal._constants import CONF, CONFIG_KEY_RUNTIME
|
||||
from langgraph.types import StreamWriter
|
||||
|
||||
_tool_call_writer: ContextVar[Callable[[Any], None] | None] = ContextVar(
|
||||
"langgraph_tool_call_writer", default=None
|
||||
)
|
||||
"""ContextVar holding the writer for the currently-executing tool call.
|
||||
|
||||
Set by `StreamToolCallHandler.on_tool_start` and reset on end/error.
|
||||
Defined here (rather than alongside the handler in `pregel/_tools.py`)
|
||||
so `emit_tool_output_delta` can import it without triggering the
|
||||
pregel import chain — user tool code does
|
||||
`from langgraph.config import emit_tool_output_delta` at import time.
|
||||
"""
|
||||
|
||||
|
||||
def _no_op_stream_writer(c: Any) -> None:
|
||||
pass
|
||||
@@ -208,30 +194,3 @@ def get_stream_writer() -> StreamWriter:
|
||||
"""
|
||||
runtime = get_config()[CONF][CONFIG_KEY_RUNTIME]
|
||||
return runtime.stream_writer
|
||||
|
||||
|
||||
def emit_tool_output_delta(delta: Any) -> None:
|
||||
"""Emit a `tool-output-delta` event onto the `tools` stream mode.
|
||||
|
||||
Must be called from inside a tool's execution scope (sync or async).
|
||||
While a tool is running, `StreamToolCallHandler.on_tool_start` sets a
|
||||
writer closure on a ContextVar keyed to that call's `tool_call_id`
|
||||
and namespace; this helper reads the ContextVar and forwards `delta`
|
||||
through it.
|
||||
|
||||
When called outside any tool call, or when the graph was not
|
||||
streamed with `"tools"` in `stream_mode`, this is a silent no-op —
|
||||
tool authors can leave `emit_tool_output_delta` calls in place
|
||||
without gating them on stream mode.
|
||||
|
||||
Args:
|
||||
delta: The partial output chunk to stream. Shape is up to the
|
||||
caller — strings are the common case, but any JSON-
|
||||
serializable value is accepted and surfaced as-is on the
|
||||
`tools` channel's `tool-output-delta` payload under
|
||||
`"delta"`.
|
||||
"""
|
||||
writer = _tool_call_writer.get()
|
||||
if writer is None:
|
||||
return
|
||||
writer(delta)
|
||||
|
||||
@@ -1045,7 +1045,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
|
||||
interrupt_after: All | list[str] | None = None,
|
||||
debug: bool = False,
|
||||
name: str | None = None,
|
||||
transformers: Sequence[Callable[..., Any]] | None = None,
|
||||
) -> CompiledStateGraph[StateT, ContextT, InputT, OutputT]:
|
||||
"""Compiles the `StateGraph` into a `CompiledStateGraph` object.
|
||||
|
||||
@@ -1078,11 +1077,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
|
||||
interrupt_after: An optional list of node names to interrupt after.
|
||||
debug: A flag indicating whether to enable debug mode.
|
||||
name: The name to use for the compiled graph.
|
||||
transformers: Optional sequence of zero-arg factories returning
|
||||
`StreamTransformer` instances. Registered on the compiled
|
||||
graph and instantiated per-run whenever `stream_v2` /
|
||||
`astream_v2` is called. Appended after the built-in
|
||||
`ValuesTransformer` and `MessagesTransformer`.
|
||||
|
||||
Returns:
|
||||
CompiledStateGraph: The compiled `StateGraph`.
|
||||
@@ -1165,7 +1159,6 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
|
||||
store=store,
|
||||
cache=cache,
|
||||
name=name or "LangGraph",
|
||||
stream_transformers=transformers,
|
||||
)
|
||||
compiled._serde_allowlist = serde_allowlist
|
||||
|
||||
|
||||
@@ -1,274 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import AsyncIterator, Callable, Iterator
|
||||
from typing import Any, TypeVar, cast
|
||||
from uuid import UUID
|
||||
|
||||
from langchain_core.callbacks import BaseCallbackHandler
|
||||
|
||||
from langgraph._internal._constants import NS_SEP
|
||||
from langgraph.errors import GraphInterrupt
|
||||
from langgraph.pregel.protocol import StreamChunk
|
||||
|
||||
try:
|
||||
from langchain_core.tracers._streaming import _StreamingCallbackHandler
|
||||
except ImportError:
|
||||
_StreamingCallbackHandler = object # type: ignore[assignment,misc]
|
||||
|
||||
|
||||
T = TypeVar("T")
|
||||
|
||||
|
||||
_LANGGRAPH_SENTINEL_NODES = frozenset({"__start__", "__end__"})
|
||||
|
||||
|
||||
def _is_nested_pregel_start(
|
||||
name: str | None,
|
||||
metadata: dict[str, Any] | None,
|
||||
parent_run_id: UUID | None,
|
||||
task_run_ids: set[UUID],
|
||||
) -> bool:
|
||||
"""Recognize a nested `Pregel` invocation from its `on_chain_start` metadata.
|
||||
|
||||
When a compiled graph is added as a node, pregel fires two
|
||||
`on_chain_start` callbacks at that task: first for the node chain
|
||||
(whose `name` matches `metadata["langgraph_node"]`) and second for
|
||||
the inner `Pregel` chain (whose `name` is the graph's `name`, not
|
||||
the node name). Both share the same `langgraph_checkpoint_ns`.
|
||||
|
||||
Primary signal: a `langgraph_checkpoint_ns` is set AND `name`
|
||||
differs from the owning task's `langgraph_node`. This covers the
|
||||
common case where the compiled subgraph's name differs from the
|
||||
node name it was registered under.
|
||||
|
||||
Fallback for name collisions (subgraph compiled with
|
||||
`name == node_name`): the inner `Pregel` start's `parent_run_id`
|
||||
is the run_id of the node chain's start event, which the handler
|
||||
records in `task_run_ids` on the first start. Matching
|
||||
`parent_run_id` to that set identifies the second start as the
|
||||
nested `Pregel` even when names coincide.
|
||||
|
||||
Regular node chains are skipped; the root `Pregel` (which has no
|
||||
`langgraph_node` metadata) isn't observed by this handler because
|
||||
the root's start fires before the handler is attached.
|
||||
|
||||
Metadata-based detection is used because `on_chain_start`'s
|
||||
`serialized` argument is `None` for compiled graphs in this
|
||||
version of langchain-core, so class-based detection via
|
||||
`serialized["id"]` isn't available.
|
||||
|
||||
Sentinel nodes (`__start__` / `__end__`) are excluded: conditional
|
||||
edges from `START` fire an `on_chain_start` with `lg_node=__start__`
|
||||
and the router function's name as `name`, which would otherwise
|
||||
match the discriminator without representing an actual nested
|
||||
`Pregel`.
|
||||
|
||||
Args:
|
||||
name: The `name` kwarg from `on_chain_start`.
|
||||
metadata: The `metadata` kwarg from `on_chain_start`.
|
||||
parent_run_id: The `parent_run_id` kwarg from `on_chain_start`.
|
||||
task_run_ids: The set of run_ids the handler has already seen
|
||||
as node-chain starts (i.e. `name == langgraph_node`).
|
||||
"""
|
||||
if not metadata:
|
||||
return False
|
||||
if not metadata.get("langgraph_checkpoint_ns"):
|
||||
return False
|
||||
lg_node = metadata.get("langgraph_node")
|
||||
if lg_node is None or lg_node in _LANGGRAPH_SENTINEL_NODES:
|
||||
return False
|
||||
if name != lg_node:
|
||||
return True
|
||||
# Name collision fallback: the inner Pregel's parent_run_id is
|
||||
# the node chain's run_id, which we recorded when that node
|
||||
# chain's start fired.
|
||||
return parent_run_id is not None and parent_run_id in task_run_ids
|
||||
|
||||
|
||||
class StreamLifecycleHandler(BaseCallbackHandler, _StreamingCallbackHandler):
|
||||
"""Callback handler that emits subgraph lifecycle events on the stream.
|
||||
|
||||
Pushes `LifecycleData`-shaped payloads onto the pregel stream under
|
||||
the `"lifecycle"` mode, keyed by the subgraph's namespace tuple.
|
||||
Drives the `started` → `running` → `completed` / `failed` /
|
||||
`interrupted` state machine.
|
||||
|
||||
The handler is attached to `run_manager.inheritable_handlers` inside
|
||||
a `Pregel.stream` / `astream` call, so it sees callbacks for every
|
||||
descendant chain (nodes, nested `Pregel` subgraphs) but *not* for
|
||||
the root `Pregel` whose start event has already fired. The root's
|
||||
`started` event is emitted eagerly at construction; its terminal
|
||||
state is emitted by `SubgraphTransformer.finalize` / `fail`.
|
||||
|
||||
`run_inline = True` keeps event ordering deterministic.
|
||||
"""
|
||||
|
||||
run_inline = True
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
stream: Callable[[StreamChunk], None],
|
||||
*,
|
||||
root_graph_name: str | None = None,
|
||||
) -> None:
|
||||
"""Initialize the handler and emit the root graph's `started` event.
|
||||
|
||||
Args:
|
||||
stream: Callable that accepts a `StreamChunk` tuple
|
||||
`(namespace, mode, payload)` and enqueues it.
|
||||
root_graph_name: The root `Pregel` instance's `name`, emitted
|
||||
with the root's `started` lifecycle payload.
|
||||
"""
|
||||
self.stream = stream
|
||||
# Namespaces awaiting the started→running transition.
|
||||
self._pending_running: set[tuple[str, ...]] = set()
|
||||
# run_id → subgraph namespace; populated only for Pregel chains.
|
||||
self._run_to_ns: dict[UUID, tuple[str, ...]] = {}
|
||||
# run_ids of node-chain starts (name == langgraph_node); used
|
||||
# as the parent_run_id fallback when a subgraph's name equals
|
||||
# its node name. Cleared as each chain ends.
|
||||
self._task_run_ids: set[UUID] = set()
|
||||
|
||||
root_payload: dict[str, Any] = {"event": "started"}
|
||||
if root_graph_name is not None:
|
||||
root_payload["graph_name"] = root_graph_name
|
||||
self.stream(((), "lifecycle", root_payload))
|
||||
self._pending_running.add(())
|
||||
|
||||
@staticmethod
|
||||
def _subgraph_ns_from_metadata(metadata: dict[str, Any] | None) -> tuple[str, ...]:
|
||||
"""Return the running subgraph's own namespace from task metadata.
|
||||
|
||||
For a nested `Pregel` invoked as a node, `langgraph_checkpoint_ns`
|
||||
ends at the node segment (no inner task appended yet), so
|
||||
splitting on `NS_SEP` gives the subgraph's own namespace.
|
||||
"""
|
||||
if not metadata:
|
||||
return ()
|
||||
nskey = metadata.get("langgraph_checkpoint_ns")
|
||||
if not nskey:
|
||||
return ()
|
||||
return tuple(cast(str, nskey).split(NS_SEP))
|
||||
|
||||
@staticmethod
|
||||
def _containing_ns_from_metadata(
|
||||
metadata: dict[str, Any] | None,
|
||||
) -> tuple[str, ...]:
|
||||
"""Return the namespace of the subgraph that contains this task.
|
||||
|
||||
For an inner task with `langgraph_checkpoint_ns`
|
||||
`"seg_a|seg_b"`, the containing subgraph is `("seg_a",)`.
|
||||
"""
|
||||
if not metadata:
|
||||
return ()
|
||||
nskey = metadata.get("langgraph_checkpoint_ns")
|
||||
if not nskey:
|
||||
return ()
|
||||
return tuple(cast(str, nskey).split(NS_SEP))[:-1]
|
||||
|
||||
def _emit(self, ns: tuple[str, ...], payload: dict[str, Any]) -> None:
|
||||
self.stream((ns, "lifecycle", payload))
|
||||
|
||||
def tap_output_aiter(
|
||||
self, run_id: UUID, output: AsyncIterator[T]
|
||||
) -> AsyncIterator[T]:
|
||||
"""Pass-through — required by the `_StreamingCallbackHandler` protocol.
|
||||
|
||||
Returns the iterator unchanged. A missing implementation lets
|
||||
langchain's default `Protocol` body return `None`, which breaks
|
||||
the `_consume_aiter` code path in `_runnable.py:900`.
|
||||
"""
|
||||
return output
|
||||
|
||||
def tap_output_iter(self, run_id: UUID, output: Iterator[T]) -> Iterator[T]:
|
||||
"""Pass-through — sync counterpart to `tap_output_aiter`."""
|
||||
return output
|
||||
|
||||
def _fire_running_if_pending(self, ns: tuple[str, ...]) -> None:
|
||||
if ns in self._pending_running:
|
||||
self._pending_running.discard(ns)
|
||||
self._emit(ns, {"event": "running"})
|
||||
|
||||
def on_chain_start(
|
||||
self,
|
||||
serialized: dict[str, Any],
|
||||
inputs: dict[str, Any],
|
||||
*,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
tags: list[str] | None = None,
|
||||
metadata: dict[str, Any] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
# Any descendant activity transitions the containing subgraph to running.
|
||||
containing = self._containing_ns_from_metadata(metadata)
|
||||
self._fire_running_if_pending(containing)
|
||||
|
||||
name = cast(str | None, kwargs.get("name"))
|
||||
lg_node = (metadata or {}).get("langgraph_node")
|
||||
|
||||
# Record node-chain starts so the name-collision fallback in
|
||||
# `_is_nested_pregel_start` can match the inner Pregel's
|
||||
# parent_run_id to them.
|
||||
if (
|
||||
lg_node is not None
|
||||
and lg_node not in _LANGGRAPH_SENTINEL_NODES
|
||||
and name == lg_node
|
||||
):
|
||||
self._task_run_ids.add(run_id)
|
||||
|
||||
if not _is_nested_pregel_start(
|
||||
name, metadata, parent_run_id, self._task_run_ids
|
||||
):
|
||||
return
|
||||
|
||||
ns = self._subgraph_ns_from_metadata(metadata)
|
||||
if not ns:
|
||||
return
|
||||
|
||||
self._run_to_ns[run_id] = ns
|
||||
payload: dict[str, Any] = {"event": "started"}
|
||||
if name:
|
||||
payload["graph_name"] = name
|
||||
# `cause` is intentionally not populated here: pregel does not know
|
||||
# what on the parent namespace triggered this subgraph. Product-
|
||||
# specific stream transformers populate `cause` before events
|
||||
# reach the wire. See LifecycleCause in the protocol definition.
|
||||
self._emit(ns, payload)
|
||||
self._pending_running.add(ns)
|
||||
|
||||
def on_chain_end(
|
||||
self,
|
||||
response: Any,
|
||||
*,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
self._task_run_ids.discard(run_id)
|
||||
ns = self._run_to_ns.pop(run_id, None)
|
||||
if ns is None:
|
||||
return
|
||||
# Ensure started→running fired even for empty subgraphs.
|
||||
if ns in self._pending_running:
|
||||
self._pending_running.discard(ns)
|
||||
self._emit(ns, {"event": "running"})
|
||||
self._emit(ns, {"event": "completed"})
|
||||
|
||||
def on_chain_error(
|
||||
self,
|
||||
error: BaseException,
|
||||
*,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
self._task_run_ids.discard(run_id)
|
||||
ns = self._run_to_ns.pop(run_id, None)
|
||||
if ns is None:
|
||||
return
|
||||
self._pending_running.discard(ns)
|
||||
if isinstance(error, GraphInterrupt):
|
||||
self._emit(ns, {"event": "interrupted"})
|
||||
else:
|
||||
self._emit(ns, {"event": "failed", "error": str(error)})
|
||||
@@ -692,7 +692,7 @@ class PregelLoop:
|
||||
# writes so that interrupt() calls re-fire instead of returning
|
||||
# stale values. But if we're actively resuming, keep them —
|
||||
# multi-interrupt scenarios need previously resolved values preserved.
|
||||
if self.is_replaying and (
|
||||
is_time_traveling = self.is_replaying and (
|
||||
# Time-travel to a subgraph checkpoint: the parent sets
|
||||
# RESUMING=True (it can't distinguish time-travel from resume),
|
||||
# so we check if this subgraph's own ns is in checkpoint_map.
|
||||
@@ -710,7 +710,8 @@ class PregelLoop:
|
||||
# (subgraph input is a Send arg, not a Command)
|
||||
or configurable.get(CONFIG_KEY_RESUMING, False)
|
||||
)
|
||||
):
|
||||
)
|
||||
if is_time_traveling:
|
||||
self.checkpoint_pending_writes = [
|
||||
w for w in self.checkpoint_pending_writes if w[1] != RESUME
|
||||
]
|
||||
@@ -765,6 +766,26 @@ class PregelLoop:
|
||||
if k in self.checkpoint["channel_versions"]:
|
||||
version = self.checkpoint["channel_versions"][k]
|
||||
self.checkpoint["versions_seen"][INTERRUPT][k] = version
|
||||
# When time-traveling (replaying from a specific checkpoint),
|
||||
# save a fork checkpoint so the replayed execution creates a
|
||||
# new branch. Without this, if the execution hits an interrupt
|
||||
# before after_tick() runs, no new checkpoint is created —
|
||||
# the parent's latest checkpoint remains the old one and
|
||||
# subsequent resumes load the wrong state.
|
||||
# Skip for update_state forks (source=update/fork) since they
|
||||
# already have their own fork checkpoint.
|
||||
if is_time_traveling and self.checkpoint_metadata.get("source") not in (
|
||||
"update",
|
||||
"fork",
|
||||
):
|
||||
# Clear old INTERRUPT writes from the loaded checkpoint.
|
||||
# The fork will have a new checkpoint_id which changes
|
||||
# task IDs — stale interrupt writes would accumulate and
|
||||
# confuse the multiple-interrupt check in future resumes.
|
||||
self.checkpoint_pending_writes = [
|
||||
w for w in self.checkpoint_pending_writes if w[1] != INTERRUPT
|
||||
]
|
||||
self._put_checkpoint({"source": "fork"})
|
||||
# produce values output
|
||||
self._emit(
|
||||
"values", map_output_values, self.output_keys, True, self.channels
|
||||
@@ -807,14 +828,28 @@ class PregelLoop:
|
||||
if not self.is_nested:
|
||||
# Pass the resolved before-bound checkpoint ID so subgraphs can
|
||||
# find their corresponding checkpoint without re-fetching the
|
||||
# parent. For forks (source=update), use the fork's parent
|
||||
# parent. For forks (source=update/fork), use the fork's parent
|
||||
# checkpoint ID since the fork was created after the subgraph's
|
||||
# checkpoints from the original execution.
|
||||
#
|
||||
# Only gate on is_time_traveling (not is_replaying). When the
|
||||
# client resumes with an explicit checkpoint_id that happens to
|
||||
# point at the current head (e.g. LangGraph Studio sending
|
||||
# `checkpoint: {checkpoint_id}` alongside Command(resume=...)),
|
||||
# is_replaying is True but is_time_traveling is False. In that
|
||||
# case subgraphs should load their latest checkpoint normally,
|
||||
# not go through ReplayState's before-bound lookup which would
|
||||
# miss subgraph checkpoints created during processing of the
|
||||
# current parent step.
|
||||
replay_state: ReplayState | None = None
|
||||
if self.is_replaying:
|
||||
if is_time_traveling:
|
||||
replay_checkpoint_id = self.checkpoint["id"]
|
||||
if (
|
||||
self.checkpoint_metadata.get("source") == "update"
|
||||
self.checkpoint_metadata.get("source")
|
||||
in (
|
||||
"update",
|
||||
"fork",
|
||||
)
|
||||
and self.prev_checkpoint_config
|
||||
):
|
||||
replay_checkpoint_id = self.prev_checkpoint_config[CONF].get(
|
||||
|
||||
@@ -14,7 +14,7 @@ from langchain_core.messages import BaseMessage
|
||||
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
|
||||
from pydantic import BaseModel
|
||||
|
||||
from langgraph._internal._constants import NS_END, NS_SEP
|
||||
from langgraph._internal._constants import NS_SEP
|
||||
from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
|
||||
from langgraph.pregel.protocol import StreamChunk
|
||||
from langgraph.types import Command
|
||||
@@ -24,11 +24,6 @@ try:
|
||||
except ImportError:
|
||||
_StreamingCallbackHandler = object # type: ignore
|
||||
|
||||
try:
|
||||
from langchain_core.tracers._streaming import _V2StreamingCallbackHandler
|
||||
except ImportError:
|
||||
_V2StreamingCallbackHandler = object # type: ignore
|
||||
|
||||
T = TypeVar("T")
|
||||
Meta = tuple[tuple[str, ...], dict[str, Any]]
|
||||
|
||||
@@ -137,23 +132,15 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
if metadata and (not tags or (TAG_NOSTREAM not in tags)):
|
||||
task_checkpoint_ns = cast(str, metadata["langgraph_checkpoint_ns"])
|
||||
checkpoint_ns = (
|
||||
f"{task_checkpoint_ns.rsplit(NS_END, 1)[0]}{NS_END}"
|
||||
if NS_END in task_checkpoint_ns
|
||||
else task_checkpoint_ns
|
||||
)
|
||||
ns = tuple(task_checkpoint_ns.split(NS_SEP))[:-1]
|
||||
ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))[
|
||||
:-1
|
||||
]
|
||||
if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
|
||||
return
|
||||
stream_metadata = dict(metadata)
|
||||
stream_metadata["langgraph_checkpoint_ns"] = checkpoint_ns
|
||||
# Preserve backwards-compatible streamed checkpoint metadata shape.
|
||||
stream_metadata["checkpoint_ns"] = checkpoint_ns
|
||||
if tags:
|
||||
if filtered_tags := [t for t in tags if not t.startswith("seq:step")]:
|
||||
stream_metadata["tags"] = filtered_tags
|
||||
self.metadata[run_id] = (ns, stream_metadata)
|
||||
metadata["tags"] = filtered_tags
|
||||
self.metadata[run_id] = (ns, metadata)
|
||||
|
||||
def on_llm_new_token(
|
||||
self,
|
||||
@@ -261,185 +248,3 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
self.metadata.pop(run_id, None)
|
||||
|
||||
|
||||
class StreamMessagesHandlerV2(StreamMessagesHandler, _V2StreamingCallbackHandler):
|
||||
"""v2 variant of `StreamMessagesHandler`.
|
||||
|
||||
Declaring `_V2StreamingCallbackHandler` as a base flips
|
||||
`BaseChatModel.invoke` to route through `_stream_chat_model_events`
|
||||
(firing `on_stream_event`) instead of `_stream` (firing
|
||||
`on_llm_new_token`). Inherits `on_stream_event` from the parent,
|
||||
which forwards protocol events onto the messages stream channel.
|
||||
|
||||
Pregel attaches this class instead of the v1 handler only when
|
||||
`GraphStreamer` opts in via the internal
|
||||
`CONFIG_KEY_STREAM_MESSAGES_V2` config key; direct
|
||||
`graph.stream(stream_mode="messages")` callers keep the v1
|
||||
AIMessageChunk shape.
|
||||
"""
|
||||
|
||||
def on_chat_model_start(
|
||||
self,
|
||||
serialized: dict[str, Any],
|
||||
messages: list[list[BaseMessage]],
|
||||
*,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
tags: list[str] | None = None,
|
||||
metadata: dict[str, Any] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
"""Record metadata with the FULL checkpoint namespace for v2.
|
||||
|
||||
v1's ``on_chat_model_start`` (inherited) slices the ns tuple
|
||||
with ``[:-1]`` to re-position chat model tokens onto the
|
||||
*containing pregel's* namespace — historically convenient for
|
||||
consumers of ``stream_mode="messages"`` who want "where did
|
||||
this node produce its output" rather than the chat-model's
|
||||
own task ns.
|
||||
|
||||
For the protocol-v2 wire shape that is wrong: the client
|
||||
subscribes the root feed at ``namespaces=[[]]`` with
|
||||
``depth=1``, and any message emitted at depth ``>=1`` that
|
||||
still carries the containing node's ns must appear at the
|
||||
*full* path from root so that depth filtering cleanly isolates
|
||||
subgraph chatter from the root conversation. JS's
|
||||
``StreamMessagesHandlerV2`` already does
|
||||
``metadata.langgraph_checkpoint_ns.split("|")`` (no slice); this
|
||||
override brings the Python v2 handler to the same shape.
|
||||
|
||||
Without this, a chat model invoked inside a nested subgraph
|
||||
(e.g. ``research -> researcher``, ``research`` being a root
|
||||
node that ``.ainvoke()``s a ``researcher`` subgraph) emits at
|
||||
``["research:<task>"]`` — a single level deep — which slips
|
||||
through the root-feed depth-1 filter and pollutes the main
|
||||
conversation with subgraph tokens. With this override we emit
|
||||
at ``["research:<task>", "researcher:<task>"]`` so the client
|
||||
routes those tokens to the subgraph card instead.
|
||||
"""
|
||||
if metadata and (not tags or (TAG_NOSTREAM not in tags)):
|
||||
task_checkpoint_ns = cast(str, metadata["langgraph_checkpoint_ns"])
|
||||
# Keep the trailing ``:<task_id>`` segment (unlike the v1
|
||||
# handler which strips it via ``[:-1]``). The client's
|
||||
# lifecycle events land on the same ns, so message deltas
|
||||
# now correlate 1:1 with a ``lifecycle: started`` event —
|
||||
# ``useMessages(stream, subgraph)`` picks them up without
|
||||
# needing to collapse sibling namespaces.
|
||||
ns = tuple(task_checkpoint_ns.split(NS_SEP))
|
||||
if not self.subgraphs and len(ns) > 1 and ns != self.parent_ns:
|
||||
return
|
||||
stream_metadata = dict(metadata)
|
||||
# Preserve the v1-shaped ``langgraph_checkpoint_ns`` (task
|
||||
# id stripped, trailing ``NS_END`` retained) so downstream
|
||||
# consumers reading checkpoint metadata off a streamed
|
||||
# message see the same shape they did pre-v2. Only the ns
|
||||
# tuple emitted on the wire changes.
|
||||
checkpoint_ns = (
|
||||
f"{task_checkpoint_ns.rsplit(NS_END, 1)[0]}{NS_END}"
|
||||
if NS_END in task_checkpoint_ns
|
||||
else task_checkpoint_ns
|
||||
)
|
||||
stream_metadata["langgraph_checkpoint_ns"] = checkpoint_ns
|
||||
stream_metadata["checkpoint_ns"] = checkpoint_ns
|
||||
if tags:
|
||||
if filtered_tags := [t for t in tags if not t.startswith("seq:step")]:
|
||||
stream_metadata["tags"] = filtered_tags
|
||||
self.metadata[run_id] = (ns, stream_metadata)
|
||||
|
||||
def on_chain_start(
|
||||
self,
|
||||
serialized: dict[str, Any],
|
||||
inputs: dict[str, Any],
|
||||
*,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
tags: list[str] | None = None,
|
||||
metadata: dict[str, Any] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
"""Record chain (node) metadata with the FULL checkpoint ns.
|
||||
|
||||
Mirror of :meth:`on_chat_model_start` for the node-start path,
|
||||
so messages returned by ``on_chain_end`` (``Command`` updates
|
||||
and plain state dict outputs) land at the same full-path ns as
|
||||
any chat-model deltas from within that node. See the
|
||||
:meth:`on_chat_model_start` docstring for why the v1 ``[:-1]``
|
||||
slice is dropped here.
|
||||
"""
|
||||
if (
|
||||
metadata
|
||||
and kwargs.get("name") == metadata.get("langgraph_node")
|
||||
and (not tags or TAG_HIDDEN not in tags)
|
||||
):
|
||||
ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))
|
||||
if not self.subgraphs and len(ns) > 1:
|
||||
return
|
||||
self.metadata[run_id] = (ns, metadata)
|
||||
for value in _state_values(inputs):
|
||||
if isinstance(value, BaseMessage):
|
||||
if value.id is not None:
|
||||
self.seen.add(value.id)
|
||||
elif isinstance(value, Sequence) and not isinstance(value, str):
|
||||
for item in value:
|
||||
if isinstance(item, BaseMessage):
|
||||
if item.id is not None:
|
||||
self.seen.add(item.id)
|
||||
|
||||
def on_llm_new_token(
|
||||
self,
|
||||
token: str,
|
||||
*,
|
||||
chunk: ChatGenerationChunk | None = None,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
tags: list[str] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
"""Intentional no-op — v1 chunks are not used on v2-flagged runs.
|
||||
|
||||
The v2 marker already steers `invoke` to the event generator, so
|
||||
`on_llm_new_token` should not fire under normal routing. This
|
||||
override stays a pass-through (no call to `super()`) to make
|
||||
the intent explicit and to guard against any caller (e.g. a
|
||||
node that calls `model.stream()` directly, which still fires
|
||||
the v1 callback) leaking AIMessageChunks onto a v2-flagged
|
||||
messages stream.
|
||||
"""
|
||||
# Intentionally empty: v2 handler does not forward v1 chunks.
|
||||
|
||||
def on_stream_event(
|
||||
self,
|
||||
event: dict[str, Any],
|
||||
*,
|
||||
run_id: UUID,
|
||||
parent_run_id: UUID | None = None,
|
||||
tags: list[str] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
"""Forward a protocol event from `stream_v2` as a messages stream part.
|
||||
|
||||
Fires once per `MessagesData` event (`message-start`, per-block
|
||||
`content-block-*`, `message-finish`). The transformer layer
|
||||
correlates events back to a single `ChatModelStream` via
|
||||
`metadata["run_id"]` — attached here so the v1
|
||||
`stream_mode="messages"` output (which emits
|
||||
`(AIMessageChunk, metadata)` via `on_llm_new_token`) keeps its
|
||||
original metadata shape.
|
||||
|
||||
Lives on the v2 handler rather than the v1 base: content-block
|
||||
events are a v2-only concept, and forwarding them only when the
|
||||
v2 handler is attached keeps the message channel's shape
|
||||
predictable for v1 callers.
|
||||
"""
|
||||
if meta := self.metadata.get(run_id):
|
||||
# Record message_id on message-start so on_chain_end's
|
||||
# dedupe skips the finalized AIMessage the node returns
|
||||
# (otherwise the messages projection double-counts: once
|
||||
# from streaming, once from the chain output).
|
||||
if event.get("event") == "message-start":
|
||||
msg_id = event.get("message_id")
|
||||
if msg_id:
|
||||
self.seen.add(msg_id)
|
||||
v2_meta = {**meta[1], "run_id": str(run_id)}
|
||||
self.stream((meta[0], "messages", (event, v2_meta)))
|
||||
|
||||
@@ -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)
|
||||
@@ -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,
|
||||
@@ -130,19 +129,14 @@ 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
|
||||
@@ -346,65 +340,6 @@ class NodeBuilder:
|
||||
)
|
||||
|
||||
|
||||
def _collect_stream_modes(mux: Any) -> list[StreamMode]:
|
||||
"""Return the union of `required_stream_modes` across registered transformers.
|
||||
|
||||
Transformers declare the stream modes they need to function, and
|
||||
`stream_v2` asks the graph for exactly that union — no hardcoded
|
||||
default set. If zero transformers are registered (or none declares
|
||||
a given mode), the graph does not stream events for that mode.
|
||||
"""
|
||||
modes: set[str] = set()
|
||||
for transformer in mux._transformers:
|
||||
modes.update(transformer.required_stream_modes)
|
||||
return cast("list[StreamMode]", list(modes))
|
||||
|
||||
|
||||
def _build_stream_factories(
|
||||
compile_time: Sequence[Callable[..., Any]],
|
||||
call_site: Sequence[Any] | None,
|
||||
) -> list[Callable[..., Any]]:
|
||||
"""Assemble the factory list handed to `StreamMux(factories=...)`.
|
||||
|
||||
Prepends the built-in `ValuesTransformer`, `MessagesTransformer`,
|
||||
and `SubgraphTransformer` factories, then appends the graph's
|
||||
compile-time `stream_transformers` followed by any call-site
|
||||
additions. Factories flow down into subgraph mini-muxes, so
|
||||
per-scope instances propagate automatically.
|
||||
"""
|
||||
from langgraph.stream.transformers import (
|
||||
MessagesTransformer,
|
||||
SubgraphTransformer,
|
||||
ToolLifecycleTransformer,
|
||||
ValuesTransformer,
|
||||
)
|
||||
|
||||
builtins: list[Callable[..., Any]] = [
|
||||
ValuesTransformer,
|
||||
ToolLifecycleTransformer,
|
||||
MessagesTransformer,
|
||||
SubgraphTransformer,
|
||||
]
|
||||
return [*builtins, *compile_time, *(call_site or ())]
|
||||
|
||||
|
||||
def _merge_v2_messages_flag(
|
||||
config: RunnableConfig | None,
|
||||
) -> RunnableConfig:
|
||||
"""Return a config with the v2 messages flag set in `configurable`.
|
||||
|
||||
Signals to pregel that `stream_mode="messages"` should attach
|
||||
`StreamMessagesHandlerV2` for this call so invoke-time model runs
|
||||
route through the v2 event generator and their protocol events
|
||||
reach the messages channel.
|
||||
"""
|
||||
merged: RunnableConfig = dict(config or {}) # type: ignore[assignment]
|
||||
configurable = dict(merged.get(CONF) or {})
|
||||
configurable[CONFIG_KEY_STREAM_MESSAGES_V2] = True
|
||||
merged[CONF] = configurable
|
||||
return merged
|
||||
|
||||
|
||||
class Pregel(
|
||||
PregelProtocol[StateT, ContextT, InputT, OutputT],
|
||||
Generic[StateT, ContextT, InputT, OutputT],
|
||||
@@ -736,7 +671,6 @@ class Pregel(
|
||||
config: RunnableConfig | None = None,
|
||||
trigger_to_nodes: Mapping[str, Sequence[str]] | None = None,
|
||||
name: str = "LangGraph",
|
||||
stream_transformers: Sequence[Callable[..., Any]] | None = None,
|
||||
**deprecated_kwargs: Unpack[DeprecatedKwargs],
|
||||
) -> None:
|
||||
if (
|
||||
@@ -783,9 +717,6 @@ class Pregel(
|
||||
self.config = config
|
||||
self.trigger_to_nodes = trigger_to_nodes or {}
|
||||
self.name = name
|
||||
self._stream_transformers: tuple[Callable[..., Any], ...] = tuple(
|
||||
stream_transformers or ()
|
||||
)
|
||||
self._serde_allowlist: set[tuple[str, ...]] | None = None
|
||||
if auto_validate:
|
||||
self.validate()
|
||||
@@ -876,15 +807,6 @@ class Pregel(
|
||||
|
||||
def copy(self, update: dict[str, Any] | None = None) -> Self:
|
||||
attrs = {k: v for k, v in self.__dict__.items() if k != "__orig_class__"}
|
||||
# ``__init__`` accepts ``stream_transformers`` (public parameter) but
|
||||
# the attribute is stored as ``_stream_transformers`` (private). Map
|
||||
# the private key back onto the public kwarg so compile-time
|
||||
# transformers survive ``copy()`` / ``with_config()``. Without this,
|
||||
# ``_stream_transformers`` gets captured by ``**deprecated_kwargs``
|
||||
# and the resulting instance silently has an empty transformer
|
||||
# pipeline.
|
||||
if "_stream_transformers" in attrs:
|
||||
attrs["stream_transformers"] = attrs.pop("_stream_transformers")
|
||||
attrs.update(update or {})
|
||||
return self.__class__(**attrs)
|
||||
|
||||
@@ -2704,34 +2626,14 @@ 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:
|
||||
|
||||
@@ -3101,34 +3003,14 @@ 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(
|
||||
@@ -3355,106 +3237,6 @@ class Pregel(
|
||||
await asyncio.shield(run_manager.on_chain_error(e))
|
||||
raise
|
||||
|
||||
def stream_v2(
|
||||
self,
|
||||
input: InputT | Command | None,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
transformers: Sequence[Any] | None = None,
|
||||
stream_modes: Sequence[StreamMode] | None = None,
|
||||
output_keys: str | Sequence[str] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
"""Start a sync v2 streaming run driven by transformer projections.
|
||||
|
||||
Builds a `StreamMux` from the built-in `ValuesTransformer` /
|
||||
`MessagesTransformer`, this graph's compile-time
|
||||
`stream_transformers`, and any additional `transformers=`
|
||||
supplied at the call site. Returns a `GraphRunStream` that the
|
||||
caller drives by iterating any projection — no background
|
||||
thread.
|
||||
|
||||
Args:
|
||||
input: Graph input.
|
||||
config: Optional runnable config forwarded to the graph.
|
||||
interrupt_before: Nodes to interrupt before, if any.
|
||||
interrupt_after: Nodes to interrupt after, if any.
|
||||
transformers: Extra transformer instances appended after
|
||||
compile-time `stream_transformers`.
|
||||
|
||||
Returns:
|
||||
A `GraphRunStream` the caller iterates to drive the run.
|
||||
"""
|
||||
from langgraph.stream._mux import StreamMux
|
||||
from langgraph.stream.run_stream import GraphRunStream
|
||||
|
||||
factories = _build_stream_factories(self._stream_transformers, transformers)
|
||||
mux = StreamMux(factories=factories, is_async=False)
|
||||
requested_stream_modes = set(_collect_stream_modes(mux))
|
||||
requested_stream_modes.update(stream_modes or ())
|
||||
graph_iter = iter(
|
||||
self.stream(
|
||||
input,
|
||||
_merge_v2_messages_flag(config),
|
||||
stream_mode=list(requested_stream_modes),
|
||||
subgraphs=True,
|
||||
version="v2",
|
||||
output_keys=output_keys,
|
||||
interrupt_before=interrupt_before,
|
||||
interrupt_after=interrupt_after,
|
||||
**kwargs,
|
||||
)
|
||||
)
|
||||
return GraphRunStream(graph_iter, mux)
|
||||
|
||||
async def astream_v2(
|
||||
self,
|
||||
input: InputT | Command | None,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
transformers: Sequence[Any] | None = None,
|
||||
stream_modes: Sequence[StreamMode] | None = None,
|
||||
output_keys: str | Sequence[str] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> Any:
|
||||
"""Async counterpart to `stream_v2`.
|
||||
|
||||
Returns an `AsyncGraphRunStream` whose projections can be awaited
|
||||
concurrently; each subscribed cursor drives the pump when its
|
||||
buffer is empty.
|
||||
|
||||
Args:
|
||||
input: Graph input.
|
||||
config: Optional runnable config forwarded to the graph.
|
||||
interrupt_before: Nodes to interrupt before, if any.
|
||||
interrupt_after: Nodes to interrupt after, if any.
|
||||
transformers: Extra transformer instances appended after
|
||||
compile-time `stream_transformers`.
|
||||
"""
|
||||
from langgraph.stream._mux import StreamMux
|
||||
from langgraph.stream.run_stream import AsyncGraphRunStream
|
||||
|
||||
factories = _build_stream_factories(self._stream_transformers, transformers)
|
||||
mux = StreamMux(factories=factories, is_async=True)
|
||||
requested_stream_modes = set(_collect_stream_modes(mux))
|
||||
requested_stream_modes.update(stream_modes or ())
|
||||
graph_aiter = self.astream(
|
||||
input,
|
||||
_merge_v2_messages_flag(config),
|
||||
stream_mode=list(requested_stream_modes),
|
||||
subgraphs=True,
|
||||
version="v2",
|
||||
output_keys=output_keys,
|
||||
interrupt_before=interrupt_before,
|
||||
interrupt_after=interrupt_after,
|
||||
**kwargs,
|
||||
).__aiter__()
|
||||
return AsyncGraphRunStream(graph_aiter, mux)
|
||||
|
||||
@overload
|
||||
def invoke(
|
||||
self,
|
||||
|
||||
@@ -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",
|
||||
]
|
||||
@@ -1,71 +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 _is_v2_messages_payload(data: Any) -> bool:
|
||||
return isinstance(data, dict) and isinstance(data.get("event"), str)
|
||||
|
||||
|
||||
def _normalize_messages_data(data: dict[str, Any]) -> dict[str, Any]:
|
||||
"""Normalize Python Core message fields to the protocol wire shape."""
|
||||
normalized = {**data}
|
||||
if (
|
||||
normalized["event"] == "message-start"
|
||||
and "id" not in normalized
|
||||
and isinstance(normalized.get("message_id"), str)
|
||||
):
|
||||
normalized["id"] = normalized["message_id"]
|
||||
if (
|
||||
normalized["event"]
|
||||
in ("content-block-start", "content-block-delta", "content-block-finish")
|
||||
and "content" not in normalized
|
||||
and isinstance(normalized.get("content_block"), dict)
|
||||
):
|
||||
normalized["content"] = normalized["content_block"]
|
||||
normalized.pop("message_id", None)
|
||||
normalized.pop("content_block", None)
|
||||
return normalized
|
||||
|
||||
|
||||
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)
|
||||
data = part_dict["data"]
|
||||
params: _ProtocolEventParams = {
|
||||
"namespace": list(part_dict["ns"]),
|
||||
"timestamp": int(time.time() * 1000),
|
||||
"data": data,
|
||||
}
|
||||
if (
|
||||
part_dict["type"] == "messages"
|
||||
and isinstance(data, tuple)
|
||||
and len(data) == 2
|
||||
and _is_v2_messages_payload(data[0])
|
||||
and isinstance(data[1], dict)
|
||||
):
|
||||
payload, metadata = data
|
||||
params["data"] = _normalize_messages_data(payload)
|
||||
if isinstance(metadata.get("langgraph_node"), str):
|
||||
params["node"] = metadata["langgraph_node"]
|
||||
if isinstance(metadata.get("run_id"), str):
|
||||
params["run_id"] = metadata["run_id"]
|
||||
if "interrupts" in part_dict:
|
||||
params["interrupts"] = part_dict["interrupts"]
|
||||
return {
|
||||
"type": "event",
|
||||
"method": part_dict["type"],
|
||||
"params": params,
|
||||
}
|
||||
@@ -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))
|
||||
@@ -1,497 +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 emit(self, event: ProtocolEvent) -> None:
|
||||
"""Append a protocol event directly to the main log.
|
||||
|
||||
Built-in transformers use this for protocol repair events that
|
||||
must appear before the source event they are processing. Direct
|
||||
emission intentionally bypasses the transformer pipeline, but
|
||||
still lets this mux remain the only local sequencing authority.
|
||||
"""
|
||||
self._seq += 1
|
||||
event["seq"] = self._seq
|
||||
self._events.push(event)
|
||||
|
||||
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.
|
||||
"""
|
||||
event: ProtocolEvent = {
|
||||
"type": "event",
|
||||
"method": f"custom:{channel_name}",
|
||||
"params": {
|
||||
"namespace": [],
|
||||
"timestamp": int(time.time() * 1000),
|
||||
"data": item,
|
||||
},
|
||||
}
|
||||
self.emit(event)
|
||||
@@ -1,312 +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
|
||||
node: NotRequired[str]
|
||||
run_id: NotRequired[str]
|
||||
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"]
|
||||
event_id: 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)
|
||||
@@ -1,750 +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,
|
||||
LifecycleCause,
|
||||
LifecycleData,
|
||||
MessagesData,
|
||||
)
|
||||
|
||||
from langgraph.errors import GraphInterrupt
|
||||
from langgraph.stream._event_log import EventLog
|
||||
from langgraph.stream._types import ProtocolEvent, StreamTransformer
|
||||
from langgraph.stream.run_stream import BaseRunStream
|
||||
|
||||
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"}
|
||||
)
|
||||
|
||||
|
||||
def _is_record(value: Any) -> bool:
|
||||
return isinstance(value, dict)
|
||||
|
||||
|
||||
def _to_chat_model_stream_event(event: MessagesData) -> MessagesData:
|
||||
"""Convert wire-shaped message fields to ChatModelStream's internal shape."""
|
||||
event_type = event.get("event")
|
||||
converted: dict[str, Any] = dict(event)
|
||||
if (
|
||||
event_type == "message-start"
|
||||
and "message_id" not in converted
|
||||
and isinstance(converted.get("id"), str)
|
||||
):
|
||||
converted["message_id"] = converted["id"]
|
||||
if (
|
||||
event_type in ("content-block-start", "content-block-delta", "content-block-finish")
|
||||
and "content_block" not in converted
|
||||
and isinstance(converted.get("content"), dict)
|
||||
):
|
||||
converted["content_block"] = converted["content"]
|
||||
return cast("MessagesData", converted)
|
||||
|
||||
|
||||
def _message_event_id(event: MessagesData) -> str | None:
|
||||
raw_id = event.get("id") or event.get("message_id")
|
||||
return str(raw_id) if raw_id is not None else None
|
||||
|
||||
|
||||
def _content_block_start_skeleton(content: Any) -> dict[str, Any] | None:
|
||||
"""Return a minimal content-block-start payload for a delta/finish block."""
|
||||
if not _is_record(content) or not isinstance(content.get("type"), str):
|
||||
return None
|
||||
|
||||
block_type = content["type"]
|
||||
skeleton: dict[str, Any] = {"type": block_type}
|
||||
if block_type == "text":
|
||||
skeleton["text"] = ""
|
||||
elif block_type == "reasoning":
|
||||
skeleton["reasoning"] = ""
|
||||
elif block_type in ("tool_call", "tool_call_chunk"):
|
||||
skeleton["type"] = "tool_call_chunk"
|
||||
if isinstance(content.get("id"), str):
|
||||
skeleton["id"] = content["id"]
|
||||
if isinstance(content.get("name"), str):
|
||||
skeleton["name"] = content["name"]
|
||||
skeleton["args"] = ""
|
||||
elif block_type in ("server_tool_call", "server_tool_call_chunk"):
|
||||
skeleton["type"] = "server_tool_call_chunk"
|
||||
if isinstance(content.get("id"), str):
|
||||
skeleton["id"] = content["id"]
|
||||
if isinstance(content.get("name"), str):
|
||||
skeleton["name"] = content["name"]
|
||||
skeleton["args"] = ""
|
||||
return skeleton
|
||||
|
||||
|
||||
def _copy_event(
|
||||
source: ProtocolEvent,
|
||||
*,
|
||||
method: str,
|
||||
namespace: list[str],
|
||||
data: Any,
|
||||
) -> ProtocolEvent:
|
||||
params = {**source["params"], "namespace": namespace, "data": data}
|
||||
return {"type": "event", "method": method, "params": params}
|
||||
|
||||
|
||||
def _message_repair_key(event: ProtocolEvent, run_id: str) -> str:
|
||||
namespace_key = "\x1f".join(event["params"]["namespace"])
|
||||
return f"{namespace_key}\x1e{run_id}"
|
||||
|
||||
|
||||
def _extract_tool_calls_from_values(data: Any) -> dict[str, dict[str, Any]]:
|
||||
if not _is_record(data):
|
||||
return {}
|
||||
messages = data.get("messages")
|
||||
if not isinstance(messages, list):
|
||||
return {}
|
||||
known: dict[str, dict[str, Any]] = {}
|
||||
for message in messages:
|
||||
if not _is_record(message):
|
||||
continue
|
||||
tool_calls = message.get("tool_calls")
|
||||
if not isinstance(tool_calls, list):
|
||||
continue
|
||||
for tool_call in tool_calls:
|
||||
if not _is_record(tool_call):
|
||||
continue
|
||||
tool_call_id = tool_call.get("id")
|
||||
if not isinstance(tool_call_id, str):
|
||||
continue
|
||||
name = tool_call.get("name")
|
||||
args = tool_call.get("args")
|
||||
known[tool_call_id] = {
|
||||
"tool_name": name if isinstance(name, str) else "",
|
||||
"input": args if _is_record(args) else {},
|
||||
}
|
||||
return known
|
||||
|
||||
|
||||
class ValuesTransformer(StreamTransformer):
|
||||
"""Capture values events as a drainable stream of state snapshots.
|
||||
|
||||
Keeps `_latest` / `_interrupted` / `_interrupts` as scalar state
|
||||
regardless of whether the log has a subscriber — so `run.output()`
|
||||
and `run.interrupted` work without forcing the caller to iterate
|
||||
`run.values`. Log pushes are silent no-ops when unsubscribed.
|
||||
|
||||
Native transformer — projection keys are exposed as direct
|
||||
attributes on the run stream (e.g. `run.values`).
|
||||
|
||||
`scope` (inherited from `StreamTransformer`) is the namespace the
|
||||
transformer captures values for. `()` matches the root graph;
|
||||
subgraph mini-muxes pass their subgraph's namespace, so each
|
||||
instance sees only its own level.
|
||||
"""
|
||||
|
||||
_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 ToolLifecycleTransformer(StreamTransformer):
|
||||
"""Repair tool-start events needed for deterministic subagent discovery.
|
||||
|
||||
Some subagent frameworks expose a tool-caused subgraph lifecycle before
|
||||
a LangChain tool callback has emitted the matching `tool-started`
|
||||
frame. Core can infer the missing start from the latest values snapshot
|
||||
(`messages[*].tool_calls`) and emit it before the lifecycle event leaves
|
||||
the mux, keeping remote clients from guessing from values snapshots.
|
||||
"""
|
||||
|
||||
scope_exact = False
|
||||
required_stream_modes = ("values", "tools", "lifecycle")
|
||||
|
||||
def __init__(self, scope: tuple[str, ...] = ()) -> None:
|
||||
super().__init__(scope)
|
||||
self._known_tool_calls: dict[str, dict[str, Any]] = {}
|
||||
self._emitted_tool_starts: set[str] = set()
|
||||
self._mux: StreamMux | None = None
|
||||
|
||||
def init(self) -> dict[str, Any]:
|
||||
return {}
|
||||
|
||||
def _on_register(self, mux: StreamMux) -> None:
|
||||
self._mux = mux
|
||||
|
||||
def process(self, event: ProtocolEvent) -> bool:
|
||||
method = event["method"]
|
||||
data = event["params"]["data"]
|
||||
if method == "values":
|
||||
self._known_tool_calls.update(_extract_tool_calls_from_values(data))
|
||||
return True
|
||||
if method == "tools" and _is_record(data):
|
||||
if (
|
||||
data.get("event") == "tool-started"
|
||||
and isinstance(data.get("tool_call_id"), str)
|
||||
):
|
||||
tool_call_id = cast("str", data["tool_call_id"])
|
||||
if tool_call_id in self._emitted_tool_starts:
|
||||
return False
|
||||
self._emitted_tool_starts.add(tool_call_id)
|
||||
return True
|
||||
if method == "lifecycle":
|
||||
self._emit_missing_tool_started(event)
|
||||
return True
|
||||
|
||||
def _emit_missing_tool_started(self, event: ProtocolEvent) -> None:
|
||||
if self._mux is None:
|
||||
return
|
||||
data = event["params"]["data"]
|
||||
if not _is_record(data) or data.get("event") != "started":
|
||||
return
|
||||
cause = data.get("cause")
|
||||
if not _is_record(cause) or cause.get("type") != "toolCall":
|
||||
return
|
||||
tool_call_id = cause.get("tool_call_id")
|
||||
if not isinstance(tool_call_id, str):
|
||||
return
|
||||
if tool_call_id in self._emitted_tool_starts:
|
||||
return
|
||||
known = self._known_tool_calls.get(tool_call_id)
|
||||
if known is None:
|
||||
return
|
||||
|
||||
self._emitted_tool_starts.add(tool_call_id)
|
||||
namespace = event["params"]["namespace"]
|
||||
self._mux.emit(
|
||||
_copy_event(
|
||||
event,
|
||||
method="tools",
|
||||
namespace=namespace[:-1],
|
||||
data={
|
||||
"event": "tool-started",
|
||||
"tool_call_id": tool_call_id,
|
||||
"tool_name": known["tool_name"],
|
||||
"input": known["input"],
|
||||
},
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
class MessagesTransformer(StreamTransformer):
|
||||
"""Capture messages events as ChatModelStream objects.
|
||||
|
||||
The messages projection yields one `ChatModelStream` (or
|
||||
`AsyncChatModelStream`) per LLM call. Consumers iterate
|
||||
`run.messages` to get stream handles, then use each handle's typed
|
||||
projections (`.text`, `.reasoning`, `.tool_calls`, `.usage`,
|
||||
`.output`) for per-message content.
|
||||
|
||||
Two input shapes are handled (via `params["data"] = (payload,
|
||||
metadata)` from `StreamMessagesHandler`):
|
||||
|
||||
1. Protocol event (dict with `"event"` key) — emitted by
|
||||
`stream_v2()` / `astream_v2()` via the `on_stream_event`
|
||||
callback. Routed to an existing `ChatModelStream` by
|
||||
`metadata["run_id"]`. A `message-start` event creates a new
|
||||
stream; `message-finish` closes it.
|
||||
2. Whole `AIMessage` — emitted from `on_chain_end` when a node
|
||||
returns a finalized message. Replayed as a synthetic protocol
|
||||
event lifecycle via `message_to_events`, then the
|
||||
already-complete stream is pushed to the log.
|
||||
|
||||
V1 `AIMessageChunk` tuples (from `on_llm_new_token`) are not
|
||||
streamed into this projection: chat models that want to populate
|
||||
`run.messages` with content-block streaming must use
|
||||
`stream_v2()` / `astream_v2()`. Models called via the legacy
|
||||
`stream()` method still surface their final `AIMessage` via
|
||||
`on_chain_end` when a node returns it as state.
|
||||
|
||||
`scope` (inherited from `StreamTransformer`) is the namespace the
|
||||
transformer captures messages for. `()` matches the root graph;
|
||||
subgraph mini-muxes pass their subgraph's namespace, so each
|
||||
instance sees only its own level.
|
||||
|
||||
Native transformer — the `messages` projection is exposed as a
|
||||
direct attribute on the run stream.
|
||||
|
||||
`scope_exact = False`: matches events at the transformer's own
|
||||
namespace **or** exactly one segment deeper (the chat-model /
|
||||
node's own task ns). Mirrors JS's root-feed filter
|
||||
(`namespaces=[[]], depth=1`) — root accepts depth-0 events plus
|
||||
its own nodes' depth-1 tokens; subgraph mini-muxes accept their
|
||||
own scope plus their internal nodes' tokens. Events deeper than
|
||||
scope + 1 are dropped (the enclosing `SubgraphTransformer` has
|
||||
already forwarded them to the matching child mini-mux).
|
||||
"""
|
||||
|
||||
_native = True
|
||||
scope_exact = False
|
||||
required_stream_modes = ("messages",)
|
||||
|
||||
def __init__(self, scope: tuple[str, ...] = ()) -> None:
|
||||
super().__init__(scope)
|
||||
self._log: EventLog[ChatModelStream] = EventLog()
|
||||
# Correlate protocol events back to a ChatModelStream by run_id
|
||||
# (attached to the event's metadata by StreamMessagesHandler).
|
||||
self._by_run: dict[str, ChatModelStream] = {}
|
||||
self._started_blocks: dict[str, set[int]] = {}
|
||||
self._mux: StreamMux | None = None
|
||||
self._pump_fn: Callable[[], bool] | None = None
|
||||
self._apump_fn: Callable[[], Awaitable[bool]] | None = None
|
||||
|
||||
def init(self) -> dict[str, Any]:
|
||||
return {"messages": self._log}
|
||||
|
||||
def _on_register(self, mux: StreamMux) -> None:
|
||||
self._mux = mux
|
||||
|
||||
def _bind_pump(self, fn: Callable[[], bool]) -> None:
|
||||
"""Wire the sync pull callback. Called by GraphRunStream._wire_request_more."""
|
||||
self._pump_fn = fn
|
||||
|
||||
def _bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
|
||||
"""Wire the async pull callback.
|
||||
|
||||
Called by `AsyncGraphRunStream._wire_arequest_more` so each
|
||||
`AsyncChatModelStream` this transformer creates can drive the
|
||||
shared graph pump from its projection cursors.
|
||||
"""
|
||||
self._apump_fn = fn
|
||||
|
||||
def _make_stream(
|
||||
self,
|
||||
*,
|
||||
namespace: list[str],
|
||||
node: str | None,
|
||||
message_id: str | None,
|
||||
) -> ChatModelStream:
|
||||
"""Create a ChatModelStream (sync) or AsyncChatModelStream (async).
|
||||
|
||||
Wires whichever pump is bound. Prefers the async pump so nested
|
||||
iteration under `AsyncGraphRunStream` drives the graph forward
|
||||
without a background task. The unwired fallback (no pump bound)
|
||||
is used by unit tests that dispatch events manually.
|
||||
"""
|
||||
if self._apump_fn is not None:
|
||||
astream = AsyncChatModelStream(
|
||||
namespace=namespace,
|
||||
node=node,
|
||||
message_id=message_id,
|
||||
)
|
||||
astream.set_arequest_more(self._apump_fn)
|
||||
return astream
|
||||
if self._pump_fn is not None:
|
||||
stream: ChatModelStream = ChatModelStream(
|
||||
namespace=namespace,
|
||||
node=node,
|
||||
message_id=message_id,
|
||||
)
|
||||
stream.set_request_more(self._pump_fn)
|
||||
return stream
|
||||
return AsyncChatModelStream(
|
||||
namespace=namespace,
|
||||
node=node,
|
||||
message_id=message_id,
|
||||
)
|
||||
|
||||
def process(self, event: ProtocolEvent) -> bool:
|
||||
if event["method"] != "messages":
|
||||
return True
|
||||
params = event["params"]
|
||||
# Accept events at our scope or exactly one segment deeper
|
||||
# (the chat-model / node's own task ns). Deeper events belong
|
||||
# to a subgraph and are routed by `SubgraphTransformer`.
|
||||
ns = tuple(params["namespace"])
|
||||
depth = len(self.scope)
|
||||
if ns[:depth] != self.scope:
|
||||
return True
|
||||
|
||||
raw_data = params["data"]
|
||||
metadata: dict[str, Any] = {}
|
||||
if isinstance(raw_data, tuple) and len(raw_data) == 2:
|
||||
payload, raw_metadata = raw_data
|
||||
metadata = raw_metadata if isinstance(raw_metadata, dict) else {}
|
||||
else:
|
||||
payload = raw_data
|
||||
node = params.get("node")
|
||||
if not isinstance(node, str):
|
||||
node = metadata.get("langgraph_node")
|
||||
if not isinstance(node, str):
|
||||
node = None
|
||||
raw_run_id = params.get("run_id", metadata.get("run_id"))
|
||||
run_id = str(raw_run_id) if raw_run_id is not None else ""
|
||||
|
||||
if isinstance(payload, dict) and "event" in payload:
|
||||
self._repair_content_block_lifecycle(
|
||||
event, cast("MessagesData", payload), run_id=run_id
|
||||
)
|
||||
if len(ns) > depth + 1:
|
||||
return True
|
||||
self._route_protocol_event(
|
||||
cast("MessagesData", payload), run_id=run_id, node=node
|
||||
)
|
||||
elif isinstance(payload, BaseMessage) and not isinstance(
|
||||
payload, AIMessageChunk
|
||||
):
|
||||
self._route_whole_message(payload, node=node)
|
||||
# Legacy AIMessageChunk tuples (from on_llm_new_token) are ignored;
|
||||
# v1 streaming callers must switch to stream_v2() to populate this
|
||||
# projection.
|
||||
|
||||
return True
|
||||
|
||||
def _route_protocol_event(
|
||||
self,
|
||||
event: MessagesData,
|
||||
*,
|
||||
run_id: str,
|
||||
node: str | None,
|
||||
) -> None:
|
||||
stream_event = _to_chat_model_stream_event(event)
|
||||
event_type = event.get("event")
|
||||
if event_type == "message-start":
|
||||
message_id = _message_event_id(event)
|
||||
stream = self._make_stream(
|
||||
namespace=list(self.scope),
|
||||
node=node,
|
||||
message_id=message_id,
|
||||
)
|
||||
self._by_run[run_id or message_id or ""] = stream
|
||||
self._log.push(stream)
|
||||
stream.dispatch(stream_event)
|
||||
elif run_id in self._by_run:
|
||||
stream = self._by_run[run_id]
|
||||
stream.dispatch(stream_event)
|
||||
if event_type == "message-finish":
|
||||
del self._by_run[run_id]
|
||||
|
||||
def _repair_content_block_lifecycle(
|
||||
self,
|
||||
source: ProtocolEvent,
|
||||
event: MessagesData,
|
||||
*,
|
||||
run_id: str,
|
||||
) -> None:
|
||||
if self._mux is None:
|
||||
return
|
||||
event_type = event.get("event")
|
||||
key = _message_repair_key(source, run_id)
|
||||
if event_type == "message-start":
|
||||
self._started_blocks[key] = set()
|
||||
return
|
||||
if event_type == "content-block-start":
|
||||
index = event.get("index")
|
||||
if isinstance(index, int):
|
||||
self._started_blocks.setdefault(key, set()).add(index)
|
||||
return
|
||||
if event_type in ("content-block-delta", "content-block-finish"):
|
||||
index = event.get("index")
|
||||
if not isinstance(index, int):
|
||||
return
|
||||
started = self._started_blocks.setdefault(key, set())
|
||||
if index in started:
|
||||
return
|
||||
skeleton = _content_block_start_skeleton(event.get("content"))
|
||||
if skeleton is None:
|
||||
return
|
||||
started.add(index)
|
||||
self._mux.emit(
|
||||
_copy_event(
|
||||
source,
|
||||
method="messages",
|
||||
namespace=list(source["params"]["namespace"]),
|
||||
data={
|
||||
"event": "content-block-start",
|
||||
"index": index,
|
||||
"content": skeleton,
|
||||
},
|
||||
)
|
||||
)
|
||||
elif event_type == "message-finish":
|
||||
self._started_blocks.pop(key, None)
|
||||
|
||||
def _route_whole_message(self, message: BaseMessage, *, node: str | None) -> None:
|
||||
stream = self._make_stream(
|
||||
namespace=list(self.scope),
|
||||
node=node,
|
||||
message_id=message.id,
|
||||
)
|
||||
for evt in message_to_events(message, message_id=message.id):
|
||||
stream.dispatch(evt)
|
||||
self._log.push(stream)
|
||||
|
||||
def finalize(self) -> None:
|
||||
"""Clear any routing state — streams close themselves via `message-finish`."""
|
||||
self._by_run.clear()
|
||||
self._started_blocks.clear()
|
||||
|
||||
def fail(self, err: BaseException) -> None:
|
||||
"""Propagate run error to any streams still open when the graph fails."""
|
||||
for stream in list(self._by_run.values()):
|
||||
stream.fail(err)
|
||||
self._by_run.clear()
|
||||
self._started_blocks.clear()
|
||||
|
||||
|
||||
class SubgraphRunStream(BaseRunStream):
|
||||
"""Scoped view of a single nested subgraph execution.
|
||||
|
||||
Yielded on `run.subgraphs` (or `parent.subgraphs` for grandchildren)
|
||||
when a nested `Pregel` spawns. Wraps a mini-`StreamMux` built with
|
||||
the same transformer factories as the root mux, so `.values`,
|
||||
`.messages`, `.subgraphs` are populated by the standard
|
||||
transformers scoped to this handle's namespace — no duplicated
|
||||
routing logic. The mini-mux borrows the root's pump via
|
||||
`make_child`'s pump inheritance, so any cursor on a subagent
|
||||
projection drives the whole run forward.
|
||||
|
||||
Lifecycle fields update in place as events arrive:
|
||||
|
||||
- `path`: the namespace tuple — stable for the life of the handle.
|
||||
- `graph_name` / `cause`: set once from the `started` payload.
|
||||
`cause` is populated by product-specific stream transformers
|
||||
(see `LifecycleCause` in the protocol definition); pregel itself
|
||||
emits no `cause`, so it may be `None` for subgraphs not covered
|
||||
by a product transformer.
|
||||
- `status`: advances `started` → `running` → `completed` /
|
||||
`failed` / `interrupted`.
|
||||
- `error` / `checkpoint`: set on the terminal event when present.
|
||||
|
||||
`.output` is a snapshot of the latest values seen at this
|
||||
namespace — it doesn't drive the pump (unlike root's
|
||||
`GraphRunStream.output`), because advancing a subgraph to
|
||||
completion is only meaningful as part of advancing the whole run.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
path: tuple[str, ...],
|
||||
mux: StreamMux,
|
||||
*,
|
||||
graph_name: str | None = None,
|
||||
cause: LifecycleCause | None = None,
|
||||
) -> None:
|
||||
super().__init__(mux)
|
||||
self.path: tuple[str, ...] = path
|
||||
self.graph_name: str | None = graph_name
|
||||
self.cause: LifecycleCause | None = cause
|
||||
self.status: SubgraphStatus = "started"
|
||||
self.error: str | None = None
|
||||
self.checkpoint: CheckpointRef | None = None
|
||||
|
||||
@property
|
||||
def output(self) -> dict[str, Any] | None:
|
||||
"""Latest values snapshot at this namespace, or `None`.
|
||||
|
||||
Snapshot-only — iterating other projections or the root's
|
||||
`.output` is what drives the pump.
|
||||
"""
|
||||
values_t = self._mux.transformer_by_key("values")
|
||||
if isinstance(values_t, ValuesTransformer):
|
||||
return values_t._latest
|
||||
return None
|
||||
|
||||
|
||||
class SubgraphTransformer(StreamTransformer):
|
||||
"""Discover subgraphs and route events into per-subgraph mini-muxes.
|
||||
|
||||
Thin state-machine + dispatcher. At its own `scope` (inherited
|
||||
from `StreamTransformer`, determined by the enclosing mux), it
|
||||
watches for `lifecycle` events at exactly one level deeper to
|
||||
discover direct children. Each discovered child gets its own
|
||||
`SubgraphRunStream` backed by a mini-`StreamMux` — built via
|
||||
`parent_mux.make_child(path)`, so the same factory list produces
|
||||
fresh transformer instances at the child's scope.
|
||||
|
||||
Every incoming event that falls under one of the direct children
|
||||
(ns starts with a child's `path`) is forwarded into that child's
|
||||
mini-mux via `push`. The standard transformers in that mini-mux
|
||||
(`ValuesTransformer`, `MessagesTransformer`, and another
|
||||
`SubgraphTransformer` for grandchildren) handle the rest. No
|
||||
duplicated routing or assembly logic.
|
||||
|
||||
Lifecycle state for each handle (running / completed / failed /
|
||||
interrupted) is updated in place as events fire. On terminal
|
||||
events, the handle's mini-mux is closed so any subscribed cursors
|
||||
unblock. `finalize` / `fail` handle dangling handles left mid-run.
|
||||
|
||||
Native transformer — `subgraphs` exposes the direct-children log.
|
||||
|
||||
`scope_exact = False`: this transformer sees events at any
|
||||
namespace, because it forwards out-of-scope events to the matching
|
||||
direct-child mini-mux.
|
||||
"""
|
||||
|
||||
_native = True
|
||||
scope_exact = False
|
||||
required_stream_modes = ("lifecycle",)
|
||||
|
||||
def __init__(self, scope: tuple[str, ...] = ()) -> None:
|
||||
super().__init__(scope)
|
||||
self._root_log: EventLog[SubgraphRunStream] = EventLog()
|
||||
# Direct children only (namespace = scope + one segment).
|
||||
self._by_ns: dict[tuple[str, ...], SubgraphRunStream] = {}
|
||||
self._mux: StreamMux | None = None
|
||||
|
||||
def init(self) -> dict[str, Any]:
|
||||
return {"subgraphs": self._root_log}
|
||||
|
||||
def _on_register(self, mux: StreamMux) -> None:
|
||||
"""Capture the enclosing mux so we can build child mini-muxes."""
|
||||
self._mux = mux
|
||||
|
||||
def process(self, event: ProtocolEvent) -> bool:
|
||||
ns = tuple(event["params"]["namespace"])
|
||||
method = event["method"]
|
||||
depth = len(self.scope)
|
||||
|
||||
# 1. On `started` for a direct child (ns depth = mine + 1 and
|
||||
# ns prefix matches mine), register the handle.
|
||||
if method == "lifecycle" and len(ns) == depth + 1 and ns[:-1] == self.scope:
|
||||
data = cast(LifecycleData, event["params"]["data"])
|
||||
if data.get("event") == "started":
|
||||
self._on_started(ns, data)
|
||||
|
||||
# 2. Forward the event to the matching direct-child mini-mux
|
||||
# before the status-change step below so that terminal events
|
||||
# reach the child's log and grandchild transformers *before*
|
||||
# the child's mini-mux is closed. Prefix-match: ns must start
|
||||
# with some child's path.
|
||||
direct_child_ns = ns[: depth + 1] if len(ns) > depth else None
|
||||
if direct_child_ns is not None and direct_child_ns in self._by_ns:
|
||||
self._by_ns[direct_child_ns]._mux.push(event)
|
||||
|
||||
# 3. Status change for a direct child (ns = child's path, method
|
||||
# = lifecycle). Update handle fields, close mini-mux on
|
||||
# terminal.
|
||||
if (
|
||||
method == "lifecycle"
|
||||
and ns in self._by_ns
|
||||
and len(ns) == depth + 1
|
||||
and ns[:-1] == self.scope
|
||||
):
|
||||
data = cast(LifecycleData, event["params"]["data"])
|
||||
event_type = data.get("event")
|
||||
if event_type in ("running", "completed", "failed", "interrupted"):
|
||||
self._on_status_change(ns, event_type, data)
|
||||
|
||||
return True
|
||||
|
||||
def _on_started(self, ns: tuple[str, ...], data: LifecycleData) -> None:
|
||||
if ns in self._by_ns:
|
||||
# Duplicate started — ignore.
|
||||
return
|
||||
# `_on_register` is called by the mux during registration, which
|
||||
# happens before any event can be dispatched — so this should
|
||||
# always be set by the time we process an event.
|
||||
assert self._mux is not None, (
|
||||
"SubgraphTransformer processed an event before _on_register; "
|
||||
"transformer registration ordering is broken."
|
||||
)
|
||||
child_mux = self._mux.make_child(ns)
|
||||
handle = SubgraphRunStream(
|
||||
path=ns,
|
||||
mux=child_mux,
|
||||
graph_name=data.get("graph_name"),
|
||||
cause=data.get("cause"),
|
||||
)
|
||||
self._by_ns[ns] = handle
|
||||
self._root_log.push(handle)
|
||||
|
||||
def _on_status_change(
|
||||
self,
|
||||
ns: tuple[str, ...],
|
||||
event_type: SubgraphStatus,
|
||||
data: LifecycleData,
|
||||
) -> None:
|
||||
handle = self._by_ns[ns]
|
||||
handle.status = event_type
|
||||
err = data.get("error")
|
||||
if err is not None:
|
||||
handle.error = err
|
||||
checkpoint = data.get("checkpoint")
|
||||
if checkpoint is not None:
|
||||
handle.checkpoint = checkpoint
|
||||
if event_type in _TERMINAL_STATUSES:
|
||||
self._close_handle_mux(handle)
|
||||
|
||||
@staticmethod
|
||||
def _close_handle_mux(handle: SubgraphRunStream) -> None:
|
||||
# Idempotent close — mux.close() runs finalize on its transformers
|
||||
# (which cascades through grandchildren) and closes projection logs.
|
||||
if not handle._mux._events._closed:
|
||||
try:
|
||||
handle._mux.close()
|
||||
except Exception:
|
||||
logger.warning(
|
||||
"Error closing subgraph mini-mux at %s; subscribers "
|
||||
"may not see a clean close.",
|
||||
handle.path,
|
||||
exc_info=True,
|
||||
)
|
||||
|
||||
def finalize(self) -> None:
|
||||
"""Transition any still-open direct children to `completed`."""
|
||||
for handle in self._by_ns.values():
|
||||
if handle.status not in _TERMINAL_STATUSES:
|
||||
handle.status = "completed"
|
||||
self._close_handle_mux(handle)
|
||||
|
||||
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 = "1.1.9"
|
||||
description = "Building stateful, multi-actor applications with LLMs"
|
||||
authors = []
|
||||
requires-python = ">=3.10"
|
||||
@@ -24,7 +24,7 @@ classifiers = [
|
||||
'Programming Language :: Python :: 3.13',
|
||||
]
|
||||
dependencies = [
|
||||
"langchain-core>=1.3.2",
|
||||
"langchain-core>=1.3.0,<2",
|
||||
"langgraph-checkpoint>=2.1.0,<5.0.0",
|
||||
"langgraph-sdk>=0.3.0,<0.4.0",
|
||||
"langgraph-prebuilt>=1.0.9,<1.1.0",
|
||||
|
||||
@@ -275,3 +275,70 @@ def test_graph_callbacks_accept_base_callback_manager() -> None:
|
||||
|
||||
assert "__interrupt__" in first
|
||||
assert len(graph_handler.interrupt_events) == 1
|
||||
|
||||
|
||||
def test_non_graph_handler_via_add_handler_does_not_crash() -> None:
|
||||
"""Non-GraphCallbackHandler added via add_handler should not raise.
|
||||
|
||||
Libraries like opentelemetry-instrumentation-langchain monkey-patch
|
||||
BaseCallbackManager.__init__ and inject handlers via add_handler().
|
||||
These handlers inherit from BaseCallbackHandler, not
|
||||
GraphCallbackHandler. They must be silently accepted — graph lifecycle
|
||||
events will simply not be dispatched to them.
|
||||
"""
|
||||
from langgraph.callbacks import _GraphCallbackManager
|
||||
|
||||
manager = _GraphCallbackManager()
|
||||
plain_handler = _LangChainCustomEventHandler()
|
||||
|
||||
manager.add_handler(plain_handler, inherit=True)
|
||||
assert plain_handler in manager.handlers
|
||||
|
||||
|
||||
def test_non_graph_handler_does_not_receive_lifecycle_events() -> None:
|
||||
"""Non-GraphCallbackHandler added alongside a GraphCallbackHandler
|
||||
should not interfere with lifecycle event dispatch."""
|
||||
graph = _build_interrupt_graph()
|
||||
graph_handler = _GraphEventHandler()
|
||||
plain_handler = _LangChainCustomEventHandler()
|
||||
|
||||
config = {
|
||||
"configurable": {"thread_id": "graph-callback-mixed-handlers"},
|
||||
"callbacks": [plain_handler, graph_handler],
|
||||
}
|
||||
|
||||
first = graph.invoke({"answer": None}, config)
|
||||
assert "__interrupt__" in first
|
||||
|
||||
assert len(graph_handler.interrupt_events) == 1
|
||||
assert plain_handler.events == []
|
||||
|
||||
resumed = graph.invoke(Command(resume="done"), config)
|
||||
assert resumed == {"answer": "done"}
|
||||
assert len(graph_handler.resume_events) == 1
|
||||
assert plain_handler.events == []
|
||||
|
||||
|
||||
@pytest.mark.anyio
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_non_graph_handler_does_not_receive_lifecycle_events_async() -> None:
|
||||
"""Async variant: non-GraphCallbackHandler should not interfere."""
|
||||
graph = _build_interrupt_graph()
|
||||
graph_handler = _GraphEventHandler()
|
||||
plain_handler = _LangChainCustomEventHandler()
|
||||
|
||||
config = {
|
||||
"configurable": {"thread_id": "graph-callback-mixed-handlers-async"},
|
||||
"callbacks": [plain_handler, graph_handler],
|
||||
}
|
||||
|
||||
first = await graph.ainvoke({"answer": None}, config)
|
||||
assert "__interrupt__" in first
|
||||
|
||||
assert len(graph_handler.interrupt_events) == 1
|
||||
assert plain_handler.events == []
|
||||
|
||||
resumed = await graph.ainvoke(Command(resume="done"), config)
|
||||
assert resumed == {"answer": "done"}
|
||||
assert len(graph_handler.resume_events) == 1
|
||||
assert plain_handler.events == []
|
||||
|
||||
@@ -615,8 +615,11 @@ def test_run_from_checkpoint_id_retains_previous_writes(
|
||||
)
|
||||
]
|
||||
|
||||
assert len(new_history) == len(history) + 1
|
||||
for original, new in zip(history, new_history[1:]):
|
||||
# +2: one fork checkpoint from time travel, one from the new execution
|
||||
assert len(new_history) == len(history) + 2
|
||||
# new_history[0] is the new execution result, new_history[1] is the fork
|
||||
assert new_history[1].metadata["source"] == "fork"
|
||||
for original, new in zip(history, new_history[2:]):
|
||||
assert original.values == new.values
|
||||
assert original.next == new.next
|
||||
assert original.metadata["step"] == new.metadata["step"]
|
||||
@@ -624,7 +627,7 @@ def test_run_from_checkpoint_id_retains_previous_writes(
|
||||
def _get_tasks(hist: list, start: int):
|
||||
return [h.tasks for h in hist[start:]]
|
||||
|
||||
assert _get_tasks(new_history, 1) == _get_tasks(history, 0)
|
||||
assert _get_tasks(new_history, 2) == _get_tasks(history, 0)
|
||||
|
||||
|
||||
def test_batch_two_processes_in_out() -> None:
|
||||
|
||||
@@ -2086,8 +2086,11 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
|
||||
)
|
||||
]
|
||||
|
||||
assert len(new_history) == len(history) + 1
|
||||
for original, new in zip(history, new_history[1:]):
|
||||
# +2: one fork checkpoint from time travel, one from the new execution
|
||||
assert len(new_history) == len(history) + 2
|
||||
# new_history[0] is the new execution result, new_history[1] is the fork
|
||||
assert new_history[1].metadata["source"] == "fork"
|
||||
for original, new in zip(history, new_history[2:]):
|
||||
assert original.values == new.values
|
||||
assert original.next == new.next
|
||||
assert original.metadata["step"] == new.metadata["step"]
|
||||
@@ -2095,7 +2098,7 @@ async def test_run_from_checkpoint_id_retains_previous_writes(
|
||||
def _get_tasks(hist: list, start: int):
|
||||
return [h.tasks for h in hist[start:]]
|
||||
|
||||
assert _get_tasks(new_history, 1) == _get_tasks(history, 0)
|
||||
assert _get_tasks(new_history, 2) == _get_tasks(history, 0)
|
||||
|
||||
|
||||
async def test_cond_edge_after_send() -> None:
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -1,628 +0,0 @@
|
||||
"""Tests for subgraph lifecycle events and the SubgraphTransformer."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import operator
|
||||
import time
|
||||
from typing import Annotated, Any
|
||||
|
||||
import pytest
|
||||
from langgraph.checkpoint.memory import InMemorySaver
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from langgraph.constants import END, START
|
||||
from langgraph.errors import GraphInterrupt
|
||||
from langgraph.graph import StateGraph
|
||||
from langgraph.stream._event_log import EventLog
|
||||
from langgraph.stream._mux import StreamMux
|
||||
from langgraph.stream._types import ProtocolEvent
|
||||
from langgraph.stream.transformers import (
|
||||
MessagesTransformer,
|
||||
SubgraphRunStream,
|
||||
SubgraphTransformer,
|
||||
ToolLifecycleTransformer,
|
||||
ValuesTransformer,
|
||||
)
|
||||
from langgraph.types import interrupt
|
||||
|
||||
TS = int(time.time() * 1000)
|
||||
|
||||
|
||||
def _lifecycle(
|
||||
event: str,
|
||||
*,
|
||||
namespace: list[str] | None = None,
|
||||
graph_name: str | None = None,
|
||||
cause: dict[str, Any] | None = None,
|
||||
error: str | None = None,
|
||||
) -> ProtocolEvent:
|
||||
data: dict[str, Any] = {"event": event}
|
||||
if graph_name is not None:
|
||||
data["graph_name"] = graph_name
|
||||
if cause is not None:
|
||||
data["cause"] = cause
|
||||
if error is not None:
|
||||
data["error"] = error
|
||||
return {
|
||||
"type": "event",
|
||||
"method": "lifecycle",
|
||||
"params": {
|
||||
"namespace": namespace or [],
|
||||
"timestamp": TS,
|
||||
"data": data,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def _values(payload: dict[str, Any], *, namespace: list[str]) -> ProtocolEvent:
|
||||
return {
|
||||
"type": "event",
|
||||
"method": "values",
|
||||
"params": {
|
||||
"namespace": namespace,
|
||||
"timestamp": TS,
|
||||
"data": payload,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def _subscribe(log: EventLog) -> None:
|
||||
"""Flip `_subscribed = True` so pushes retain items for test inspection."""
|
||||
log._subscribed = True
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Unit tests: feed events directly into the transformer
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
_FACTORIES = [
|
||||
ValuesTransformer,
|
||||
ToolLifecycleTransformer,
|
||||
MessagesTransformer,
|
||||
SubgraphTransformer,
|
||||
]
|
||||
|
||||
|
||||
def _handle_values_items(handle: SubgraphRunStream) -> list:
|
||||
return list(handle._mux.extensions["values"]._items) # type: ignore[attr-defined]
|
||||
|
||||
|
||||
def _handle_subgraphs_items(handle: SubgraphRunStream) -> list:
|
||||
return list(handle._mux.extensions["subgraphs"]._items) # type: ignore[attr-defined]
|
||||
|
||||
|
||||
def _pre_subscribe_handle(handle: SubgraphRunStream) -> None:
|
||||
"""Flip `_subscribed` on every EventLog inside the handle's mini-mux.
|
||||
|
||||
The mini-mux is built via `make_child` with the full factory list,
|
||||
so values / messages / subgraphs logs all exist as projections.
|
||||
Tests that feed events directly need them subscribed so pushes
|
||||
retain items in the deque for `_items` inspection.
|
||||
"""
|
||||
for value in handle._mux.extensions.values():
|
||||
if isinstance(value, EventLog):
|
||||
_subscribe(value)
|
||||
|
||||
|
||||
class TestSubgraphTransformerUnit:
|
||||
def _mux(self) -> tuple[StreamMux, SubgraphTransformer]:
|
||||
mux = StreamMux(factories=_FACTORIES, is_async=False)
|
||||
transformer = mux.transformer_by_key("subgraphs")
|
||||
assert isinstance(transformer, SubgraphTransformer)
|
||||
_subscribe(transformer._root_log)
|
||||
return mux, transformer
|
||||
|
||||
def _handle(self, transformer: SubgraphTransformer) -> SubgraphRunStream:
|
||||
"""Return the single root handle after pushing one lifecycle started."""
|
||||
(handle,) = list(transformer._root_log._items)
|
||||
return handle
|
||||
|
||||
def test_root_started_is_ignored(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", graph_name="root"))
|
||||
assert list(transformer._root_log._items) == []
|
||||
assert transformer._by_ns == {}
|
||||
|
||||
def test_child_started_yields_handle(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(
|
||||
_lifecycle(
|
||||
"started",
|
||||
namespace=["task_a:child"],
|
||||
graph_name="child",
|
||||
cause={"type": "toolCall", "tool_call_id": "call_abc"},
|
||||
)
|
||||
)
|
||||
|
||||
handle = self._handle(transformer)
|
||||
assert handle.path == ("task_a:child",)
|
||||
assert handle.graph_name == "child"
|
||||
assert handle.cause == {"type": "toolCall", "tool_call_id": "call_abc"}
|
||||
assert handle.status == "started"
|
||||
|
||||
def test_tool_started_is_synthesized_before_tool_caused_lifecycle(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
events = iter(mux._events)
|
||||
mux.push(
|
||||
_values(
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_abc",
|
||||
"name": "task",
|
||||
"args": {"subagent_type": "researcher"},
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
namespace=[],
|
||||
)
|
||||
)
|
||||
mux.push(
|
||||
_lifecycle(
|
||||
"started",
|
||||
namespace=["task:child"],
|
||||
graph_name="child",
|
||||
cause={"type": "toolCall", "tool_call_id": "call_abc"},
|
||||
)
|
||||
)
|
||||
|
||||
mux.close()
|
||||
tool_started, lifecycle_started = list(events)[1:3]
|
||||
assert tool_started["method"] == "tools"
|
||||
assert tool_started["params"]["namespace"] == []
|
||||
assert tool_started["params"]["data"] == {
|
||||
"event": "tool-started",
|
||||
"tool_call_id": "call_abc",
|
||||
"tool_name": "task",
|
||||
"input": {"subagent_type": "researcher"},
|
||||
}
|
||||
assert lifecycle_started["method"] == "lifecycle"
|
||||
assert tool_started["seq"] < lifecycle_started["seq"]
|
||||
assert self._handle(transformer).path == ("task:child",)
|
||||
|
||||
def test_core_golden_trace_uses_js_wire_shape_and_ordering(self) -> None:
|
||||
mux, _transformer = self._mux()
|
||||
events = iter(mux._events)
|
||||
mux.push(
|
||||
_values(
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_abc",
|
||||
"name": "task",
|
||||
"args": {"subagent_type": "researcher"},
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
namespace=[],
|
||||
)
|
||||
)
|
||||
for data in (
|
||||
{"event": "message-start", "id": "msg-1", "role": "ai"},
|
||||
{
|
||||
"event": "content-block-delta",
|
||||
"index": 0,
|
||||
"content": {"type": "text", "text": "hi"},
|
||||
},
|
||||
):
|
||||
mux.push(
|
||||
{
|
||||
"type": "event",
|
||||
"method": "messages",
|
||||
"params": {
|
||||
"namespace": ["call_model:task-1"],
|
||||
"timestamp": TS,
|
||||
"data": data,
|
||||
"run_id": "run-1",
|
||||
},
|
||||
}
|
||||
)
|
||||
mux.push(
|
||||
_lifecycle(
|
||||
"started",
|
||||
namespace=["task:child"],
|
||||
graph_name="child",
|
||||
cause={"type": "toolCall", "tool_call_id": "call_abc"},
|
||||
)
|
||||
)
|
||||
mux.close()
|
||||
|
||||
trace = [
|
||||
(event["method"], event["params"]["namespace"], event["params"]["data"])
|
||||
for event in events
|
||||
]
|
||||
assert trace == [
|
||||
(
|
||||
"values",
|
||||
[],
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_abc",
|
||||
"name": "task",
|
||||
"args": {"subagent_type": "researcher"},
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
),
|
||||
(
|
||||
"messages",
|
||||
["call_model:task-1"],
|
||||
{"event": "message-start", "id": "msg-1", "role": "ai"},
|
||||
),
|
||||
(
|
||||
"messages",
|
||||
["call_model:task-1"],
|
||||
{
|
||||
"event": "content-block-start",
|
||||
"index": 0,
|
||||
"content": {"type": "text", "text": ""},
|
||||
},
|
||||
),
|
||||
(
|
||||
"messages",
|
||||
["call_model:task-1"],
|
||||
{
|
||||
"event": "content-block-delta",
|
||||
"index": 0,
|
||||
"content": {"type": "text", "text": "hi"},
|
||||
},
|
||||
),
|
||||
(
|
||||
"tools",
|
||||
[],
|
||||
{
|
||||
"event": "tool-started",
|
||||
"tool_call_id": "call_abc",
|
||||
"tool_name": "task",
|
||||
"input": {"subagent_type": "researcher"},
|
||||
},
|
||||
),
|
||||
(
|
||||
"lifecycle",
|
||||
["task:child"],
|
||||
{
|
||||
"event": "started",
|
||||
"graph_name": "child",
|
||||
"cause": {"type": "toolCall", "tool_call_id": "call_abc"},
|
||||
},
|
||||
),
|
||||
]
|
||||
|
||||
def test_status_transitions(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
mux.push(_lifecycle("running", namespace=["t:c"]))
|
||||
mux.push(_lifecycle("completed", namespace=["t:c"]))
|
||||
|
||||
handle = self._handle(transformer)
|
||||
assert handle.status == "completed"
|
||||
|
||||
def test_grandchild_surfaces_under_child(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:child"], graph_name="child"))
|
||||
|
||||
child = self._handle(transformer)
|
||||
_pre_subscribe_handle(child)
|
||||
|
||||
mux.push(
|
||||
_lifecycle(
|
||||
"started",
|
||||
namespace=["t:child", "u:grand"],
|
||||
graph_name="grand",
|
||||
)
|
||||
)
|
||||
|
||||
(grand,) = _handle_subgraphs_items(child)
|
||||
assert grand.path == ("t:child", "u:grand")
|
||||
assert grand.graph_name == "grand"
|
||||
|
||||
def test_failed_stores_error(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
mux.push(_lifecycle("failed", namespace=["t:c"], error="boom"))
|
||||
|
||||
handle = self._handle(transformer)
|
||||
assert handle.status == "failed"
|
||||
assert handle.error == "boom"
|
||||
|
||||
def test_values_routed_into_handle(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
|
||||
handle = self._handle(transformer)
|
||||
_pre_subscribe_handle(handle)
|
||||
|
||||
mux.push(_values({"value": 1}, namespace=["t:c"]))
|
||||
mux.push(_values({"value": 2}, namespace=["t:c"]))
|
||||
|
||||
assert _handle_values_items(handle) == [{"value": 1}, {"value": 2}]
|
||||
assert handle.output == {"value": 2}
|
||||
|
||||
def test_root_values_not_routed(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
handle = self._handle(transformer)
|
||||
_pre_subscribe_handle(handle)
|
||||
|
||||
# Values event at root namespace — must not leak into child handle.
|
||||
mux.push(_values({"value": "root"}, namespace=[]))
|
||||
assert _handle_values_items(handle) == []
|
||||
|
||||
def test_finalize_closes_dangling(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
handle = self._handle(transformer)
|
||||
|
||||
mux.close()
|
||||
assert handle.status == "completed"
|
||||
assert handle._mux.extensions["values"]._closed
|
||||
assert handle._mux.extensions["subgraphs"]._closed
|
||||
|
||||
def test_fail_with_graph_interrupt_marks_interrupted(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
handle = self._handle(transformer)
|
||||
|
||||
mux.fail(GraphInterrupt())
|
||||
assert handle.status == "interrupted"
|
||||
|
||||
def test_fail_with_generic_error_marks_failed(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
handle = self._handle(transformer)
|
||||
|
||||
mux.fail(RuntimeError("explode"))
|
||||
assert handle.status == "failed"
|
||||
assert handle.error == "explode"
|
||||
|
||||
def test_duplicate_started_ignored(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="c"))
|
||||
mux.push(_lifecycle("started", namespace=["t:c"], graph_name="other"))
|
||||
|
||||
handles = list(transformer._root_log._items)
|
||||
assert len(handles) == 1
|
||||
assert handles[0].graph_name == "c"
|
||||
|
||||
def test_non_lifecycle_non_values_passthrough(self) -> None:
|
||||
mux, transformer = self._mux()
|
||||
mux.push(
|
||||
{
|
||||
"type": "event",
|
||||
"method": "messages",
|
||||
"params": {
|
||||
"namespace": ["t:c"],
|
||||
"timestamp": TS,
|
||||
"data": (
|
||||
{"event": "message-start", "message_id": "m1"},
|
||||
{"run_id": "m1"},
|
||||
),
|
||||
},
|
||||
}
|
||||
)
|
||||
assert list(transformer._root_log._items) == []
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# End-to-end tests via stream_v2 on real graphs
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class SimpleState(TypedDict):
|
||||
value: str
|
||||
items: Annotated[list[str], operator.add]
|
||||
|
||||
|
||||
def _build_nested_graph():
|
||||
"""Parent graph with a compiled subgraph node."""
|
||||
|
||||
def inner_node(state: SimpleState) -> dict:
|
||||
return {"value": state["value"] + "X", "items": ["x"]}
|
||||
|
||||
inner_builder = StateGraph(SimpleState)
|
||||
inner_builder.add_node("inner_node", inner_node)
|
||||
inner_builder.add_edge(START, "inner_node")
|
||||
inner_builder.add_edge("inner_node", END)
|
||||
inner = inner_builder.compile()
|
||||
|
||||
def outer_node(state: SimpleState) -> dict:
|
||||
return {"value": state["value"] + "Y", "items": ["y"]}
|
||||
|
||||
outer_builder = StateGraph(SimpleState)
|
||||
outer_builder.add_node("outer_node", outer_node)
|
||||
outer_builder.add_node("sub", inner)
|
||||
outer_builder.add_edge(START, "outer_node")
|
||||
outer_builder.add_edge("outer_node", "sub")
|
||||
outer_builder.add_edge("sub", END)
|
||||
return outer_builder.compile()
|
||||
|
||||
|
||||
class TestSubgraphTransformerEndToEnd:
|
||||
def test_flat_graph_yields_no_subgraphs(self) -> None:
|
||||
builder = StateGraph(SimpleState)
|
||||
builder.add_node("n", lambda s: {"value": s["value"] + "!", "items": ["!"]})
|
||||
builder.add_edge(START, "n")
|
||||
builder.add_edge("n", END)
|
||||
graph = builder.compile()
|
||||
|
||||
run = graph.stream_v2({"value": "", "items": []})
|
||||
|
||||
collected: list[SubgraphRunStream] = []
|
||||
for sub in run.subgraphs:
|
||||
collected.append(sub)
|
||||
assert collected == []
|
||||
# Output still resolves.
|
||||
assert run.output is not None
|
||||
|
||||
def test_nested_graph_yields_one_child(self) -> None:
|
||||
graph = _build_nested_graph()
|
||||
run = graph.stream_v2({"value": "", "items": []})
|
||||
|
||||
collected: list[SubgraphRunStream] = []
|
||||
for sub in run.subgraphs:
|
||||
collected.append(sub)
|
||||
|
||||
assert len(collected) == 1
|
||||
child = collected[0]
|
||||
assert len(child.path) == 1
|
||||
assert child.path[0].startswith("sub:")
|
||||
assert child.status == "completed"
|
||||
|
||||
def test_error_in_subgraph_fails_child(self) -> None:
|
||||
def boom(state: SimpleState) -> dict:
|
||||
raise RuntimeError("subgraph_failed")
|
||||
|
||||
inner_builder = StateGraph(SimpleState)
|
||||
inner_builder.add_node("inner", boom)
|
||||
inner_builder.add_edge(START, "inner")
|
||||
inner_builder.add_edge("inner", END)
|
||||
inner = inner_builder.compile()
|
||||
|
||||
outer_builder = StateGraph(SimpleState)
|
||||
outer_builder.add_node("sub", inner)
|
||||
outer_builder.add_edge(START, "sub")
|
||||
outer_builder.add_edge("sub", END)
|
||||
graph = outer_builder.compile()
|
||||
|
||||
run = graph.stream_v2({"value": "", "items": []})
|
||||
|
||||
collected: list[SubgraphRunStream] = []
|
||||
with pytest.raises(RuntimeError):
|
||||
for sub in run.subgraphs:
|
||||
collected.append(sub)
|
||||
|
||||
assert len(collected) == 1
|
||||
assert collected[0].status == "failed"
|
||||
|
||||
|
||||
class TestSubgraphTransformerAsyncEndToEnd:
|
||||
@pytest.mark.anyio
|
||||
async def test_nested_graph_yields_one_child(self) -> None:
|
||||
async def inner(state: SimpleState) -> dict:
|
||||
return {"value": state["value"] + "X", "items": ["x"]}
|
||||
|
||||
inner_builder = StateGraph(SimpleState)
|
||||
inner_builder.add_node("inner", inner)
|
||||
inner_builder.add_edge(START, "inner")
|
||||
inner_builder.add_edge("inner", END)
|
||||
inner_graph = inner_builder.compile()
|
||||
|
||||
outer_builder = StateGraph(SimpleState)
|
||||
outer_builder.add_node("sub", inner_graph)
|
||||
outer_builder.add_edge(START, "sub")
|
||||
outer_builder.add_edge("sub", END)
|
||||
graph = outer_builder.compile()
|
||||
|
||||
run = await graph.astream_v2({"value": "", "items": []})
|
||||
|
||||
collected: list[SubgraphRunStream] = []
|
||||
async for sub in run.subgraphs:
|
||||
collected.append(sub)
|
||||
|
||||
assert len(collected) == 1
|
||||
child = collected[0]
|
||||
assert child.status == "completed"
|
||||
|
||||
|
||||
class TestSubgraphCause:
|
||||
"""Pregel core emits no `cause`; product transformers populate it."""
|
||||
|
||||
def test_cause_not_populated_by_pregel(self) -> None:
|
||||
graph = _build_nested_graph()
|
||||
run = graph.stream_v2({"value": "", "items": []})
|
||||
|
||||
collected: list[SubgraphRunStream] = list(run.subgraphs)
|
||||
assert len(collected) == 1
|
||||
child = collected[0]
|
||||
|
||||
# The child's single-segment path still encodes `node_name:task_id`
|
||||
# (that's pregel's internal namespace format), but `cause` is now
|
||||
# product-agnostic and must be populated by a stream transformer,
|
||||
# not by pregel itself.
|
||||
assert ":" in child.path[0]
|
||||
node_name, _, task_id = child.path[0].partition(":")
|
||||
assert node_name == "sub"
|
||||
assert task_id # non-empty
|
||||
assert child.cause is None
|
||||
|
||||
|
||||
class TestSubgraphInterrupt:
|
||||
"""Interrupts raised inside a subgraph surface as status=interrupted."""
|
||||
|
||||
def _build_interrupt_subgraph(self):
|
||||
def inner_node(state: SimpleState) -> dict:
|
||||
interrupt("need approval")
|
||||
return {"value": state["value"] + "X", "items": ["x"]}
|
||||
|
||||
inner_builder = StateGraph(SimpleState)
|
||||
inner_builder.add_node("inner_node", inner_node)
|
||||
inner_builder.add_edge(START, "inner_node")
|
||||
inner_builder.add_edge("inner_node", END)
|
||||
inner = inner_builder.compile()
|
||||
|
||||
outer_builder = StateGraph(SimpleState)
|
||||
outer_builder.add_node("sub", inner)
|
||||
outer_builder.add_edge(START, "sub")
|
||||
outer_builder.add_edge("sub", END)
|
||||
return outer_builder.compile(checkpointer=InMemorySaver())
|
||||
|
||||
def test_interrupt_in_subgraph_marks_handle_interrupted(self) -> None:
|
||||
graph = self._build_interrupt_subgraph()
|
||||
run = graph.stream_v2(
|
||||
{"value": "", "items": []},
|
||||
config={"configurable": {"thread_id": "t1"}},
|
||||
)
|
||||
|
||||
collected: list[SubgraphRunStream] = list(run.subgraphs)
|
||||
|
||||
assert run.interrupted is True
|
||||
assert len(collected) == 1
|
||||
assert collected[0].status == "interrupted"
|
||||
|
||||
|
||||
class TestSubgraphNameCollision:
|
||||
"""The subgraph's compiled `name` equaling its node name is detected.
|
||||
|
||||
Primary detector `name != langgraph_node` fails here; the
|
||||
parent_run_id fallback in `_is_nested_pregel_start` is what keeps
|
||||
the subgraph visible.
|
||||
"""
|
||||
|
||||
def test_name_equals_node_name_still_detected(self) -> None:
|
||||
def inner_node(state: SimpleState) -> dict:
|
||||
return {"value": state["value"] + "X", "items": ["x"]}
|
||||
|
||||
inner_builder = StateGraph(SimpleState)
|
||||
inner_builder.add_node("inner_node", inner_node)
|
||||
inner_builder.add_edge(START, "inner_node")
|
||||
inner_builder.add_edge("inner_node", END)
|
||||
# Compile with the same name as the node it will be registered as.
|
||||
inner = inner_builder.compile(name="sub")
|
||||
|
||||
outer_builder = StateGraph(SimpleState)
|
||||
outer_builder.add_node("sub", inner)
|
||||
outer_builder.add_edge(START, "sub")
|
||||
outer_builder.add_edge("sub", END)
|
||||
graph = outer_builder.compile()
|
||||
|
||||
run = graph.stream_v2({"value": "", "items": []})
|
||||
|
||||
collected: list[SubgraphRunStream] = list(run.subgraphs)
|
||||
assert len(collected) == 1
|
||||
child = collected[0]
|
||||
assert child.graph_name == "sub"
|
||||
assert child.status == "completed"
|
||||
@@ -37,6 +37,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
|
||||
Returns a list of dicts (newest-first, matching get_state_history order) with:
|
||||
- id: short checkpoint id suffix (last 6 chars)
|
||||
- parent_id: short parent checkpoint id suffix or None
|
||||
- source: checkpoint metadata source (input, loop, fork, update)
|
||||
- next: tuple of next node names
|
||||
- values: channel values snapshot
|
||||
"""
|
||||
@@ -52,6 +53,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
|
||||
{
|
||||
"id": cid[-6:],
|
||||
"parent_id": pid[-6:] if pid else None,
|
||||
"source": s.metadata.get("source"),
|
||||
"next": s.next,
|
||||
"values": s.values,
|
||||
}
|
||||
@@ -280,6 +282,116 @@ def test_replay_from_before_interrupt_refires(
|
||||
assert call_count["node_b"] == 1 # NOT re-executed (after interrupt)
|
||||
|
||||
|
||||
def test_replay_from_before_interrupt_then_resume(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Replay from checkpoint before interrupt node, then resume with a new
|
||||
answer and verify the graph completes with the new value.
|
||||
|
||||
Graph: START --> node_a --> ask_human (interrupt) --> node_b --> END
|
||||
|
||||
Original run:
|
||||
source=input next=(__start__,) values=[]
|
||||
source=loop next=(node_a,) values=[]
|
||||
source=loop next=(ask_human,) values=[a] <-- replay from here
|
||||
source=loop next=(node_b,) values=[a, human:old_answer]
|
||||
source=loop next=() values=[a, human:old_answer, b]
|
||||
|
||||
After replay (fork created) + resume with "new_answer":
|
||||
source=input next=(__start__,) values=[]
|
||||
source=loop next=(node_a,) values=[]
|
||||
source=loop next=(ask_human,) values=[a] <-- branch point
|
||||
source=loop next=(node_b,) values=[a, human:old_answer]
|
||||
source=loop next=() values=[a, human:old_answer, b] (old branch)
|
||||
source=fork next=(ask_human,) values=[a] <-- fork from branch point
|
||||
source=loop next=(node_b,) values=[a, human:new_answer]
|
||||
source=loop next=() values=[a, human:new_answer, b] (new branch)
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def node_a(state: State) -> State:
|
||||
called.append("node_a")
|
||||
return {"value": ["a"]}
|
||||
|
||||
def ask_human(state: State) -> State:
|
||||
called.append("ask_human")
|
||||
answer = interrupt("What is your input?")
|
||||
return {"value": [f"human:{answer}"]}
|
||||
|
||||
def node_b(state: State) -> State:
|
||||
called.append("node_b")
|
||||
return {"value": ["b"]}
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("node_a", node_a)
|
||||
.add_node("ask_human", ask_human)
|
||||
.add_node("node_b", node_b)
|
||||
.add_edge(START, "node_a")
|
||||
.add_edge("node_a", "ask_human")
|
||||
.add_edge("ask_human", "node_b")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# --- Original run: invoke until interrupt, then resume to complete ---
|
||||
graph.invoke({"value": []}, config)
|
||||
graph.invoke(Command(resume="old_answer"), config)
|
||||
|
||||
original_history = list(graph.get_state_history(config))
|
||||
original = _checkpoint_summary(original_history)
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["a", "human:old_answer", "b"]}),
|
||||
("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
|
||||
("loop", ("ask_human",), {"value": ["a"]}),
|
||||
("loop", ("node_a",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# --- Replay from checkpoint before ask_human ---
|
||||
before_ask = next(s for s in original_history if s.next == ("ask_human",))
|
||||
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, before_ask.config)
|
||||
assert replay_result["__interrupt__"][0].value == "What is your input?"
|
||||
assert "ask_human" in called
|
||||
assert "node_a" not in called # before the replay point, not re-executed
|
||||
|
||||
# A fork checkpoint is now the latest — it branches from the replay point
|
||||
post_replay = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"]) for s in post_replay] == [
|
||||
("fork", ("ask_human",)), # <-- new fork (latest)
|
||||
("loop", ()), # original done
|
||||
("loop", ("node_b",)),
|
||||
("loop", ("ask_human",)), # branch point
|
||||
("loop", ("node_a",)),
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
|
||||
# --- Resume with a new answer ---
|
||||
called.clear()
|
||||
final_result = graph.invoke(Command(resume="new_answer"), config)
|
||||
assert final_result["value"] == ["a", "human:new_answer", "b"]
|
||||
assert "ask_human" in called
|
||||
assert "node_b" in called
|
||||
|
||||
final = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch (from fork)
|
||||
("loop", (), {"value": ["a", "human:new_answer", "b"]}),
|
||||
("loop", ("node_b",), {"value": ["a", "human:new_answer"]}),
|
||||
("fork", ("ask_human",), {"value": ["a"]}),
|
||||
# Original branch (preserved)
|
||||
("loop", (), {"value": ["a", "human:old_answer", "b"]}),
|
||||
("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
|
||||
("loop", ("ask_human",), {"value": ["a"]}),
|
||||
("loop", ("node_a",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
def test_replay_interrupt_stable_across_replays(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
@@ -320,8 +432,14 @@ def test_replay_interrupt_stable_across_replays(
|
||||
r = graph.invoke(None, before_ask.config)
|
||||
results.append(r)
|
||||
|
||||
assert all(r == results[0] for r in results)
|
||||
assert "__interrupt__" in results[0]
|
||||
# Each replay creates a fork with a unique interrupt ID, so we compare
|
||||
# interrupt values and state values rather than full equality.
|
||||
assert all("__interrupt__" in r for r in results)
|
||||
assert all(
|
||||
r["__interrupt__"][0].value == results[0]["__interrupt__"][0].value
|
||||
for r in results
|
||||
)
|
||||
assert all(r["value"] == results[0]["value"] for r in results)
|
||||
|
||||
|
||||
def test_fork_from_before_interrupt_refires(
|
||||
@@ -854,6 +972,356 @@ def test_subgraph_interrupt_replay_from_interrupt_checkpoint(
|
||||
assert "step_b" not in called
|
||||
|
||||
|
||||
def test_subgraph_interrupt_replay_from_parent_then_resume(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Replay from the parent checkpoint where a subgraph interrupt fired,
|
||||
then resume with a new answer. Verifies that a fork is created and the
|
||||
full graph completes. Checks full checkpoint history at each stage."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def router(state: State) -> State:
|
||||
called.append("router")
|
||||
return {"value": ["routed"]}
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["sub_a"]}
|
||||
|
||||
def ask_human(state: State) -> State:
|
||||
called.append("ask_human")
|
||||
answer = interrupt("Provide input:")
|
||||
return {"value": [f"human:{answer}"]}
|
||||
|
||||
def step_b(state: State) -> State:
|
||||
called.append("step_b")
|
||||
return {"value": ["sub_b"]}
|
||||
|
||||
subgraph = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_human", ask_human)
|
||||
.add_node("step_b", step_b)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_human")
|
||||
.add_edge("ask_human", "step_b")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
def post_process(state: State) -> State:
|
||||
called.append("post_process")
|
||||
return {"value": ["post"]}
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("router", router)
|
||||
.add_node("subgraph_node", subgraph)
|
||||
.add_node("post_process", post_process)
|
||||
.add_edge(START, "router")
|
||||
.add_edge("router", "subgraph_node")
|
||||
.add_edge("subgraph_node", "post_process")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until interrupt, then resume to complete
|
||||
graph.invoke({"value": []}, config)
|
||||
graph.invoke(Command(resume="old_answer"), config)
|
||||
|
||||
# Original parent history (newest first)
|
||||
original_history = list(graph.get_state_history(config))
|
||||
assert [s.next for s in original_history] == [
|
||||
(), # done
|
||||
("post_process",),
|
||||
("subgraph_node",), # subgraph ran, interrupt fired here
|
||||
("router",),
|
||||
("__start__",),
|
||||
]
|
||||
|
||||
# Find the parent checkpoint where the interrupt fired
|
||||
interrupt_checkpoint = next(
|
||||
s for s in original_history if s.next == ("subgraph_node",)
|
||||
)
|
||||
|
||||
# Replay from parent checkpoint — subgraph re-executes, interrupt re-fires
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, interrupt_checkpoint.config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Provide input:"
|
||||
assert "step_a" in called
|
||||
assert "ask_human" in called
|
||||
assert "step_b" not in called
|
||||
|
||||
# Verify fork checkpoint was created
|
||||
post_replay_history = list(graph.get_state_history(config))
|
||||
assert [s.next for s in post_replay_history] == [
|
||||
("subgraph_node",), # fork (interrupt pending)
|
||||
(), # original done
|
||||
("post_process",),
|
||||
("subgraph_node",),
|
||||
("router",),
|
||||
("__start__",),
|
||||
]
|
||||
assert [s.metadata["source"] for s in post_replay_history] == [
|
||||
"fork",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"input",
|
||||
]
|
||||
fork = post_replay_history[0]
|
||||
assert (
|
||||
fork.parent_config["configurable"]["checkpoint_id"]
|
||||
== interrupt_checkpoint.config["configurable"]["checkpoint_id"]
|
||||
)
|
||||
|
||||
# Resume with a new answer — full graph should complete
|
||||
called.clear()
|
||||
final_result = graph.invoke(Command(resume="new_answer"), config)
|
||||
assert "__interrupt__" not in final_result
|
||||
assert "human:new_answer" in final_result["value"]
|
||||
assert "sub_b" in final_result["value"]
|
||||
assert "post" in final_result["value"]
|
||||
assert "ask_human" in called
|
||||
assert "step_b" in called
|
||||
assert "post_process" in called
|
||||
|
||||
# Final checkpoint history
|
||||
final_history = list(graph.get_state_history(config))
|
||||
assert [s.next for s in final_history] == [
|
||||
(), # new branch done
|
||||
("post_process",), # new branch post_process
|
||||
("subgraph_node",), # fork
|
||||
(), # original done
|
||||
("post_process",),
|
||||
("subgraph_node",),
|
||||
("router",),
|
||||
("__start__",),
|
||||
]
|
||||
assert [s.metadata["source"] for s in final_history] == [
|
||||
"loop",
|
||||
"loop",
|
||||
"fork",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"input",
|
||||
]
|
||||
|
||||
|
||||
def test_subgraph_interrupt_resume_with_explicit_head_checkpoint_id(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Resume with Command(resume=...) plus the current head checkpoint_id
|
||||
in config. The subgraph must continue from the interrupted node, not
|
||||
restart from scratch. Explicit checkpoint_id triggers is_replaying but
|
||||
this is a resume, not a time-travel, so ReplayState should not apply."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["sub_a"]}
|
||||
|
||||
def ask_human(state: State) -> State:
|
||||
called.append("ask_human")
|
||||
answer = interrupt("Provide input:")
|
||||
return {"value": [f"human:{answer}"]}
|
||||
|
||||
def step_b(state: State) -> State:
|
||||
called.append("step_b")
|
||||
return {"value": ["sub_b"]}
|
||||
|
||||
subgraph = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_human", ask_human)
|
||||
.add_node("step_b", step_b)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_human")
|
||||
.add_edge("ask_human", "step_b")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("subgraph_node", subgraph)
|
||||
.add_edge(START, "subgraph_node")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until interrupt fires in subgraph
|
||||
graph.invoke({"value": []}, config)
|
||||
assert called == ["step_a", "ask_human"]
|
||||
|
||||
# Resume with explicit head checkpoint_id in config
|
||||
head_checkpoint_id = graph.get_state(config).config["configurable"][
|
||||
"checkpoint_id"
|
||||
]
|
||||
called.clear()
|
||||
resume_config = {
|
||||
"configurable": {
|
||||
"thread_id": "1",
|
||||
"checkpoint_id": head_checkpoint_id,
|
||||
"checkpoint_ns": "",
|
||||
}
|
||||
}
|
||||
result = graph.invoke(Command(resume="answer"), resume_config)
|
||||
|
||||
assert called == ["ask_human", "step_b"]
|
||||
assert "__interrupt__" not in result
|
||||
assert result["value"] == ["sub_a", "human:answer", "sub_b"]
|
||||
|
||||
|
||||
def test_subgraph_replay_loads_accumulated_state_then_resume(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Two parent invocations, then replay from before the subgraph in the
|
||||
2nd invocation. The subgraph (checkpointer=True) should load its
|
||||
accumulated state from the 1st invocation via ReplayState, re-fire
|
||||
the interrupt, and then resume + complete.
|
||||
|
||||
This tests the ReplayState path: the parent is replaying and the
|
||||
subgraph uses list(before=parent_checkpoint_id) to find its
|
||||
corresponding checkpoint from the original execution.
|
||||
"""
|
||||
|
||||
class SubState(TypedDict):
|
||||
value: Annotated[list[str], operator.add]
|
||||
|
||||
class ParentState(TypedDict):
|
||||
results: Annotated[list[str], operator.add]
|
||||
|
||||
started_state: list[dict] = []
|
||||
|
||||
def step_a(state: SubState) -> SubState:
|
||||
started_state.append(dict(state))
|
||||
answer = interrupt("question_a")
|
||||
return {"value": [f"a:{answer}"]}
|
||||
|
||||
subgraph = (
|
||||
StateGraph(SubState)
|
||||
.add_node("step_a", step_a)
|
||||
.add_edge(START, "step_a")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
def parent_node(state: ParentState) -> ParentState:
|
||||
return {"results": ["p"]}
|
||||
|
||||
graph = (
|
||||
StateGraph(ParentState)
|
||||
.add_node("parent_node", parent_node)
|
||||
.add_node("sub_node", subgraph)
|
||||
.add_edge(START, "parent_node")
|
||||
.add_edge("parent_node", "sub_node")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# === 1st invocation: complete with answer "a1" ===
|
||||
graph.invoke({"results": []}, config)
|
||||
graph.invoke(Command(resume="a1"), config)
|
||||
|
||||
# step_a saw empty state (fresh subgraph)
|
||||
assert started_state[0] == {"value": []}
|
||||
|
||||
# === 2nd invocation: complete with answer "a2" ===
|
||||
started_state.clear()
|
||||
graph.invoke({"results": []}, config)
|
||||
graph.invoke(Command(resume="a2"), config)
|
||||
|
||||
# Stateful subgraph retained state from 1st invocation
|
||||
assert started_state[0] == {"value": ["a:a1"]}
|
||||
|
||||
# Original history (newest first)
|
||||
original_history = list(graph.get_state_history(config))
|
||||
assert [s.next for s in original_history] == [
|
||||
(), # 2nd done
|
||||
("sub_node",), # 2nd sub_node
|
||||
("parent_node",), # 2nd parent_node
|
||||
("__start__",), # 2nd input
|
||||
(), # 1st done
|
||||
("sub_node",), # 1st sub_node
|
||||
("parent_node",), # 1st parent_node
|
||||
("__start__",), # 1st input
|
||||
]
|
||||
|
||||
# Replay from before sub_node in 2nd invocation (newest match)
|
||||
before_sub_2nd = [s for s in original_history if s.next == ("sub_node",)][0]
|
||||
started_state.clear()
|
||||
replay = graph.invoke(None, before_sub_2nd.config)
|
||||
assert "__interrupt__" in replay
|
||||
|
||||
# Subgraph should see accumulated state from END of 1st invocation
|
||||
assert started_state[0] == {"value": ["a:a1"]}
|
||||
|
||||
# Verify fork was created
|
||||
post_replay_history = list(graph.get_state_history(config))
|
||||
assert [s.next for s in post_replay_history] == [
|
||||
("sub_node",), # fork (interrupt pending)
|
||||
(), # 2nd done
|
||||
("sub_node",), # 2nd sub_node
|
||||
("parent_node",), # 2nd parent_node
|
||||
("__start__",), # 2nd input
|
||||
(), # 1st done
|
||||
("sub_node",), # 1st sub_node
|
||||
("parent_node",), # 1st parent_node
|
||||
("__start__",), # 1st input
|
||||
]
|
||||
assert [s.metadata["source"] for s in post_replay_history] == [
|
||||
"fork",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"input",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"input",
|
||||
]
|
||||
|
||||
# Resume with a new answer
|
||||
started_state.clear()
|
||||
final = graph.invoke(Command(resume="a3"), config)
|
||||
assert "__interrupt__" not in final
|
||||
assert final["results"] == ["p", "p"]
|
||||
|
||||
# Final history
|
||||
final_history = list(graph.get_state_history(config))
|
||||
assert [s.next for s in final_history] == [
|
||||
(), # new branch done
|
||||
("sub_node",), # fork
|
||||
(), # 2nd done
|
||||
("sub_node",), # 2nd sub_node
|
||||
("parent_node",), # 2nd parent_node
|
||||
("__start__",), # 2nd input
|
||||
(), # 1st done
|
||||
("sub_node",), # 1st sub_node
|
||||
("parent_node",), # 1st parent_node
|
||||
("__start__",), # 1st input
|
||||
]
|
||||
assert [s.metadata["source"] for s in final_history] == [
|
||||
"loop",
|
||||
"fork",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"input",
|
||||
"loop",
|
||||
"loop",
|
||||
"loop",
|
||||
"input",
|
||||
]
|
||||
|
||||
|
||||
def test_subgraph_interrupt_full_flow(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
@@ -1290,6 +1758,321 @@ def test_subgraph_time_travel_to_second_interrupt(
|
||||
assert "ask_1" not in called
|
||||
|
||||
|
||||
def test_subgraph_time_travel_resume_from_first_interrupt(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the first interrupt, then
|
||||
resume through both interrupts with new answers.
|
||||
|
||||
This verifies the key bug fix: after time-traveling to a subgraph
|
||||
checkpoint with an interrupt, a fork checkpoint is created so that
|
||||
subsequent resumes find the correct state (not the old branch tip).
|
||||
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
|
||||
Parent history after original run completes:
|
||||
source=input next=(__start__,) values=[]
|
||||
source=loop next=(executor,) values=[]
|
||||
source=loop next=() values=[step_a_done, ask_1:answer_1, ask_2:answer_2]
|
||||
|
||||
After time-traveling to 1st interrupt + resuming with new answers:
|
||||
source=input next=(__start__,) values=[]
|
||||
source=loop next=(executor,) values=[] <-- branch point
|
||||
source=loop next=() values=[..., ask_2:answer_2] (old branch)
|
||||
source=fork next=(executor,) values=[] <-- fork from time travel
|
||||
source=loop next=() values=[..., ask_2:new_answer_2] (new branch)
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# --- Original run: hit both interrupts and resume ---
|
||||
graph.invoke({"value": []}, config)
|
||||
sub_config_at_first = graph.get_state(config, subgraphs=True).tasks[0].state.config
|
||||
graph.invoke(Command(resume="answer_1"), config)
|
||||
graph.invoke(Command(resume="answer_2"), config)
|
||||
|
||||
original = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# --- Time travel to first interrupt's subgraph checkpoint ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, sub_config_at_first)
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called # before interrupt, not re-executed
|
||||
|
||||
# Fork is now the latest parent checkpoint
|
||||
post_tt = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"]) for s in post_tt] == [
|
||||
("fork", ("executor",)), # <-- new fork (latest)
|
||||
("loop", ()), # original done
|
||||
("loop", ("executor",)),
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
|
||||
# --- Resume both interrupts with new answers ---
|
||||
called.clear()
|
||||
resume_1 = graph.invoke(Command(resume="new_answer_1"), config)
|
||||
assert resume_1["__interrupt__"][0].value == "Question 2?"
|
||||
assert "ask_1" in called
|
||||
|
||||
called.clear()
|
||||
resume_2 = graph.invoke(Command(resume="new_answer_2"), config)
|
||||
assert resume_2["value"] == [
|
||||
"step_a_done",
|
||||
"ask_1:new_answer_1",
|
||||
"ask_2:new_answer_2",
|
||||
]
|
||||
|
||||
# Verify final history: original branch preserved, new branch appended
|
||||
final = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch (from time travel fork)
|
||||
(
|
||||
"loop",
|
||||
(),
|
||||
{"value": ["step_a_done", "ask_1:new_answer_1", "ask_2:new_answer_2"]},
|
||||
),
|
||||
("fork", ("executor",), {"value": []}),
|
||||
# Original branch (preserved)
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
def test_subgraph_time_travel_resume_from_second_interrupt(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the second interrupt, then
|
||||
resume with a new answer. The first interrupt's answer should be preserved.
|
||||
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
|
||||
Key assertion: after resuming from a time-travel to the 2nd interrupt,
|
||||
the final state keeps ask_1's original answer but uses the new ask_2 answer.
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# --- Original run: hit both interrupts and resume ---
|
||||
graph.invoke({"value": []}, config)
|
||||
graph.invoke(Command(resume="answer_1"), config)
|
||||
sub_config_at_second = graph.get_state(config, subgraphs=True).tasks[0].state.config
|
||||
graph.invoke(Command(resume="answer_2"), config)
|
||||
|
||||
original = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# --- Time travel to second interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, sub_config_at_second)
|
||||
assert replay_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called # already resolved, not re-executed
|
||||
|
||||
# Fork is now the latest parent checkpoint
|
||||
post_tt = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"]) for s in post_tt] == [
|
||||
("fork", ("executor",)), # <-- new fork (latest)
|
||||
("loop", ()), # original done
|
||||
("loop", ("executor",)),
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
|
||||
# --- Resume with a new answer for ask_2 only ---
|
||||
called.clear()
|
||||
resume_result = graph.invoke(Command(resume="new_answer_2"), config)
|
||||
# ask_1's original answer preserved, ask_2 uses the new answer
|
||||
assert resume_result["value"] == [
|
||||
"step_a_done",
|
||||
"ask_1:answer_1",
|
||||
"ask_2:new_answer_2",
|
||||
]
|
||||
|
||||
# Verify final history: original branch preserved, new branch appended
|
||||
final = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch (from time travel fork)
|
||||
(
|
||||
"loop",
|
||||
(),
|
||||
{"value": ["step_a_done", "ask_1:answer_1", "ask_2:new_answer_2"]},
|
||||
),
|
||||
("fork", ("executor",), {"value": []}),
|
||||
# Original branch (preserved)
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
def test_subgraph_time_travel_checkpoint_pattern(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Verify the checkpoint pattern created by time travel to a subgraph
|
||||
interrupt. A fork checkpoint should branch from the replay point and
|
||||
become the latest parent checkpoint.
|
||||
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> ask (interrupt) --> END
|
||||
|
||||
Original run (after completing):
|
||||
source=input next=(__start__,) values=[]
|
||||
source=loop next=(executor,) values=[] <-- replay point
|
||||
source=loop next=() values=[a:first]
|
||||
|
||||
After time travel to interrupt + resume with "second":
|
||||
source=input next=(__start__,) values=[]
|
||||
source=loop next=(executor,) values=[] <-- branch point
|
||||
source=loop next=() values=[a:first] (old branch)
|
||||
source=fork next=(executor,) values=[] <-- fork
|
||||
source=loop next=() values=[a:second] (new branch)
|
||||
"""
|
||||
|
||||
def ask(state: State) -> State:
|
||||
answer = interrupt("Q?")
|
||||
return {"value": [f"a:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("ask", ask)
|
||||
.add_edge(START, "ask")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until interrupt, then complete
|
||||
graph.invoke({"value": []}, config)
|
||||
sub_config = graph.get_state(config, subgraphs=True).tasks[0].state.config
|
||||
graph.invoke(Command(resume="first"), config)
|
||||
|
||||
original = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["a:first"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# Time travel to the interrupt
|
||||
graph.invoke(None, sub_config)
|
||||
|
||||
# Fork is now the latest, branching from the original replay point
|
||||
post_tt = list(graph.get_state_history(config))
|
||||
post_tt_summary = _checkpoint_summary(post_tt)
|
||||
assert [(s["source"], s["next"]) for s in post_tt_summary] == [
|
||||
("fork", ("executor",)), # <-- new fork (latest)
|
||||
("loop", ()),
|
||||
("loop", ("executor",)), # <-- replay point / fork parent
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
# Verify the fork's parent is the original replay point
|
||||
replay_point_id = sub_config["configurable"]["checkpoint_map"][""]
|
||||
assert post_tt[0].parent_config["configurable"]["checkpoint_id"] == replay_point_id
|
||||
|
||||
# Resume from the fork — graph completes with new answer
|
||||
result = graph.invoke(Command(resume="second"), config)
|
||||
assert result["value"] == ["a:second"]
|
||||
|
||||
final = _checkpoint_summary(list(graph.get_state_history(config)))
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch
|
||||
("loop", (), {"value": ["a:second"]}),
|
||||
("fork", ("executor",), {"value": []}),
|
||||
# Original branch
|
||||
("loop", (), {"value": ["a:first"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
def test_subgraph_time_travel_after_completion(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
@@ -2283,14 +3066,16 @@ def test_replay_creates_branch_preserving_old_checkpoints(
|
||||
# -- Post-replay checkpoint history (newest first) --
|
||||
post_replay_history = list(graph.get_state_history(config))
|
||||
post_summary = _checkpoint_summary(post_replay_history)
|
||||
assert len(post_summary) == 7 # 5 original + 2 new branch checkpoints
|
||||
# 5 original + 1 fork + 2 new branch checkpoints = 8
|
||||
assert len(post_summary) == 8
|
||||
|
||||
# Verify the full shape after replay
|
||||
assert [s["next"] for s in post_summary] == [
|
||||
(), # new branch tip (C6)
|
||||
("node_c",), # new branch (C5)
|
||||
(), # old branch tip (C4)
|
||||
("node_c",), # old (C3)
|
||||
(), # new branch tip
|
||||
("node_c",), # new branch
|
||||
("node_b",), # fork from replay point
|
||||
(), # old branch tip
|
||||
("node_c",), # old
|
||||
("node_b",), # branch point (C2)
|
||||
("node_a",), # old (C1)
|
||||
("__start__",), # old (C0)
|
||||
@@ -2298,6 +3083,7 @@ def test_replay_creates_branch_preserving_old_checkpoints(
|
||||
assert [s["values"] for s in post_summary] == [
|
||||
{"value": ["a", "b2", "c"]}, # new branch tip
|
||||
{"value": ["a", "b2"]}, # new: node_b re-ran with call_count=2
|
||||
{"value": ["a"]}, # fork from replay point
|
||||
{"value": ["a", "b1", "c"]}, # old branch tip preserved
|
||||
{"value": ["a", "b1"]}, # old
|
||||
{"value": ["a"]}, # branch point
|
||||
|
||||
@@ -46,6 +46,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
|
||||
Returns a list of dicts (newest-first, matching get_state_history order) with:
|
||||
- id: short checkpoint id suffix (last 6 chars)
|
||||
- parent_id: short parent checkpoint id suffix or None
|
||||
- source: checkpoint metadata source (input, loop, fork, update)
|
||||
- next: tuple of next node names
|
||||
- values: channel values snapshot
|
||||
"""
|
||||
@@ -61,6 +62,7 @@ def _checkpoint_summary(history: list) -> list[dict]:
|
||||
{
|
||||
"id": cid[-6:],
|
||||
"parent_id": pid[-6:] if pid else None,
|
||||
"source": s.metadata.get("source"),
|
||||
"next": s.next,
|
||||
"values": s.values,
|
||||
}
|
||||
@@ -335,8 +337,14 @@ async def test_replay_interrupt_stable_across_replays(
|
||||
r = await graph.ainvoke(None, before_ask.config)
|
||||
results.append(r)
|
||||
|
||||
assert all(r == results[0] for r in results)
|
||||
assert "__interrupt__" in results[0]
|
||||
# Each replay creates a fork with a unique interrupt ID, so we compare
|
||||
# interrupt values and state values rather than full equality.
|
||||
assert all("__interrupt__" in r for r in results)
|
||||
assert all(
|
||||
r["__interrupt__"][0].value == results[0]["__interrupt__"][0].value
|
||||
for r in results
|
||||
)
|
||||
assert all(r["value"] == results[0]["value"] for r in results)
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
@@ -1261,6 +1269,391 @@ async def test_subgraph_time_travel_after_completion_async(
|
||||
assert "ask_2:answer_2" in replay_result["value"]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_replay_from_before_interrupt_then_resume_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Replay from checkpoint before interrupt node, then resume with a new
|
||||
answer and verify the graph completes with the new value.
|
||||
|
||||
Graph: START --> node_a --> ask_human (interrupt) --> node_b --> END
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def node_a(state: State) -> State:
|
||||
called.append("node_a")
|
||||
return {"value": ["a"]}
|
||||
|
||||
async def ask_human(state: State) -> State:
|
||||
called.append("ask_human")
|
||||
answer = interrupt("What is your input?")
|
||||
return {"value": [f"human:{answer}"]}
|
||||
|
||||
async def node_b(state: State) -> State:
|
||||
called.append("node_b")
|
||||
return {"value": ["b"]}
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("node_a", node_a)
|
||||
.add_node("ask_human", ask_human)
|
||||
.add_node("node_b", node_b)
|
||||
.add_edge(START, "node_a")
|
||||
.add_edge("node_a", "ask_human")
|
||||
.add_edge("ask_human", "node_b")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# --- Original run: invoke until interrupt, then resume to complete ---
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
await graph.ainvoke(Command(resume="old_answer"), config)
|
||||
|
||||
original_history = [s async for s in graph.aget_state_history(config)]
|
||||
original = _checkpoint_summary(original_history)
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["a", "human:old_answer", "b"]}),
|
||||
("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
|
||||
("loop", ("ask_human",), {"value": ["a"]}),
|
||||
("loop", ("node_a",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# --- Replay from checkpoint before ask_human ---
|
||||
before_ask = next(s for s in original_history if s.next == ("ask_human",))
|
||||
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, before_ask.config)
|
||||
assert replay_result["__interrupt__"][0].value == "What is your input?"
|
||||
assert "ask_human" in called
|
||||
assert "node_a" not in called
|
||||
|
||||
# A fork checkpoint is now the latest
|
||||
post_replay = _checkpoint_summary(
|
||||
[s async for s in graph.aget_state_history(config)]
|
||||
)
|
||||
assert [(s["source"], s["next"]) for s in post_replay] == [
|
||||
("fork", ("ask_human",)),
|
||||
("loop", ()),
|
||||
("loop", ("node_b",)),
|
||||
("loop", ("ask_human",)),
|
||||
("loop", ("node_a",)),
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
|
||||
# --- Resume with a new answer ---
|
||||
called.clear()
|
||||
final_result = await graph.ainvoke(Command(resume="new_answer"), config)
|
||||
assert final_result["value"] == ["a", "human:new_answer", "b"]
|
||||
assert "ask_human" in called
|
||||
assert "node_b" in called
|
||||
|
||||
final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch (from fork)
|
||||
("loop", (), {"value": ["a", "human:new_answer", "b"]}),
|
||||
("loop", ("node_b",), {"value": ["a", "human:new_answer"]}),
|
||||
("fork", ("ask_human",), {"value": ["a"]}),
|
||||
# Original branch (preserved)
|
||||
("loop", (), {"value": ["a", "human:old_answer", "b"]}),
|
||||
("loop", ("node_b",), {"value": ["a", "human:old_answer"]}),
|
||||
("loop", ("ask_human",), {"value": ["a"]}),
|
||||
("loop", ("node_a",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_subgraph_time_travel_resume_from_first_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the first interrupt, then
|
||||
resume through both interrupts with new answers.
|
||||
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# --- Original run: hit both interrupts and resume ---
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
sub_config_at_first = (
|
||||
(await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
|
||||
)
|
||||
await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# --- Time travel to first interrupt's subgraph checkpoint ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, sub_config_at_first)
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
|
||||
# Fork is now the latest parent checkpoint
|
||||
post_tt = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"]) for s in post_tt] == [
|
||||
("fork", ("executor",)), # <-- new fork (latest)
|
||||
("loop", ()), # original done
|
||||
("loop", ("executor",)),
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
|
||||
# --- Resume both interrupts with new answers ---
|
||||
called.clear()
|
||||
resume_1 = await graph.ainvoke(Command(resume="new_answer_1"), config)
|
||||
assert resume_1["__interrupt__"][0].value == "Question 2?"
|
||||
assert "ask_1" in called
|
||||
|
||||
called.clear()
|
||||
resume_2 = await graph.ainvoke(Command(resume="new_answer_2"), config)
|
||||
assert resume_2["value"] == [
|
||||
"step_a_done",
|
||||
"ask_1:new_answer_1",
|
||||
"ask_2:new_answer_2",
|
||||
]
|
||||
|
||||
# Verify final history: original branch preserved, new branch appended
|
||||
final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch (from time travel fork)
|
||||
(
|
||||
"loop",
|
||||
(),
|
||||
{"value": ["step_a_done", "ask_1:new_answer_1", "ask_2:new_answer_2"]},
|
||||
),
|
||||
("fork", ("executor",), {"value": []}),
|
||||
# Original branch (preserved)
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_subgraph_time_travel_resume_from_second_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the second interrupt, then
|
||||
resume with a new answer. The first interrupt's answer should be preserved.
|
||||
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# --- Original run: hit both interrupts and resume ---
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
sub_config_at_second = (
|
||||
(await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
|
||||
)
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# --- Time travel to second interrupt ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, sub_config_at_second)
|
||||
assert replay_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# Fork is now the latest parent checkpoint
|
||||
post_tt = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"]) for s in post_tt] == [
|
||||
("fork", ("executor",)), # <-- new fork (latest)
|
||||
("loop", ()), # original done
|
||||
("loop", ("executor",)),
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
|
||||
# --- Resume with a new answer for ask_2 only ---
|
||||
called.clear()
|
||||
resume_result = await graph.ainvoke(Command(resume="new_answer_2"), config)
|
||||
assert resume_result["value"] == [
|
||||
"step_a_done",
|
||||
"ask_1:answer_1",
|
||||
"ask_2:new_answer_2",
|
||||
]
|
||||
|
||||
# Verify final history
|
||||
final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch (from time travel fork)
|
||||
(
|
||||
"loop",
|
||||
(),
|
||||
{"value": ["step_a_done", "ask_1:answer_1", "ask_2:new_answer_2"]},
|
||||
),
|
||||
("fork", ("executor",), {"value": []}),
|
||||
# Original branch (preserved)
|
||||
("loop", (), {"value": ["step_a_done", "ask_1:answer_1", "ask_2:answer_2"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_subgraph_time_travel_checkpoint_pattern_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Verify the checkpoint pattern created by time travel to a subgraph
|
||||
interrupt. A fork checkpoint should branch from the replay point.
|
||||
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> ask (interrupt) --> END
|
||||
"""
|
||||
|
||||
async def ask(state: State) -> State:
|
||||
answer = interrupt("Q?")
|
||||
return {"value": [f"a:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("ask", ask)
|
||||
.add_edge(START, "ask")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until interrupt, then complete
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
sub_config = (await graph.aget_state(config, subgraphs=True)).tasks[0].state.config
|
||||
await graph.ainvoke(Command(resume="first"), config)
|
||||
|
||||
original = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in original] == [
|
||||
("loop", (), {"value": ["a:first"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
# Time travel to the interrupt
|
||||
await graph.ainvoke(None, sub_config)
|
||||
|
||||
# Fork is now the latest, branching from the original replay point
|
||||
post_tt = [s async for s in graph.aget_state_history(config)]
|
||||
post_tt_summary = _checkpoint_summary(post_tt)
|
||||
assert [(s["source"], s["next"]) for s in post_tt_summary] == [
|
||||
("fork", ("executor",)), # <-- new fork (latest)
|
||||
("loop", ()),
|
||||
("loop", ("executor",)), # <-- replay point / fork parent
|
||||
("input", ("__start__",)),
|
||||
]
|
||||
# Verify the fork's parent is the original replay point
|
||||
replay_point_id = sub_config["configurable"]["checkpoint_map"][""]
|
||||
assert post_tt[0].parent_config["configurable"]["checkpoint_id"] == replay_point_id
|
||||
|
||||
# Resume from the fork
|
||||
result = await graph.ainvoke(Command(resume="second"), config)
|
||||
assert result["value"] == ["a:second"]
|
||||
|
||||
final = _checkpoint_summary([s async for s in graph.aget_state_history(config)])
|
||||
assert [(s["source"], s["next"], s["values"]) for s in final] == [
|
||||
# New branch
|
||||
("loop", (), {"value": ["a:second"]}),
|
||||
("fork", ("executor",), {"value": []}),
|
||||
# Original branch
|
||||
("loop", (), {"value": ["a:first"]}),
|
||||
("loop", ("executor",), {"value": []}),
|
||||
("input", ("__start__",), {"value": []}),
|
||||
]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_3_levels_deep_time_travel_to_first_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
@@ -2088,13 +2481,15 @@ async def test_replay_creates_branch_preserving_old_checkpoints(
|
||||
# -- Post-replay checkpoint history (newest first) --
|
||||
post_replay_history = [s async for s in graph.aget_state_history(config)]
|
||||
post_summary = _checkpoint_summary(post_replay_history)
|
||||
assert len(post_summary) == 7 # 5 original + 2 new branch checkpoints
|
||||
# 5 original + 1 fork + 2 new branch checkpoints = 8
|
||||
assert len(post_summary) == 8
|
||||
|
||||
assert [s["next"] for s in post_summary] == [
|
||||
(), # new branch tip (C6)
|
||||
("node_c",), # new branch (C5)
|
||||
(), # old branch tip (C4)
|
||||
("node_c",), # old (C3)
|
||||
(), # new branch tip
|
||||
("node_c",), # new branch
|
||||
("node_b",), # fork from replay point
|
||||
(), # old branch tip
|
||||
("node_c",), # old
|
||||
("node_b",), # branch point (C2)
|
||||
("node_a",), # old (C1)
|
||||
("__start__",), # old (C0)
|
||||
@@ -2102,6 +2497,7 @@ async def test_replay_creates_branch_preserving_old_checkpoints(
|
||||
assert [s["values"] for s in post_summary] == [
|
||||
{"value": ["a", "b2", "c"]}, # new branch tip
|
||||
{"value": ["a", "b2"]}, # new: node_b re-ran with call_count=2
|
||||
{"value": ["a"]}, # fork from replay point
|
||||
{"value": ["a", "b1", "c"]}, # old branch tip preserved
|
||||
{"value": ["a", "b1"]}, # old
|
||||
{"value": ["a"]}, # branch point
|
||||
|
||||
@@ -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:")
|
||||
Generated
+12
-24
@@ -1348,11 +1348,10 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "1.3.2"
|
||||
version = "1.3.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jsonpatch" },
|
||||
{ name = "langchain-protocol" },
|
||||
{ name = "langsmith" },
|
||||
{ name = "packaging" },
|
||||
{ name = "pydantic" },
|
||||
@@ -1361,26 +1360,14 @@ dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
{ name = "uuid-utils" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/a8/03/7219502e8ca728d65eb44d7a3eb60239230742a70dbfc9241b9bfd61c4ab/langchain_core-1.3.2.tar.gz", hash = "sha256:fd7a50b2f28ba561fd9d7f5d2760bc9e06cf00cdf820a3ccafe88a94ffa8d5b7", size = 911813, upload-time = "2026-04-24T15:49:23.699Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/92/fe/20190232d9b513242899dbb0c2bb77e31b4d61e343743adbe90ebc2603d2/langchain_core-1.3.0.tar.gz", hash = "sha256:14a39f528bf459aa3aa40d0a7f7f1bae7520d435ef991ae14a4ceb74d8c49046", size = 860755, upload-time = "2026-04-17T14:51:38.298Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/7d/d5/8fa4431007cbb7cfed7590f4d6a5dea3ad724f4174d248f6642ef5ce7d05/langchain_core-1.3.2-py3-none-any.whl", hash = "sha256:d44a66127f9f8db735bdfd0ab9661bccb47a97113cfd3f2d89c74864422b7274", size = 542390, upload-time = "2026-04-24T15:49:21.991Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langchain-protocol"
|
||||
version = "0.0.12"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5c/51/1157009b6f94e6e58be58fa8b620187d657909a8b36a6bf5b0c52a2711f6/langchain_protocol-0.0.12.tar.gz", hash = "sha256:5e14c434290a705c9510fdb1a83ecf7561a5e6e0dfd053930ade80dba069269f", size = 6408, upload-time = "2026-04-25T01:05:01.489Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/95/82/3431e3061c917439589fa88a6b23c9bc0e154cba0f05d2e895a68c76ff74/langchain_protocol-0.0.12-py3-none-any.whl", hash = "sha256:402b61f42d4139692528cf37226c367bb6efc8ff8165b29380accb0abfece7b2", size = 6639, upload-time = "2026-04-25T01:05:00.487Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f8/e2/dbfa347aa072a6dc4cd38d6f9ebfc730b4c14c258c47f480f4c5c546f177/langchain_core-1.3.0-py3-none-any.whl", hash = "sha256:baf16ee028475df177b9ab8869a751c79406d64a6f12125b93802991b566cced", size = 515140, upload-time = "2026-04-17T14:51:36.274Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.1.7a2"
|
||||
version = "1.1.9"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -1452,7 +1439,7 @@ test = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain-core", specifier = ">=1.3.2" },
|
||||
{ name = "langchain-core", specifier = ">=1.3.0,<2" },
|
||||
{ name = "langgraph-checkpoint", editable = "../checkpoint" },
|
||||
{ name = "langgraph-prebuilt", editable = "../prebuilt" },
|
||||
{ name = "langgraph-sdk", editable = "../sdk-py" },
|
||||
@@ -1561,7 +1548,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.0.1"
|
||||
version = "4.0.2"
|
||||
source = { editable = "../checkpoint" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -1719,7 +1706,7 @@ inmem = [
|
||||
requires-dist = [
|
||||
{ name = "click", specifier = ">=8.1.7" },
|
||||
{ name = "httpx", specifier = ">=0.24.0" },
|
||||
{ name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.8.0" },
|
||||
{ name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.5.35,<0.9.0" },
|
||||
{ name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.7" },
|
||||
{ name = "langgraph-sdk", marker = "python_full_version >= '3.11'", specifier = ">=0.1.0" },
|
||||
{ name = "pathspec", specifier = ">=0.11.0" },
|
||||
@@ -1755,7 +1742,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-prebuilt"
|
||||
version = "1.0.9"
|
||||
version = "1.0.10"
|
||||
source = { editable = "../prebuilt" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -1865,7 +1852,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.6.4"
|
||||
version = "0.7.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
@@ -1875,11 +1862,12 @@ dependencies = [
|
||||
{ name = "requests" },
|
||||
{ name = "requests-toolbelt" },
|
||||
{ name = "uuid-utils" },
|
||||
{ name = "xxhash" },
|
||||
{ name = "zstandard" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e7/85/9c7933052a997da1b85bc5c774f3865e9b1da1c8d71541ea133178b13229/langsmith-0.6.4.tar.gz", hash = "sha256:36f7223a01c218079fbb17da5e536ebbaf5c1468c028abe070aa3ae59bc99ec8", size = 919964, upload-time = "2026-01-15T20:02:28.873Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/66/0f/09a6637a7ba777eb307b7c80852d9ee26438e2bdafbad6fcc849ff9d9192/langsmith-0.6.4-py3-none-any.whl", hash = "sha256:ac4835860160be371042c7adbba3cb267bcf8d96a5ea976c33a8a4acad6c5486", size = 283503, upload-time = "2026-01-15T20:02:26.662Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
|
||||
@@ -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()
|
||||
@@ -614,6 +614,7 @@ class _InjectedArgs:
|
||||
store: str | None
|
||||
runtime: str | None
|
||||
all_injected_keys: set[str]
|
||||
_optional_state_args: set[str]
|
||||
|
||||
|
||||
class ToolNode(RunnableCallable):
|
||||
@@ -807,6 +808,7 @@ class ToolNode(RunnableCallable):
|
||||
context=runtime.context,
|
||||
store=runtime.store,
|
||||
stream_writer=runtime.stream_writer,
|
||||
tools=list(self.tools_by_name.values()),
|
||||
execution_info=runtime.execution_info,
|
||||
server_info=runtime.server_info,
|
||||
)
|
||||
@@ -841,6 +843,7 @@ class ToolNode(RunnableCallable):
|
||||
context=runtime.context,
|
||||
store=runtime.store,
|
||||
stream_writer=runtime.stream_writer,
|
||||
tools=list(self.tools_by_name.values()),
|
||||
execution_info=runtime.execution_info,
|
||||
server_info=runtime.server_info,
|
||||
)
|
||||
@@ -1333,7 +1336,7 @@ class ToolNode(RunnableCallable):
|
||||
return tool_call
|
||||
|
||||
tool_call_copy: ToolCall = copy(tool_call)
|
||||
injected_args = {}
|
||||
injected_args: dict[str, Any] = {}
|
||||
|
||||
# Inject state
|
||||
if injected.state:
|
||||
@@ -1361,14 +1364,20 @@ class ToolNode(RunnableCallable):
|
||||
# Extract state values
|
||||
if isinstance(state, dict):
|
||||
for tool_arg, state_field in injected.state.items():
|
||||
injected_args[tool_arg] = (
|
||||
state[state_field] if state_field else state
|
||||
)
|
||||
if not state_field:
|
||||
injected_args[tool_arg] = state
|
||||
elif state_field in state:
|
||||
injected_args[tool_arg] = state[state_field]
|
||||
elif tool_arg not in injected._optional_state_args:
|
||||
raise KeyError(state_field)
|
||||
else:
|
||||
for tool_arg, state_field in injected.state.items():
|
||||
injected_args[tool_arg] = (
|
||||
getattr(state, state_field) if state_field else state
|
||||
)
|
||||
if not state_field:
|
||||
injected_args[tool_arg] = state
|
||||
elif hasattr(state, state_field):
|
||||
injected_args[tool_arg] = getattr(state, state_field)
|
||||
elif tool_arg not in injected._optional_state_args:
|
||||
raise AttributeError(state_field)
|
||||
|
||||
# Inject store
|
||||
if injected.store:
|
||||
@@ -1569,6 +1578,7 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
|
||||
- `context`: Runtime context (shared with `Runtime`)
|
||||
- `store`: `BaseStore` instance for persistent storage (shared with `Runtime`)
|
||||
- `stream_writer`: `StreamWriter` for streaming output (shared with `Runtime`)
|
||||
- `tools`: List of all available `BaseTool` instances
|
||||
|
||||
No `Annotated` wrapper is needed - just use `runtime: ToolRuntime`
|
||||
as a parameter.
|
||||
@@ -1611,6 +1621,7 @@ class ToolRuntime(_DirectlyInjectedToolArg, Generic[ContextT, StateT]):
|
||||
context: ContextT
|
||||
config: RunnableConfig
|
||||
stream_writer: StreamWriter
|
||||
tools: list[BaseTool]
|
||||
tool_call_id: str | None
|
||||
store: BaseStore | None
|
||||
execution_info: ExecutionInfo | None = None
|
||||
@@ -1859,6 +1870,7 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
|
||||
store_arg: str | None = None
|
||||
runtime_arg: str | None = None
|
||||
all_injected_keys: set[str] = set()
|
||||
_optional_state_args: set[str] = set()
|
||||
|
||||
for name, type_ in all_annotations.items():
|
||||
# Track all InjectedToolArg-annotated params (including custom subclasses)
|
||||
@@ -1873,6 +1885,9 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
|
||||
if state_inj := _get_injection_from_type(type_, InjectedState):
|
||||
if isinstance(state_inj, InjectedState) and state_inj.field:
|
||||
state_args[name] = state_inj.field
|
||||
field_info = full_schema.model_fields.get(name)
|
||||
if field_info and not field_info.is_required():
|
||||
_optional_state_args.add(name)
|
||||
else:
|
||||
state_args[name] = None
|
||||
|
||||
@@ -1889,4 +1904,5 @@ def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
|
||||
store=store_arg,
|
||||
runtime=runtime_arg,
|
||||
all_injected_keys=all_injected_keys,
|
||||
_optional_state_args=_optional_state_args,
|
||||
)
|
||||
|
||||
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
|
||||
|
||||
[project]
|
||||
name = "langgraph-prebuilt"
|
||||
version = "1.0.9"
|
||||
version = "1.0.10"
|
||||
description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
|
||||
authors = []
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@@ -0,0 +1,285 @@
|
||||
"""Test InjectedState with NotRequired state fields.
|
||||
|
||||
This tests the fix for https://github.com/langchain-ai/langchain/issues/35585
|
||||
|
||||
When using InjectedState(<field>) on a tool parameter, and the referenced field is
|
||||
declared as NotRequired in the custom state schema, the ToolNode should gracefully
|
||||
handle missing fields by injecting None instead of raising KeyError.
|
||||
"""
|
||||
|
||||
import sys
|
||||
from typing import Annotated
|
||||
|
||||
import pytest
|
||||
from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, ToolMessage
|
||||
from langchain_core.tools import tool
|
||||
from langgraph.graph.message import add_messages
|
||||
from pydantic import BaseModel, Field
|
||||
from typing_extensions import NotRequired
|
||||
|
||||
from langgraph.prebuilt import InjectedState, ToolNode, create_react_agent
|
||||
from langgraph.prebuilt.chat_agent_executor import AgentState
|
||||
|
||||
from .model import FakeToolCallingModel
|
||||
|
||||
|
||||
class CustomAgentStateWithNotRequired(AgentState):
|
||||
"""Custom state with a NotRequired field (TypedDict style)."""
|
||||
|
||||
city: NotRequired[str]
|
||||
|
||||
|
||||
class CustomAgentStatePydanticWithDefault(BaseModel):
|
||||
"""Custom state with Optional field and default (Pydantic style)."""
|
||||
|
||||
messages: Annotated[list[AnyMessage], add_messages]
|
||||
remaining_steps: int = Field(default=10)
|
||||
city: str | None = Field(default=None)
|
||||
|
||||
|
||||
@tool
|
||||
def get_weather(city: Annotated[str | None, InjectedState("city")] = None) -> str:
|
||||
"""Get weather for a given city."""
|
||||
if city is None:
|
||||
return "No city provided"
|
||||
return f"It's always sunny in {city}!"
|
||||
|
||||
|
||||
def _create_mock_runtime(
|
||||
state: dict | None = None,
|
||||
store=None,
|
||||
):
|
||||
"""Create a mock Runtime for testing ToolNode directly."""
|
||||
from unittest.mock import Mock
|
||||
|
||||
from langgraph.runtime import Runtime
|
||||
|
||||
mock_runtime = Mock(spec=Runtime)
|
||||
mock_runtime.context = {}
|
||||
return mock_runtime
|
||||
|
||||
|
||||
def _create_config_with_runtime(store=None, state=None):
|
||||
"""Create a RunnableConfig with mocked runtime for direct ToolNode testing."""
|
||||
from langgraph.prebuilt.tool_node import ToolRuntime
|
||||
|
||||
tool_runtime = ToolRuntime(
|
||||
state=state or {},
|
||||
config={},
|
||||
context={},
|
||||
store=store,
|
||||
stream_writer=None,
|
||||
tools=[],
|
||||
tool_call_id="test_id",
|
||||
)
|
||||
return {
|
||||
"configurable": {
|
||||
"__pregel_runtime": _create_mock_runtime(),
|
||||
"__tool_runtime__": tool_runtime,
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.version_info < (3, 11),
|
||||
reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
|
||||
)
|
||||
def test_injected_state_not_required_field_missing_injects_none():
|
||||
"""Test that InjectedState with NotRequired field injects None when field is missing.
|
||||
|
||||
This verifies the fix for https://github.com/langchain-ai/langchain/issues/35585
|
||||
"""
|
||||
tool_node = ToolNode([get_weather])
|
||||
|
||||
tool_call = {
|
||||
"name": "get_weather",
|
||||
"args": {},
|
||||
"id": "call_1",
|
||||
"type": "tool_call",
|
||||
}
|
||||
ai_msg = AIMessage("Let me check the weather", tool_calls=[tool_call])
|
||||
|
||||
# State WITHOUT the "city" field - should inject None instead of raising KeyError
|
||||
state_without_city: CustomAgentStateWithNotRequired = {
|
||||
"messages": [HumanMessage("What's the weather?"), ai_msg],
|
||||
}
|
||||
|
||||
result = tool_node.invoke(
|
||||
state_without_city,
|
||||
config=_create_config_with_runtime(state=state_without_city),
|
||||
)
|
||||
|
||||
assert len(result["messages"]) == 1
|
||||
tool_msg = result["messages"][0]
|
||||
assert isinstance(tool_msg, ToolMessage)
|
||||
assert "No city provided" in tool_msg.content
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.version_info < (3, 11),
|
||||
reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
|
||||
)
|
||||
def test_injected_state_not_required_field_present_works():
|
||||
"""Test that InjectedState with NotRequired field works when field IS present."""
|
||||
tool_node = ToolNode([get_weather])
|
||||
|
||||
tool_call = {
|
||||
"name": "get_weather",
|
||||
"args": {},
|
||||
"id": "call_1",
|
||||
"type": "tool_call",
|
||||
}
|
||||
ai_msg = AIMessage("Let me check the weather", tool_calls=[tool_call])
|
||||
|
||||
# State WITH the "city" field - this should work
|
||||
state_with_city: CustomAgentStateWithNotRequired = {
|
||||
"messages": [HumanMessage("What's the weather?"), ai_msg],
|
||||
"city": "San Francisco",
|
||||
}
|
||||
|
||||
result = tool_node.invoke(
|
||||
state_with_city,
|
||||
config=_create_config_with_runtime(state=state_with_city),
|
||||
)
|
||||
|
||||
assert len(result["messages"]) == 1
|
||||
tool_msg = result["messages"][0]
|
||||
assert isinstance(tool_msg, ToolMessage)
|
||||
assert "San Francisco" in tool_msg.content
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.version_info < (3, 11),
|
||||
reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
|
||||
)
|
||||
def test_create_react_agent_injected_state_not_required_field_missing():
|
||||
"""Test create_react_agent with InjectedState using NotRequired field that is missing.
|
||||
|
||||
This verifies the fix for https://github.com/langchain-ai/langchain/issues/35585
|
||||
"""
|
||||
model = FakeToolCallingModel(
|
||||
tool_calls=[
|
||||
[{"name": "get_weather", "args": {}, "id": "call_1"}],
|
||||
[], # No more tool calls, agent should stop
|
||||
]
|
||||
)
|
||||
|
||||
agent = create_react_agent(
|
||||
model,
|
||||
tools=[get_weather],
|
||||
state_schema=CustomAgentStateWithNotRequired,
|
||||
)
|
||||
|
||||
# Invoke WITHOUT the city field - should work, injecting None
|
||||
result = agent.invoke(
|
||||
{"messages": [HumanMessage("What's the weather?")]},
|
||||
)
|
||||
|
||||
# Check that the tool was called successfully with None injected
|
||||
messages = result["messages"]
|
||||
tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
|
||||
assert len(tool_messages) == 1
|
||||
assert "No city provided" in tool_messages[0].content
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.version_info < (3, 11),
|
||||
reason="InjectedState field extraction from Optional[Annotated[...]] not supported on Python <3.11",
|
||||
)
|
||||
def test_create_react_agent_injected_state_not_required_field_present():
|
||||
"""Test create_react_agent with InjectedState using NotRequired field that IS present."""
|
||||
model = FakeToolCallingModel(
|
||||
tool_calls=[
|
||||
[{"name": "get_weather", "args": {}, "id": "call_1"}],
|
||||
[], # No more tool calls, agent should stop
|
||||
]
|
||||
)
|
||||
|
||||
agent = create_react_agent(
|
||||
model,
|
||||
tools=[get_weather],
|
||||
state_schema=CustomAgentStateWithNotRequired,
|
||||
)
|
||||
|
||||
# Invoke WITH the city field
|
||||
result = agent.invoke(
|
||||
{
|
||||
"messages": [HumanMessage("What's the weather?")],
|
||||
"city": "San Francisco",
|
||||
},
|
||||
)
|
||||
|
||||
# Check that the tool was called successfully
|
||||
messages = result["messages"]
|
||||
tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
|
||||
assert len(tool_messages) == 1
|
||||
assert "San Francisco" in tool_messages[0].content
|
||||
|
||||
|
||||
@tool
|
||||
def get_weather_optional(city: Annotated[str | None, InjectedState("city")]) -> str:
|
||||
"""Get weather for a given city (accepts None)."""
|
||||
if city is None:
|
||||
return "Please provide a city!"
|
||||
return f"It's always sunny in {city}!"
|
||||
|
||||
|
||||
def test_pydantic_state_with_default_field_missing_works():
|
||||
"""Test that Pydantic state with Optional field and default=None works when field is missing.
|
||||
|
||||
This is the workaround suggested in the issue comments - using Pydantic BaseModel
|
||||
with `city: Optional[str] = Field(default=None)` instead of TypedDict with NotRequired.
|
||||
"""
|
||||
model = FakeToolCallingModel(
|
||||
tool_calls=[
|
||||
[{"name": "get_weather_optional", "args": {}, "id": "call_1"}],
|
||||
[], # No more tool calls, agent should stop
|
||||
]
|
||||
)
|
||||
|
||||
agent = create_react_agent(
|
||||
model,
|
||||
tools=[get_weather_optional],
|
||||
state_schema=CustomAgentStatePydanticWithDefault,
|
||||
)
|
||||
|
||||
# Invoke WITHOUT the city field - should work because Pydantic provides default
|
||||
result = agent.invoke(
|
||||
{"messages": [HumanMessage("What's the weather?")]},
|
||||
)
|
||||
|
||||
# Check that the tool was called successfully with None
|
||||
messages = result["messages"]
|
||||
tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
|
||||
assert len(tool_messages) == 1
|
||||
assert "Please provide a city!" in tool_messages[0].content
|
||||
|
||||
|
||||
def test_pydantic_state_with_default_field_present_works():
|
||||
"""Test that Pydantic state with Optional field works when field IS present."""
|
||||
model = FakeToolCallingModel(
|
||||
tool_calls=[
|
||||
[{"name": "get_weather_optional", "args": {}, "id": "call_1"}],
|
||||
[], # No more tool calls, agent should stop
|
||||
]
|
||||
)
|
||||
|
||||
agent = create_react_agent(
|
||||
model,
|
||||
tools=[get_weather_optional],
|
||||
state_schema=CustomAgentStatePydanticWithDefault,
|
||||
)
|
||||
|
||||
# Invoke WITH the city field
|
||||
result = agent.invoke(
|
||||
{
|
||||
"messages": [HumanMessage("What's the weather?")],
|
||||
"city": "San Francisco",
|
||||
},
|
||||
)
|
||||
|
||||
# Check that the tool was called successfully
|
||||
messages = result["messages"]
|
||||
tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
|
||||
assert len(tool_messages) == 1
|
||||
assert "San Francisco" in tool_messages[0].content
|
||||
@@ -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
|
||||
@@ -2016,8 +2016,8 @@ async def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call_async()
|
||||
assert tool_message.tool_call_id == "call_dynamic_2"
|
||||
|
||||
|
||||
def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
|
||||
"""Test that execution_info and server_info are forwarded from Runtime to ToolRuntime."""
|
||||
def test_tool_runtime_forwards_execution_info_server_info_and_tools() -> None:
|
||||
"""Test that execution_info, server_info, and tools are forwarded from Runtime to ToolRuntime."""
|
||||
from langgraph.runtime import ExecutionInfo, ServerInfo
|
||||
|
||||
exec_info = ExecutionInfo(
|
||||
@@ -2043,9 +2043,15 @@ def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
|
||||
"""Tool that captures runtime info."""
|
||||
captured["execution_info"] = runtime.execution_info
|
||||
captured["server_info"] = runtime.server_info
|
||||
captured["tools"] = runtime.tools
|
||||
return "ok"
|
||||
|
||||
node = ToolNode([info_tool])
|
||||
@dec_tool
|
||||
def other_tool(y: int) -> str:
|
||||
"""Another tool available to the runtime."""
|
||||
return str(y)
|
||||
|
||||
node = ToolNode([info_tool, other_tool])
|
||||
tool_call = {
|
||||
"name": "info_tool",
|
||||
"args": {"x": 1},
|
||||
@@ -2054,17 +2060,21 @@ def test_tool_runtime_forwards_execution_info_and_server_info() -> None:
|
||||
}
|
||||
msg = AIMessage("", tool_calls=[tool_call])
|
||||
config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
|
||||
node.invoke({"messages": [msg]}, config=config)
|
||||
result = node.invoke({"messages": [msg]}, config=config)
|
||||
|
||||
assert result["messages"][-1].content == "ok"
|
||||
assert captured["execution_info"] is exec_info
|
||||
assert captured["execution_info"].thread_id == "t-1"
|
||||
assert captured["execution_info"].task_id == "tk-1"
|
||||
assert captured["server_info"] is server_info
|
||||
assert captured["server_info"].assistant_id == "asst-1"
|
||||
assert [tool.name for tool in captured["tools"]] == ["info_tool", "other_tool"]
|
||||
|
||||
|
||||
async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> None:
|
||||
"""Test that execution_info and server_info are forwarded in async path."""
|
||||
async def test_tool_runtime_forwards_execution_info_server_info_and_tools_async() -> (
|
||||
None
|
||||
):
|
||||
"""Test that execution_info, server_info, and tools are forwarded in async path."""
|
||||
from langgraph.runtime import ExecutionInfo, ServerInfo
|
||||
|
||||
exec_info = ExecutionInfo(
|
||||
@@ -2090,9 +2100,15 @@ async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> N
|
||||
"""Async tool that captures runtime info."""
|
||||
captured["execution_info"] = runtime.execution_info
|
||||
captured["server_info"] = runtime.server_info
|
||||
captured["tools"] = runtime.tools
|
||||
return "ok"
|
||||
|
||||
node = ToolNode([info_tool_async])
|
||||
@dec_tool
|
||||
async def other_tool_async(y: int) -> str:
|
||||
"""Another async tool available to the runtime."""
|
||||
return str(y)
|
||||
|
||||
node = ToolNode([info_tool_async, other_tool_async])
|
||||
tool_call = {
|
||||
"name": "info_tool_async",
|
||||
"args": {"x": 1},
|
||||
@@ -2101,12 +2117,17 @@ async def test_tool_runtime_forwards_execution_info_and_server_info_async() -> N
|
||||
}
|
||||
msg = AIMessage("", tool_calls=[tool_call])
|
||||
config: RunnableConfig = {"configurable": {"__pregel_runtime": mock_runtime}}
|
||||
await node.ainvoke({"messages": [msg]}, config=config)
|
||||
result = await node.ainvoke({"messages": [msg]}, config=config)
|
||||
|
||||
assert result["messages"][-1].content == "ok"
|
||||
assert captured["execution_info"] is exec_info
|
||||
assert captured["execution_info"].thread_id == "t-2"
|
||||
assert captured["server_info"] is server_info
|
||||
assert captured["server_info"].graph_id == "graph-2"
|
||||
assert [tool.name for tool in captured["tools"]] == [
|
||||
"info_tool_async",
|
||||
"other_tool_async",
|
||||
]
|
||||
|
||||
|
||||
# --- InjectedToolArg security tests ---
|
||||
|
||||
Generated
+11
-10
@@ -249,7 +249,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "1.3.0a2"
|
||||
version = "1.3.0"
|
||||
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/92/fe/20190232d9b513242899dbb0c2bb77e31b4d61e343743adbe90ebc2603d2/langchain_core-1.3.0.tar.gz", hash = "sha256:14a39f528bf459aa3aa40d0a7f7f1bae7520d435ef991ae14a4ceb74d8c49046", size = 860755, upload-time = "2026-04-17T14:51:38.298Z" }
|
||||
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/f8/e2/dbfa347aa072a6dc4cd38d6f9ebfc730b4c14c258c47f480f4c5c546f177/langchain_core-1.3.0-py3-none-any.whl", hash = "sha256:baf16ee028475df177b9ab8869a751c79406d64a6f12125b93802991b566cced", size = 515140, upload-time = "2026-04-17T14:51:36.274Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.1.7a2"
|
||||
version = "1.1.9"
|
||||
source = { editable = "../langgraph" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -281,7 +281,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain-core", specifier = "==1.3.0a2" },
|
||||
{ name = "langchain-core", specifier = ">=1.3.0,<2" },
|
||||
{ name = "langgraph-checkpoint", editable = "../checkpoint" },
|
||||
{ name = "langgraph-prebuilt", editable = "." },
|
||||
{ name = "langgraph-sdk", editable = "../sdk-py" },
|
||||
@@ -352,7 +352,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.0.1"
|
||||
version = "4.0.2"
|
||||
source = { editable = "../checkpoint" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -490,7 +490,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-prebuilt"
|
||||
version = "1.0.9"
|
||||
version = "1.0.10"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -619,7 +619,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.6.4"
|
||||
version = "0.7.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
@@ -629,11 +629,12 @@ dependencies = [
|
||||
{ name = "requests" },
|
||||
{ name = "requests-toolbelt" },
|
||||
{ name = "uuid-utils" },
|
||||
{ name = "xxhash" },
|
||||
{ name = "zstandard" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e7/85/9c7933052a997da1b85bc5c774f3865e9b1da1c8d71541ea133178b13229/langsmith-0.6.4.tar.gz", hash = "sha256:36f7223a01c218079fbb17da5e536ebbaf5c1468c028abe070aa3ae59bc99ec8", size = 919964, upload-time = "2026-01-15T20:02:28.873Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/66/0f/09a6637a7ba777eb307b7c80852d9ee26438e2bdafbad6fcc849ff9d9192/langsmith-0.6.4-py3-none-any.whl", hash = "sha256:ac4835860160be371042c7adbba3cb267bcf8d96a5ea976c33a8a4acad6c5486", size = 283503, upload-time = "2026-01-15T20:02:26.662Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+10
-10
@@ -262,7 +262,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "1.3.0a2"
|
||||
version = "1.3.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jsonpatch" },
|
||||
@@ -274,14 +274,14 @@ dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
{ name = "uuid-utils" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/af/bc/0bff31fcaff174d86031cc713471a3e85ed4ec8e5cd95ad0217f2aced20e/langchain_core-1.3.0a2.tar.gz", hash = "sha256:52d978c84552b74b9a3f16c1fced84f9e27cc96d7a67c601925ce6cbc4ea3cf9", size = 854580, upload-time = "2026-04-13T14:37:55.745Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/92/fe/20190232d9b513242899dbb0c2bb77e31b4d61e343743adbe90ebc2603d2/langchain_core-1.3.0.tar.gz", hash = "sha256:14a39f528bf459aa3aa40d0a7f7f1bae7520d435ef991ae14a4ceb74d8c49046", size = 860755, upload-time = "2026-04-17T14:51:38.298Z" }
|
||||
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/f8/e2/dbfa347aa072a6dc4cd38d6f9ebfc730b4c14c258c47f480f4c5c546f177/langchain_core-1.3.0-py3-none-any.whl", hash = "sha256:baf16ee028475df177b9ab8869a751c79406d64a6f12125b93802991b566cced", size = 515140, upload-time = "2026-04-17T14:51:36.274Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.1.7a2"
|
||||
version = "1.1.9"
|
||||
source = { editable = "../langgraph" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -294,7 +294,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain-core", specifier = "==1.3.0a2" },
|
||||
{ name = "langchain-core", specifier = ">=1.3.0,<2" },
|
||||
{ name = "langgraph-checkpoint", editable = "../checkpoint" },
|
||||
{ name = "langgraph-prebuilt", editable = "../prebuilt" },
|
||||
{ name = "langgraph-sdk", editable = "." },
|
||||
@@ -365,7 +365,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.0.1"
|
||||
version = "4.0.2"
|
||||
source = { editable = "../checkpoint" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -413,7 +413,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-prebuilt"
|
||||
version = "1.0.9"
|
||||
version = "1.0.10"
|
||||
source = { editable = "../prebuilt" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -534,7 +534,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.7.20"
|
||||
version = "0.7.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
@@ -547,9 +547,9 @@ dependencies = [
|
||||
{ name = "xxhash" },
|
||||
{ name = "zstandard" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/80/c6/cbdc6638207f68a3c61ec0b64fa593f6b11de3170d03c852238c31b54960/langsmith-0.7.20.tar.gz", hash = "sha256:fa983a74f75648ee0e80d3f9751162b6f9a438896d5f9bdb6cba9abda451e234", size = 1134732, upload-time = "2026-03-18T00:03:39.129Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/11/696019490992db5c87774dc20515529ef42a01e1d770fb754ed6d9b12fb0/langsmith-0.7.31.tar.gz", hash = "sha256:331ee4f7c26bb5be4022b9859b7d7b122cbf8c9d01d9f530114c1914b0349ffb", size = 1178480, upload-time = "2026-04-14T17:55:41.242Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/e8/46/9294d4f49de6a8f08e8b83907713ca545459d87d474c6add15d31a36f5dc/langsmith-0.7.20-py3-none-any.whl", hash = "sha256:0162faf791ea48d69009a12a3da917468556b99cf5d5fcacbb8cda064262e118", size = 359314, upload-time = "2026-03-18T00:03:37.59Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/1d/a1/a013cf458c301cda86a213dd153ce0a01c93f1ab5833f951e6a44c9763ce/langsmith-0.7.31-py3-none-any.whl", hash = "sha256:0291d49203f6e80dda011af1afda61eb0595a4d697adb684590a8805e1d61fb6", size = 373276, upload-time = "2026-04-14T17:55:39.677Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Reference in New Issue
Block a user