mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-30 21:45:08 +02:00
fix(langgraph): give each bulk_update_state update its own task id
An update whose node has no pending task to reuse was stored under
uuid5(checkpoint_id, INTERRUPT), so every such update in one superstep
shared a task id. Savers keep one write per (task_id, idx), so all but the
first update's writes were dropped. Plain channels were unaffected, since
their value is stored in the new checkpoint, but a DeltaChannel replays
those writes and lost every update after the first.
The ith update now gets uuid5(checkpoint_id, f"{INTERRUPT}:{i}"). The first
keeps the old id, so a single update stores exactly what it did before.
This commit is contained in:
@@ -1950,7 +1950,7 @@ class Pregel(
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run_tasks: list[PregelTaskWrites] = []
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run_task_ids: list[str] = []
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for as_node, values, provided_task_id in valid_updates:
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for i, (as_node, values, provided_task_id) in enumerate(valid_updates):
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# create task to run all writers of the chosen node
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writers = self.nodes[as_node].flat_writers
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if not writers:
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@@ -1964,7 +1964,7 @@ class Pregel(
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task_id = provided_task_id or (
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prepared_task_ids.popleft()
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if prepared_task_ids
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else str(uuid5(UUID(checkpoint["id"]), INTERRUPT))
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else _update_task_id(checkpoint["id"], i)
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)
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run_tasks.append(task)
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run_task_ids.append(task_id)
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@@ -2410,7 +2410,7 @@ class Pregel(
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run_tasks: list[PregelTaskWrites] = []
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run_task_ids: list[str] = []
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for as_node, values, provided_task_id in valid_updates:
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for i, (as_node, values, provided_task_id) in enumerate(valid_updates):
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# create task to run all writers of the chosen node
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writers = self.nodes[as_node].flat_writers
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if not writers:
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@@ -2424,7 +2424,7 @@ class Pregel(
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task_id = provided_task_id or (
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prepared_task_ids.popleft()
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if prepared_task_ids
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else str(uuid5(UUID(checkpoint["id"]), INTERRUPT))
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else _update_task_id(checkpoint["id"], i)
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)
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run_tasks.append(task)
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run_task_ids.append(task_id)
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@@ -4172,6 +4172,16 @@ class Pregel(
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await self.cache.aclear(namespaces)
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def _update_task_id(checkpoint_id: str, i: int) -> str:
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"""Task id for the `i`th update of a superstep that has no task to reuse.
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Savers keep one write per `(task_id, idx)`, so updates sharing an id lose
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all but the first one's writes, which a `DeltaChannel` replays from. The
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first update keeps the id a lone update has always had.
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"""
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return str(uuid5(UUID(checkpoint_id), INTERRUPT if i == 0 else f"{INTERRUPT}:{i}"))
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def _trigger_to_nodes(nodes: dict[str, PregelNode]) -> Mapping[str, Sequence[str]]:
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"""Index from a trigger to nodes that depend on it."""
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trigger_to_nodes: defaultdict[str, list[str]] = defaultdict(list)
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@@ -20,6 +20,7 @@ from typing import Annotated, Any
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import pytest
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from langchain_core.messages import HumanMessage
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from langgraph.checkpoint.base import BaseCheckpointSaver
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from langgraph.checkpoint.memory import InMemorySaver
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from langgraph.checkpoint.serde.types import _DeltaSnapshot
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from typing_extensions import TypedDict
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@@ -27,16 +28,17 @@ from typing_extensions import TypedDict
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from langgraph.channels.delta import DeltaChannel
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from langgraph.graph import START, StateGraph
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from langgraph.graph.message import _messages_delta_reducer
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from langgraph.types import StateUpdate
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from langgraph.types import StateSnapshot, StateUpdate
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pytestmark = pytest.mark.anyio
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def _build_graph(
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checkpointer: InMemorySaver,
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checkpointer: BaseCheckpointSaver,
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*,
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two_nodes: bool = False,
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snapshot_frequency: int = 1000,
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interrupt_before: list[str] | None = None,
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) -> Any:
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"""Compile a minimal DeltaChannel-backed `messages` graph.
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@@ -63,7 +65,7 @@ def _build_graph(
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builder.set_finish_point("assistant")
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else:
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builder.set_finish_point("model")
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return builder.compile(checkpointer=checkpointer)
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return builder.compile(checkpointer=checkpointer, interrupt_before=interrupt_before)
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# ---------------------------------------------------------------------------
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@@ -273,10 +275,6 @@ def test_bulk_update_state_multi_task_per_superstep_delta_channel() -> None:
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that each call `put_writes`. Guards the regression where moving
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`put_writes` outside the per-task loop would persist only the last
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task's writes.
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Explicit `task_id`s are required to disambiguate writes belonging to
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different `StateUpdate`s targeting the same node — otherwise both share
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the deterministic interrupt-derived id and collide in the saver.
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"""
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saver = InMemorySaver()
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@@ -310,6 +308,92 @@ def test_bulk_update_state_multi_task_per_superstep_delta_channel() -> None:
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assert sorted(ids) == ["m1", "m2"]
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def _update(content: str, as_node: str) -> StateUpdate:
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return StateUpdate(
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values={"messages": [HumanMessage(content=content, id=content)]},
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as_node=as_node,
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)
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def _contents(state: StateSnapshot) -> list[str]:
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return [m.content for m in state.values["messages"]]
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def test_bulk_update_state_keeps_every_update_without_task_ids(
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sync_checkpointer: BaseCheckpointSaver,
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) -> None:
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graph = _build_graph(sync_checkpointer, two_nodes=True)
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config = {"configurable": {"thread_id": "bulk-no-task-ids"}}
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graph.invoke({"messages": [HumanMessage(content="hi", id="hi")]}, config)
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graph.bulk_update_state(
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config,
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[
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[
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_update("first", "model"),
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_update("second", "model"),
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_update("third", "assistant"),
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]
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],
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)
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contents = _contents(graph.get_state(config))
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assert sorted(contents) == ["first", "hi", "second", "third"], (
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f"every update's writes must persist; got {contents}"
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)
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async def test_abulk_update_state_keeps_every_update_without_task_ids(
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async_checkpointer: BaseCheckpointSaver,
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) -> None:
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graph = _build_graph(async_checkpointer, two_nodes=True)
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config = {"configurable": {"thread_id": "bulk-no-task-ids"}}
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await graph.ainvoke({"messages": [HumanMessage(content="hi", id="hi")]}, config)
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await graph.abulk_update_state(
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config,
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[
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[
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_update("first", "model"),
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_update("second", "model"),
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_update("third", "assistant"),
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]
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],
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)
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contents = _contents(await graph.aget_state(config))
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assert sorted(contents) == ["first", "hi", "second", "third"], (
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f"every update's writes must persist; got {contents}"
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)
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def test_bulk_update_state_keeps_every_update_next_to_a_pending_task(
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sync_checkpointer: BaseCheckpointSaver,
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) -> None:
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graph = _build_graph(
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sync_checkpointer, two_nodes=True, interrupt_before=["assistant"]
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)
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config = {"configurable": {"thread_id": "bulk-pending-task"}}
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graph.invoke({"messages": [HumanMessage(content="hi", id="hi")]}, config)
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assert graph.get_state(config).next == ("assistant",)
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graph.bulk_update_state(
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config,
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[
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[
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_update("first", "assistant"),
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_update("second", "model"),
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_update("third", "model"),
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]
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],
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)
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contents = _contents(graph.get_state(config))
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assert sorted(contents) == ["first", "hi", "second", "third"], (
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f"every update's writes must persist; got {contents}"
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)
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# ---------------------------------------------------------------------------
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# Public-API observation of fresh-thread checkpoint shape
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# ---------------------------------------------------------------------------
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