Files
langgraph/libs/langgraph/tests/test_interruption.py
T
Baihao WangandGitHub 5965d72ff7 fix(langgraph,prebuilt): stop ToolNode from swallowing invalid resume values (#9232)
**Problem.** `interrupt(response_schema=...)` checks a human's answer
when the graph resumes. If the answer doesn't match the schema, the
resume fails, nothing is saved, and the human can answer again (#8886).
That works when the interrupt runs in a graph node, but not when it runs
inside a tool: either the tool calls `interrupt()` itself, or it starts
a graph that does, such as a subagent called as a tool. There, the
resume returns normally and the interrupt disappears.

**Why.** `interrupt()` raises a `pydantic.ValidationError` for an
invalid answer. When one comes out of a tool, `ToolNode` assumes the
model passed bad arguments, so it hands the error to the model ("Error
invoking tool … Please fix the error and try again") and the run carries
on. The human never sees the error, the model is blamed for it, and the
interrupt is no longer pending.

**Fix.** `interrupt()` still raises the same `ValidationError`, but
marks it so a new helper, `langgraph.errors.is_invalid_resume(error)`,
can recognize it. `ToolNode` re-raises these errors instead of handing
them to the model, whatever `handle_tool_errors` is set to, so a bad
answer fails the resume the same way inside a tool as outside one:
nothing is saved and the interrupt can be answered again. Every other
`ValidationError` from a tool is handled as before.

**Also fixed, in the same error handling.** With `wrap_tool_call` set
and a `handle_tool_errors` other than the default (for example `True`),
`ToolNode` turned any exception from the wrapper into an error
`ToolMessage`, including `GraphInterrupt`. So an interrupt in that setup
never paused: the model got `Error: GraphInterrupt(...)` instead.
Interrupts now propagate there too, as they already do without a
wrapper. `create_agent` uses the default handler, so it was not
affected.

**Compatibility.** Not a breaking change: the error type is unchanged.
Worth a careful look: a wrapped `ToolNode` with a non-default
`handle_tool_errors` now pauses on interrupts instead of returning them
to the model as errors. With an older `langgraph` that doesn't have
`is_invalid_resume`, `ToolNode` keeps today's behavior.
2026-10-08 12:59:25 -07:00

254 lines
8.3 KiB
Python

from dataclasses import dataclass
from typing import Any
import pytest
from langgraph.checkpoint.base import BaseCheckpointSaver
from pydantic import BaseModel, ValidationError
from typing_extensions import TypedDict
from langgraph.errors import is_invalid_resume
from langgraph.graph import END, START, StateGraph
from langgraph.types import Command, Durability, Interrupt, interrupt
from tests.any_str import AnyStr
pytestmark = pytest.mark.anyio
def test_interruption_without_state_updates(
sync_checkpointer: BaseCheckpointSaver, durability: Durability
) -> None:
"""Test interruption without state updates. This test confirms that
interrupting doesn't require a state key having been updated in the prev step"""
class State(TypedDict):
input: str
def noop(_state):
pass
builder = StateGraph(State)
builder.add_node("step_1", noop)
builder.add_node("step_2", noop)
builder.add_node("step_3", noop)
builder.add_edge(START, "step_1")
builder.add_edge("step_1", "step_2")
builder.add_edge("step_2", "step_3")
builder.add_edge("step_3", END)
graph = builder.compile(checkpointer=sync_checkpointer, interrupt_after="*")
initial_input = {"input": "hello world"}
thread = {"configurable": {"thread_id": "1"}}
graph.invoke(initial_input, thread, durability=durability)
assert graph.get_state(thread).next == ("step_2",)
n_checkpoints = len([c for c in graph.get_state_history(thread)])
assert n_checkpoints == (3 if durability != "exit" else 1)
graph.invoke(None, thread, durability=durability)
assert graph.get_state(thread).next == ("step_3",)
n_checkpoints = len([c for c in graph.get_state_history(thread)])
assert n_checkpoints == (4 if durability != "exit" else 2)
graph.invoke(None, thread, durability=durability)
assert graph.get_state(thread).next == ()
n_checkpoints = len([c for c in graph.get_state_history(thread)])
assert n_checkpoints == (5 if durability != "exit" else 3)
async def test_interruption_without_state_updates_async(
async_checkpointer: BaseCheckpointSaver, durability: Durability
) -> None:
"""Test interruption without state updates. This test confirms that
interrupting doesn't require a state key having been updated in the prev step"""
class State(TypedDict):
input: str
async def noop(_state):
pass
builder = StateGraph(State)
builder.add_node("step_1", noop)
builder.add_node("step_2", noop)
builder.add_node("step_3", noop)
builder.add_edge(START, "step_1")
builder.add_edge("step_1", "step_2")
builder.add_edge("step_2", "step_3")
builder.add_edge("step_3", END)
graph = builder.compile(checkpointer=async_checkpointer, interrupt_after="*")
initial_input = {"input": "hello world"}
thread = {"configurable": {"thread_id": "1"}}
await graph.ainvoke(initial_input, thread, durability=durability)
assert (await graph.aget_state(thread)).next == ("step_2",)
n_checkpoints = len([c async for c in graph.aget_state_history(thread)])
assert n_checkpoints == (3 if durability != "exit" else 1)
await graph.ainvoke(None, thread, durability=durability)
assert (await graph.aget_state(thread)).next == ("step_3",)
n_checkpoints = len([c async for c in graph.aget_state_history(thread)])
assert n_checkpoints == (4 if durability != "exit" else 2)
await graph.ainvoke(None, thread, durability=durability)
assert (await graph.aget_state(thread)).next == ()
n_checkpoints = len([c async for c in graph.aget_state_history(thread)])
assert n_checkpoints == (5 if durability != "exit" else 3)
class Decision(BaseModel):
approved: bool
note: str | None = None
class DecisionDict(TypedDict):
approved: bool
@dataclass
class DecisionData:
approved: bool
RAW_SCHEMA = {"type": "object", "properties": {"approved": {"type": "boolean"}}}
@pytest.mark.parametrize(
("response_schema", "expected_schema", "expected_answer"),
[
(None, None, {"approved": True, "extra": 1}),
(RAW_SCHEMA, RAW_SCHEMA, {"approved": True, "extra": 1}),
(Decision, Decision.model_json_schema(), Decision(approved=True)),
(
DecisionDict,
{
"properties": {"approved": {"title": "Approved", "type": "boolean"}},
"required": ["approved"],
"title": "DecisionDict",
"type": "object",
},
{"approved": True},
),
(
DecisionData,
{
"properties": {"approved": {"title": "Approved", "type": "boolean"}},
"required": ["approved"],
"title": "DecisionData",
"type": "object",
},
DecisionData(approved=True),
),
],
ids=["none", "raw_dict", "pydantic", "typeddict", "dataclass"],
)
def test_interrupt_response_schema(
sync_checkpointer: BaseCheckpointSaver,
response_schema: Any,
expected_schema: dict[str, Any] | None,
expected_answer: Any,
) -> None:
class State(TypedDict):
answer: Any
def node(state: State) -> State:
return {
"answer": interrupt(
{"question": "approve?"}, response_schema=response_schema
)
}
graph = (
StateGraph(State)
.add_node("node", node)
.add_edge(START, "node")
.compile(checkpointer=sync_checkpointer)
)
config = {"configurable": {"thread_id": "1"}}
expected = Interrupt(
value={"question": "approve?"}, id=AnyStr(), response_schema=expected_schema
)
assert list(graph.stream({"answer": None}, config)) == [
{"__interrupt__": (expected,)}
]
assert graph.get_state(config).tasks[0].interrupts == (expected,)
assert graph.invoke(Command(resume={"approved": True, "extra": 1}), config) == {
"answer": expected_answer
}
@pytest.mark.parametrize("resume_style", ["null", "map"])
def test_interrupt_response_schema_rejects_invalid_resume(
sync_checkpointer: BaseCheckpointSaver, resume_style: str
) -> None:
class State(TypedDict):
answer: Any
def node(state: State) -> State:
return {"answer": interrupt("approve?", response_schema=Decision)}
graph = (
StateGraph(State)
.add_node("node", node)
.add_edge(START, "node")
.compile(checkpointer=sync_checkpointer)
)
config = {"configurable": {"thread_id": "1"}}
graph.invoke({"answer": None}, config)
[pending] = graph.get_state(config).tasks[0].interrupts
def resume(value: dict[str, Any]) -> Command:
return Command(resume=value if resume_style == "null" else {pending.id: value})
with pytest.raises(ValidationError, match="approved") as exc_info:
graph.invoke(resume({"approved": "nope"}), config)
assert is_invalid_resume(exc_info.value)
assert graph.invoke(resume({"approved": False}), config) == {
"answer": Decision(approved=False)
}
def test_is_invalid_resume_ignores_other_errors() -> None:
with pytest.raises(ValidationError) as exc_info:
Decision.model_validate({"approved": "nope"})
assert not is_invalid_resume(exc_info.value)
assert not is_invalid_resume(ValueError("nope"))
@pytest.mark.parametrize("resume_style", ["null", "id_map"])
def test_interrupt_response_schema_invalid_resume_after_earlier_interrupt(
sync_checkpointer: BaseCheckpointSaver, resume_style: str
) -> None:
class State(TypedDict):
answer: Any
def node(state: State) -> State:
first = interrupt("first")
second = interrupt("approve?", response_schema=Decision)
return {"answer": [first, second]}
graph = (
StateGraph(State)
.add_node("node", node)
.add_edge(START, "node")
.compile(checkpointer=sync_checkpointer)
)
config = {"configurable": {"thread_id": "1"}}
graph.invoke({"answer": None}, config)
graph.invoke(Command(resume="ok"), config)
[pending] = graph.get_state(config).tasks[0].interrupts
def resume(value: dict[str, Any]) -> Command:
return Command(resume=value if resume_style == "null" else {pending.id: value})
with pytest.raises(ValidationError, match="approved"):
graph.invoke(resume({"approved": "nope"}), config)
assert graph.invoke(resume({"approved": True}), config) == {
"answer": ["ok", Decision(approved=True)]
}