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prebuilt: switch to executing parallel tool calls via Send by default (#4438)

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This commit is contained in:
Sydney Runkle
2025-05-05 09:49:09 -04:00
committed by GitHub
parent b19405b296 78f809bc52
commit a0a302dec5
4 changed files with 87 additions and 105 deletions
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libs/langgraph/tests/test_large_cases.py
+39 -87
View File
@@ -39,6 +39,7 @@ from langgraph.types import (
interrupt,
)
from tests.agents import AgentAction, AgentFinish
from tests.any_int import AnyInt
from tests.any_str import AnyDict, AnyStr, UnsortedSequence
from tests.conftest import (
ALL_CHECKPOINTERS_SYNC,
@@ -2480,13 +2481,15 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
]
}
assert [
events = [
c
for c in app.stream(
{"messages": [HumanMessage(content="what is weather in sf")]},
stream_mode="messages",
)
] == [
]
assert events[:3] == [
(
_AnyIdAIMessageChunk(
content="",
@@ -2528,8 +2531,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
{
"langgraph_step": 2,
"langgraph_node": "tools",
"langgraph_triggers": ("branch:to:tools",),
"langgraph_path": (PULL, "tools"),
"langgraph_triggers": (PUSH,),
"langgraph_path": (PUSH, AnyInt(), False),
"langgraph_checkpoint_ns": AnyStr("tools:"),
},
),
@@ -2578,6 +2581,9 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
"ls_model_type": "chat",
},
),
]
assert events[3:5] == UnsortedSequence(
(
_AnyIdToolMessage(
content="result for another",
@@ -2587,8 +2593,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
{
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": ("branch:to:tools",),
"langgraph_path": (PULL, "tools"),
"langgraph_triggers": (PUSH,),
"langgraph_path": (PUSH, AnyInt(), False),
"langgraph_checkpoint_ns": AnyStr("tools:"),
},
),
@@ -2601,11 +2607,13 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
{
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": ("branch:to:tools",),
"langgraph_path": (PULL, "tools"),
"langgraph_triggers": (PUSH,),
"langgraph_path": (PUSH, AnyInt(), False),
"langgraph_checkpoint_ns": AnyStr("tools:"),
},
),
)
assert events[5:] == [
(
_AnyIdAIMessageChunk(
content="answer",
@@ -2636,12 +2644,17 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
model.i = 0 # reset the model
assert (
app.invoke(
{"messages": [HumanMessage(content="what is weather in sf")]},
stream_mode="updates",
)[0]["agent"]["messages"]
== [
invoke_updates_events = app.invoke(
{"messages": [HumanMessage(content="what is weather in sf")]},
stream_mode="updates",
)
stream_updates_events = [
*app.stream({"messages": [HumanMessage(content="what is weather in sf")]})
]
for output in (invoke_updates_events, stream_updates_events):
assert output[:3] == [
{
"agent": {
"messages": [
@@ -2690,6 +2703,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
]
}
},
]
assert output[3:5] == UnsortedSequence(
{
"tools": {
"messages": [
@@ -2698,6 +2713,12 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
name="search_api",
tool_call_id="tool_call234",
),
]
}
},
{
"tools": {
"messages": [
_AnyIdToolMessage(
content="result for a third one",
name="search_api",
@@ -2706,79 +2727,10 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
]
}
},
{"agent": {"messages": [_AnyIdAIMessage(content="answer")]}},
][0]["agent"]["messages"]
)
assert [
*app.stream({"messages": [HumanMessage(content="what is weather in sf")]})
] == [
{
"agent": {
"messages": [
_AnyIdAIMessage(
content="",
tool_calls=[
{
"id": "tool_call123",
"name": "search_api",
"args": {"query": "query"},
},
],
)
]
}
},
{
"tools": {
"messages": [
_AnyIdToolMessage(
content="result for query",
name="search_api",
tool_call_id="tool_call123",
)
]
}
},
{
"agent": {
"messages": [
_AnyIdAIMessage(
content="",
tool_calls=[
{
"id": "tool_call234",
"name": "search_api",
"args": {"query": "another"},
},
{
"id": "tool_call567",
"name": "search_api",
"args": {"query": "a third one"},
},
],
)
]
}
},
{
"tools": {
"messages": [
_AnyIdToolMessage(
content="result for another",
name="search_api",
tool_call_id="tool_call234",
),
_AnyIdToolMessage(
content="result for a third one",
name="search_api",
tool_call_id="tool_call567",
),
]
}
},
{"agent": {"messages": [_AnyIdAIMessage(content="answer")]}},
]
)
assert output[5:] == [
{"agent": {"messages": [_AnyIdAIMessage(content="answer")]}}
]
@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
libs/langgraph/tests/test_large_cases_async.py
+34 -15
View File
@@ -35,7 +35,8 @@ from langgraph.prebuilt.tool_node import ToolNode
from langgraph.pregel import Channel, Pregel
from langgraph.store.memory import InMemoryStore
from langgraph.types import PregelTask, Send, StateSnapshot, StreamWriter
from tests.any_str import AnyDict, AnyStr
from tests.any_int import AnyInt
from tests.any_str import AnyDict, AnyStr, UnsortedSequence
from tests.conftest import (
ALL_CHECKPOINTERS_ASYNC,
REGULAR_CHECKPOINTERS_ASYNC,
@@ -2297,13 +2298,15 @@ async def test_prebuilt_tool_chat() -> None:
]
}
assert [
events = [
c
async for c in app.astream(
{"messages": [HumanMessage(content="what is weather in sf")]},
stream_mode="messages",
)
] == [
]
assert events[:3] == [
(
_AnyIdAIMessageChunk(
content="",
@@ -2329,7 +2332,7 @@ async def test_prebuilt_tool_chat() -> None:
"langgraph_step": 1,
"langgraph_node": "agent",
"langgraph_triggers": ("branch:to:agent",),
"langgraph_path": ("__pregel_pull", "agent"),
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"ls_provider": "fakechatmodel",
@@ -2345,8 +2348,8 @@ async def test_prebuilt_tool_chat() -> None:
{
"langgraph_step": 2,
"langgraph_node": "tools",
"langgraph_triggers": ("branch:to:tools",),
"langgraph_path": ("__pregel_pull", "tools"),
"langgraph_triggers": (PUSH,),
"langgraph_path": (PUSH, AnyInt(), False),
"langgraph_checkpoint_ns": AnyStr("tools:"),
},
),
@@ -2388,13 +2391,16 @@ async def test_prebuilt_tool_chat() -> None:
"langgraph_step": 3,
"langgraph_node": "agent",
"langgraph_triggers": ("branch:to:agent",),
"langgraph_path": ("__pregel_pull", "agent"),
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"ls_provider": "fakechatmodel",
"ls_model_type": "chat",
},
),
]
assert events[3:5] == UnsortedSequence(
(
_AnyIdToolMessage(
content="result for another",
@@ -2404,8 +2410,8 @@ async def test_prebuilt_tool_chat() -> None:
{
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": ("branch:to:tools",),
"langgraph_path": ("__pregel_pull", "tools"),
"langgraph_triggers": (PUSH,),
"langgraph_path": (PUSH, AnyInt(), False),
"langgraph_checkpoint_ns": AnyStr("tools:"),
},
),
@@ -2418,11 +2424,13 @@ async def test_prebuilt_tool_chat() -> None:
{
"langgraph_step": 4,
"langgraph_node": "tools",
"langgraph_triggers": ("branch:to:tools",),
"langgraph_path": ("__pregel_pull", "tools"),
"langgraph_triggers": (PUSH,),
"langgraph_path": (PUSH, AnyInt(), False),
"langgraph_checkpoint_ns": AnyStr("tools:"),
},
),
)
assert events[5:] == [
(
_AnyIdAIMessageChunk(
content="answer",
@@ -2431,7 +2439,7 @@ async def test_prebuilt_tool_chat() -> None:
"langgraph_step": 5,
"langgraph_node": "agent",
"langgraph_triggers": ("branch:to:agent",),
"langgraph_path": ("__pregel_pull", "agent"),
"langgraph_path": (PULL, "agent"),
"langgraph_checkpoint_ns": AnyStr("agent:"),
"checkpoint_ns": AnyStr("agent:"),
"ls_provider": "fakechatmodel",
@@ -2440,12 +2448,13 @@ async def test_prebuilt_tool_chat() -> None:
),
]
assert [
stream_updates_events = [
c
async for c in app.astream(
{"messages": [HumanMessage(content="what is weather in sf")]}
)
] == [
]
assert stream_updates_events[:3] == [
{
"agent": {
"messages": [
@@ -2494,6 +2503,8 @@ async def test_prebuilt_tool_chat() -> None:
]
}
},
]
assert stream_updates_events[3:5] == UnsortedSequence(
{
"tools": {
"messages": [
@@ -2502,6 +2513,12 @@ async def test_prebuilt_tool_chat() -> None:
name="search_api",
tool_call_id="tool_call234",
),
]
}
},
{
"tools": {
"messages": [
_AnyIdToolMessage(
content="result for a third one",
name="search_api",
@@ -2510,7 +2527,9 @@ async def test_prebuilt_tool_chat() -> None:
]
}
},
{"agent": {"messages": [_AnyIdAIMessage(content="answer")]}},
)
assert stream_updates_events[5:] == [
{"agent": {"messages": [_AnyIdAIMessage(content="answer")]}}
]
libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py
+8 -1
View File
@@ -277,7 +277,7 @@ def create_react_agent(
interrupt_before: Optional[list[str]] = None,
interrupt_after: Optional[list[str]] = None,
debug: bool = False,
version: Literal["v1", "v2"] = "v1",
version: Literal["v1", "v2"] = "v2",
name: Optional[str] = None,
) -> CompiledGraph:
"""Creates an agent graph that calls tools in a loop until a stopping condition is met.
@@ -701,6 +701,13 @@ def create_react_agent(
break
if m.name in should_return_direct:
return END
# handle a case of parallel tool calls where
# the tool w/ `return_direct` was executed in a different `Send`
if isinstance(m, AIMessage) and m.tool_calls:
if any(call["name"] in should_return_direct for call in m.tool_calls):
return END
return entrypoint
if should_return_direct:
libs/prebuilt/tests/test_react_agent.py
+6 -2
View File
@@ -1078,7 +1078,9 @@ async def test_return_direct(version: str) -> None:
),
]
model = FakeToolCallingModel(tool_calls=[second_tool_call, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
agent = create_react_agent(
model, [tool_return_direct, tool_normal], version=version
)
result = agent.invoke(
{"messages": [HumanMessage(content="Test normal", id="hum1")]}
)
@@ -1107,7 +1109,9 @@ async def test_return_direct(version: str) -> None:
),
]
model = FakeToolCallingModel(tool_calls=[both_tool_calls, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
agent = create_react_agent(
model, [tool_return_direct, tool_normal], version=version
)
result = agent.invoke({"messages": [HumanMessage(content="Test both", id="hum2")]})
assert result["messages"] == [
HumanMessage(content="Test both", id="hum2"),