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langgraph/libs/langgraph/tests/test_prebuilt.py
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2043 lines
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Python

import dataclasses
import json
from functools import partial
from typing import (
Annotated,
Any,
Callable,
Dict,
List,
Literal,
Optional,
Sequence,
Type,
TypeVar,
Union,
)
import pytest
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models import BaseChatModel, LanguageModelInput
from langchain_core.messages import (
AIMessage,
AnyMessage,
BaseMessage,
HumanMessage,
SystemMessage,
ToolCall,
ToolMessage,
)
from langchain_core.outputs import ChatGeneration, ChatResult
from langchain_core.runnables import Runnable, RunnableLambda
from langchain_core.tools import BaseTool, ToolException
from langchain_core.tools import tool as dec_tool
from pydantic import BaseModel, ValidationError
from pydantic.v1 import BaseModel as BaseModelV1
from pydantic.v1 import ValidationError as ValidationErrorV1
from typing_extensions import TypedDict
from langgraph.checkpoint.base import BaseCheckpointSaver
from langgraph.checkpoint.memory import MemorySaver
from langgraph.errors import NodeInterrupt
from langgraph.graph import START, MessagesState, StateGraph, add_messages
from langgraph.prebuilt import (
ToolNode,
ValidationNode,
create_react_agent,
tools_condition,
)
from langgraph.prebuilt.chat_agent_executor import AgentState, _validate_chat_history
from langgraph.prebuilt.tool_node import (
TOOL_CALL_ERROR_TEMPLATE,
InjectedState,
InjectedStore,
_get_state_args,
_infer_handled_types,
)
from langgraph.store.base import BaseStore
from langgraph.store.memory import InMemoryStore
from langgraph.types import Command, Interrupt, interrupt
from tests.conftest import (
ALL_CHECKPOINTERS_ASYNC,
ALL_CHECKPOINTERS_SYNC,
IS_LANGCHAIN_CORE_030_OR_GREATER,
awith_checkpointer,
)
from tests.messages import _AnyIdHumanMessage, _AnyIdToolMessage
pytestmark = pytest.mark.anyio
class FakeToolCallingModel(BaseChatModel):
tool_calls: Optional[list[list[ToolCall]]] = None
index: int = 0
tool_style: Literal["openai", "anthropic"] = "openai"
def _generate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> ChatResult:
"""Top Level call"""
messages_string = "-".join([m.content for m in messages])
tool_calls = (
self.tool_calls[self.index % len(self.tool_calls)]
if self.tool_calls
else []
)
message = AIMessage(
content=messages_string, id=str(self.index), tool_calls=tool_calls.copy()
)
self.index += 1
return ChatResult(generations=[ChatGeneration(message=message)])
@property
def _llm_type(self) -> str:
return "fake-tool-call-model"
def bind_tools(
self,
tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
**kwargs: Any,
) -> Runnable[LanguageModelInput, BaseMessage]:
if len(tools) == 0:
raise ValueError("Must provide at least one tool")
tool_dicts = []
for tool in tools:
if not isinstance(tool, BaseTool):
raise TypeError(
"Only BaseTool is supported by FakeToolCallingModel.bind_tools"
)
# NOTE: this is a simplified tool spec for testing purposes only
if self.tool_style == "openai":
tool_dicts.append(
{
"type": "function",
"function": {
"name": tool.name,
},
}
)
elif self.tool_style == "anthropic":
tool_dicts.append(
{
"name": tool.name,
}
)
return self.bind(tools=tool_dicts)
@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
def test_no_modifier(request: pytest.FixtureRequest, checkpointer_name: str) -> None:
checkpointer: BaseCheckpointSaver = request.getfixturevalue(
"checkpointer_" + checkpointer_name
)
model = FakeToolCallingModel()
agent = create_react_agent(model, [], checkpointer=checkpointer)
inputs = [HumanMessage("hi?")]
thread = {"configurable": {"thread_id": "123"}}
response = agent.invoke({"messages": inputs}, thread, debug=True)
expected_response = {"messages": inputs + [AIMessage(content="hi?", id="0")]}
assert response == expected_response
if checkpointer:
saved = checkpointer.get_tuple(thread)
assert saved is not None
assert saved.checkpoint["channel_values"] == {
"messages": [
_AnyIdHumanMessage(content="hi?"),
AIMessage(content="hi?", id="0"),
],
"agent": "agent",
}
assert saved.metadata == {
"parents": {},
"source": "loop",
"writes": {"agent": {"messages": [AIMessage(content="hi?", id="0")]}},
"step": 1,
"thread_id": "123",
}
assert saved.pending_writes == []
@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_ASYNC)
async def test_no_modifier_async(checkpointer_name: str) -> None:
async with awith_checkpointer(checkpointer_name) as checkpointer:
model = FakeToolCallingModel()
agent = create_react_agent(model, [], checkpointer=checkpointer)
inputs = [HumanMessage("hi?")]
thread = {"configurable": {"thread_id": "123"}}
response = await agent.ainvoke({"messages": inputs}, thread, debug=True)
expected_response = {"messages": inputs + [AIMessage(content="hi?", id="0")]}
assert response == expected_response
if checkpointer:
saved = await checkpointer.aget_tuple(thread)
assert saved is not None
assert saved.checkpoint["channel_values"] == {
"messages": [
_AnyIdHumanMessage(content="hi?"),
AIMessage(content="hi?", id="0"),
],
"agent": "agent",
}
assert saved.metadata == {
"parents": {},
"source": "loop",
"writes": {"agent": {"messages": [AIMessage(content="hi?", id="0")]}},
"step": 1,
"thread_id": "123",
}
assert saved.pending_writes == []
def test_passing_two_modifiers():
model = FakeToolCallingModel()
with pytest.raises(ValueError):
create_react_agent(model, [], messages_modifier="Foo", state_modifier="Bar")
def test_system_message_modifier():
messages_modifier = SystemMessage(content="Foo")
agent_1 = create_react_agent(
FakeToolCallingModel(), [], messages_modifier=messages_modifier
)
agent_2 = create_react_agent(
FakeToolCallingModel(), [], state_modifier=messages_modifier
)
for agent in [agent_1, agent_2]:
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {
"messages": inputs + [AIMessage(content="Foo-hi?", id="0", tool_calls=[])]
}
assert response == expected_response
def test_system_message_string_modifier():
messages_modifier = "Foo"
agent_1 = create_react_agent(
FakeToolCallingModel(), [], messages_modifier=messages_modifier
)
agent_2 = create_react_agent(
FakeToolCallingModel(), [], state_modifier=messages_modifier
)
for agent in [agent_1, agent_2]:
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {
"messages": inputs + [AIMessage(content="Foo-hi?", id="0", tool_calls=[])]
}
assert response == expected_response
def test_callable_messages_modifier():
model = FakeToolCallingModel()
def messages_modifier(messages):
modified_message = f"Bar {messages[-1].content}"
return [HumanMessage(content=modified_message)]
agent = create_react_agent(model, [], messages_modifier=messages_modifier)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Bar hi?", id="0")]}
assert response == expected_response
def test_callable_state_modifier():
model = FakeToolCallingModel()
def state_modifier(state):
modified_message = f"Bar {state['messages'][-1].content}"
return [HumanMessage(content=modified_message)]
agent = create_react_agent(model, [], state_modifier=state_modifier)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Bar hi?", id="0")]}
assert response == expected_response
def test_runnable_messages_modifier():
model = FakeToolCallingModel()
messages_modifier = RunnableLambda(
lambda messages: [HumanMessage(content=f"Baz {messages[-1].content}")]
)
agent = create_react_agent(model, [], messages_modifier=messages_modifier)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Baz hi?", id="0")]}
assert response == expected_response
def test_runnable_state_modifier():
model = FakeToolCallingModel()
state_modifier = RunnableLambda(
lambda state: [HumanMessage(content=f"Baz {state['messages'][-1].content}")]
)
agent = create_react_agent(model, [], state_modifier=state_modifier)
inputs = [HumanMessage("hi?")]
response = agent.invoke({"messages": inputs})
expected_response = {"messages": inputs + [AIMessage(content="Baz hi?", id="0")]}
assert response == expected_response
def test_state_modifier_with_store():
def add(a: int, b: int):
"""Adds a and b"""
return a + b
in_memory_store = InMemoryStore()
in_memory_store.put(("memories", "1"), "user_name", {"data": "User name is Alice"})
in_memory_store.put(("memories", "2"), "user_name", {"data": "User name is Bob"})
def modify(state, config, *, store):
user_id = config["configurable"]["user_id"]
system_str = store.get(("memories", user_id), "user_name").value["data"]
return [SystemMessage(system_str)] + state["messages"]
def modify_no_store(state, config):
return SystemMessage("foo") + state["messages"]
model = FakeToolCallingModel()
# test state modifier that uses store works
agent = create_react_agent(
model, [add], state_modifier=modify, store=in_memory_store
)
response = agent.invoke(
{"messages": [("user", "hi")]}, {"configurable": {"user_id": "1"}}
)
assert response["messages"][-1].content == "User name is Alice-hi"
# test state modifier that doesn't use store works
agent = create_react_agent(
model, [add], state_modifier=modify_no_store, store=in_memory_store
)
response = agent.invoke(
{"messages": [("user", "hi")]}, {"configurable": {"user_id": "2"}}
)
assert response["messages"][-1].content == "foo-hi"
@pytest.mark.parametrize("tool_style", ["openai", "anthropic"])
def test_model_with_tools(tool_style: str):
model = FakeToolCallingModel(tool_style=tool_style)
@dec_tool
def tool1(some_val: int) -> str:
"""Tool 1 docstring."""
return f"Tool 1: {some_val}"
@dec_tool
def tool2(some_val: int) -> str:
"""Tool 2 docstring."""
return f"Tool 2: {some_val}"
# check valid agent constructor
agent = create_react_agent(model.bind_tools([tool1, tool2]), [tool1, tool2])
result = agent.nodes["tools"].invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 2},
"id": "some 1",
},
{
"name": "tool2",
"args": {"some_val": 2},
"id": "some 2",
},
],
)
]
}
)
tool_messages: ToolMessage = result["messages"][-2:]
for tool_message in tool_messages:
assert tool_message.type == "tool"
assert tool_message.content in {"Tool 1: 2", "Tool 2: 2"}
assert tool_message.tool_call_id in {"some 1", "some 2"}
# test mismatching tool lengths
with pytest.raises(ValueError):
create_react_agent(model.bind_tools([tool1]), [tool1, tool2])
# test missing bound tools
with pytest.raises(ValueError):
create_react_agent(model.bind_tools([tool1]), [tool2])
def test__validate_messages():
# empty input
_validate_chat_history([])
# single human message
_validate_chat_history(
[
HumanMessage(content="What's the weather?"),
]
)
# human + AI
_validate_chat_history(
[
HumanMessage(content="What's the weather?"),
AIMessage(content="The weather is sunny and 75°F."),
]
)
# Answered tool calls
_validate_chat_history(
[
HumanMessage(content="What's the weather?"),
AIMessage(
content="Let me check that for you.",
tool_calls=[{"id": "call1", "name": "get_weather", "args": {}}],
),
ToolMessage(content="Sunny, 75°F", tool_call_id="call1"),
AIMessage(content="The weather is sunny and 75°F."),
]
)
# Unanswered tool calls
with pytest.raises(ValueError):
_validate_chat_history(
[
AIMessage(
content="I'll check that for you.",
tool_calls=[
{"id": "call1", "name": "get_weather", "args": {}},
{"id": "call2", "name": "get_time", "args": {}},
],
)
]
)
with pytest.raises(ValueError):
_validate_chat_history(
[
HumanMessage(content="What's the weather and time?"),
AIMessage(
content="I'll check that for you.",
tool_calls=[
{"id": "call1", "name": "get_weather", "args": {}},
{"id": "call2", "name": "get_time", "args": {}},
],
),
ToolMessage(content="Sunny, 75°F", tool_call_id="call1"),
AIMessage(
content="The weather is sunny and 75°F. Let me check the time."
),
]
)
def test__infer_handled_types() -> None:
def handle(e): # type: ignore
return ""
def handle2(e: Exception) -> str:
return ""
def handle3(e: Union[ValueError, ToolException]) -> str:
return ""
class Handler:
def handle(self, e: ValueError) -> str:
return ""
handle4 = Handler().handle
def handle5(e: Union[Union[TypeError, ValueError], ToolException]):
return ""
expected: tuple = (Exception,)
actual = _infer_handled_types(handle)
assert expected == actual
expected = (Exception,)
actual = _infer_handled_types(handle2)
assert expected == actual
expected = (ValueError, ToolException)
actual = _infer_handled_types(handle3)
assert expected == actual
expected = (ValueError,)
actual = _infer_handled_types(handle4)
assert expected == actual
expected = (TypeError, ValueError, ToolException)
actual = _infer_handled_types(handle5)
assert expected == actual
with pytest.raises(ValueError):
def handler(e: str):
return ""
_infer_handled_types(handler)
with pytest.raises(ValueError):
def handler(e: list[Exception]):
return ""
_infer_handled_types(handler)
with pytest.raises(ValueError):
def handler(e: Union[str, int]):
return ""
_infer_handled_types(handler)
# tools for testing Too
def tool1(some_val: int, some_other_val: str) -> str:
"""Tool 1 docstring."""
if some_val == 0:
raise ValueError("Test error")
return f"{some_val} - {some_other_val}"
async def tool2(some_val: int, some_other_val: str) -> str:
"""Tool 2 docstring."""
if some_val == 0:
raise ToolException("Test error")
return f"tool2: {some_val} - {some_other_val}"
async def tool3(some_val: int, some_other_val: str) -> str:
"""Tool 3 docstring."""
return [
{"key_1": some_val, "key_2": "foo"},
{"key_1": some_other_val, "key_2": "baz"},
]
async def tool4(some_val: int, some_other_val: str) -> str:
"""Tool 4 docstring."""
return [
{"type": "image_url", "image_url": {"url": "abdc"}},
]
@dec_tool
def tool5(some_val: int):
"""Tool 5 docstring."""
raise ToolException("Test error")
tool5.handle_tool_error = "foo"
async def test_tool_node():
result = ToolNode([tool1]).invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 1, "some_other_val": "foo"},
"id": "some 0",
}
],
)
]
}
)
tool_message: ToolMessage = result["messages"][-1]
assert tool_message.type == "tool"
assert tool_message.content == "1 - foo"
assert tool_message.tool_call_id == "some 0"
result2 = await ToolNode([tool2]).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool2",
"args": {"some_val": 2, "some_other_val": "bar"},
"id": "some 1",
}
],
)
]
}
)
tool_message: ToolMessage = result2["messages"][-1]
assert tool_message.type == "tool"
assert tool_message.content == "tool2: 2 - bar"
# list of dicts tool content
result3 = await ToolNode([tool3]).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool3",
"args": {"some_val": 2, "some_other_val": "bar"},
"id": "some 2",
}
],
)
]
}
)
tool_message: ToolMessage = result3["messages"][-1]
assert tool_message.type == "tool"
assert (
tool_message.content
== '[{"key_1": 2, "key_2": "foo"}, {"key_1": "bar", "key_2": "baz"}]'
)
assert tool_message.tool_call_id == "some 2"
# list of content blocks tool content
result4 = await ToolNode([tool4]).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool4",
"args": {"some_val": 2, "some_other_val": "bar"},
"id": "some 3",
}
],
)
]
}
)
tool_message: ToolMessage = result4["messages"][-1]
assert tool_message.type == "tool"
assert tool_message.content == [{"type": "image_url", "image_url": {"url": "abdc"}}]
assert tool_message.tool_call_id == "some 3"
async def test_tool_node_error_handling():
def handle_all(e: Union[ValueError, ToolException, ValidationError]):
return TOOL_CALL_ERROR_TEMPLATE.format(error=repr(e))
# test catching all exceptions, via:
# - handle_tool_errors = True
# - passing a tuple of all exceptions
# - passing a callable with all exceptions in the signature
for handle_tool_errors in (
True,
(ValueError, ToolException, ValidationError),
handle_all,
):
result_error = await ToolNode(
[tool1, tool2, tool3], handle_tool_errors=handle_tool_errors
).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 0, "some_other_val": "foo"},
"id": "some id",
},
{
"name": "tool2",
"args": {"some_val": 0, "some_other_val": "bar"},
"id": "some other id",
},
{
"name": "tool3",
"args": {"some_val": 0},
"id": "another id",
},
],
)
]
}
)
assert all(m.type == "tool" for m in result_error["messages"])
assert all(m.status == "error" for m in result_error["messages"])
assert (
result_error["messages"][0].content
== f"Error: {repr(ValueError('Test error'))}\n Please fix your mistakes."
)
assert (
result_error["messages"][1].content
== f"Error: {repr(ToolException('Test error'))}\n Please fix your mistakes."
)
assert (
"ValidationError" in result_error["messages"][2].content
or "validation error" in result_error["messages"][2].content
)
assert result_error["messages"][0].tool_call_id == "some id"
assert result_error["messages"][1].tool_call_id == "some other id"
assert result_error["messages"][2].tool_call_id == "another id"
async def test_tool_node_error_handling_callable():
def handle_value_error(e: ValueError):
return "Value error"
def handle_tool_exception(e: ToolException):
return "Tool exception"
for handle_tool_errors in ("Value error", handle_value_error):
result_error = await ToolNode(
[tool1], handle_tool_errors=handle_tool_errors
).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 0, "some_other_val": "foo"},
"id": "some id",
},
],
)
]
}
)
tool_message: ToolMessage = result_error["messages"][-1]
assert tool_message.type == "tool"
assert tool_message.status == "error"
assert tool_message.content == "Value error"
# test raising for an unhandled exception, via:
# - passing a tuple of all exceptions
# - passing a callable with all exceptions in the signature
for handle_tool_errors in ((ValueError,), handle_value_error):
with pytest.raises(ToolException) as exc_info:
await ToolNode(
[tool1, tool2], handle_tool_errors=handle_tool_errors
).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 0, "some_other_val": "foo"},
"id": "some id",
},
{
"name": "tool2",
"args": {"some_val": 0, "some_other_val": "bar"},
"id": "some other id",
},
],
)
]
}
)
assert str(exc_info.value) == "Test error"
for handle_tool_errors in ((ToolException,), handle_tool_exception):
with pytest.raises(ValueError) as exc_info:
await ToolNode(
[tool1, tool2], handle_tool_errors=handle_tool_errors
).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 0, "some_other_val": "foo"},
"id": "some id",
},
{
"name": "tool2",
"args": {"some_val": 0, "some_other_val": "bar"},
"id": "some other id",
},
],
)
]
}
)
assert str(exc_info.value) == "Test error"
async def test_tool_node_handle_tool_errors_false():
with pytest.raises(ValueError) as exc_info:
ToolNode([tool1], handle_tool_errors=False).invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 0, "some_other_val": "foo"},
"id": "some id",
}
],
)
]
}
)
assert str(exc_info.value) == "Test error"
with pytest.raises(ToolException):
await ToolNode([tool2], handle_tool_errors=False).ainvoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool2",
"args": {"some_val": 0, "some_other_val": "bar"},
"id": "some id",
}
],
)
]
}
)
assert str(exc_info.value) == "Test error"
# test validation errors get raised if handle_tool_errors is False
with pytest.raises((ValidationError, ValidationErrorV1)):
ToolNode([tool1], handle_tool_errors=False).invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool1",
"args": {"some_val": 0},
"id": "some id",
}
],
)
]
}
)
def test_tool_node_individual_tool_error_handling():
# test error handling on individual tools (and that it overrides overall error handling!)
result_individual_tool_error_handler = ToolNode(
[tool5], handle_tool_errors="bar"
).invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool5",
"args": {"some_val": 0},
"id": "some 0",
}
],
)
]
}
)
tool_message: ToolMessage = result_individual_tool_error_handler["messages"][-1]
assert tool_message.type == "tool"
assert tool_message.status == "error"
assert tool_message.content == "foo"
assert tool_message.tool_call_id == "some 0"
def test_tool_node_incorrect_tool_name():
result_incorrect_name = ToolNode([tool1, tool2]).invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool3",
"args": {"some_val": 1, "some_other_val": "foo"},
"id": "some 0",
}
],
)
]
}
)
tool_message: ToolMessage = result_incorrect_name["messages"][-1]
assert tool_message.type == "tool"
assert tool_message.status == "error"
assert (
tool_message.content
== "Error: tool3 is not a valid tool, try one of [tool1, tool2]."
)
assert tool_message.tool_call_id == "some 0"
def test_tool_node_node_interrupt():
def tool_normal(some_val: int) -> str:
"""Tool docstring."""
return "normal"
def tool_interrupt(some_val: int) -> str:
"""Tool docstring."""
raise NodeInterrupt("foo")
def handle(e: NodeInterrupt):
return "handled"
for handle_tool_errors in (True, (NodeInterrupt,), "handled", handle, False):
node = ToolNode([tool_interrupt], handle_tool_errors=handle_tool_errors)
with pytest.raises(NodeInterrupt) as exc_info:
node.invoke(
{
"messages": [
AIMessage(
"hi?",
tool_calls=[
{
"name": "tool_interrupt",
"args": {"some_val": 0},
"id": "some 0",
}
],
)
]
}
)
assert exc_info.value == "foo"
# test inside react agent
model = FakeToolCallingModel(
tool_calls=[
[
ToolCall(name="tool_interrupt", args={"some_val": 0}, id="1"),
ToolCall(name="tool_normal", args={"some_val": 1}, id="2"),
],
[],
]
)
checkpointer = MemorySaver()
config = {"configurable": {"thread_id": "1"}}
agent = create_react_agent(
model, [tool_interrupt, tool_normal], checkpointer=checkpointer
)
result = agent.invoke({"messages": [HumanMessage("hi?")]}, config)
assert result["messages"] == [
_AnyIdHumanMessage(
content="hi?",
),
AIMessage(
content="hi?",
id="0",
tool_calls=[
{
"name": "tool_interrupt",
"args": {"some_val": 0},
"id": "1",
"type": "tool_call",
},
{
"name": "tool_normal",
"args": {"some_val": 1},
"id": "2",
"type": "tool_call",
},
],
),
]
state = agent.get_state(config)
assert state.next == ("tools",)
task = state.tasks[0]
assert task.name == "tools"
assert task.interrupts == (Interrupt(value="foo", when="during"),)
@pytest.mark.skipif(
not IS_LANGCHAIN_CORE_030_OR_GREATER,
reason="Langchain core 0.3.0 or greater is required",
)
async def test_tool_node_command():
from langchain_core.tools.base import InjectedToolCallId
@dec_tool
def transfer_to_bob(tool_call_id: Annotated[str, InjectedToolCallId]):
"""Transfer to Bob"""
return Command(
update={
"messages": [
ToolMessage(content="Transferred to Bob", tool_call_id=tool_call_id)
]
},
goto="bob",
graph=Command.PARENT,
)
@dec_tool
async def async_transfer_to_bob(tool_call_id: Annotated[str, InjectedToolCallId]):
"""Transfer to Bob"""
return Command(
update={
"messages": [
ToolMessage(content="Transferred to Bob", tool_call_id=tool_call_id)
]
},
goto="bob",
graph=Command.PARENT,
)
class CustomToolSchema(BaseModel):
tool_call_id: Annotated[str, InjectedToolCallId]
class MyCustomTool(BaseTool):
def _run(*args: Any, **kwargs: Any):
return Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id=kwargs["tool_call_id"],
)
]
},
goto="bob",
graph=Command.PARENT,
)
async def _arun(*args: Any, **kwargs: Any):
return Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id=kwargs["tool_call_id"],
)
]
},
goto="bob",
graph=Command.PARENT,
)
custom_tool = MyCustomTool(
name="custom_transfer_to_bob",
description="Transfer to bob",
args_schema=CustomToolSchema,
)
async_custom_tool = MyCustomTool(
name="async_custom_transfer_to_bob",
description="Transfer to bob",
args_schema=CustomToolSchema,
)
# test mixing regular tools and tools returning commands
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
result = ToolNode([add, transfer_to_bob]).invoke(
{
"messages": [
AIMessage(
"",
tool_calls=[
{"args": {"a": 1, "b": 2}, "id": "1", "name": "add"},
{"args": {}, "id": "2", "name": "transfer_to_bob"},
],
)
]
}
)
assert result == [
{
"messages": [
ToolMessage(
content="3",
tool_call_id="1",
name="add",
)
]
},
Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id="2",
name="transfer_to_bob",
)
]
},
goto="bob",
graph=Command.PARENT,
),
]
# test tools returning commands
# test sync tools
for tool in [transfer_to_bob, custom_tool]:
result = ToolNode([tool]).invoke(
{
"messages": [
AIMessage(
"", tool_calls=[{"args": {}, "id": "1", "name": tool.name}]
)
]
}
)
assert result == [
Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id="1",
name=tool.name,
)
]
},
goto="bob",
graph=Command.PARENT,
)
]
# test async tools
for tool in [async_transfer_to_bob, async_custom_tool]:
result = await ToolNode([tool]).ainvoke(
{
"messages": [
AIMessage(
"", tool_calls=[{"args": {}, "id": "1", "name": tool.name}]
)
]
}
)
assert result == [
Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id="1",
name=tool.name,
)
]
},
goto="bob",
graph=Command.PARENT,
)
]
# test multiple commands
result = ToolNode([transfer_to_bob, custom_tool]).invoke(
{
"messages": [
AIMessage(
"",
tool_calls=[
{"args": {}, "id": "1", "name": "transfer_to_bob"},
{"args": {}, "id": "2", "name": "custom_transfer_to_bob"},
],
)
]
}
)
assert result == [
Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id="1",
name="transfer_to_bob",
)
]
},
goto="bob",
graph=Command.PARENT,
),
Command(
update={
"messages": [
ToolMessage(
content="Transferred to Bob",
tool_call_id="2",
name="custom_transfer_to_bob",
)
]
},
goto="bob",
graph=Command.PARENT,
),
]
# test validation (mismatch between input type and command.update type)
with pytest.raises(ValueError):
@dec_tool
def list_update_tool(tool_call_id: Annotated[str, InjectedToolCallId]):
"""My tool"""
return Command(
update=[ToolMessage(content="foo", tool_call_id=tool_call_id)]
)
ToolNode([list_update_tool]).invoke(
{
"messages": [
AIMessage(
"",
tool_calls=[
{"args": {}, "id": "1", "name": "list_update_tool"}
],
)
]
}
)
# test validation (missing tool message in the update for current graph)
with pytest.raises(ValueError):
@dec_tool
def no_update_tool():
"""My tool"""
return Command(update={"messages": []})
ToolNode([no_update_tool]).invoke(
{
"messages": [
AIMessage(
"",
tool_calls=[{"args": {}, "id": "1", "name": "no_update_tool"}],
)
]
}
)
# test validation (tool message with a wrong tool call ID)
with pytest.raises(ValueError):
@dec_tool
def mismatching_tool_call_id_tool():
"""My tool"""
return Command(
update={"messages": [ToolMessage(content="foo", tool_call_id="2")]}
)
ToolNode([mismatching_tool_call_id_tool]).invoke(
{
"messages": [
AIMessage(
"",
tool_calls=[
{
"args": {},
"id": "1",
"name": "mismatching_tool_call_id_tool",
}
],
)
]
}
)
# test validation (missing tool message in the update for parent graph is OK)
@dec_tool
def node_update_parent_tool():
"""No update"""
return Command(update={"messages": []}, graph=Command.PARENT)
assert ToolNode([node_update_parent_tool]).invoke(
{
"messages": [
AIMessage(
"",
tool_calls=[
{"args": {}, "id": "1", "name": "node_update_parent_tool"}
],
)
]
}
) == [Command(update={"messages": []}, graph=Command.PARENT)]
@pytest.mark.skipif(
not IS_LANGCHAIN_CORE_030_OR_GREATER,
reason="Langchain core 0.3.0 or greater is required",
)
async def test_tool_node_command_list_input():
from langchain_core.tools.base import InjectedToolCallId
@dec_tool
def transfer_to_bob(tool_call_id: Annotated[str, InjectedToolCallId]):
"""Transfer to Bob"""
return Command(
update=[
ToolMessage(content="Transferred to Bob", tool_call_id=tool_call_id)
],
goto="bob",
graph=Command.PARENT,
)
@dec_tool
async def async_transfer_to_bob(tool_call_id: Annotated[str, InjectedToolCallId]):
"""Transfer to Bob"""
return Command(
update=[
ToolMessage(content="Transferred to Bob", tool_call_id=tool_call_id)
],
goto="bob",
graph=Command.PARENT,
)
class CustomToolSchema(BaseModel):
tool_call_id: Annotated[str, InjectedToolCallId]
class MyCustomTool(BaseTool):
def _run(*args: Any, **kwargs: Any):
return Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id=kwargs["tool_call_id"],
)
],
goto="bob",
graph=Command.PARENT,
)
async def _arun(*args: Any, **kwargs: Any):
return Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id=kwargs["tool_call_id"],
)
],
goto="bob",
graph=Command.PARENT,
)
custom_tool = MyCustomTool(
name="custom_transfer_to_bob",
description="Transfer to bob",
args_schema=CustomToolSchema,
)
async_custom_tool = MyCustomTool(
name="async_custom_transfer_to_bob",
description="Transfer to bob",
args_schema=CustomToolSchema,
)
# test mixing regular tools and tools returning commands
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
result = ToolNode([add, transfer_to_bob]).invoke(
[
AIMessage(
"",
tool_calls=[
{"args": {"a": 1, "b": 2}, "id": "1", "name": "add"},
{"args": {}, "id": "2", "name": "transfer_to_bob"},
],
)
]
)
assert result == [
[
ToolMessage(
content="3",
tool_call_id="1",
name="add",
)
],
Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id="2",
name="transfer_to_bob",
)
],
goto="bob",
graph=Command.PARENT,
),
]
# test tools returning commands
# test sync tools
for tool in [transfer_to_bob, custom_tool]:
result = ToolNode([tool]).invoke(
[AIMessage("", tool_calls=[{"args": {}, "id": "1", "name": tool.name}])]
)
assert result == [
Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id="1",
name=tool.name,
)
],
goto="bob",
graph=Command.PARENT,
)
]
# test async tools
for tool in [async_transfer_to_bob, async_custom_tool]:
result = await ToolNode([tool]).ainvoke(
[AIMessage("", tool_calls=[{"args": {}, "id": "1", "name": tool.name}])]
)
assert result == [
Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id="1",
name=tool.name,
)
],
goto="bob",
graph=Command.PARENT,
)
]
# test multiple commands
result = ToolNode([transfer_to_bob, custom_tool]).invoke(
[
AIMessage(
"",
tool_calls=[
{"args": {}, "id": "1", "name": "transfer_to_bob"},
{"args": {}, "id": "2", "name": "custom_transfer_to_bob"},
],
)
]
)
assert result == [
Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id="1",
name="transfer_to_bob",
)
],
goto="bob",
graph=Command.PARENT,
),
Command(
update=[
ToolMessage(
content="Transferred to Bob",
tool_call_id="2",
name="custom_transfer_to_bob",
)
],
goto="bob",
graph=Command.PARENT,
),
]
# test validation (mismatch between input type and command.update type)
with pytest.raises(ValueError):
@dec_tool
def list_update_tool(tool_call_id: Annotated[str, InjectedToolCallId]):
"""My tool"""
return Command(
update={
"messages": [ToolMessage(content="foo", tool_call_id=tool_call_id)]
}
)
ToolNode([list_update_tool]).invoke(
[
AIMessage(
"",
tool_calls=[{"args": {}, "id": "1", "name": "list_update_tool"}],
)
]
)
# test validation (missing tool message in the update for current graph)
with pytest.raises(ValueError):
@dec_tool
def no_update_tool():
"""My tool"""
return Command(update=[])
ToolNode([no_update_tool]).invoke(
[
AIMessage(
"",
tool_calls=[{"args": {}, "id": "1", "name": "no_update_tool"}],
)
]
)
# test validation (tool message with a wrong tool call ID)
with pytest.raises(ValueError):
@dec_tool
def mismatching_tool_call_id_tool():
"""My tool"""
return Command(update=[ToolMessage(content="foo", tool_call_id="2")])
ToolNode([mismatching_tool_call_id_tool]).invoke(
[
AIMessage(
"",
tool_calls=[
{"args": {}, "id": "1", "name": "mismatching_tool_call_id_tool"}
],
)
]
)
# test validation (missing tool message in the update for parent graph is OK)
@dec_tool
def node_update_parent_tool():
"""No update"""
return Command(update=[], graph=Command.PARENT)
assert ToolNode([node_update_parent_tool]).invoke(
[
AIMessage(
"",
tool_calls=[{"args": {}, "id": "1", "name": "node_update_parent_tool"}],
)
]
) == [Command(update=[], graph=Command.PARENT)]
@pytest.mark.skipif(
not IS_LANGCHAIN_CORE_030_OR_GREATER,
reason="Langchain core 0.3.0 or greater is required",
)
def test_react_agent_update_state():
from langchain_core.tools.base import InjectedToolCallId
class State(AgentState):
user_name: str
@dec_tool
def get_user_name(tool_call_id: Annotated[str, InjectedToolCallId]):
"""Retrieve user name"""
user_name = interrupt("Please provider user name:")
return Command(
update={
"user_name": user_name,
"messages": [
ToolMessage(
"Successfully retrieved user name", tool_call_id=tool_call_id
)
],
}
)
def state_modifier(state: State):
user_name = state.get("user_name")
if user_name is None:
return state["messages"]
system_msg = f"User name is {user_name}"
return [{"role": "system", "content": system_msg}] + state["messages"]
checkpointer = MemorySaver()
tool_calls = [[{"args": {}, "id": "1", "name": "get_user_name"}]]
model = FakeToolCallingModel(tool_calls=tool_calls)
agent = create_react_agent(
model,
[get_user_name],
state_schema=State,
state_modifier=state_modifier,
checkpointer=checkpointer,
)
config = {"configurable": {"thread_id": "1"}}
# run until interrpupted
agent.invoke({"messages": [("user", "what's my name")]}, config)
# supply the value for the interrupt
response = agent.invoke(Command(resume="Archibald"), config)
# confirm that the state was updated
assert response["user_name"] == "Archibald"
assert len(response["messages"]) == 4
tool_message: ToolMessage = response["messages"][-2]
assert tool_message.content == "Successfully retrieved user name"
assert tool_message.tool_call_id == "1"
assert tool_message.name == "get_user_name"
def my_function(some_val: int, some_other_val: str) -> str:
return f"{some_val} - {some_other_val}"
class MyModel(BaseModel):
some_val: int
some_other_val: str
class MyModelV1(BaseModelV1):
some_val: int
some_other_val: str
@dec_tool
def my_tool(some_val: int, some_other_val: str) -> str:
"""Cool."""
return f"{some_val} - {some_other_val}"
@pytest.mark.parametrize(
"tool_schema",
[
my_function,
MyModel,
MyModelV1,
my_tool,
],
)
@pytest.mark.parametrize("use_message_key", [True, False])
async def test_validation_node(tool_schema: Any, use_message_key: bool):
validation_node = ValidationNode([tool_schema])
tool_name = getattr(tool_schema, "name", getattr(tool_schema, "__name__", None))
inputs = [
AIMessage(
"hi?",
tool_calls=[
{
"name": tool_name,
"args": {"some_val": 1, "some_other_val": "foo"},
"id": "some 0",
},
{
"name": tool_name,
# Wrong type for some_val
"args": {"some_val": "bar", "some_other_val": "foo"},
"id": "some 1",
},
],
),
]
if use_message_key:
inputs = {"messages": inputs}
result = await validation_node.ainvoke(inputs)
if use_message_key:
result = result["messages"]
def check_results(messages: list):
assert len(messages) == 2
assert all(m.type == "tool" for m in messages)
assert not messages[0].additional_kwargs.get("is_error")
assert messages[1].additional_kwargs.get("is_error")
check_results(result)
result_sync = validation_node.invoke(inputs)
if use_message_key:
result_sync = result_sync["messages"]
check_results(result_sync)
class _InjectStateSchema(TypedDict):
messages: list
foo: str
class _InjectedStatePydanticSchema(BaseModelV1):
messages: list
foo: str
class _InjectedStatePydanticV2Schema(BaseModel):
messages: list
foo: str
@dataclasses.dataclass
class _InjectedStateDataclassSchema:
messages: list
foo: str
T = TypeVar("T")
@pytest.mark.parametrize(
"schema_",
[
_InjectStateSchema,
_InjectedStatePydanticSchema,
_InjectedStatePydanticV2Schema,
_InjectedStateDataclassSchema,
],
)
def test_tool_node_inject_state(schema_: Type[T]) -> None:
def tool1(some_val: int, state: Annotated[T, InjectedState]) -> str:
"""Tool 1 docstring."""
if isinstance(state, dict):
return state["foo"]
else:
return getattr(state, "foo")
def tool2(some_val: int, state: Annotated[T, InjectedState()]) -> str:
"""Tool 2 docstring."""
if isinstance(state, dict):
return state["foo"]
else:
return getattr(state, "foo")
def tool3(
some_val: int,
foo: Annotated[str, InjectedState("foo")],
msgs: Annotated[List[AnyMessage], InjectedState("messages")],
) -> str:
"""Tool 1 docstring."""
return foo
def tool4(
some_val: int, msgs: Annotated[List[AnyMessage], InjectedState("messages")]
) -> str:
"""Tool 1 docstring."""
return msgs[0].content
node = ToolNode([tool1, tool2, tool3, tool4])
for tool_name in ("tool1", "tool2", "tool3"):
tool_call = {
"name": tool_name,
"args": {"some_val": 1},
"id": "some 0",
"type": "tool_call",
}
msg = AIMessage("hi?", tool_calls=[tool_call])
result = node.invoke(schema_(**{"messages": [msg], "foo": "bar"}))
tool_message = result["messages"][-1]
assert tool_message.content == "bar", f"Failed for tool={tool_name}"
if tool_name == "tool3":
failure_input = None
try:
failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
except Exception:
pass
if failure_input is not None:
with pytest.raises(KeyError):
node.invoke(failure_input)
with pytest.raises(ValueError):
node.invoke([msg])
else:
failure_input = None
try:
failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
except Exception:
# We'd get a validation error from pydantic state and wouldn't make it to the node
# anyway
pass
if failure_input is not None:
messages_ = node.invoke(failure_input)
tool_message = messages_["messages"][-1]
assert "KeyError" in tool_message.content
tool_message = node.invoke([msg])[-1]
assert "KeyError" in tool_message.content
tool_call = {
"name": "tool4",
"args": {"some_val": 1},
"id": "some 0",
"type": "tool_call",
}
msg = AIMessage("hi?", tool_calls=[tool_call])
result = node.invoke(schema_(**{"messages": [msg], "foo": ""}))
tool_message = result["messages"][-1]
assert tool_message.content == "hi?"
result = node.invoke([msg])
tool_message = result[-1]
assert tool_message.content == "hi?"
@pytest.mark.skipif(
not IS_LANGCHAIN_CORE_030_OR_GREATER,
reason="Langchain core 0.3.0 or greater is required",
)
def test_tool_node_inject_store() -> None:
store = InMemoryStore()
namespace = ("test",)
def tool1(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
"""Tool 1 docstring."""
store_val = store.get(namespace, "test_key").value["foo"]
return f"Some val: {some_val}, store val: {store_val}"
def tool2(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
"""Tool 2 docstring."""
store_val = store.get(namespace, "test_key").value["foo"]
return f"Some val: {some_val}, store val: {store_val}"
def tool3(
some_val: int,
bar: Annotated[str, InjectedState("bar")],
store: Annotated[BaseStore, InjectedStore()],
) -> str:
"""Tool 3 docstring."""
store_val = store.get(namespace, "test_key").value["foo"]
return f"Some val: {some_val}, store val: {store_val}, state val: {bar}"
node = ToolNode([tool1, tool2, tool3], handle_tool_errors=True)
store.put(namespace, "test_key", {"foo": "bar"})
class State(MessagesState):
bar: str
builder = StateGraph(State)
builder.add_node("tools", node)
builder.add_edge(START, "tools")
graph = builder.compile(store=store)
for tool_name in ("tool1", "tool2"):
tool_call = {
"name": tool_name,
"args": {"some_val": 1},
"id": "some 0",
"type": "tool_call",
}
msg = AIMessage("hi?", tool_calls=[tool_call])
node_result = node.invoke({"messages": [msg]}, store=store)
graph_result = graph.invoke({"messages": [msg]})
for result in (node_result, graph_result):
result["messages"][-1]
tool_message = result["messages"][-1]
assert (
tool_message.content == "Some val: 1, store val: bar"
), f"Failed for tool={tool_name}"
tool_call = {
"name": "tool3",
"args": {"some_val": 1},
"id": "some 0",
"type": "tool_call",
}
msg = AIMessage("hi?", tool_calls=[tool_call])
node_result = node.invoke({"messages": [msg], "bar": "baz"}, store=store)
graph_result = graph.invoke({"messages": [msg], "bar": "baz"})
for result in (node_result, graph_result):
result["messages"][-1]
tool_message = result["messages"][-1]
assert (
tool_message.content == "Some val: 1, store val: bar, state val: baz"
), f"Failed for tool={tool_name}"
# test injected store without passing store to compiled graph
failing_graph = builder.compile()
with pytest.raises(ValueError):
failing_graph.invoke({"messages": [msg], "bar": "baz"})
def test_tool_node_ensure_utf8() -> None:
@dec_tool
def get_day_list(days: list[str]) -> list[str]:
"""choose days"""
return days
data = ["星期一", "水曜日", "목요일", "Friday"]
tools = [get_day_list]
tool_calls = [ToolCall(name=get_day_list.name, args={"days": data}, id="test_id")]
outputs: list[ToolMessage] = ToolNode(tools).invoke(
[AIMessage(content="", tool_calls=tool_calls)]
)
assert outputs[0].content == json.dumps(data, ensure_ascii=False)
def test_tool_node_messages_key() -> None:
@dec_tool
def add(a: int, b: int):
"""Adds a and b."""
return a + b
model = FakeToolCallingModel(
tool_calls=[[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")]]
)
class State(TypedDict):
subgraph_messages: Annotated[list[AnyMessage], add_messages]
def call_model(state: State):
response = model.invoke(state["subgraph_messages"])
model.tool_calls = []
return {"subgraph_messages": response}
builder = StateGraph(State)
builder.add_node("agent", call_model)
builder.add_node("tools", ToolNode([add], messages_key="subgraph_messages"))
builder.add_conditional_edges(
"agent", partial(tools_condition, messages_key="subgraph_messages")
)
builder.add_edge(START, "agent")
builder.add_edge("tools", "agent")
graph = builder.compile()
result = graph.invoke({"subgraph_messages": [HumanMessage(content="hi")]})
assert result["subgraph_messages"] == [
_AnyIdHumanMessage(content="hi"),
AIMessage(
content="hi",
id="0",
tool_calls=[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")],
),
_AnyIdToolMessage(content="3", name=add.name, tool_call_id="test_id"),
AIMessage(content="hi-hi-3", id="1"),
]
async def test_return_direct() -> None:
@dec_tool(return_direct=True)
def tool_return_direct(input: str) -> str:
"""A tool that returns directly."""
return f"Direct result: {input}"
@dec_tool
def tool_normal(input: str) -> str:
"""A normal tool."""
return f"Normal result: {input}"
first_tool_call = [
ToolCall(
name="tool_return_direct",
args={"input": "Test direct"},
id="1",
),
]
expected_ai = AIMessage(
content="Test direct",
id="0",
tool_calls=first_tool_call,
)
model = FakeToolCallingModel(tool_calls=[first_tool_call, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
# Test direct return for tool_return_direct
result = agent.invoke(
{"messages": [HumanMessage(content="Test direct", id="hum0")]}
)
assert result["messages"] == [
HumanMessage(content="Test direct", id="hum0"),
expected_ai,
ToolMessage(
content="Direct result: Test direct",
name="tool_return_direct",
tool_call_id="1",
id=result["messages"][2].id,
),
]
second_tool_call = [
ToolCall(
name="tool_normal",
args={"input": "Test normal"},
id="2",
),
]
model = FakeToolCallingModel(tool_calls=[second_tool_call, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
result = agent.invoke(
{"messages": [HumanMessage(content="Test normal", id="hum1")]}
)
assert result["messages"] == [
HumanMessage(content="Test normal", id="hum1"),
AIMessage(content="Test normal", id="0", tool_calls=second_tool_call),
ToolMessage(
content="Normal result: Test normal",
name="tool_normal",
tool_call_id="2",
id=result["messages"][2].id,
),
AIMessage(content="Test normal-Test normal-Normal result: Test normal", id="1"),
]
both_tool_calls = [
ToolCall(
name="tool_return_direct",
args={"input": "Test both direct"},
id="3",
),
ToolCall(
name="tool_normal",
args={"input": "Test both normal"},
id="4",
),
]
model = FakeToolCallingModel(tool_calls=[both_tool_calls, []])
agent = create_react_agent(model, [tool_return_direct, tool_normal])
result = agent.invoke({"messages": [HumanMessage(content="Test both", id="hum2")]})
assert result["messages"] == [
HumanMessage(content="Test both", id="hum2"),
AIMessage(content="Test both", id="0", tool_calls=both_tool_calls),
ToolMessage(
content="Direct result: Test both direct",
name="tool_return_direct",
tool_call_id="3",
id=result["messages"][2].id,
),
ToolMessage(
content="Normal result: Test both normal",
name="tool_normal",
tool_call_id="4",
id=result["messages"][3].id,
),
]
def test__get_state_args() -> None:
class Schema1(BaseModel):
a: Annotated[str, InjectedState]
class Schema2(Schema1):
b: Annotated[int, InjectedState("bar")]
@dec_tool(args_schema=Schema2)
def foo(a: str, b: int) -> float:
"""return"""
return 0.0
assert _get_state_args(foo) == {"a": None, "b": "bar"}