mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-07 18:27:52 +02:00
temp: remove ToolInterruptNode code (#4792)
remove tool node specific code for post_model_hook release
This commit is contained in:
Sydney Runkle
@@ -1,12 +1,7 @@
|
||||
from copy import deepcopy
|
||||
from typing import Any, Literal, Optional, Union, cast
|
||||
from typing import Literal, Optional, Union
|
||||
|
||||
from langchain_core.messages import ToolCall, ToolMessage
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from langgraph.types import Command, interrupt
|
||||
from langgraph.utils.runnable import RunnableCallable
|
||||
|
||||
|
||||
class HumanInterruptConfig(TypedDict):
|
||||
"""Configuration that defines what actions are allowed for a human interrupt.
|
||||
@@ -93,159 +88,3 @@ class HumanResponse(TypedDict):
|
||||
|
||||
type: Literal["accept", "ignore", "response", "edit"]
|
||||
args: Union[None, str, ActionRequest]
|
||||
|
||||
|
||||
class InterruptToolNode(RunnableCallable):
|
||||
"""Prebuilt post model hook node used to enable common patterns for tool interrupts.
|
||||
|
||||
For any tools with specified policies, an interrupt will be raised when the LLM returns
|
||||
a tool call for said tool. The interrupt policy will be used to determine what sort of resume logic is allowed.
|
||||
Any of the following resume patterns are supported:
|
||||
|
||||
* accept: the tool call is executed as planned
|
||||
* edit: the args for the tool call are edited and then the tool call is executed
|
||||
* response: text response/feedback is fed back into the LLM
|
||||
* ignore: the current tool call is ignored / skipped
|
||||
|
||||
Args:
|
||||
**interrupt_policy: a mapping of tool names to [`HumanInterruptConfig`][prebuilt.interrupt.HumanInterruptConfig] dictionaries
|
||||
specifying which interrupt patterns to enable for said tool.
|
||||
|
||||
Example:
|
||||
```python
|
||||
from langgraph.prebuilt import create_react_agent
|
||||
from langgraph.checkpoint.memory import InMemorySaver
|
||||
from langgraph.prebuilt.interrupt import HumanInterruptConfig, InterruptToolNode
|
||||
from langgraph.types import Command
|
||||
|
||||
|
||||
def book_hotel(hotel_name: str) -> str:
|
||||
'''Book a room at the provided hotel.'''
|
||||
# Some hotel API calls, a sensitive / expensive operation
|
||||
return f"Booked a hotel at {hotel_name}."
|
||||
|
||||
|
||||
agent = create_react_agent(
|
||||
"openai:gpt-4.1",
|
||||
tools=[book_hotel],
|
||||
prompt="You are a hotel booking assistant.",
|
||||
post_model_hook=InterruptToolNode(
|
||||
book_hotel=HumanInterruptConfig(
|
||||
allow_accept=True,
|
||||
allow_edit=True,
|
||||
allow_ignore=True,
|
||||
allow_respond=True,
|
||||
)
|
||||
),
|
||||
checkpointer=InMemorySaver(),
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": 1}}
|
||||
|
||||
response = agent.invoke(
|
||||
{"messages": [{"role": "user", "content": "please book a hotel at the hilton inn in boston."}]},
|
||||
config=config,
|
||||
)
|
||||
|
||||
response = agent.invoke(Command(resume={"type": "accept"}), config=config)
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(self, **interrupt_policy: HumanInterruptConfig):
|
||||
super().__init__(self._func, self._afunc)
|
||||
self.interrupt_policy = interrupt_policy
|
||||
|
||||
def _interrupt(
|
||||
self,
|
||||
tool_call: ToolCall,
|
||||
interrupt_config: HumanInterruptConfig,
|
||||
) -> Union[ToolCall, ToolMessage]:
|
||||
"""Interrupt before a tool call and ask for human input."""
|
||||
call_id = tool_call["id"]
|
||||
tool_name = tool_call["name"]
|
||||
|
||||
request = HumanInterrupt(
|
||||
action_request=ActionRequest(
|
||||
action=tool_name,
|
||||
args=tool_call["args"],
|
||||
),
|
||||
config=interrupt_config,
|
||||
description=f"Please review tool call for `{tool_name}` before execution.",
|
||||
)
|
||||
response = interrupt([request])
|
||||
|
||||
# resume provided by agent inbox as a list
|
||||
response = response[0] if isinstance(response, list) else response
|
||||
|
||||
try:
|
||||
response_type = response.get("type")
|
||||
except AttributeError:
|
||||
raise TypeError(
|
||||
f"Unexpected resume value: {response}."
|
||||
f"Expected a dict with `'type'` key."
|
||||
)
|
||||
|
||||
if response_type == "accept" and interrupt_config["allow_accept"]:
|
||||
return tool_call
|
||||
elif response_type == "edit" and interrupt_config["allow_edit"]:
|
||||
return ToolCall(
|
||||
args=cast(ActionRequest, response)["args"]["args"],
|
||||
name=tool_name,
|
||||
id=call_id,
|
||||
type="tool_call",
|
||||
)
|
||||
elif response_type == "response" and interrupt_config["allow_respond"]:
|
||||
return ToolMessage(
|
||||
content=cast(str, response["args"]),
|
||||
name=tool_name,
|
||||
tool_call_id=call_id,
|
||||
status="error",
|
||||
)
|
||||
elif response_type == "ignore" and interrupt_config["allow_ignore"]:
|
||||
return ToolMessage(
|
||||
content=f"User ignored the tool call for `{tool_name}` with id {call_id}",
|
||||
name=tool_name,
|
||||
tool_call_id=call_id,
|
||||
status="success",
|
||||
)
|
||||
|
||||
allowed_types = [
|
||||
type_name
|
||||
for type_name, is_allowed in {
|
||||
"accept": interrupt_config["allow_accept"],
|
||||
"edit": interrupt_config["allow_edit"],
|
||||
"response": interrupt_config["allow_respond"],
|
||||
"ignore": interrupt_config["allow_ignore"],
|
||||
}.items()
|
||||
if is_allowed
|
||||
]
|
||||
|
||||
raise ValueError(
|
||||
f"Unexpected human response: {response}. "
|
||||
f"Expected one with `'type'` in {allowed_types} based on {tool_name}'s interrupt configuration."
|
||||
)
|
||||
|
||||
def _func(self, input: dict[str, Any]) -> Command:
|
||||
ai_msg = input["messages"][-1]
|
||||
tool_calls: list[ToolCall] = deepcopy(ai_msg.tool_calls) or []
|
||||
tool_messages: list[ToolMessage] = []
|
||||
|
||||
for idx, tool_call in enumerate(tool_calls):
|
||||
if interrupt_config := self.interrupt_policy.get(tool_call["name"]):
|
||||
interrupt_result = self._interrupt(
|
||||
tool_call=tool_call, interrupt_config=interrupt_config
|
||||
)
|
||||
|
||||
if isinstance(interrupt_result, ToolMessage):
|
||||
tool_messages.append(interrupt_result)
|
||||
else:
|
||||
tool_calls[idx] = interrupt_result
|
||||
|
||||
updated_ai_msg = ai_msg.copy(update={"tool_calls": tool_calls})
|
||||
|
||||
# conditional routing logic for post_model_hook will direct to the tools node
|
||||
# or agent node depending on if there are pending tool calls
|
||||
return {"messages": [updated_ai_msg, *tool_messages]}
|
||||
|
||||
async def _afunc(self, input: dict[str, Any]) -> Command:
|
||||
return self._func(input)
|
||||
|
||||
@@ -1,191 +0,0 @@
|
||||
import pytest
|
||||
from langchain_core.messages import ToolMessage
|
||||
from langchain_core.runnables import RunnableConfig
|
||||
|
||||
from langgraph.checkpoint.base import BaseCheckpointSaver
|
||||
from langgraph.prebuilt import create_react_agent
|
||||
from langgraph.prebuilt.interrupt import HumanInterruptConfig, InterruptToolNode
|
||||
from langgraph.types import Command
|
||||
from tests.model import FakeToolCallingModel
|
||||
|
||||
|
||||
def hello_tool(name: str) -> str:
|
||||
"""Return a greeting for the provided person."""
|
||||
return f"Hello, {name}!"
|
||||
|
||||
|
||||
post_model_hook = InterruptToolNode(
|
||||
hello_tool=HumanInterruptConfig(
|
||||
allow_accept=True,
|
||||
allow_edit=True,
|
||||
allow_ignore=True,
|
||||
allow_respond=True,
|
||||
)
|
||||
)
|
||||
|
||||
default_model = FakeToolCallingModel(
|
||||
tool_calls=[
|
||||
[
|
||||
{
|
||||
"name": "hello_tool",
|
||||
"args": {"name": "lady gaga"},
|
||||
"id": "some-random-id",
|
||||
}
|
||||
]
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
def test_interrupt_surfaced(
|
||||
request: pytest.FixtureRequest,
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
agent = create_react_agent(
|
||||
default_model,
|
||||
[hello_tool],
|
||||
checkpointer=sync_checkpointer,
|
||||
post_model_hook=post_model_hook,
|
||||
)
|
||||
config: RunnableConfig = {"configurable": {"thread_id": "1"}}
|
||||
result = agent.invoke({"messages": [("user", "Say hi to lady gaga!")]}, config)
|
||||
|
||||
interrupt_data = result["__interrupt__"]
|
||||
assert interrupt_data[0].value == [
|
||||
{
|
||||
"action_request": {"action": "hello_tool", "args": {"name": "lady gaga"}},
|
||||
"config": {
|
||||
"allow_accept": True,
|
||||
"allow_edit": True,
|
||||
"allow_ignore": True,
|
||||
"allow_respond": True,
|
||||
},
|
||||
"description": "Please review tool call for `hello_tool` before execution.",
|
||||
}
|
||||
]
|
||||
|
||||
response = agent.invoke(Command(resume={"type": "accept"}), config=config)
|
||||
tool_message: ToolMessage = response["messages"][-2]
|
||||
assert tool_message.content == "Hello, lady gaga!"
|
||||
assert tool_message.name == "hello_tool"
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"resume, expected_content",
|
||||
[
|
||||
({"type": "accept"}, "Hello, lady gaga!"),
|
||||
(
|
||||
{"type": "ignore"},
|
||||
"User ignored the tool call for `hello_tool` with id some-random-id",
|
||||
),
|
||||
(
|
||||
{
|
||||
"type": "edit",
|
||||
"args": {"action": "hello_tool", "args": {"name": "bruno mars"}},
|
||||
},
|
||||
"Hello, bruno mars!",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_interrupt_resume_variants(
|
||||
request: pytest.FixtureRequest,
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
resume: dict,
|
||||
expected_content: str,
|
||||
) -> None:
|
||||
agent = create_react_agent(
|
||||
default_model,
|
||||
[hello_tool],
|
||||
checkpointer=sync_checkpointer,
|
||||
post_model_hook=post_model_hook,
|
||||
)
|
||||
|
||||
config: RunnableConfig = {"configurable": {"thread_id": "1"}}
|
||||
agent.invoke({"messages": [("user", "Say hi to lady gaga!")]}, config)
|
||||
|
||||
response = agent.invoke(Command(resume=resume), config=config)
|
||||
tool_message: ToolMessage = response["messages"][-2]
|
||||
assert tool_message.name == "hello_tool"
|
||||
assert tool_message.content == expected_content
|
||||
|
||||
if resume["type"] == "edit":
|
||||
ai_msg = response["messages"][-1]
|
||||
assert ai_msg.tool_calls == [
|
||||
{
|
||||
"name": "hello_tool",
|
||||
"args": {"name": "lady gaga"},
|
||||
"id": "some-random-id",
|
||||
"type": "tool_call",
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
def test_resume_with_response(
|
||||
request: pytest.FixtureRequest,
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
model = FakeToolCallingModel(
|
||||
tool_calls=[
|
||||
[
|
||||
{
|
||||
"name": "hello_tool",
|
||||
"args": {"name": "lady gaga"},
|
||||
"id": "some-random-id",
|
||||
}
|
||||
],
|
||||
[
|
||||
{
|
||||
"name": "hello_tool",
|
||||
"args": {"name": "bruno mars"},
|
||||
"id": "some-random-id-2",
|
||||
}
|
||||
],
|
||||
]
|
||||
)
|
||||
|
||||
agent = create_react_agent(
|
||||
model,
|
||||
[hello_tool],
|
||||
checkpointer=sync_checkpointer,
|
||||
post_model_hook=post_model_hook,
|
||||
)
|
||||
|
||||
config: RunnableConfig = {"configurable": {"thread_id": "1"}}
|
||||
agent.invoke({"messages": [("user", "Say hi to lady gaga!")]}, config)
|
||||
|
||||
# Provide user response
|
||||
agent.invoke(
|
||||
Command(
|
||||
resume={
|
||||
"type": "response",
|
||||
"args": "actually, please say hello to bruno mars",
|
||||
}
|
||||
),
|
||||
config=config,
|
||||
)
|
||||
|
||||
# Accept the updated call
|
||||
response = agent.invoke(Command(resume={"type": "accept"}), config=config)
|
||||
|
||||
assert len(response["messages"]) == 6
|
||||
tool_message: ToolMessage = response["messages"][-2]
|
||||
assert tool_message.name == "hello_tool"
|
||||
assert tool_message.content == "Hello, bruno mars!"
|
||||
|
||||
|
||||
def test_resume_with_type_not_allowed(sync_checkpointer: BaseCheckpointSaver) -> None:
|
||||
agent = create_react_agent(
|
||||
default_model,
|
||||
[hello_tool],
|
||||
checkpointer=sync_checkpointer,
|
||||
post_model_hook=post_model_hook,
|
||||
)
|
||||
config: RunnableConfig = {"configurable": {"thread_id": "1"}}
|
||||
agent.invoke({"messages": [("user", "Say hi to lady gaga!")]}, config)
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
agent.invoke(Command(resume={"type": "not-allowed"}), config=config)
|
||||
|
||||
assert (
|
||||
str(exc_info.value)
|
||||
== "Unexpected human response: {'type': 'not-allowed'}. Expected one with `'type'` in ['accept', 'edit', 'response', 'ignore'] based on hello_tool's interrupt configuration."
|
||||
)
|
||||
Reference in New Issue
Block a user