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from langchain_core.tools import tool
from langchain_core.messages import ToolMessage
from langgraph.types import Command
from typing import Annotated, Any
from langgraph_swarm.handoff import _get_field, InjectedState
from loguru import logger
def create_end_conversation_tool(
name: str = "end_conversation",
description: str = "End the conversation naturally when the discussion has reached its conclusion or the user indicates they want to stop",
) -> callable:
"""Create a tool that can end the conversation.
Args:
name: Name of the tool to use for ending the conversation.
description: Description for the end conversation tool.
Returns:
A tool that when called will end the conversation.
"""
@tool(name, description=description)
def end_conversation(
reason: str,
# Annotation is typed as Any instead of StateLike. StateLike
# trigger validation issues from Pydantic / langchain_core interaction.
# https://github.com/langchain-ai/langchain/issues/32067
state: Annotated[Any, InjectedState],
tool_call_id: str,
) -> Command:
"""End the conversation with the given reason.
Args:
reason: The reason for ending the conversation
"""
logger.info(f"Conversation ended. Reason: {reason}")
tool_message = ToolMessage(
content=f"Conversation ended: {reason}",
name=name,
tool_call_id=tool_call_id,
)
# Return a Command that goes to END node
return Command(
# goto="END",
graph=Command.PARENT,
update={
"messages": [*_get_field(state, "messages"), tool_message],
},
)
return end_conversation
@tool
def function_name(
input: str,
) -> str:
"""
Mô tả chức năng của hàm này.
"""
logger.info(f"Received input: {input}")
# Thực hiện các thao tác cần thiết với input
result: str = f"Processed: {input}"
logger.info(f"Returning result: {result}")
return result
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