The subgraph’s model is bind tools (the following course_qa_agent), when the query is not match the correct tool (maybe the query should rewrite, or the query is in the scope of subagent, but without correspond tool), then the model will response empty string.How to make the conversation continue ? maybe suggest better expression or tell the user “this query is no supported“ as response.
from typing import Literal
from langgraph.types import Command
from nodes.router import router
from agents.course_qa_agent import course_qa_graph
from agents.general_agent import general_graph
from langgraph.graph import START, StateGraph, MessagesState, END
from langchain_core.messages import AIMessage, ToolMessage # 导入消息对象
from langgraph.prebuilt import ToolNode, tools_condition
from tools.api_client import load_chat_model, toolbox
model = load_chat_model()
course_tools = toolbox.load_toolset('course_information_tools')
class CourseQAState(MessagesState):
"""数据库问答代理的状态类"""
answer: str
def call_model(state: CourseQAState) -> dict:
"""
使用检索到的信息作为上下文回答问题
Args:
state: 数据库问答状态
Returns:
dict: 包含答案和消息的字典
"""
system_message = '你是一个高效的数据查询助手'
model_with_tools = model.bind_tools(course_tools)
response = model_with_tools.invoke([
{"role": "system", "content": system_message},
*state['messages']])
response.name = 'course_qa_agent'
answer = response.content
return {"answer": answer,
"messages": [response]}
course_qa_graph_builder = StateGraph(CourseQAState)
course_qa_graph_builder.add_node('course_call_model', call_model)
course_qa_graph_builder.add_node('course_tools', ToolNode(course_tools))
course_qa_graph_builder.add_edge(START, "course_call_model")
course_qa_graph_builder.add_conditional_edges(
"course_call_model",
tools_condition,
{'tools': 'course_tools', '__end__': END}
)
course_qa_graph_builder.add_edge("course_tools", "course_call_model")
course_qa_graph = course_qa_graph_builder.compile(checkpointer=True)
class AgentState(MessagesState):
"""代理状态类，继承自MessagesState"""
pass
def supervisor(state: AgentState) -> Command[
Literal['course_qa_agent', 'general_agent', END]]:
"""
主管代理，负责路由到相应的子代理
Args:
state: 代理状态
Returns:
Command: 包含目标节点的命令
"""
messages = state.get('messages', [])
last_message = messages[-1]
# 如果是AI消息或工具消息，结束流程
if isinstance(last_message, AIMessage) or isinstance(last_message, ToolMessage):
return Command(goto=END)
response = router(state)
intent = response.get('intent', '通用对话')
routing_map = {
'课程查询': 'course_qa_agent',
'通用对话': 'general_agent'
}
target = routing_map.get(intent, 'general_agent')
return Command(goto=target)
def course_qa_agent(state: AgentState) -> Command[Literal['supervisor']]:
"""
数据库问答代理
Args:
state: 代理状态
Returns:
Command: 返回主管代理的命令
"""
response = course_qa_graph.invoke({'messages': state.get('messages', [])})
last_message = response.get('messages', [])[-1]
return Command(goto='supervisor', update={'messages': last_message})
def general_agent(state: AgentState) -> Command[Literal['supervisor']]:
"""
通用对话代理
Args:
state: 代理状态
Returns:
Command: 返回主管代理的命令
"""
response = general_graph.invoke({'messages': state.get('messages', [])})
last_message = response.get('messages', [])[-1]
# print('response:',last_message)
return Command(goto='supervisor', update={'messages': last_message})
builder = StateGraph(AgentState)
builder.add_node(supervisor)
builder.add_node(course_qa_agent)
builder.add_edge(START, "supervisor")