From cb516b4986b1ea928ad1c476b435c551a2f19895 Mon Sep 17 00:00:00 2001
From: miluELK <2636626273@qq.com>
Date: Tue, 28 Oct 2025 08:22:52 +0800
Subject: [PATCH] =?UTF-8?q?feat:=20=E4=B8=BAagent=E5=B0=81=E8=A3=85?=
 =?UTF-8?q?=E4=B8=BAtool=E8=B0=83=E7=94=A8=E6=B7=BB=E5=8A=A0=E4=BA=86runti?=
 =?UTF-8?q?meconfig=EF=BC=8C=E5=8F=AF=E4=BB=A5=E4=BC=A0=E9=80=92=E8=AE=B0?=
 =?UTF-8?q?=E5=BF=86?=
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Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 src/agents/multiAgent/state.py |  4 +++-
 src/agents/multiAgent/tools.py | 21 +++++++++++++++++----
 2 files changed, 20 insertions(+), 5 deletions(-)

diff --git a/src/agents/multiAgent/state.py b/src/agents/multiAgent/state.py
index f46bfb9c..927bfa95 100644
--- a/src/agents/multiAgent/state.py
+++ b/src/agents/multiAgent/state.py
@@ -9,9 +9,11 @@ from typing import Annotated
 from langchain.messages import AnyMessage
 from langgraph.graph import add_messages
 
+from src.agents.common.state import BaseState
+
 
 @dataclass
-class State:
+class State(BaseState):
     """Defines the input state for the agent, representing a narrower interface to the outside world.
 
     This class is used to define the initial state and structure of incoming data.
diff --git a/src/agents/multiAgent/tools.py b/src/agents/multiAgent/tools.py
index 246d8ddd..19c4e417 100644
--- a/src/agents/multiAgent/tools.py
+++ b/src/agents/multiAgent/tools.py
@@ -2,6 +2,7 @@ import os
 from typing import Any
 
 from langchain.tools import tool
+from langchain_core.runnables import RunnableConfig
 
 from src.agents import agent_manager
 from src.agents.common.toolkits.mysql import get_mysql_tools
@@ -11,19 +12,25 @@ from src.utils import logger
 # TODO[修改建议]:能不能通过前端直接指定子智能体？
 # 调用子智能体后的日志是输出到tool_calls的
 @tool(name_or_callable="对话聊天智能体", description="调用指定智能体进行对话聊天的功能")
-async def call_chatbot(query: str) -> str:
+async def call_chatbot(query: str, config: RunnableConfig) -> str:
     """
     调用指定chatbot智能体进行对话聊天的功能
 
     Args:
         query: 根据需要构造的提问
+        config: LangGraph运行时配置(自动注入)
     Returns:
         str: 最终的回答结果
     """
     try:
         input = [{"role": "user", "content": query}]
         chatbot = agent_manager.get_agent("ChatbotAgent")
-        message = await chatbot.invoke_messages(input)
+        configurable = config.get("configurable",{})
+        input_context = {
+            "thread_id":configurable.get("thread_id"),
+            "user_id": configurable.get("user_id"),
+        }
+        message = await chatbot.invoke_messages(input,input_context=input_context)
         # 直接获取最后一个消息的内容
         final_answer = message.get('messages', [])[-1].content
         logger.info(f"ChatbotAgent: {final_answer}")
@@ -33,19 +40,25 @@ async def call_chatbot(query: str) -> str:
         raise
 
 @tool(name_or_callable="加密计算智能体", description="调用指定智能体进行加密计算的功能")
-async def call_react_agent(query: str) -> str:
+async def call_react_agent(query: str, config: RunnableConfig) -> str:
     """
     调用指定智能体进行加密计算的功能
 
     Args:
         query: 根据需要构造的提问
+        config: LangGraph运行时配置(自动注入)
     Returns:
         str: 最终的回答结果
     """
     try:
         input = [{"role": "user", "content": query}]
         chatbot = agent_manager.get_agent("ReActAgent")
-        message = await chatbot.invoke_messages(input)
+        configurable = config.get("configurable",{})
+        input_context = {
+            "thread_id":configurable.get("thread_id"),
+            "user_id": configurable.get("user_id"),
+        }
+        message = await chatbot.invoke_messages(input,input_context=input_context)
         # 直接获取最后一个消息的内容
         final_answer = message.get('messages', [])[-1].content
         logger.info(f"ReActAgent: {final_answer}")