use langgraph's multi-agents and the deepseek-r1

[Zhengyu-Ju]

I want to use langgraph's multi-agents and the deepseek-r1 large model. However, it seems that when the agent is called, there is no prompt for the tool in the prompt, resulting in the inability to call the agent's tool. But it is possible to use qwen-72b

import re
from typing import Annotated, Literal
from langchain.chat_models import init_chat_model
from langchain_core.tools import tool
from langchain_experimental.utilities import PythonREPL

# 移除真实搜索工具，创建模拟工具
@tool
def mock_search_tool(query: Annotated[str, "The search query to process"]) -> str:
    """获取2023年纽约和加州的GDP预设数据。支持查询参数示例：'latest GDP of New York'"""
    preset_data = {
        "latest GDP of New York": "2023年纽约州GDP为2.1万亿美元",
        "latest GDP of California": "2023年加利福尼亚州GDP为3.6万亿美元"
    }
    return preset_data.get(query, "2023年纽约州GDP为2.1万亿美元，2023年加利福尼亚州GDP为3.6万亿美元")

repl = PythonREPL()

@tool
def python_repl_tool(
    code: Annotated[str, "The python code to execute to generate your chart."],
):
    """Use this to execute python code and do math. If you want to see the output of a value,
    you should print it out with `print(...)`. This is visible to the user."""
    try:
        result = repl.run(code)
    except BaseException as e:
        return f"Failed to execute. Error: {repr(e)}"
    result_str = f"Successfully executed:\n\`\`\`python\n{code}\n\`\`\`\nStdout: {result}"
    return result_str

from typing_extensions import TypedDict
from langgraph.graph import MessagesState, END
from langgraph.types import Command

members = ["researcher", "coder"]
options = members + ["FINISH"]
system_prompt = (
    "你是一个工作流协调员，负责管理研究人员和程序员的协作。"
    f"当前工作人员: {members}。根据用户请求，"
    "选择需要执行下一步操作的工作人员。当所有任务完成时，"
    "回复 FINISH。"
    "输出格式为{\"next\":""}"

)

class Router(TypedDict):
    """路由决策"""
    next: Literal["researcher", "coder", "FINISH"]


llm = init_chat_model(model="openai:deepseek-r1", api_key="xxx",
                 base_url="xxx")

class State(MessagesState):
    next: str

def supervisor_node(state: State) -> Command[Literal["researcher", "coder", "__end__"]]:
    messages = [
        {"role": "system", "content": system_prompt},
    ] + state["messages"]
    response = llm.invoke(messages)
    goto = eval(re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL))["next"]
    if goto == "FINISH":
        goto = END
    return Command(goto=goto, update={"next": goto})

from langchain_core.messages import HumanMessage
from langgraph.graph import StateGraph, START, END
from langgraph.prebuilt import create_react_agent

# 修改研究代理使用模拟工具
research_agent = create_react_agent(
    llm,
    tools=[mock_search_tool],
    prompt="您是经济数据分析员，使用模拟工具获取预设的GDP数据。请不要进行数学计算。"
)

def research_node(state: State) -> Command[Literal["supervisor"]]:
    result = research_agent.invoke(state)
    return Command(
        update={
            "messages": [
                HumanMessage(content=result["messages"][-1].content, name="researcher")
            ]
        },
        goto="supervisor",
    )

# 代码执行节点保持不变
code_agent = create_react_agent(llm, tools=[python_repl_tool])

def code_node(state: State) -> Command[Literal["supervisor"]]:
    result = code_agent.invoke(state)
    return Command(
        update={
            "messages": [
                HumanMessage(content=result["messages"][-1].content, name="coder")
            ]
        },
        goto="supervisor",
    )

# 构建工作流
builder = StateGraph(State)
builder.add_edge(START, "supervisor")
builder.add_node("supervisor", supervisor_node)
builder.add_node("researcher", research_node)
builder.add_node("coder", code_node)

# 设置节点间连接
builder.add_edge("researcher", "supervisor")
builder.add_edge("coder", "supervisor")

graph = builder.compile()

# 测试执行
for s in graph.stream(
    {
        "messages": [
            (
                "user",
                "找出2023年纽约和加州的GDP，然后计算平均值",
            )
        ]
    },
    subgraphs=True,
):
    print(s)
    print("----")

When calling researcher_agent, it was found that the definition tool was not used at all,how can l modify it

[whtoo]

How to fix it? Anyone can help ? I face similiar issues!

[eternal-bug]

是不是要bind_tools？

llm_with_tools = llm.bind_tools([mock_search_tool])
research_agent = create_react_agent(
    llm_with_tools,
    tools=[mock_search_tool],
    prompt="您是经济数据分析员，使用模拟工具获取预设的GDP数据。请不要进行数学计算。"
)