工具

from langchain_core.messages import AIMessage
from langchain_core.tools import tool

from langgraph.prebuilt import ToolNode

@tool
def get_weather(location: str):
  """获取当前城市的天气状态"""
  if location.lower() in ["北京", "beijing"]:
    return "今天阳光明媚"
  else:
    return "今天在下雨"
  
@tool
def get_coolest_cities() -> list[str]:
  """获取一组最近的城市列表"""
  return ["北京"]

tools = [get_weather, get_coolest_cities]
tool_node = ToolNode(tools)

tools = [get_weather, get_coolest_cities]
tool_node = ToolNode(tools)

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
	model_name="gpt-4.1-mini-2025-04-14",
    temperature=0
).bind_tools(tools)

llm.invoke("北京天气怎么样").tool_calls

res = tool_node.invoke({"messages": [llm.invoke("北京天气怎么样")]})

from langgraph.graph.message import MessagesState
from langchain_core.messages import HumanMessage
from langchain_core.tools import tool
from my_openai.deepseekv3 import get_deepseek_v3_client
from langgraph.graph import StateGraph, START
from langgraph.prebuilt import ToolNode, tools_condition

@tool
def wheather(city: str):
  """模拟一个天气搜索工具"""
  if "北京" in city.lower() or "Beijing" in city.lower():
    return "北京天气晴朗，气温20度"
  elif "上海" in city.lower() or "Shanghai" in city.lower():
    return "上海多云，气温15度"
  else:
    return "现在天气很好"

tools = [wheather]
tool_node = ToolNode(tools)
llm = get_deepseek_v3_client().bind_tools(tools)


def chatbot(state: MessagesState):
  return { "messages": [llm.invoke(state["messages"])] }

builder = StateGraph(MessagesState)
builder.add_node("chatbot", chatbot)
builder.add_node("tools", tool_node)
builder.add_edge(START, "chatbot")
# 使用 tools_condition 简化工具路由边
builder.add_conditional_edges("chatbot", tools_condition)
builder.add_edge("tools", "chatbot")

graph = builder.compile()

result = graph.invoke({ "messages": [HumanMessage(content="北京天气怎么样？")] })
print(result)

from langgraph.prebuilt import InjectedState, InjectedStore
from typing_extensions import Annotated
from langgraph.store.base import BaseStore
from langchain_core.runnables import RunnableConfig

@tool
def wheather(
  # 参数正常传入
  city: str,
  # 状态
  state: Annotated[MessagesState, InjectedState],
  # 配置
  config: RunnableConfig,
  # 数据库
  store: Annotated[BaseStore, InjectedStore()],
):
  return "好天气"

class state(MessagesState):
    user_info: dict[str, Any]

@tool
def lookup_user_info(tool_call_id: Annotated[str, InjectedToolCallId], config: RunnableConfig):
    """用这个来查找用户信息，以便更好地帮助他们解答问题。"""
    user_info = get_user_info(config)
    return Command(
        update={
            # 更新用户信息
            "user_info": user_info,
            # 更新消息列表
            "messages": [ToolMessage(f"用户名称是{user_info['name']}。用户居住在{user_info['location']}", tool_call_id=tool_call_id)]
        }
    )

from langchain_core.tools import StructuredTool

def get_weather(location: str):
  if location.lower() in ["北京", "beijing"]:
    return "今天阳光明媚"
  else:
    return "今天在下雨"

tool = StructuredTool.from_function(
  get_weather,
  name="get_weather",
  description="模拟一个天气搜索工具",
)