同一个任务的六种写法

WEATHER = {"北京": "晴，25°C", "上海": "小雨，22°C"}
get_weather(city) -> WEATHER.get(city, "暂无数据")

import json
from typing import Any

from openai import OpenAI
from openai.types.responses import FunctionToolParam

WEATHER = {"北京": "晴，25°C", "上海": "小雨，22°C"}
client = OpenAI()
TOOLS: list[FunctionToolParam] = [
    {
        "type": "function",
        "name": "get_weather",
        "description": "查询某个城市今天的天气",
        "parameters": {
            "type": "object",
            "properties": {"city": {"type": "string"}},
            "required": ["city"],
            "additionalProperties": False,
        },
        "strict": True,
    }
]

history: list[Any] = [{"role": "user", "content": "北京和上海今天天气怎么样？"}]
while True:
    r = client.responses.create(model="gpt-6-astra", instructions="你是简洁的中文助手。", tools=TOOLS, input=history)
    history += r.output
    calls = [i for i in r.output if i.type == "function_call"]
    if not calls:
        print(r.output_text)
        break
    for c in calls:
        city = json.loads(c.arguments)["city"]
        history.append({"type": "function_call_output", "call_id": c.call_id, "output": WEATHER.get(city, "暂无数据")})

from agents import Agent, Runner
from agents.decorators import tool

WEATHER = {"北京": "晴，25°C", "上海": "小雨，22°C"}


@tool
def get_weather(city: str) -> str:
    """查询某个城市今天的天气。

    Args:
        city: 城市名，例如 北京。
    """
    return WEATHER.get(city, "暂无数据")


agent = Agent(name="天气助手", instructions="你是简洁的中文助手。", tools=[get_weather])
result = Runner.run_sync(agent, "北京和上海今天天气怎么样？")
print(result.final_output)

from anthropic import Anthropic, beta_tool

WEATHER = {"北京": "晴，25°C", "上海": "小雨，22°C"}
client = Anthropic()


@beta_tool
def get_weather(city: str) -> str:
    """查询某个城市今天的天气。

    Args:
        city: 城市名，例如 北京。
    """
    return WEATHER.get(city, "暂无数据")


runner = client.beta.messages.tool_runner(
    model="claude-opus-5-5",
    max_tokens=16000,
    system="你是简洁的中文助手。",
    tools=[get_weather],
    messages=[{"role": "user", "content": "北京和上海今天天气怎么样？"}],
)
final = runner.until_done()
print("".join(b.text for b in final.content if b.type == "text"))

import asyncio
from typing import Annotated, Any

from claude_agent_sdk import ClaudeAgentOptions, ResultMessage, create_sdk_mcp_server, query, tool

WEATHER = {"北京": "晴，25°C", "上海": "小雨，22°C"}


@tool("get_weather", "查询某个城市今天的天气", {"city": Annotated[str, "城市名，例如 北京"]})
async def get_weather(args: dict[str, Any]) -> dict[str, Any]:
    return {"content": [{"type": "text", "text": WEATHER.get(args["city"], "暂无数据")}]}


async def main() -> None:
    options = ClaudeAgentOptions(
        system_prompt="你是简洁的中文助手。",
        mcp_servers={"weather": create_sdk_mcp_server(name="weather", version="1.0.0", tools=[get_weather])},
        allowed_tools=["mcp__weather__get_weather"],  # 预先批准，不弹审批
        tools=[],  # 为了公平对比，移除所有内置工具（Read、Bash 等）
    )
    async for message in query(prompt="北京和上海今天天气怎么样？", options=options):
        if isinstance(message, ResultMessage) and message.subtype == "success":
            print(message.result)


asyncio.run(main())

import { Agent, type AgentTool } from "@earendil-works/pi-agent-core";
import { createModels, Type } from "@earendil-works/pi-ai";
import { anthropicProvider } from "@earendil-works/pi-ai/providers/anthropic";

const WEATHER: Record<string, string> = { 北京: "晴，25°C", 上海: "小雨，22°C" };

const models = createModels();
models.setProvider(anthropicProvider()); // 换成 openaiProvider() 或 deepseekProvider()，其余代码都不用改
const model = models.getModel("anthropic", "claude-opus-5-5")!;

const params = Type.Object({ city: Type.String({ description: "城市名，例如 北京" }) });
const getWeather: AgentTool<typeof params> = {
  name: "get_weather",
  label: "查询天气",
  description: "查询某个城市今天的天气",
  parameters: params,
  execute: async (_id, { city }) => ({ content: [{ type: "text", text: WEATHER[city] ?? "暂无数据" }], details: {} }),
};

const agent = new Agent({
  initialState: { systemPrompt: "你是简洁的中文助手。", model, tools: [getWeather] },
  streamFn: models.streamSimple.bind(models),
});
agent.subscribe((e) => {
  if (e.type === "message_update" && e.assistantMessageEvent.type === "text_delta") {
    process.stdout.write(e.assistantMessageEvent.delta); // 流式输出
  }
});
await agent.prompt("北京和上海今天天气怎么样？");

# weather.cordis.yml（示意：格式参照仓库中 presets/*.patch.yml 的 insert 写法，笔者没有实际运行过）
- insert:
    - id: weather-tool
      name: './weather-tool.ts'

// 片段（no-check）：仓库源码 API，npm 0.0.1-rc.1 尚不支持 profile 和 patches 选项
import { DeepSeekHarness } from '@deepseek-ai/dsh-sdk-client'

await using harness = new DeepSeekHarness({
  profile: 'sdk',
  patches: ['./weather.cordis.yml'], // 叠加我们的插件
  provider: 'deepseek-official',
  model: 'deepseek-v4-flash',
})
const result = await harness.run('北京和上海今天天气怎么样？')
console.log(result.finalResponse)