目标流水线

import asyncio
import os

from agentscope.agent import Agent
from agentscope.console import launch_console
from agentscope.credential import DashScopeCredential
from agentscope.model import DashScopeChatModel
from agentscope.pipeline import GoalPipeline
from agentscope.tool import Toolkit
from agentscope.workspace import LocalWorkspace


async def main() -> None:
    # 两个智能体共享同一个工作区，验证者才能看到执行者真正写出来的
    # 内容，而不是它声称写了什么
    async with LocalWorkspace(workdir="./workspace") as workspace:
        model = DashScopeChatModel(
            credential=DashScopeCredential(
                api_key=os.getenv("DASHSCOPE_API_KEY"),
            ),
            model="qwen3.8-max",
        )

        # 执行者：负责干活，用工作区的文件工具写代码
        executor = Agent(
            name="Executor",
            system_prompt="You're a programmer named 'Executor'.",
            model=model,
            toolkit=Toolkit(tools=await workspace.list_tools()),
            offloader=workspace,
        )

        # 验证者：负责判定。装配同一套工具，因此它能真的去读代码、
        # 跑测试，而不是只凭执行者的自述下结论
        verifier = Agent(
            name="Verifier",
            system_prompt="You're a reviewer named 'Verifier'.",
            model=model,
            toolkit=Toolkit(tools=await workspace.list_tools()),
            offloader=workspace,
        )

        pipe = GoalPipeline(
            executor=executor,
            verifier=verifier,
            # 最多被驳回 5 次，之后即便未通过也停止
            max_iters=5,
        )

        # 流水线满足 PipelineProtocol，可以直接交给终端 UI
        await launch_console(agent=pipe)


asyncio.run(main())

# 中途出现 RequireUserConfirmEvent，事件流随即结束
async for event in pipe.reply_stream(user_msg):
    ...

# 把用户的答复递回去，从中断处接着跑
async for event in pipe.reply_stream(user_confirm_result_event):
    ...

await launch_console(agent=pipe)