# 从 GitHub 拉取源码
git clone -b main https://github.com/agentscope-ai/agentscope.git

# 以可编辑模式安装包
cd agentscope
pip install -e .

pip install agentscope

from agentscope.agent import ReActAgent, UserAgent
from agentscope.model import DashScopeChatModel
from agentscope.formatter import DashScopeChatFormatter
from agentscope.memory import InMemoryMemory
from agentscope.tool import Toolkit, execute_python_code, execute_shell_command
import os, asyncio


async def main():
    toolkit = Toolkit()
    toolkit.register_tool_function(execute_python_code)
    toolkit.register_tool_function(execute_shell_command)

    agent = ReActAgent(
        name="Friday",
        sys_prompt="You're a helpful assistant named Friday.",
        model=DashScopeChatModel(
            model_name="qwen-max",
            api_key=os.environ["DASHSCOPE_API_KEY"],
            stream=True,
        ),
        memory=InMemoryMemory(),
        formatter=DashScopeChatFormatter(),
        toolkit=toolkit,
    )

    user = UserAgent(name="user")

    msg = None
    while True:
        msg = await agent(msg)
        msg = await user(msg)
        if msg.get_text_content() == "exit":
            break

asyncio.run(main())

from agentscope.mcp import HttpStatelessClient
from agentscope.tool import Toolkit
import os

async def fine_grained_mcp_control():
    # 以高德MCP为例，初始化MCP客户端
    client = HttpStatelessClient(
        name="gaode_mcp",
        transport="streamable_http",
        url=f"https://mcp.amap.com/mcp?key={os.environ['GAODE_API_KEY']}",
    )

    # 将MCP工具获取为**本地可调用函数**，并在任何地方使用
    func = await client.get_callable_function(func_name="maps_geo")

    # 选项1：直接调用
    await func(address="天安门广场", city="北京")

    # 选项2：作为工具传递给智能体
    toolkit = Toolkit()
    toolkit.register_tool_function(func)
    # ...

    # 选项3：包装为更复杂的工具
    # ...

from agentscope.pipeline import MsgHub, sequential_pipeline
from agentscope.message import Msg
import asyncio

async def multi_agent_conversation():
    # 创建智能体
    agent1 = ...
    agent2 = ...
    agent3 = ...
    agent4 = ...

    # 创建消息中心来管理多智能体对话
    async with MsgHub(
        participants=[agent1, agent2, agent3],
        announcement=Msg("Host", "请介绍一下自己。", "assistant")
    ) as hub:
        # 按顺序发言
        await sequential_pipeline([agent1, agent2, agent3])
        # 动态管理参与者
        hub.add(agent4)
        hub.delete(agent3)
        await hub.broadcast(Msg("Host", "再见！", "assistant"))

asyncio.run(multi_agent_conversation())

npm install -g @agentscope/studio

as_studio

@article{agentscope_v1,
    author  = {
        Dawei Gao,
        Zitao Li,
        Yuexiang Xie,
        Weirui Kuang,
        Liuyi Yao,
        Bingchen Qian,
        Zhijian Ma,
        Yue Cui,
        Haohao Luo,
        Shen Li,
        Lu Yi,
        Yi Yu,
        Shiqi He,
        Zhiling Luo,
        Wenmeng Zhou,
        Zhicheng Zhang,
        Xuguang He,
        Ziqian Chen,
        Weikai Liao,
        Farruh Isakulovich Kushnazarov,
        Yaliang Li,
        Bolin Ding,
        Jingren Zhou}
    title   = {AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications},
    journal = {CoRR},
    volume  = {abs/2508.16279},
    year    = {2025},
}

@article{agentscope,
    author  = {
        Dawei Gao,
        Zitao Li,
        Xuchen Pan,
        Weirui Kuang,
        Zhijian Ma,
        Bingchen Qian,
        Fei Wei,
        Wenhao Zhang,
        Yuexiang Xie,
        Daoyuan Chen,
        Liuyi Yao,
        Hongyi Peng,
        Zeyu Zhang,
        Lin Zhu,
        Chen Cheng,
        Hongzhu Shi,
        Yaliang Li,
        Bolin Ding,
        Jingren Zhou}
    title   = {AgentScope: A Flexible yet Robust Multi-Agent Platform},
    journal = {CoRR},
    volume  = {abs/2402.14034},
    year    = {2024},
}