agentscope

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What is AgentScope 2.0?

AgentScope 2.0 is a production-ready, easy-to-use agent framework with essential abstractions that keep up with rising model capability.

We design for increasingly agentic LLMs. Our approach leverages the models' reasoning and tool use abilities rather than constraining them with strict prompts and opinionated orchestrations.

News

• [2026-10] FEAT Experimental: Agent service supports realtime voice conversations over WebRTC, with text and voice sharing the same session history.

• [2026-09] FEAT Experimental: SOP supported — run multi-step tasks as standard operating procedures, in both the framework and agent service. Docs | Service

• [2026-09] FEAT: TeamPipeline supported — a leader agent delegates tasks to member agents. Docs

• [2026-09] INTE: MiniMax chat models supported via MiniMaxChatModel (MiniMax-M3 by default).

• [2026-09] FEAT: Model routing supported — use ModelRouterMiddleware to select an appropriate chat model for each reply.

• [2026-09] INTE: Jev classifier model supported through the TypeSafe SDK via JevClassifierModel.

• [2026-09] FEAT: agentscope-skill now supports AgentScope v2.

• [2026-09] INTE: Support DashScope, OpenAI, Gemini and xAI realtime APIs in RealtimeAgent. Example | Docs

• [2026-09] FEAT Experimental: Realtime voice agent supported. Example | Docs

• [2026-09] FEAT: A2A protocol supported — chat with any remote A2A agent via A2AAgent. Example | Docs

More news →

Community

Welcome to join our community on

Quickstart

Installation

AgentScope requires Python 3.11 or higher.

From PyPI

uv pip install agentscope

From source

# Pull the source code from GitHub
git clone -b main https://github.com/agentscope-ai/agentscope.git

# Install the package in editable mode
cd agentscope

uv pip install -e .

Agent

The SDK layer — compose an agent from a rich set of building blocks:

Start your first agent with AgentScope 2.0 in console:

from agentscope.agent import Agent
from agentscope.console import launch_console
from agentscope.tool import Toolkit, Bash, Grep, Glob, Read, Write, Edit
from agentscope.credential import DashScopeCredential
from agentscope.model import DashScopeChatModel

import os, asyncio


async def main() -> None:
    agent = Agent(
        name="Friday",
        system_prompt="You're a helpful assistant named Friday.",
        model=DashScopeChatModel(
            credential=DashScopeCredential(
              api_key=os.environ["DASHSCOPE_API_KEY"]
            ),
            model="qwen3.6-plus",
        ),
        toolkit=Toolkit(
            tools=[
                Bash(),
                Grep(),
                Glob(),
                Read(),
                Write(),
                Edit(),
            ]
        ),
    )

    # Chat with the agent in the terminal — streamed output, tool-call
    # confirmation and Ctrl+C interruption are all handled for you
    await launch_console(agent)

asyncio.run(main())

Agent Service — All You Need to Build Your App