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| [**Tutorial**](https://doc.agentscope.io/) | [**Roadmap**](https://github.com/agentscope-ai/agentscope/blob/main/docs/roadmap.md) | [**FAQ**](https://doc.agentscope.io/tutorial/faq.html)\n\n\u003cp align=\"center\"\u003e\n  \u003cimg\n    src=\"https://img.alicdn.com/imgextra/i1/O1CN01nTg6w21NqT5qFKH1u_!!6000000001621-55-tps-550-550.svg\"\n    alt=\"AgentScope Logo\"\n    width=\"200\"\n  /\u003e\n\u003c/p\u003e\n\n\u003ch2 align=\"center\"\u003eAgentScope: Agent-Oriented Programming for Building LLM Applications\u003c/h2\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://arxiv.org/abs/2402.14034\"\u003e\n        \u003cimg\n            src=\"https://img.shields.io/badge/cs.MA-2402.14034-B31C1C?logo=arxiv\u0026logoColor=B31C1C\"\n            alt=\"arxiv\"\n        /\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pypi.org/project/agentscope/\"\u003e\n        \u003cimg\n            src=\"https://img.shields.io/badge/python-3.10+-blue?logo=python\"\n            alt=\"pypi\"\n        /\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pypi.org/project/agentscope/\"\u003e\n        \u003cimg\n            src=\"https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fpypi.org%2Fpypi%2Fagentscope%2Fjson\u0026query=%24.info.version\u0026prefix=v\u0026logo=pypi\u0026label=version\"\n            alt=\"pypi\"\n        /\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://doc.agentscope.io/\"\u003e\n        \u003cimg\n            src=\"https://img.shields.io/badge/Docs-English%7C%E4%B8%AD%E6%96%87-blue?logo=markdown\"\n            alt=\"docs\"\n        /\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://agentscope.io/\"\u003e\n        \u003cimg\n            src=\"https://img.shields.io/badge/GUI-AgentScope_Studio-blue?logo=look\u0026logoColor=green\u0026color=dark-green\"\n            alt=\"workstation\"\n        /\u003e\n    \u003c/a\u003e\n    \u003ca href=\"./LICENSE\"\u003e\n        \u003cimg\n            src=\"https://img.shields.io/badge/license-Apache--2.0-black\"\n            alt=\"license\"\n        /\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://trendshift.io/api/badge/repositories/10079\" alt=\"modelscope%2Fagentscope | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"/\u003e\n\u003c/p\u003e\n\n## 📢 News\n- **[2026-01]** Hi community, we are launching AgentScope Biweekly Meetings to share ecosystem updates and development plans - join us! [Details \u0026 Schedule](https://github.com/agentscope-ai/agentscope/discussions/1126)\n- **[2026-01]** AgentScope integrates [database support](https://doc.agentscope.io/tutorial/task_memory.html) in the memory module now, as well as the [memory compression](https://doc.agentscope.io/tutorial/task_agent.html) feature. Check our [example](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/short_term_memory/memory_compression) and [tutorial](https://doc.agentscope.io/tutorial/task_memory.html) for more details.\n- **[2025-12]** AgentScope supports [A2A(Agent-to-Agent) protocol](https://doc.agentscope.io/tutorial/task_a2a.html) now! Check our [example](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/a2a_agent) and [tutorial](https://doc.agentscope.io/tutorial/task_a2a.html) for more details.\n- **[2025-12]** AgentScope supports [TTS(Text-to-Speech)](https://doc.agentscope.io/tutorial/task_tts.html) now! Check our [example](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/tts) and [tutorial](https://doc.agentscope.io/tutorial/task_tts.html) for more details.\n- **[2025-11]** AgentScope supports [Anthropic Agent Skill](https://claude.com/blog/skills) now! Check our [example](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/agent_skill) and [tutorial](https://doc.agentscope.io/tutorial/task_agent_skill.html) for more details.\n- **[2025-11]** AgentScope open-sources [Alias-Agent](https://github.com/agentscope-ai/agentscope-samples/tree/main/alias) for diverse real-world tasks and [Data-Juicer Agent](https://github.com/agentscope-ai/agentscope-samples/tree/main/data_juicer_agent) for data processing.\n- **[2025-11]** AgentScope supports [Agentic RL](https://github.com/agentscope-ai/agentscope/tree/main/examples/tuner/react_agent) via integrating [Trinity-RFT](https://github.com/modelscope/Trinity-RFT) library.\n- **[2025-11]** AgentScope integrates [ReMe](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/long_term_memory/reme) for enhanced long-term memory.\n- **[2025-11]** AgentScope launches [agentscope-samples](https://github.com/agentscope-ai/agentscope-samples) repository and upgrades [agentscope-runtime](https://github.com/agentscope-ai/agentscope-runtime) with Docker/K8s deployment and VNC-powered GUI sandboxes.\n- **[2025-11]** [Contributing Guide](./CONTRIBUTING.md) is online now! Welcome to contribute to AgentScope.\n- **[2025-09]** **RAG** module in AgentScope 1.0 is online now! Check our [tutorial](https://doc.agentscope.io/tutorial/task_rag.html) and [example](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/rag) for more details.\n- **[2025-09]** **Voice agent** is online! `ReActAgent` supports Qwen-Omni and GPT-Audio natively now, check our [new example](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/voice_agent) and [roadmap](https://github.com/agentscope-ai/agentscope/issues/773).\n- **[2025-09]** A new powerful 📋**Plan** module is online now! Check out the [tutorial](https://doc.agentscope.io/tutorial/task_plan.html) for more details.\n- **[2025-09]** **AgentScope Runtime** is open-sourced now! Enabling effective agent deployment with sandboxed tool execution for production-ready AI applications. Check out the [GitHub repo](https://github.com/agentscope-ai/agentscope-runtime).\n- **[2025-09]** **AgentScope Studio** is open-sourced now! Check out the [GitHub repo](https://github.com/agentscope-ai/agentscope-studio).\n- **[2025-08]** The new tutorial of v1 is online now! Check out the [tutorial](https://doc.agentscope.io) for more details.\n- **[2025-08]** 🎉🎉 AgentScope v1 is released now! This version fully embraces the asynchronous execution, providing many new features and improvements. Check out [changelog](https://github.com/agentscope-ai/agentscope/blob/main/docs/changelog.md) for detailed changes.\n\n\n## ✨ Why AgentScope?\n\nEasy for beginners, powerful for experts.\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"./assets/images/agentscope_v1_0822.png\" alt=\"AgentScope Framework\" width=\"80%\"/\u003e\n\u003c/p\u003e\n\n- **Transparent to Developers**: Transparent is our **FIRST principle**. Prompt engineering, API invocation, agent building, workflow orchestration, all are visible and controllable for developers. No deep encapsulation or implicit magic.\n- **[Realtime Steering](https://doc.agentscope.io/tutorial/task_agent.html#realtime-steering)**: Native support for realtime interruption and customized handling.\n- **More Agentic**: Support [agentic tools management](https://doc.agentscope.io/tutorial/task_tool.html), [agentic long-term memory control](https://doc.agentscope.io/tutorial/task_long_term_memory.html) and agentic RAG, etc.\n- **Model Agnostic**: Programming once, run with all models.\n- **LEGO-style Agent Building**: All components are **modular** and **independent**.\n- **Multi-Agent Oriented**: Designed for **multi-agent**, **explicit** message passing and workflow orchestration, NO deep encapsulation.\n- **Highly Customizable**: Tools, prompt, agent, workflow, third-party libs \u0026 visualization, customization is encouraged everywhere.\n\nQuick overview of important features in **AgentScope 1.0**:\n\n| Module     | Feature                                                                                                        | Tutorial                                                                |\n|------------|----------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------|\n| model      | Support async invocation                                                                                       | [Model](https://doc.agentscope.io/tutorial/task_model.html)             |\n|            | Support reasoning model                                                                                        |                                                                         |\n|            | Support streaming/non-streaming returns                                                                        |                                                                         |\n| tool       | Support async/sync tool functions                                                                              | [Tool](https://doc.agentscope.io/tutorial/task_tool.html)               |\n|            | Support streaming/non-streaming returns                                                                        |                                                                         |\n|            | Support user interruption                                                                                      |                                                                         |\n|            | Support post-processing                                                                                        |                                                                         |\n|            | Support group-wise tools management                                                                            |                                                                         |\n|            | Support agentic tools management by meta tool                                                                  |                                                                         |\n| MCP        | Support streamable HTTP/SSE/StdIO transport                                                                    | [MCP](https://doc.agentscope.io/tutorial/task_mcp.html)                 |\n|            | Support both **stateful** and **stateless** mode MCP Client                                                    |                                                                         |\n|            | Support client- \u0026 function-level fine-grained control                                                          |                                                                         |\n| agent      | Support async execution                                                                                        |                                                                         |\n|            | Support parallel tool calls                                                                                    |                                                                         |\n|            | Support realtime steering interruption and customized handling                                                 |                                                                         |\n|            | Support automatic state management                                                                             |                                                                         |\n|            | Support agent-controlled long-term memory                                                                      |                                                                         |\n|            | Support agent hooks                                                                                            |                                                                         |\n| tracing    | Support OpenTelemetry-based tracing in LLM, tools, agent and formatter                                         | [Tracing](https://doc.agentscope.io/tutorial/task_tracing.html)         |\n|            | Support connecting to third-party tracing platforms (e.g. Alibaba Cloud CloudMonitor, Arize-Phoenix, Langfuse) |                                                                         |\n| memory     | Support long-term memory                                                                                       | [Memory](https://doc.agentscope.io/tutorial/task_long_term_memory.html) |\n| session    | Provide session/application-level automatic state management                                                   | [Session](https://doc.agentscope.io/tutorial/task_state.html)           |\n| evaluation | Provide distributed and parallel evaluation                                                                    | [Evaluation](https://doc.agentscope.io/tutorial/task_eval.html)         |\n| formatter  | Support multi-agent prompt formatting with tools API                                                           | [Prompt Formatter](https://doc.agentscope.io/tutorial/task_prompt.html) |\n|            | Support truncation-based formatter strategy                                                                    |                                                                         |\n| plan       | Support ReAct-based long-term planning                                                                         | [Plan](https://doc.agentscope.io/tutorial/task_plan.html)               |\n|            | Support manual plan specification                                                                              |                                                                         |\n| RAG        | Support agentic RAG                                                                                            | [RAG](https://doc.agentscope.io/tutorial/task_rag.html)                 |\n|            | Support multimodal RAG                                                                                         |                                                                         |\n| A2A        | Support A2A agent                                                                                              | [A2A](https://doc.agentscope.io/tutorial/task_a2a.html)                       |\n| ...        |                                                                                                                |                                                                         |\n\n\n## 💬 Contact\n\nWelcome to join our community on\n\n| [Discord](https://discord.gg/eYMpfnkG8h)                                                                                         | DingTalk                                                                  |\n|----------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------|\n| \u003cimg src=\"https://gw.alicdn.com/imgextra/i1/O1CN01hhD1mu1Dd3BWVUvxN_!!6000000000238-2-tps-400-400.png\" width=\"100\" height=\"100\"\u003e | \u003cimg src=\"./assets/images/dingtalk_qr_code.png\" width=\"100\" height=\"100\"\u003e |\n\n\u003c!-- START doctoc generated TOC please keep comment here to allow auto update --\u003e\n\u003c!-- DON'T EDIT THIS SECTION, INSTEAD RE-RUN doctoc TO UPDATE --\u003e\n## 📑 Table of Contents\n\n- [🚀 Quickstart](#-quickstart)\n  - [💻 Installation](#-installation)\n    - [🛠️ From source](#-from-source)\n    - [🔄 Using uv (recommended for faster installs)](#-using-uv-recommended-for-faster-installs)\n    - [📦 From PyPi](#-from-pypi)\n- [📝 Example](#-example)\n  - [👋 Hello AgentScope!](#-hello-agentscope)\n  - [🎯 Realtime Steering](#-realtime-steering)\n  - [🛠️ Fine-Grained MCP Control](#-fine-grained-mcp-control)\n  - [🧑‍🤝‍🧑 Multi-Agent Conversation](#-multi-agent-conversation)\n  - [💻 AgentScope Studio](#-agentscope-studio)\n- [📖 Documentation](#-documentation)\n- [🤝 Contributing](#-contributing)\n- [⚖️ License](#-license)\n- [📚 Publications](#-publications)\n- [✨ Contributors](#-contributors)\n\n\u003c!-- END doctoc generated TOC please keep comment here to allow auto update --\u003e\n\n## 🚀 Quickstart\n\n### 💻 Installation\n\n\u003e AgentScope requires **Python 3.10** or higher.\n\n#### 🛠️ From source\n\n```bash\n# Pull the source code from GitHub\ngit clone -b main https://github.com/agentscope-ai/agentscope.git\n\n# Install the package in editable mode\ncd agentscope\npip install -e .\n```\n\n#### 🔄 Using uv (recommended for faster installs)\n\n[uv](https://github.com/astral-sh/uv) is a fast Python package installer and resolver, written in Rust.\n\n```bash\n# Clone the repository\ngit clone -b main https://github.com/agentscope-ai/agentscope.git\ncd agentscope\n\n# Install with uv\nuv pip install -e .\n```\n\n#### 📦 From PyPi\n\n```bash\npip install agentscope\n```\n\nOr with uv:\n\n```bash\nuv pip install agentscope\n```\n\n## 📝 Example\n\n### 👋 Hello AgentScope!\n\nStart with a conversation between user and a ReAct agent 🤖 named \"Friday\"!\n\n```python\nfrom agentscope.agent import ReActAgent, UserAgent\nfrom agentscope.model import DashScopeChatModel\nfrom agentscope.formatter import DashScopeChatFormatter\nfrom agentscope.memory import InMemoryMemory\nfrom agentscope.tool import Toolkit, execute_python_code, execute_shell_command\nimport os, asyncio\n\n\nasync def main():\n    toolkit = Toolkit()\n    toolkit.register_tool_function(execute_python_code)\n    toolkit.register_tool_function(execute_shell_command)\n\n    agent = ReActAgent(\n        name=\"Friday\",\n        sys_prompt=\"You're a helpful assistant named Friday.\",\n        model=DashScopeChatModel(\n            model_name=\"qwen-max\",\n            api_key=os.environ[\"DASHSCOPE_API_KEY\"],\n            stream=True,\n        ),\n        memory=InMemoryMemory(),\n        formatter=DashScopeChatFormatter(),\n        toolkit=toolkit,\n    )\n\n    user = UserAgent(name=\"user\")\n\n    msg = None\n    while True:\n        msg = await agent(msg)\n        msg = await user(msg)\n        if msg.get_text_content() == \"exit\":\n            break\n\nasyncio.run(main())\n```\n\n### 🎯 Realtime Steering\n\nNatively support **realtime interruption** in ``ReActAgent`` with robust memory preservation, and convert interruption into an **observable event** for agent to seamlessly resume conversations.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"./assets/images/realtime_steering_zh.gif\" alt=\"Realtime Steering\" width=\"49%\"/\u003e\n  \u003cimg src=\"./assets/images/realtime_steering_en.gif\" alt=\"Realtime Steering\" width=\"49%\"/\u003e\n\u003c/p\u003e\n\n### 🛠️ Fine-Grained MCP Control\n\nDevelopers can obtain the MCP tool as a **local callable function**, and use it anywhere (e.g. call directly, pass to agent, wrap into a more complex tool, etc.)\n\n```python\nfrom agentscope.mcp import HttpStatelessClient\nfrom agentscope.tool import Toolkit\nimport os\n\nasync def fine_grained_mcp_control():\n    # Initialize the MCP client\n    client = HttpStatelessClient(\n        name=\"gaode_mcp\",\n        transport=\"streamable_http\",\n        url=f\"https://mcp.amap.com/mcp?key={os.environ['GAODE_API_KEY']}\",\n    )\n\n    # Obtain the MCP tool as a **local callable function**, and use it anywhere\n    func = await client.get_callable_function(func_name=\"maps_geo\")\n\n    # Option 1: Call directly\n    await func(address=\"Tiananmen Square\", city=\"Beijing\")\n\n    # Option 2: Pass to agent as a tool\n    toolkit = Toolkit()\n    toolkit.register_tool_function(func)\n    # ...\n\n    # Option 3: Wrap into a more complex tool\n    # ...\n```\n\n### 🧑‍🤝‍🧑 Multi-Agent Conversation\n\nAgentScope provides ``MsgHub`` and pipelines to streamline multi-agent conversations, offering efficient message routing and seamless information sharing\n\n```python\nfrom agentscope.pipeline import MsgHub, sequential_pipeline\nfrom agentscope.message import Msg\nimport asyncio\n\nasync def multi_agent_conversation():\n    # Create agents\n    agent1 = ...\n    agent2 = ...\n    agent3 = ...\n    agent4 = ...\n\n    # Create a message hub to manage multi-agent conversation\n    async with MsgHub(\n        participants=[agent1, agent2, agent3],\n        announcement=Msg(\"Host\", \"Introduce yourselves.\", \"assistant\")\n    ) as hub:\n        # Speak in a sequential manner\n        await sequential_pipeline([agent1, agent2, agent3])\n        # Dynamic manage the participants\n        hub.add(agent4)\n        hub.delete(agent3)\n        await hub.broadcast(Msg(\"Host\", \"Goodbye!\", \"assistant\"))\n\nasyncio.run(multi_agent_conversation())\n```\n\n### 💻 AgentScope Studio\n\nUse the following command to install and start AgentScope Studio, to trace and visualize your agent application.\n\n```bash\nnpm install -g @agentscope/studio\n\nas_studio\n```\n\n\u003cp align=\"center\"\u003e\n    \u003cimg\n        src=\"https://img.alicdn.com/imgextra/i1/O1CN01PG2MdF1Zc44A1QM6N_!!6000000003214-1-tps-1971-1080.gif\"\n        width=\"49%\"\n        alt=\"home\"\n    /\u003e\n    \u003cimg\n        src=\"https://img.alicdn.com/imgextra/i2/O1CN01pGHedL1L4ibmyPeiq_!!6000000001246-1-tps-1971-1080.gif\"\n        width=\"49%\"\n        alt=\"runtime\"\n    /\u003e\n    \u003cimg\n        src=\"https://img.alicdn.com/imgextra/i1/O1CN01HfFhy928SSJAcWQ8c_!!6000000007931-1-tps-1971-1080.gif\"\n        width=\"49%\"\n        alt=\"traces\"\n    /\u003e\n    \u003cimg\n        src=\"https://img.alicdn.com/imgextra/i1/O1CN01vovov821Arms9tEJ1_!!6000000006945-1-tps-1971-1080.gif\"\n        width=\"49%\"\n        alt=\"friday\"\n    /\u003e\n\u003c/p\u003e\n\n\n## 📖 Documentation\n\n- Tutorial\n  - [Installation](https://doc.agentscope.io/tutorial/quickstart_installation.html)\n  - [Key Concepts](https://doc.agentscope.io/tutorial/quickstart_key_concept.html)\n  - [Create Message](https://doc.agentscope.io/tutorial/quickstart_message.html)\n  - [ReAct Agent](https://doc.agentscope.io/tutorial/quickstart_agent.html)\n- Workflow\n  - [Conversation](https://doc.agentscope.io/tutorial/workflow_conversation.html)\n  - [Multi-Agent Debate](https://doc.agentscope.io/tutorial/workflow_multiagent_debate.html)\n  - [Concurrent Agents](https://doc.agentscope.io/tutorial/workflow_concurrent_agents.html)\n  - [Routing](https://doc.agentscope.io/tutorial/workflow_routing.html)\n  - [Handoffs](https://doc.agentscope.io/tutorial/workflow_handoffs.html)\n- FAQ\n  - [FAQ](https://doc.agentscope.io/tutorial/faq.html)\n- Task Guides\n  - [Model](https://doc.agentscope.io/tutorial/task_model.html)\n  - [Prompt Formatter](https://doc.agentscope.io/tutorial/task_prompt.html)\n  - [Tool](https://doc.agentscope.io/tutorial/task_tool.html)\n  - [Memory](https://doc.agentscope.io/tutorial/task_memory.html)\n  - [Long-Term Memory](https://doc.agentscope.io/tutorial/task_long_term_memory.html)\n  - [Agent](https://doc.agentscope.io/tutorial/task_agent.html)\n  - [Pipeline](https://doc.agentscope.io/tutorial/task_pipeline.html)\n  - [Plan](https://doc.agentscope.io/tutorial/task_plan.html)\n  - [State/Session Management](https://doc.agentscope.io/tutorial/task_state.html)\n  - [Agent Hooks](https://doc.agentscope.io/tutorial/task_hook.html)\n  - [MCP](https://doc.agentscope.io/tutorial/task_mcp.html)\n  - [AgentScope Studio](https://doc.agentscope.io/tutorial/task_studio.html)\n  - [Tracing](https://doc.agentscope.io/tutorial/task_tracing.html)\n  - [Evaluation](https://doc.agentscope.io/tutorial/task_eval.html)\n  - [Embedding](https://doc.agentscope.io/tutorial/task_embedding.html)\n  - [Token](https://doc.agentscope.io/tutorial/task_token.html)\n- API\n  - [API Docs](https://doc.agentscope.io/api/agentscope.html)\n- [Examples](https://github.com/agentscope-ai/agentscope/tree/main/examples)\n  - Functionality\n    - [MCP](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/mcp)\n    - [Anthropic Agent Skill](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/agent_skill)\n    - [Plan](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/plan)\n    - [Structured Output](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/structured_output)\n    - [RAG](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/rag)\n    - [Long-Term Memory](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/long_term_memory)\n    - [Session with SQLite](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/session_with_sqlite)\n    - [Stream Printing Messages](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/stream_printing_messages)\n    - [TTS](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/tts)\n    - [High-code Deployment](https://github.com/agentscope-ai/agentscope/tree/main/examples/deployment/planning_agent)\n    - [Memory Compression](https://github.com/agentscope-ai/agentscope/tree/main/examples/functionality/short_term_memory/memory_compression)\n  - Agent\n    - [ReAct Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/react_agent)\n    - [Voice Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/voice_agent)\n    - [Deep Research Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/deep_research_agent)\n    - [Browser-use Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/browser_agent)\n    - [Meta Planner Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/meta_planner_agent)\n    - [A2A Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/agent/a2a_agent)\n  - Game\n    - [Nine-player Werewolves](https://github.com/agentscope-ai/agentscope/tree/main/examples/game/werewolves)\n  - Workflow\n    - [Multi-agent Debate](https://github.com/agentscope-ai/agentscope/tree/main/examples/workflows/multiagent_debate)\n    - [Multi-agent Conversation](https://github.com/agentscope-ai/agentscope/tree/main/examples/workflows/multiagent_conversation)\n    - [Multi-agent Concurrent](https://github.com/agentscope-ai/agentscope/tree/main/examples/workflows/multiagent_concurrent)\n  - Evaluation\n    - [ACEBench](https://github.com/agentscope-ai/agentscope/tree/main/examples/evaluation/ace_bench)\n  - Tuner\n    - [Tune ReAct Agent](https://github.com/agentscope-ai/agentscope/tree/main/examples/tuner/react_agent)\n\n\n## 🤝 Contributing\n\nWe welcome contributions from the community! Please refer to our [CONTRIBUTING.md](./CONTRIBUTING.md) for guidelines\non how to contribute.\n\n## ⚖️ License\n\nAgentScope is released under Apache License 2.0.\n\n## 📚 Publications\n\nIf you find our work helpful for your research or application, please cite our papers.\n\n- [AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications](https://arxiv.org/abs/2508.16279)\n\n- [AgentScope: A Flexible yet Robust Multi-Agent Platform](https://arxiv.org/abs/2402.14034)\n\n```\n@article{agentscope_v1,\n    author  = {\n        Dawei Gao,\n        Zitao Li,\n        Yuexiang Xie,\n        Weirui Kuang,\n        Liuyi Yao,\n        Bingchen Qian,\n        Zhijian Ma,\n        Yue Cui,\n        Haohao Luo,\n        Shen Li,\n        Lu Yi,\n        Yi Yu,\n        Shiqi He,\n        Zhiling Luo,\n        Wenmeng Zhou,\n        Zhicheng Zhang,\n        Xuguang He,\n        Ziqian Chen,\n        Weikai Liao,\n        Farruh Isakulovich Kushnazarov,\n        Yaliang Li,\n        Bolin Ding,\n        Jingren Zhou}\n    title   = {AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications},\n    journal = {CoRR},\n    volume  = {abs/2508.16279},\n    year    = {2025},\n}\n\n@article{agentscope,\n    author  = {\n        Dawei Gao,\n        Zitao Li,\n        Xuchen Pan,\n        Weirui Kuang,\n        Zhijian Ma,\n        Bingchen Qian,\n        Fei Wei,\n        Wenhao Zhang,\n        Yuexiang Xie,\n        Daoyuan Chen,\n        Liuyi Yao,\n        Hongyi Peng,\n        Zeyu Zhang,\n        Lin Zhu,\n        Chen Cheng,\n        Hongzhu Shi,\n        Yaliang Li,\n        Bolin Ding,\n        Jingren Zhou}\n    title   = {AgentScope: A Flexible yet Robust Multi-Agent Platform},\n    journal = {CoRR},\n    volume  = {abs/2402.14034},\n    year    = {2024},\n}\n```\n\n## ✨ Contributors\n\nAll thanks to our contributors:\n\n\u003ca href=\"https://github.com/agentscope-ai/agentscope/graphs/contributors\"\u003e\n  \u003cimg src=\"https://contrib.rocks/image?repo=agentscope-ai/agentscope\u0026max=999\u0026columns=12\u0026anon=1\" /\u003e\n\u003c/a\u003e\n","funding_links":[],"categories":["September 2025","Agent Development Frameworks","精选文章","Python","📚 Projects (1974 total)","Personal Assistants \u0026 Conversational Agents","Repos","📋 Contents","Agentic Programming","Frameworks \u0026 Libraries"],"sub_categories":["AI Agent","MCP Clients","Chatbots","🤖 4. Agentic AI \u0026 Multi-Agent Systems","Frameworks and Tools","Multi-Agent Orchestration"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagentscope-ai%2Fagentscope","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fagentscope-ai%2Fagentscope","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagentscope-ai%2Fagentscope/lists"}