What is AgentScope 1.0？
AgentScope 1.0 is an open-source multi-agent development framework by Ali Tongyi. Through a three-layer technical architecture—AgentScope Core Framework, AgentScope Runtime, and AgentScope Studio—it provides full lifecycle support from development to deployment. The AgentScope Core Framework uses a modular design consisting of four main components: Messages, Models, Memory, and Tools, enabling efficient construction of agent applications based on large language models (LLMs). AgentScope Runtime provides a secure and reliable runtime and deployment environment, while AgentScope Studio offers visual development and monitoring tools. Key features of AgentScope 1.0 include real-time intervention control, intelligent context management, and efficient tool invocation, making agent application development simpler, safer to run, and more transparent to monitor.
AgentScope 1.0 Main Features
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Real-Time Intervention Control: Supports safe interruption, real-time pausing, and flexible custom interruption handling logic, ensuring controllability and flexibility in task execution.
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Intelligent Context Management: Optimizes short-term memory and manages long-term memory across sessions to effectively address agent “forgetting” and “resetting” issues.
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Efficient Tool Invocation: Provides tool registration, management, and execution functionalities, supporting parallel invocation and dynamic control for improved runtime efficiency.
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Secure and Reliable Runtime Environment: Built on container technology to provide a secure sandbox for tools, ensuring agents run in isolated environments while offering flexible deployment and monitoring support.
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Visual Development and Monitoring: Offers real-time monitoring and agent evaluation features based on state management and visual tracking, helping developers quickly optimize agent performance.
Technical Principles of AgentScope 1.0
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Core Framework: Composed of four components—Messages, Models, Memory, and Tools—allowing high decoupling and flexible expansion. Combined with reasoning and action, agents generate responses through iterative reasoning-action loops upon receiving user queries. Asynchronous design supports flexible and robust real-time intervention control, parallel tool invocation, and dynamic tool configuration.
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Runtime Environment: Built with container technology to create a system-level isolated environment for safe tool execution, supporting multiple functional scenarios. Offers complete deployment solutions with multi-protocol support, flexible deployment, and framework independence, ensuring stable and reliable applications.
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Development and Monitoring Tools: AgentScope Studio provides real-time monitoring and agent evaluation capabilities, supporting multi-granularity and multi-dimensional analysis of agent trajectories and performance metrics.
AgentScope 1.0 Project Links
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Official Website: https://doc.agentscope.io/index.html
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GitHub Repository: https://github.com/agentscope-ai/agentscope
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arXiv Technical Paper: https://arxiv.org/pdf/2508.16279
Application Scenarios of AgentScope 1.0
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User Assistant Dialogues: Build intelligent assistants to answer questions and perform tasks, such as information retrieval and scheduling.
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Multi-Agent Collaboration: Enable collaboration among multiple agents to complete complex tasks, such as team project management or multi-role conversations.
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Deep Research and Report Generation: Automatically collect and analyze multi-source information to generate detailed analytical reports, suitable for academic research, market analysis, and more.
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Browser Automation: Use agents to operate web browsers for tasks like web browsing, data extraction, and form submission.
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Complex Task Planning and Execution: Break down complex tasks into multiple sub-tasks and dynamically coordinate multiple agents to complete them, such as project planning and data analysis.
