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agentscope
by agentscope-ai
Agent-oriented framework for composing and orchestrating LLM agents
Python
Updated Feb 10, 2026
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Overview
Provides an agent-oriented programming framework to build, compose, and run LLM-based agents. Uses reusable agent abstractions, message buses, and modular skill components to construct multi-agent workflows and chatbots. Includes tools for routing, state management, and multimodal agents to simplify building complex agent orchestration patterns.
Key Benefits
As agents become more autonomous and collaborate, teams need a structured way to compose and reason about agent behavior and delegation. AgentScope makes agent design explicit—so you can instrument, test, and compare agents rather than embedding ad-hoc logic in prompts. That clarity is a prerequisite for meaningful Human-in-the-Loop and agent-to-agent evaluation because it exposes interaction points and decision logic where reputation and metrics can attach.
Ideal For
Teams building multi-agent LLM applications who want clear abstractions for orchestration, delegation, and extensibility. For practical orchestration, consider leveraging the Planning Pattern to structure agent workflows.
Real-World Examples
- Compose specialist agents that delegate subtasks and aggregate results
- Instrument agent interactions for pre-production testing and behavior analysis
- Build multimodal chatbots and workflows with reusable skill components
Works With
openaihuggingfacelangchain
Topics
agentchatbotlarge-language-modelsllmllm-agentmcpmulti-agentmulti-modalreact-agent
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Keywords
multi-agent orchestrationagent-oriented programmingagent-evaluationmulti-agent trust