by LLMP-io · Agent Tool · ★ 114
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Legion: A Provider-Agnostic Multi-Agent Framework Legion is a flexible and provider-agnostic framework designed to simplify the creation of sophisticated multi-agent systems. It provides a set of tools and abstractions to build, manage, and monitor AI agents, chains, teams, and graphs, allowing you to focus on the logic of your application rather than the underlying infrastructure. Key Features Provider Agnostic: Supports multiple LLM providers (OpenAI, Anthropic, Groq, Ollama, Gemini) through a unified interface, allowing you to switch or combine providers easily. Agent Abstraction: Define agents with clear roles, tools, and system prompts using decorators, simplifying the creation of complex agent behaviors. Tool Integration: Seamlessly integrate tools with agents using decorators, enabling agents to interact with external systems and data. Parameter Injection: Inject parameters into tools at runtime, allowing for dynamic configuration and secure handling of sensitive credentials. Chains and Teams: Build complex workflows by chaining agents and blocks together or creating collaborative teams of agents.
| Stars | 114 |
| Forks | 20 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 40.25/100 |
| Open Issues | 1 |
| Last Updated | 2025-02-27 |
| Created | 2025-01-07 |
| Platforms | python |
| Est. Tokens | ~39k |
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Legion is A Python-based framework for building multi-agent systems with LLMs. Currently in pre-launch alpha.. It is categorized as a Agent Tool with 114 GitHub stars.
Legion is primarily written in Python. It covers topics such as agent-framework, ai-framework, llm-agent.
You can find installation instructions and usage details in the Legion GitHub repository at github.com/LLMP-io/Legion. The project has 114 stars and 20 forks, indicating an active community.
Legion is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Legion on Agent Skills Hub include SimpleLLMFunc, Open-AgentRL, atlas-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.