--- title: "ruoyi-ai vs hello-agents" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ageerle-ruoyi-ai-vs-datawhalechina-hello-agents" tools: ["ageerle-ruoyi-ai", "datawhalechina-hello-agents"] --- # ruoyi-ai vs hello-agents *GraphCanon updated Jul 15, 2026* ## Verdict Pick ruoyi-ai when ruoyi-ai is primarily Java; hello-agents is Python; pick hello-agents when hello-agents is primarily Python; ruoyi-ai is Java. [ruoyi-ai](https://doc.ruoyiai.chat) reports 5.5k GitHub stars, 1.4k forks, and 8 open issues, last pushed Jul 15, 2026. [hello-agents](https://hello-agents.datawhale.cc) has 65k stars, 8.1k forks, and 144 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [ruoyi-ai's repository](https://github.com/ageerle/ruoyi-ai) and [hello-agents's repository](https://github.com/datawhalechina/hello-agents). | | [ruoyi-ai](/tools/ageerle-ruoyi-ai.md) | [hello-agents](/tools/datawhalechina-hello-agents.md) | | --- | --- | --- | | Tagline | 面向企业级市场的一站式AI应用开发框架，支持多厂商大模型统一接入与管理，具备安全可控的企业知识库与高精度检索优化能力，提供可视化流程编排、自主决策智能体与多智能体协同调度，兼容主流 Agent Skill 协议，帮助企业与开发者零门槛快速构建安全、高效、可落地的AI智能体应用与行业解决方案。 | Course on building intelligent agents from scratch | | Stars | 5,514 | 65,432 | | Forks | 1,353 | 8,109 | | Open issues | 8 | 144 | | Language | Java | Python | | Adopt for | - | hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. | | Persona | - | - | | Runtime | - | - | | License | MIT | hello-agents is covered under an unconventional license which may require further review before usage. | | Categories | AI Agents, Computer Vision, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ruoyi-ai](/tools/ageerle-ruoyi-ai.md) | [hello-agents](/tools/datawhalechina-hello-agents.md) | | --- | --- | --- | | Open issues (now) | 8 | 144 | | Owner type | User | Organization | | Full report | [trust report](/tools/ageerle-ruoyi-ai/trust.md) | [trust report](/tools/datawhalechina-hello-agents/trust.md) | ## Decision facts: hello-agents - **Requirements:** Min 4 GB RAM; Python knowledge assumed - **Adopt for:** hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. - **License detail:** hello-agents is covered under an unconventional license which may require further review before usage. ## Choose when ### Choose ruoyi-ai if… - ruoyi-ai is primarily Java; hello-agents is Python. - License: ruoyi-ai is MIT, hello-agents is Other. - Tags unique to ruoyi-ai: ai, java, knowledge, mcp. - Also covers Computer Vision. ### Choose hello-agents if… - hello-agents is primarily Python; ruoyi-ai is Java. - License: hello-agents is Other, ruoyi-ai is MIT. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Tags unique to hello-agents: llm, tutorial. - You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up. ## When NOT to use ruoyi-ai - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use hello-agents - Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. - Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG. ## Common questions ### What is the difference between ruoyi-ai and hello-agents? ruoyi-ai: 面向企业级市场的一站式AI应用开发框架，支持多厂商大模型统一接入与管理，具备安全可控的企业知识库与高精度检索优化能力，提供可视化流程编排、自主决策智能体与多智能体协同调度，兼容主流 Agent Skill 协议，帮助企业与开发者零门槛快速构建安全、高效、可落地的AI智能体应用与行业解决方案。. hello-agents: Course on building intelligent agents from scratch. See the comparison table for live GitHub stats and shared categories. ### When should I choose ruoyi-ai over hello-agents? Choose ruoyi-ai over hello-agents when ruoyi-ai is primarily Java; hello-agents is Python; License: ruoyi-ai is MIT, hello-agents is Other; Tags unique to ruoyi-ai: ai, java, knowledge, mcp; Also covers Computer Vision. ### When should I choose hello-agents over ruoyi-ai? Choose hello-agents over ruoyi-ai when hello-agents is primarily Python; ruoyi-ai is Java; License: hello-agents is Other, ruoyi-ai is MIT; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: llm, tutorial; You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up. ### When should I avoid ruoyi-ai? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid hello-agents? Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG. ### Is ruoyi-ai or hello-agents more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 5,514). Stars measure visibility, not whether either tool fits your constraints. ### Are ruoyi-ai and hello-agents open source? Yes - both are open-source projects on GitHub (ruoyi-ai: MIT, hello-agents: Other). ### Where can I find alternatives to ruoyi-ai or hello-agents? GraphCanon lists graph-backed alternatives at [ruoyi-ai alternatives](/tools/ageerle-ruoyi-ai/alternatives) and [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) ([ruoyi-ai markdown twin](/tools/ageerle-ruoyi-ai/alternatives.md), [hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/ageerle-ruoyi-ai-vs-datawhalechina-hello-agents.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ruoyi-ai or hello-agents? ruoyi-ai: Very active. hello-agents: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for ruoyi-ai and hello-agents? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ruoyi-ai trust report](/tools/ageerle-ruoyi-ai/trust); [hello-agents trust report](/tools/datawhalechina-hello-agents/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ageerle-ruoyi-ai`](/api/graphcanon/graph?tool=ageerle-ruoyi-ai) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_