--- title: "hello-agents vs ODS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-osmantic-ods" tools: ["datawhalechina-hello-agents", "osmantic-ods"] --- # hello-agents vs ODS *GraphCanon updated Jul 11, 2026* ## Verdict Pick hello-agents when hello-agents is primarily Python; ODS is Shell; pick ODS when oDS is primarily Shell; hello-agents is Python. [hello-agents](https://hello-agents.datawhale.cc) reports 65k GitHub stars, 8.1k forks, and 144 open issues, last pushed Jul 10, 2026. [ODS](https://discord.gg/qGVygYada3) has 2.9k stars, 418 forks, and 107 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [ODS's repository](https://github.com/Osmantic/ODS). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [ODS](/tools/osmantic-ods.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | Turn your PC, Mac, or Linux box into an AI server. LLM inference, chat UI, voice, agents, workflows, RAG, and image generation. | | Stars | 65,432 | 2,919 | | Forks | 8,109 | 418 | | Open issues | 144 | 107 | | Language | Python | Shell | | 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 | hello-agents is covered under an unconventional license which may require further review before usage. | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [ODS](/tools/osmantic-ods.md) | | --- | --- | --- | | Open issues (now) | 144 | 107 | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/osmantic-ods/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 hello-agents if… - hello-agents is primarily Python; ODS is Shell. - License: hello-agents is Other, ODS is Apache-2.0. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Tags unique to hello-agents: agent, rag, tutorial. - You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up. ### Choose ODS if… - ODS is primarily Shell; hello-agents is Python. - License: ODS is Apache-2.0, hello-agents is Other. - Tags unique to ODS: ai-agents, amd, comfyui, docker. - Also covers Inference & Serving. ## 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. ## When NOT to use ODS - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between hello-agents and ODS? hello-agents: Course on building intelligent agents from scratch. ODS: Turn your PC, Mac, or Linux box into an AI server. LLM inference, chat UI, voice, agents, workflows, RAG, and image generation.. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over ODS? Choose hello-agents over ODS when hello-agents is primarily Python; ODS is Shell; License: hello-agents is Other, ODS is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, rag, 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 choose ODS over hello-agents? Choose ODS over hello-agents when ODS is primarily Shell; hello-agents is Python; License: ODS is Apache-2.0, hello-agents is Other; Tags unique to ODS: ai-agents, amd, comfyui, docker; Also covers Inference & Serving. ### 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. ### When should I avoid ODS? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is hello-agents or ODS more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 2,919). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and ODS open source? Yes - both are open-source projects on GitHub (hello-agents: Other, ODS: Apache-2.0). ### Where can I find alternatives to hello-agents or ODS? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [ODS alternatives](/tools/osmantic-ods/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [ODS markdown twin](/tools/osmantic-ods/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/datawhalechina-hello-agents-vs-osmantic-ods.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or ODS? hello-agents: Very active. ODS: 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 hello-agents and ODS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [ODS trust report](/tools/osmantic-ods/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=datawhalechina-hello-agents`](/api/graphcanon/graph?tool=datawhalechina-hello-agents) - 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/_