--- title: "hello-agents vs qwed-verification" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-qwed-ai-qwed-verification" tools: ["datawhalechina-hello-agents", "qwed-ai-qwed-verification"] --- # hello-agents vs qwed-verification *GraphCanon updated Jul 11, 2026* ## Verdict Pick hello-agents when license: hello-agents is Other, qwed-verification is Apache-2.0; pick qwed-verification when license: qwed-verification is Apache-2.0, hello-agents is Other. [hello-agents](https://hello-agents.datawhale.cc) reports 65k GitHub stars, 8.1k forks, and 144 open issues, last pushed Jul 10, 2026. [qwed-verification](https://docs.qwedai.com/) has 58 stars, 11 forks, and 20 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [qwed-verification's repository](https://github.com/QWED-AI/qwed-verification). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [qwed-verification](/tools/qwed-ai-qwed-verification.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | A deterministic verification layer for AI systems. QWED verifies AI outputs using mathematics, symbolic reasoning, and formal methods (Z3, SMT, SymPy), creating an auditable trust boundary for agentic | | Stars | 65,432 | 58 | | Forks | 8,109 | 11 | | Open issues | 144 | 20 | | Language | Python | 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 | 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, Computer Vision, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [qwed-verification](/tools/qwed-ai-qwed-verification.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 144 | 20 | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/qwed-ai-qwed-verification/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… - License: hello-agents is Other, qwed-verification is Apache-2.0. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Tags unique to hello-agents: agent, llm, 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 qwed-verification if… - License: qwed-verification is Apache-2.0, hello-agents is Other. - Tags unique to qwed-verification: ai-accuracy, ai-safety, ai-security, code-security. - Also covers Computer Vision. - qwed-verification ships Docker support for self-hosted deployment. ## 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 qwed-verification - 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. ## Common questions ### What is the difference between hello-agents and qwed-verification? hello-agents: Course on building intelligent agents from scratch. qwed-verification: A deterministic verification layer for AI systems. QWED verifies AI outputs using mathematics, symbolic reasoning, and formal methods (Z3, SMT, SymPy), creating an auditable trust boundary for agentic. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over qwed-verification? Choose hello-agents over qwed-verification when License: hello-agents is Other, qwed-verification is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, 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 qwed-verification over hello-agents? Choose qwed-verification over hello-agents when License: qwed-verification is Apache-2.0, hello-agents is Other; Tags unique to qwed-verification: ai-accuracy, ai-safety, ai-security, code-security; Also covers Computer Vision; qwed-verification ships Docker support for self-hosted deployment. ### 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 qwed-verification? 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. ### Is hello-agents or qwed-verification more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 58). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and qwed-verification open source? Yes - both are open-source projects on GitHub (hello-agents: Other, qwed-verification: Apache-2.0). ### Where can I find alternatives to hello-agents or qwed-verification? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [qwed-verification alternatives](/tools/qwed-ai-qwed-verification/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [qwed-verification markdown twin](/tools/qwed-ai-qwed-verification/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-qwed-ai-qwed-verification.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or qwed-verification? hello-agents: Very active. qwed-verification: 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 qwed-verification? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [qwed-verification trust report](/tools/qwed-ai-qwed-verification/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/_