--- title: "hello-agents vs iFixAi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-ifixai-ai-ifixai" tools: ["datawhalechina-hello-agents", "ifixai-ai-ifixai"] --- # hello-agents vs iFixAi *GraphCanon updated Jul 11, 2026* ## Verdict Pick hello-agents when license: hello-agents is Other, iFixAi is Apache-2.0; pick iFixAi when license: iFixAi 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. [iFixAi](https://www.ifixai.ai) has 1.3k stars, 170 forks, and 0 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [iFixAi's repository](https://github.com/ifixai-ai/iFixAi). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [iFixAi](/tools/ifixai-ai-ifixai.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | Catch your AI's mistakes and blind spots before your customers or regulators do. iFixAi runs 45 inspections, 32 graded core plus 13 extended for frontier risks like sabotage, sandbagging, and oversigh | | Stars | 65,432 | 1,342 | | Forks | 8,109 | 170 | | Open issues | 144 | 0 | | 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) | [iFixAi](/tools/ifixai-ai-ifixai.md) | | --- | --- | --- | | Days since push | 0d | 3d | | Open issues (now) | 144 | 0 | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/ifixai-ai-ifixai/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, iFixAi 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 iFixAi if… - License: iFixAi is Apache-2.0, hello-agents is Other. - Tags unique to iFixAi: agent-evaluation, ai, ai evaluation, ai-alignment. - Also covers Computer Vision. ## 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 iFixAi - 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 iFixAi? hello-agents: Course on building intelligent agents from scratch. iFixAi: Catch your AI's mistakes and blind spots before your customers or regulators do. iFixAi runs 45 inspections, 32 graded core plus 13 extended for frontier risks like sabotage, sandbagging, and oversigh. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over iFixAi? Choose hello-agents over iFixAi when License: hello-agents is Other, iFixAi 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 iFixAi over hello-agents? Choose iFixAi over hello-agents when License: iFixAi is Apache-2.0, hello-agents is Other; Tags unique to iFixAi: agent-evaluation, ai, ai evaluation, ai-alignment; Also covers Computer Vision. ### 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 iFixAi? 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 iFixAi more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 1,342). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and iFixAi open source? Yes - both are open-source projects on GitHub (hello-agents: Other, iFixAi: Apache-2.0). ### Where can I find alternatives to hello-agents or iFixAi? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [iFixAi alternatives](/tools/ifixai-ai-ifixai/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [iFixAi markdown twin](/tools/ifixai-ai-ifixai/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-ifixai-ai-ifixai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or iFixAi? hello-agents: Very active. iFixAi: 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 iFixAi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [iFixAi trust report](/tools/ifixai-ai-ifixai/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/_