--- title: "hello-agents vs dynamiq" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-dynamiq-ai-dynamiq" tools: ["datawhalechina-hello-agents", "dynamiq-ai-dynamiq"] --- # hello-agents vs dynamiq *GraphCanon updated Aug 21, 2026* ## Verdict Pick hello-agents if hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods; pick dynamiq if decision-critical facts for Dynamiq. [hello-agents](https://hello-agents.datawhale.cc) reports 73k GitHub stars, 9.1k forks, and 155 open issues, last pushed Aug 14, 2026. [dynamiq](https://getdynamiq.ai) has 1.1k stars, 133 forks, and 6 open issues, last pushed Aug 20, 2026. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [dynamiq's repository](https://github.com/dynamiq-ai/dynamiq). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [dynamiq](/tools/dynamiq-ai-dynamiq.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | Orchestration framework for agentic AI and LLM applications | | Stars | 73,126 | 1,065 | | Forks | 9,108 | 133 | | Open issues | 155 | 6 | | 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. | Decision-critical facts for Dynamiq | | Persona | - | - | | Runtime | - | - | | License | hello-agents is covered under an unconventional license which may require further review before usage. | Licensed under Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [dynamiq](/tools/dynamiq-ai-dynamiq.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 155 | 6 | | Stars delta | +6.4k (30d) | +4 (30d) | | Open issues delta | +8 (30d) | -2 (30d) | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/dynamiq-ai-dynamiq/trust.md) | **Typed relationship:** hello-agents _(depends on)_ dynamiq Hello Agents provides a learning resource that educates on principles and practices of AI agents, which could be foundational knowledge required for utilizing Dynamiq. ## 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. ## Decision facts: dynamiq - **Requirements:** Requires Python to be installed on the machine. - **Adopt for:** Decision-critical facts for Dynamiq - **License detail:** Licensed under Apache-2.0 ## Choose when ### Choose hello-agents if… - License: hello-agents is Other, dynamiq is Apache-2.0. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Hello Agents provides a learning resource that educates on principles and practices of AI agents, which could be foundational knowledge required for utilizing Dynamiq. - Tags unique to hello-agents: agent, 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 dynamiq if… - License: dynamiq is Apache-2.0, hello-agents is Other. - Requirements: Requires Python to be installed on the machine.. - Hello Agents provides a learning resource that educates on principles and practices of AI agents, which could be foundational knowledge required for utilizing Dynamiq. - Tags unique to dynamiq: agents, ai, generative-ai, gpt. - dynamiq ships Docker support for self-hosted deployment. - When you need a robust orchestration framework specifically designed for agentic AI and LLM applications, where managing multiple agents and their interactions is crucial. ## 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 dynamiq - For scenarios requiring a lightweight framework without the overhead of advanced agent management features; simpler, static workflows might be better served by less-complex tools. - When your development team lacks experience with Python or does not foresee leveraging Dynamiq's specialized LLM orchestration capabilities. ## Common questions ### What is the difference between hello-agents and dynamiq? hello-agents: Course on building intelligent agents from scratch. dynamiq: Orchestration framework for agentic AI and LLM applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over dynamiq? Choose hello-agents over dynamiq when License: hello-agents is Other, dynamiq is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Hello Agents provides a learning resource that educates on principles and practices of AI agents, which could be foundational knowledge required for utilizing Dynamiq; Tags unique to hello-agents: agent, 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 dynamiq over hello-agents? Choose dynamiq over hello-agents when License: dynamiq is Apache-2.0, hello-agents is Other; Requirements: Requires Python to be installed on the machine.; Hello Agents provides a learning resource that educates on principles and practices of AI agents, which could be foundational knowledge required for utilizing Dynamiq; Tags unique to dynamiq: agents, ai, generative-ai, gpt; dynamiq ships Docker support for self-hosted deployment; When you need a robust orchestration framework specifically designed for agentic AI and LLM applications, where managing multiple agents and their interactions is crucial. ### 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 dynamiq? For scenarios requiring a lightweight framework without the overhead of advanced agent management features; simpler, static workflows might be better served by less-complex tools. When your development team lacks experience with Python or does not foresee leveraging Dynamiq's specialized LLM orchestration capabilities. ### Is hello-agents or dynamiq more popular on GitHub? hello-agents has more GitHub stars (73,126 vs 1,065). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and dynamiq open source? Yes - both are open-source projects on GitHub (hello-agents: Other, dynamiq: Apache-2.0). ### Where can I find alternatives to hello-agents or dynamiq? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [dynamiq alternatives](/tools/dynamiq-ai-dynamiq/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [dynamiq markdown twin](/tools/dynamiq-ai-dynamiq/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-dynamiq-ai-dynamiq.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or dynamiq? hello-agents: Very active. dynamiq: 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 dynamiq? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [dynamiq trust report](/tools/dynamiq-ai-dynamiq/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/_