hello-agents vs awesome-AutoML

Common questions

What is the difference between hello-agents and awesome-AutoML?

hello-agents: Course on building intelligent agents from scratch. awesome-AutoML: Curating a list of AutoML-related research, tools, projects and other resources. See the comparison table for live GitHub stats and shared categories.

When should I choose hello-agents over awesome-AutoML?

Choose hello-agents over awesome-AutoML when License: hello-agents is Other, awesome-AutoML is GPL-3.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: llm, rag, tutorial, agent; 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 awesome-AutoML over hello-agents?

Choose awesome-AutoML over hello-agents when License: awesome-AutoML is GPL-3.0, hello-agents is Other; Also covers Model Training; Leaner open-issue backlog (1).

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 awesome-AutoML?

Last GitHub push was 110 days ago (slowing maintenance, Mar 24, 2026). Validate activity before betting a new project on awesome-AutoML. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Is hello-agents or awesome-AutoML more popular on GitHub?

hello-agents has more GitHub stars (65,432 vs 940). Stars measure visibility, not whether either tool fits your constraints.

Are hello-agents and awesome-AutoML open source?

Yes - both are open-source projects on GitHub (hello-agents: Other, awesome-AutoML: GPL-3.0).

Where can I find alternatives to hello-agents or awesome-AutoML?

GraphCanon lists graph-backed alternatives at hello-agents alternatives and awesome-AutoML alternatives (hello-agents markdown twin, awesome-AutoML markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, hello-agents or awesome-AutoML?

hello-agents: Very active. awesome-AutoML: Slowing. 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 awesome-AutoML?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; awesome-AutoML trust report.