Home/Compare/hello-agents vs LazyLLM

Comparison

hello-agents vs LazyLLM

Verdict

Pick hello-agents when license: hello-agents is Other, LazyLLM is Apache-2.0; pick LazyLLM when license: LazyLLM is Apache-2.0, hello-agents is Other.

Markdown twin · hello-agents alternatives · LazyLLM alternatives

GraphCanon updated today

hello-agents logo

hello-agents

datawhalechina/hello-agents

65kpushed Jul 10, 2026
vs
LazyLLM logo

LazyLLM

LazyAGI/LazyLLM

3.9kpushed Jul 10, 2026

Trust & integrity

Signalhello-agentsLazyLLM
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (1d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
31 low (31 low)
As of today · osv@v1

Tagline

hello-agents
Course on building intelligent agents from scratch
LazyLLM
Easiest and laziest way for building multi-agent LLMs applications.

Stars

hello-agents
65k
LazyLLM
3.9k

Forks

hello-agents
8.1k
LazyLLM
396

Open issues

hello-agents
144
LazyLLM
46

Language

hello-agents
Python
LazyLLM
Python

Adopt for

hello-agents
hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods.
LazyLLM
-

Persona

hello-agents
-
LazyLLM
-

Runtime

hello-agents
-
LazyLLM
-

License

hello-agents
hello-agents is covered under an unconventional license which may require further review before usage.
LazyLLM
Apache-2.0

Last pushed

hello-agents
Jul 10, 2026
LazyLLM
Jul 10, 2026

Categories

hello-agents
LLM Frameworks, AI Agents
LazyLLM
AI Agents, LLM Frameworks

Trust and health

Days since push

hello-agents
0d
LazyLLM
1d

Open issues (now)

hello-agents
144
LazyLLM
46

Security scan

hello-agents
No lockfile
LazyLLM
31 low (31 low)

Full report

hello-agents
Trust report

Choose hello-agents if…

  • License: hello-agents is Other, LazyLLM is Apache-2.0.
  • 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 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.

Choose LazyLLM if…

  • License: LazyLLM is Apache-2.0, hello-agents is Other.
  • Tags unique to LazyLLM: deep-learning, agents, finetuning, data.
  • Leaner open-issue backlog (46).

When NOT to use LazyLLM

  • 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: hello-agents 65k · LazyLLM 3.9k (synced Jul 11, 2026).

Common questions

What is the difference between hello-agents and LazyLLM?
hello-agents: Course on building intelligent agents from scratch. LazyLLM: Easiest and laziest way for building multi-agent LLMs applications.. See the comparison table for live GitHub stats and shared categories.
When should I choose hello-agents over LazyLLM?
Choose hello-agents over LazyLLM when License: hello-agents is Other, LazyLLM is Apache-2.0; 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 LazyLLM over hello-agents?
Choose LazyLLM over hello-agents when License: LazyLLM is Apache-2.0, hello-agents is Other; Tags unique to LazyLLM: deep-learning, agents, finetuning, data; Leaner open-issue backlog (46).
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 LazyLLM?
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 LazyLLM more popular on GitHub?
hello-agents has more GitHub stars (65,432 vs 3,856). Stars measure visibility, not whether either tool fits your constraints.
Are hello-agents and LazyLLM open source?
Yes - both are open-source projects on GitHub (hello-agents: Other, LazyLLM: Apache-2.0).
Where can I find alternatives to hello-agents or LazyLLM?
GraphCanon lists graph-backed alternatives at hello-agents alternatives and LazyLLM alternatives (hello-agents markdown twin, LazyLLM 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 LazyLLM?
hello-agents: Very active. LazyLLM: 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 LazyLLM?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; LazyLLM trust report.