Home/Compare/hello-agents vs llm_agents

Comparison

hello-agents vs llm_agents

Verdict

Pick hello-agents when license: hello-agents is Other, llm_agents is MIT; pick llm_agents when license: llm_agents is MIT, hello-agents is Other.

Markdown twin · hello-agents alternatives · llm_agents alternatives

GraphCanon updated today

hello-agents logo

hello-agents

datawhalechina/hello-agents

65kpushed Jul 10, 2026
vs
llm_agents logo

llm_agents

mpaepper/llm_agents

1.1kpushed Jun 23, 2025

Trust & integrity

Signalhello-agentsllm_agents
Maintenance
Very active (0d since push)
As of today · github_public_v1
Dormant (382d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
32 low (32 low)
As of today · osv@v1

Tagline

hello-agents
Course on building intelligent agents from scratch
llm_agents
Build agents which are controlled by LLMs

Stars

hello-agents
65k
llm_agents
1.1k

Forks

hello-agents
8.1k
llm_agents
85

Open issues

hello-agents
144
llm_agents
3

Language

hello-agents
Python
llm_agents
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.
llm_agents
-

Persona

hello-agents
-
llm_agents
-

Runtime

hello-agents
-
llm_agents
-

License

hello-agents
hello-agents is covered under an unconventional license which may require further review before usage.
llm_agents
MIT

Last pushed

hello-agents
Jul 10, 2026
llm_agents
Jun 23, 2025

Categories

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

Trust and health

Maintenance

hello-agents
Very active (96%)
llm_agents
Dormant (18%)

Days since push

hello-agents
0d
llm_agents
382d

Open issues (now)

hello-agents
144
llm_agents
3

Owner type

hello-agents
Organization
llm_agents
User

Security scan

hello-agents
No lockfile
llm_agents
32 low (32 low)

Full report

hello-agents
Trust report
llm_agents
Trust report

Choose hello-agents if…

  • License: hello-agents is Other, llm_agents is MIT.
  • 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 llm_agents if…

  • License: llm_agents is MIT, hello-agents is Other.
  • Tags unique to llm_agents: llms, deep-learning, machine-learning, python.
  • Leaner open-issue backlog (3).

When NOT to use llm_agents

  • Last GitHub push was 383 days ago (dormant maintenance, Jun 23, 2025). Validate activity before betting a new project on llm_agents.
  • 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 · llm_agents 1.1k (synced Jul 11, 2026).

Common questions

What is the difference between hello-agents and llm_agents?
hello-agents: Course on building intelligent agents from scratch. llm_agents: Build agents which are controlled by LLMs. See the comparison table for live GitHub stats and shared categories.
When should I choose hello-agents over llm_agents?
Choose hello-agents over llm_agents when License: hello-agents is Other, llm_agents is MIT; 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 llm_agents over hello-agents?
Choose llm_agents over hello-agents when License: llm_agents is MIT, hello-agents is Other; Tags unique to llm_agents: llms, deep-learning, machine-learning, python; Leaner open-issue backlog (3).
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 llm_agents?
Last GitHub push was 383 days ago (dormant maintenance, Jun 23, 2025). Validate activity before betting a new project on llm_agents. 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 llm_agents more popular on GitHub?
hello-agents has more GitHub stars (65,432 vs 1,050). Stars measure visibility, not whether either tool fits your constraints.
Are hello-agents and llm_agents open source?
Yes - both are open-source projects on GitHub (hello-agents: Other, llm_agents: MIT).
Where can I find alternatives to hello-agents or llm_agents?
GraphCanon lists graph-backed alternatives at hello-agents alternatives and llm_agents alternatives (hello-agents markdown twin, llm_agents 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 llm_agents?
hello-agents: Very active. llm_agents: Dormant. 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 llm_agents?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; llm_agents trust report.