Home/Compare/hello-agents vs kitaru

Comparison

hello-agents vs kitaru

Verdict

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

Markdown twin · hello-agents alternatives · kitaru alternatives

GraphCanon updated today

hello-agents logo

hello-agents

datawhalechina/hello-agents

65kpushed Jul 10, 2026
vs
kitaru logo

kitaru

zenml-io/kitaru

202pushed Jul 10, 2026

Trust & integrity

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

Tagline

hello-agents
Course on building intelligent agents from scratch
kitaru
Record, replay, and improve AI agents in production, built on ZenML

Stars

hello-agents
65k
kitaru
202

Forks

hello-agents
8.1k
kitaru
15

Open issues

hello-agents
144
kitaru
36

Language

hello-agents
Python
kitaru
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.
kitaru
-

Persona

hello-agents
-
kitaru
-

Runtime

hello-agents
-
kitaru
-

License

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

Last pushed

hello-agents
Jul 10, 2026
kitaru
Jul 10, 2026

Categories

hello-agents
AI Agents, LLM Frameworks
kitaru
AI Agents, Inference & Serving, LLM Frameworks

Trust and health

Days since push

hello-agents
0d
kitaru
1d

Open issues (now)

hello-agents
144
kitaru
36

Security scan

hello-agents
No lockfile
kitaru
No criticals

Full report

hello-agents
Trust report

Choose hello-agents if…

  • License: hello-agents is Other, kitaru is Apache-2.0.
  • Requirements: Min 4 GB RAM; Python knowledge assumed.
  • Tags unique to hello-agents: agent, 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 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 kitaru if…

  • License: kitaru is Apache-2.0, hello-agents is Other.
  • Tags unique to kitaru: agent-framework, ai-agents, checkpoints, durable-execution.
  • Also covers Inference & Serving.

When NOT to use kitaru

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • 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 · kitaru 202 (synced Jul 11, 2026).

Common questions

What is the difference between hello-agents and kitaru?
hello-agents: Course on building intelligent agents from scratch. kitaru: Record, replay, and improve AI agents in production, built on ZenML. See the comparison table for live GitHub stats and shared categories.
When should I choose hello-agents over kitaru?
Choose hello-agents over kitaru when License: hello-agents is Other, kitaru is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, 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 kitaru over hello-agents?
Choose kitaru over hello-agents when License: kitaru is Apache-2.0, hello-agents is Other; Tags unique to kitaru: agent-framework, ai-agents, checkpoints, durable-execution; Also covers Inference & Serving.
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 kitaru?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is hello-agents or kitaru more popular on GitHub?
hello-agents has more GitHub stars (65,432 vs 202). Stars measure visibility, not whether either tool fits your constraints.
Are hello-agents and kitaru open source?
Yes - both are open-source projects on GitHub (hello-agents: Other, kitaru: Apache-2.0).
Where can I find alternatives to hello-agents or kitaru?
GraphCanon lists graph-backed alternatives at hello-agents alternatives and kitaru alternatives (hello-agents markdown twin, kitaru 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 kitaru?
hello-agents: Very active. kitaru: 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 kitaru?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; kitaru trust report.