Comparison
hello-agents vs continuum
Verdict
Pick hello-agents when license: hello-agents is Other, continuum is Apache-2.0; pick continuum when license: continuum is Apache-2.0, hello-agents is Other.
Markdown twin · hello-agents alternatives · continuum alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | hello-agents | continuum |
|---|---|---|
| Maintenance | Very active (0d since push) As of 4d · github_public_v1 | Very active (2d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 4d · osv@v1 | Published findings As of today · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- hello-agents
- Course on building intelligent agents from scratch
- continuum
- Continuum, the agent runtime by ShyftLabs. Build, orchestrate, ship.
Stars
- hello-agents
- 65k
- continuum
- 75
Forks
- hello-agents
- 8.1k
- continuum
- 8
Open issues
- hello-agents
- 144
- continuum
- 16
Language
- hello-agents
- Python
- continuum
- 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.
- continuum
- -
Persona
- hello-agents
- -
- continuum
- -
Runtime
- hello-agents
- -
- continuum
- -
License
- hello-agents
- hello-agents is covered under an unconventional license which may require further review before usage.
- continuum
- Apache-2.0
Last pushed
- hello-agents
- Jul 10, 2026
- continuum
- Jul 13, 2026
Categories
- hello-agents
- AI Agents, LLM Frameworks
- continuum
- AI Agents, LLM Frameworks, Vector Databases
Trust and health
Days since push
- hello-agents
- 0d
- continuum
- 2d
Open issues (now)
- hello-agents
- 144
- continuum
- 16
OSV dependency advisories
- hello-agents
- No lockfile (source not queried)
- continuum
- Published findings
Full report
- hello-agents
- Trust report
- continuum
- Trust report
Choose hello-agents if…
- License: hello-agents is Other, continuum is Apache-2.0.
- Requirements: Min 4 GB RAM; Python knowledge assumed.
- Tags unique to hello-agents: agent, llm, 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 continuum if…
- License: continuum is Apache-2.0, hello-agents is Other.
- Tags unique to continuum: agent-framework, agentic-ai, ai-agents, ai-orchestration.
- Also covers Vector Databases.
- continuum ships Docker support for self-hosted deployment.
When NOT to use continuum
- 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.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (datawhalechina/hello-agents) · observed Jul 11, 2026
- GitHub forks (datawhalechina/hello-agents) · observed Jul 11, 2026
- Last push (datawhalechina/hello-agents) · observed Jul 10, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (shyftlabs/continuum) · observed Jul 15, 2026
- GitHub forks (shyftlabs/continuum) · observed Jul 15, 2026
- Last push (shyftlabs/continuum) · observed Jul 13, 2026
- License file (Apache-2.0) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: hello-agents 65k · continuum 75 (synced Jul 11, 2026).
Common questions
- What is the difference between hello-agents and continuum?
- hello-agents: Course on building intelligent agents from scratch. continuum: Continuum, the agent runtime by ShyftLabs. Build, orchestrate, ship.. See the comparison table for live GitHub stats and shared categories.
- When should I choose hello-agents over continuum?
- Choose hello-agents over continuum when License: hello-agents is Other, continuum is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, 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 continuum over hello-agents?
- Choose continuum over hello-agents when License: continuum is Apache-2.0, hello-agents is Other; Tags unique to continuum: agent-framework, agentic-ai, ai-agents, ai-orchestration; Also covers Vector Databases; continuum ships Docker support for self-hosted deployment.
- 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 continuum?
- 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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Is hello-agents or continuum more popular on GitHub?
- hello-agents has more GitHub stars (65,432 vs 75). Stars measure visibility, not whether either tool fits your constraints.
- Are hello-agents and continuum open source?
- Yes - both are open-source projects on GitHub (hello-agents: Other, continuum: Apache-2.0).
- Where can I find alternatives to hello-agents or continuum?
- GraphCanon lists graph-backed alternatives at hello-agents alternatives and continuum alternatives (hello-agents markdown twin, continuum 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 continuum?
- hello-agents: Very active. continuum: 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 continuum?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; continuum trust report.