Comparison
hello-agents vs TradingAgents
Verdict
Pick hello-agents if hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods; pick TradingAgents if use TradingAgents for projects requiring a sophisticated framework to develop and deploy AI agents in financial market transactions leveraging Large Language Models. Avoid it if you need simpler tools or frameworks thatだ.
Markdown twin · hello-agents alternatives · TradingAgents alternatives
GraphCanon updated 5d
vs
Trust & integrity
| Signal | hello-agents | TradingAgents |
|---|---|---|
| Maintenance | Very active (1d since push) As of 5d · github_public_v1 | Active (28d since push) As of 6d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Organization account As of 6d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- TradingAgents
- Multi-Agents LLM Financial Trading Framework
Stars
- hello-agents
- 73k
- TradingAgents
- 98k
Forks
- hello-agents
- 9.1k
- TradingAgents
- 19k
Open issues
- hello-agents
- 155
- TradingAgents
- 364
Language
- hello-agents
- Python
- TradingAgents
- 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.
- TradingAgents
- Use TradingAgents for projects requiring a sophisticated framework to develop and deploy AI agents in financial market transactions leveraging Large Language Models. Avoid it if you need simpler tools or frameworks thatだ
Persona
- hello-agents
- -
- TradingAgents
- -
Runtime
- hello-agents
- -
- TradingAgents
- -
License
- hello-agents
- hello-agents is covered under an unconventional license which may require further review before usage.
- TradingAgents
- Apache-2.0
Last pushed
- hello-agents
- Aug 14, 2026
- TradingAgents
- Jul 18, 2026
Categories
- hello-agents
- AI Agents, LLM Frameworks
- TradingAgents
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- hello-agents
- Very active (96%)
- TradingAgents
- Active (82%)
Days since push
- hello-agents
- 1d
- TradingAgents
- 28d
Open issues (now)
- hello-agents
- 155
- TradingAgents
- 364
Stars delta
- hello-agents
- +6.4k (30d)
- TradingAgents
- +5.0k (30d)
Open issues delta
- hello-agents
- +8 (30d)
- TradingAgents
- +62 (30d)
Full report
- hello-agents
- Trust report
- TradingAgents
- Trust report
Choose hello-agents if…
- License: hello-agents is Other, TradingAgents is Apache-2.0.
- Requirements: Min 4 GB RAM; Python knowledge assumed.
- Tags unique to hello-agents: 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 TradingAgents if…
- License: TradingAgents is Apache-2.0, hello-agents is Other.
- Requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework..
- Tags unique to TradingAgents: finance, multiagent, trading.
- TradingAgents ships Docker support for self-hosted deployment.
- When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.
When NOT to use TradingAgents
- If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead.
- When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach.
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 Aug 16, 2026
- GitHub forks (datawhalechina/hello-agents) · observed Aug 16, 2026
- Last push (datawhalechina/hello-agents) · observed Aug 14, 2026
- License file (Other) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (TauricResearch/TradingAgents) · observed Aug 16, 2026
- GitHub forks (TauricResearch/TradingAgents) · observed Aug 16, 2026
- Last push (TauricResearch/TradingAgents) · observed Jul 18, 2026
- License file (Apache-2.0) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: hello-agents 73k · TradingAgents 98k (synced Aug 16, 2026).
Common questions
- What is the difference between hello-agents and TradingAgents?
- hello-agents: Course on building intelligent agents from scratch. TradingAgents: Multi-Agents LLM Financial Trading Framework. See the comparison table for live GitHub stats and shared categories.
- When should I choose hello-agents over TradingAgents?
- Choose hello-agents over TradingAgents when License: hello-agents is Other, TradingAgents is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: 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 TradingAgents over hello-agents?
- Choose TradingAgents over hello-agents when License: TradingAgents is Apache-2.0, hello-agents is Other; Requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework.; Tags unique to TradingAgents: finance, multiagent, trading; TradingAgents ships Docker support for self-hosted deployment; When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.
- 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 TradingAgents?
- If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead. When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach.
- Is hello-agents or TradingAgents more popular on GitHub?
- TradingAgents has more GitHub stars (98,335 vs 73,126). Stars measure visibility, not whether either tool fits your constraints.
- Are hello-agents and TradingAgents open source?
- Yes - both are open-source projects on GitHub (hello-agents: Other, TradingAgents: Apache-2.0).
- Where can I find alternatives to hello-agents or TradingAgents?
- GraphCanon lists graph-backed alternatives at hello-agents alternatives and TradingAgents alternatives (hello-agents markdown twin, TradingAgents 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 TradingAgents?
- hello-agents: Very active. TradingAgents: 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 TradingAgents?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; TradingAgents trust report.