--- title: "hello-agents vs AdalFlow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-sylphai-inc-adalflow" tools: ["datawhalechina-hello-agents", "sylphai-inc-adalflow"] --- # hello-agents vs AdalFlow *GraphCanon updated Jul 12, 2026* ## 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 AdalFlow if adalFlow is designed to streamline the development and automatic optimization of LLM applications. [hello-agents](https://hello-agents.datawhale.cc) reports 65k GitHub stars, 8.1k forks, and 144 open issues, last pushed Jul 10, 2026. [AdalFlow](http://adalflow.sylph.ai/) has 4.2k stars, 378 forks, and 65 open issues, last pushed May 29, 2026. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [AdalFlow's repository](https://github.com/SylphAI-Inc/AdalFlow). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [AdalFlow](/tools/sylphai-inc-adalflow.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | The library to build & auto-optimize LLM applications. | | Stars | 65,432 | 4,178 | | Forks | 8,109 | 378 | | Open issues | 144 | 65 | | Language | Python | Python | | Adopt for | hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. | AdalFlow is designed to streamline the development and automatic optimization of LLM applications. | | Persona | - | - | | Runtime | - | - | | License | hello-agents is covered under an unconventional license which may require further review before usage. | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, Data & Retrieval, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [AdalFlow](/tools/sylphai-inc-adalflow.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 43d | | Open issues (now) | 144 | 65 | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/sylphai-inc-adalflow/trust.md) | ## Decision facts: hello-agents - **Requirements:** Min 4 GB RAM; Python knowledge assumed - **Adopt for:** hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. - **License detail:** hello-agents is covered under an unconventional license which may require further review before usage. ## Decision facts: AdalFlow - **Adopt for:** AdalFlow is designed to streamline the development and automatic optimization of LLM applications. ## Choose when ### Choose hello-agents if… - License: hello-agents is Other, AdalFlow is MIT. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Tags unique to hello-agents: 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. ### Choose AdalFlow if… - License: AdalFlow is MIT, hello-agents is Other. - Tags unique to AdalFlow: ai, auto-prompting, bm25, chatbot. - Also covers Data & Retrieval, Model Training. - When you are working on projects that require advanced AI agents or chatbots with auto-prompting features, as AdalFlow can handle these needs comprehensively. ## 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. ## When NOT to use AdalFlow - Avoid using AdalFlow if your project does not benefit from auto-optimization features or does not involve LLM applications, as its specialized capabilities might introduce unnecessary complexity. - AdalFlow may not be the best choice for projects where custom or low-level control over all aspects of the AI model training and optimization is required, given it's designed to streamline processes. ## Common questions ### What is the difference between hello-agents and AdalFlow? hello-agents: Course on building intelligent agents from scratch. AdalFlow: The library to build & auto-optimize LLM applications.. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over AdalFlow? Choose hello-agents over AdalFlow when License: hello-agents is Other, AdalFlow is MIT; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: 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 AdalFlow over hello-agents? Choose AdalFlow over hello-agents when License: AdalFlow is MIT, hello-agents is Other; Tags unique to AdalFlow: ai, auto-prompting, bm25, chatbot; Also covers Data & Retrieval, Model Training; When you are working on projects that require advanced AI agents or chatbots with auto-prompting features, as AdalFlow can handle these needs comprehensively. ### 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 AdalFlow? Avoid using AdalFlow if your project does not benefit from auto-optimization features or does not involve LLM applications, as its specialized capabilities might introduce unnecessary complexity. AdalFlow may not be the best choice for projects where custom or low-level control over all aspects of the AI model training and optimization is required, given it's designed to streamline processes. ### Is hello-agents or AdalFlow more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 4,178). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and AdalFlow open source? Yes - both are open-source projects on GitHub (hello-agents: Other, AdalFlow: MIT). ### Where can I find alternatives to hello-agents or AdalFlow? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [AdalFlow alternatives](/tools/sylphai-inc-adalflow/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [AdalFlow markdown twin](/tools/sylphai-inc-adalflow/alternatives.md)), 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](/compare/datawhalechina-hello-agents-vs-sylphai-inc-adalflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or AdalFlow? hello-agents: Very active. AdalFlow: Steady. 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 AdalFlow? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [AdalFlow trust report](/tools/sylphai-inc-adalflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=datawhalechina-hello-agents`](/api/graphcanon/graph?tool=datawhalechina-hello-agents) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_