--- title: "hello-agents vs Learn-LangChain" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-iparesh18-learn-langchain" tools: ["datawhalechina-hello-agents", "iparesh18-learn-langchain"] --- # hello-agents vs Learn-LangChain *GraphCanon updated Jul 11, 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 Learn-LangChain if learn-LangChain is specifically designed as a comprehensive learning repository for LangChain in JavaScript, providing real-world examples and covering aspects from prompts to agents and LangGraph workflows. This makes a. [hello-agents](https://hello-agents.datawhale.cc) reports 65k GitHub stars, 8.1k forks, and 144 open issues, last pushed Jul 10, 2026. [Learn-LangChain](https://github.com/iparesh18/Learn-LangChain) has 6 stars, 2 forks, and 0 open issues, last pushed Nov 26, 2025. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [Learn-LangChain's repository](https://github.com/iparesh18/Learn-LangChain). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [Learn-LangChain](/tools/iparesh18-learn-langchain.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | End-to-end LangChain JS learning repo with real examples | | Stars | 65,432 | 6 | | Forks | 8,109 | 2 | | Open issues | 144 | 0 | | Language | Python | JavaScript | | Adopt for | hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. | Learn-LangChain is specifically designed as a comprehensive learning repository for LangChain in JavaScript, providing real-world examples and covering aspects from prompts to agents and LangGraph workflows. This makes a | | Persona | - | - | | Runtime | - | - | | License | hello-agents is covered under an unconventional license which may require further review before usage. | - | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [Learn-LangChain](/tools/iparesh18-learn-langchain.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 226d | | Open issues (now) | 144 | 0 | | Owner type | Organization | User | | Security scan | No lockfile | 16 low (16 low) | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/iparesh18-learn-langchain/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: Learn-LangChain - **Adopt for:** Learn-LangChain is specifically designed as a comprehensive learning repository for LangChain in JavaScript, providing real-world examples and covering aspects from prompts to agents and LangGraph workflows. This makes a ## Choose when ### Choose hello-agents if… - hello-agents is primarily Python; Learn-LangChain is JavaScript. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Tags unique to hello-agents: agent, llm, 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 Learn-LangChain if… - Learn-LangChain is primarily JavaScript; hello-agents is Python. - Tags unique to Learn-LangChain: agents, javascript, langchain, langgraph. - You need to learn or teach LangChain using JavaScript. ## 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 Learn-LangChain - You prefer frameworks in languages other than JavaScript, as this repository focuses specifically on JavaScript applications. - If you require support for a niche aspect of LangChain not covered by the examples provided here, such as cutting-edge research tools not included in standard LangChain JS workflows. ## Common questions ### What is the difference between hello-agents and Learn-LangChain? hello-agents: Course on building intelligent agents from scratch. Learn-LangChain: End-to-end LangChain JS learning repo with real examples. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over Learn-LangChain? Choose hello-agents over Learn-LangChain when hello-agents is primarily Python; Learn-LangChain is JavaScript; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, 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 Learn-LangChain over hello-agents? Choose Learn-LangChain over hello-agents when Learn-LangChain is primarily JavaScript; hello-agents is Python; Tags unique to Learn-LangChain: agents, javascript, langchain, langgraph; You need to learn or teach LangChain using JavaScript. ### 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 Learn-LangChain? You prefer frameworks in languages other than JavaScript, as this repository focuses specifically on JavaScript applications. If you require support for a niche aspect of LangChain not covered by the examples provided here, such as cutting-edge research tools not included in standard LangChain JS workflows. ### Is hello-agents or Learn-LangChain more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 6). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and Learn-LangChain open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to hello-agents or Learn-LangChain? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [Learn-LangChain alternatives](/tools/iparesh18-learn-langchain/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [Learn-LangChain markdown twin](/tools/iparesh18-learn-langchain/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-iparesh18-learn-langchain.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or Learn-LangChain? hello-agents: Very active. Learn-LangChain: Slowing. 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 Learn-LangChain? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [Learn-LangChain trust report](/tools/iparesh18-learn-langchain/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/_