--- title: "LangGPT vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langgptai-langgpt-vs-sindresorhus-awesome" tools: ["langgptai-langgpt", "sindresorhus-awesome"] --- # LangGPT vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick LangGPT when license: LangGPT is Apache-2.0, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, LangGPT is Apache-2.0. [LangGPT](https://github.com/langgptai) reports 12k GitHub stars, 935 forks, and 0 open issues, last pushed Jun 29, 2026. [awesome](https://github.com/sindresorhus/awesome) has 484k stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [LangGPT's repository](https://github.com/langgptai/LangGPT) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [LangGPT](/tools/langgptai-langgpt.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词（Structured Prompt）提出者 📌 元提示词（Meta-Prompt）发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-promp | 😎 Curated list of awesome topics including hardware resources | | Stars | 12,330 | 484,026 | | Forks | 935 | 35,799 | | Open issues | 0 | 92 | | Language | Jupyter Notebook | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | CC0-1.0 | | Categories | LLM Frameworks | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LangGPT](/tools/langgptai-langgpt.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Open issues (now) | 0 | 92 | | Owner type | Organization | User | | Full report | [trust report](/tools/langgptai-langgpt/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Choose when ### Choose LangGPT if… - License: LangGPT is Apache-2.0, awesome is CC0-1.0. - Tags unique to LangGPT: doubao, gemini, gpt-4, chatgpt. - Leaner open-issue backlog (0). ### Choose awesome if… - License: awesome is CC0-1.0, LangGPT is Apache-2.0. - Tags unique to awesome: resources, awesome-list. - More GitHub stars (484k vs 12k) - visibility, not fit. ## When NOT to use LangGPT - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use awesome - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between LangGPT and awesome? LangGPT: LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词（Structured Prompt）提出者 📌 元提示词（Meta-Prompt）发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-promp. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose LangGPT over awesome? Choose LangGPT over awesome when License: LangGPT is Apache-2.0, awesome is CC0-1.0; Tags unique to LangGPT: doubao, gemini, gpt-4, chatgpt; Leaner open-issue backlog (0). ### When should I choose awesome over LangGPT? Choose awesome over LangGPT when License: awesome is CC0-1.0, LangGPT is Apache-2.0; Tags unique to awesome: resources, awesome-list; More GitHub stars (484k vs 12k) - visibility, not fit. ### When should I avoid LangGPT? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid awesome? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is LangGPT or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 12,330). Stars measure visibility, not whether either tool fits your constraints. ### Are LangGPT and awesome open source? Yes - both are open-source projects on GitHub (LangGPT: Apache-2.0, awesome: CC0-1.0). ### Where can I find alternatives to LangGPT or awesome? GraphCanon lists graph-backed alternatives at [LangGPT alternatives](/tools/langgptai-langgpt/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([LangGPT markdown twin](/tools/langgptai-langgpt/alternatives.md), [awesome markdown twin](/tools/sindresorhus-awesome/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/langgptai-langgpt-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LangGPT or awesome? LangGPT: Active. awesome: 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 LangGPT and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LangGPT trust report](/tools/langgptai-langgpt/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langgptai-langgpt`](/api/graphcanon/graph?tool=langgptai-langgpt) - 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/_