Comparison
LangGPT vs awesome
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.
Markdown twin · LangGPT alternatives · awesome alternatives
GraphCanon updated today
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Trust & integrity
| Signal | LangGPT | awesome |
|---|---|---|
| Maintenance | Active (11d since push) As of today · github_public_v1 | Active (11d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- 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
Stars
- LangGPT
- 12k
- awesome
- 484k
Forks
- LangGPT
- 935
- awesome
- 36k
Open issues
- LangGPT
- 0
- awesome
- 92
Language
- LangGPT
- Jupyter Notebook
- awesome
- -
Adopt for
- LangGPT
- -
- awesome
- -
Persona
- LangGPT
- -
- awesome
- -
Runtime
- LangGPT
- -
- awesome
- -
License
- LangGPT
- Apache-2.0
- awesome
- CC0-1.0
Last pushed
- LangGPT
- Jun 29, 2026
- awesome
- Jun 30, 2026
Categories
- LangGPT
- LLM Frameworks
- awesome
- LLM Frameworks
Trust and health
Open issues (now)
- LangGPT
- 0
- awesome
- 92
Owner type
- LangGPT
- Organization
- awesome
- User
Full report
- LangGPT
- Trust report
- awesome
- Trust report
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).
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.
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 awesome
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (langgptai/LangGPT) · observed Jul 11, 2026
- GitHub forks (langgptai/LangGPT) · observed Jul 11, 2026
- Last push (langgptai/LangGPT) · observed Jun 29, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (sindresorhus/awesome) · observed Jul 11, 2026
- GitHub forks (sindresorhus/awesome) · observed Jul 11, 2026
- Last push (sindresorhus/awesome) · observed Jun 30, 2026
- License file (CC0-1.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LangGPT 12k · awesome 484k (synced Jul 11, 2026).
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 and awesome alternatives (LangGPT markdown twin, awesome 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, 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; awesome trust report.