--- title: "langchain-decorators vs AutoGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ju-bezdek-langchain-decorators-vs-significant-gravitas-autogpt" tools: ["ju-bezdek-langchain-decorators", "significant-gravitas-autogpt"] --- # langchain-decorators vs AutoGPT *GraphCanon updated Jul 12, 2026* ## Verdict Pick langchain-decorators when license: langchain-decorators is MIT, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, langchain-decorators is MIT. [langchain-decorators](https://github.com/ju-bezdek/langchain-decorators) reports 234 GitHub stars, 12 forks, and 6 open issues, last pushed Apr 18, 2026. [AutoGPT](https://agpt.co) has 185k stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [langchain-decorators's repository](https://github.com/ju-bezdek/langchain-decorators) and [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT). | | [langchain-decorators](/tools/ju-bezdek-langchain-decorators.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Tagline | syntactic sugar 🍭 for langchain | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | | Stars | 234 | 185,464 | | Forks | 12 | 46,111 | | Open issues | 6 | 494 | | Language | Python | Python | | Adopt for | - | AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | LLM Frameworks | LLM Frameworks, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain-decorators](/tools/ju-bezdek-langchain-decorators.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 84d | 0d | | Open issues (now) | 6 | 494 | | Owner type | User | Organization | | Security scan | 64 low (64 low) | No lockfile | | Full report | [trust report](/tools/ju-bezdek-langchain-decorators/trust.md) | [trust report](/tools/significant-gravitas-autogpt/trust.md) | ## Decision facts: AutoGPT - **Adopt for:** AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. ## Choose when ### Choose langchain-decorators if… - License: langchain-decorators is MIT, AutoGPT is Other. - Tags unique to langchain-decorators: python, langchain, prompt-engineering. - Leaner open-issue backlog (6). ### Choose AutoGPT if… - License: AutoGPT is Other, langchain-decorators is MIT. - Tags unique to AutoGPT: agents, ai, artificial-intelligence, agentic-ai. - Also covers AI Agents. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ## When NOT to use langchain-decorators - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use AutoGPT - Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. - If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ## Common questions ### What is the difference between langchain-decorators and AutoGPT? langchain-decorators: syntactic sugar 🍭 for langchain. AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain-decorators over AutoGPT? Choose langchain-decorators over AutoGPT when License: langchain-decorators is MIT, AutoGPT is Other; Tags unique to langchain-decorators: python, langchain, prompt-engineering; Leaner open-issue backlog (6). ### When should I choose AutoGPT over langchain-decorators? Choose AutoGPT over langchain-decorators when License: AutoGPT is Other, langchain-decorators is MIT; Tags unique to AutoGPT: agents, ai, artificial-intelligence, agentic-ai; Also covers AI Agents; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I avoid langchain-decorators? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid AutoGPT? Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ### Is langchain-decorators or AutoGPT more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 234). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain-decorators and AutoGPT open source? Yes - both are open-source projects on GitHub (langchain-decorators: MIT, AutoGPT: Other). ### Where can I find alternatives to langchain-decorators or AutoGPT? GraphCanon lists graph-backed alternatives at [langchain-decorators alternatives](/tools/ju-bezdek-langchain-decorators/alternatives) and [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) ([langchain-decorators markdown twin](/tools/ju-bezdek-langchain-decorators/alternatives.md), [AutoGPT markdown twin](/tools/significant-gravitas-autogpt/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/ju-bezdek-langchain-decorators-vs-significant-gravitas-autogpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain-decorators or AutoGPT? langchain-decorators: Steady. AutoGPT: Very 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 langchain-decorators and AutoGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain-decorators trust report](/tools/ju-bezdek-langchain-decorators/trust); [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ju-bezdek-langchain-decorators`](/api/graphcanon/graph?tool=ju-bezdek-langchain-decorators) - 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/_