--- title: "DocsGPT vs lever" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arc53-docsgpt-vs-niansong1996-lever" tools: ["arc53-docsgpt", "niansong1996-lever"] --- # DocsGPT vs lever *GraphCanon updated Jul 11, 2026* ## Verdict Pick DocsGPT when requirements: DocsGPT is built using Python and PyTorch, requiring familiarity with these technologies. It supports a wide variety of models but may need customization based.; pick lever when tags unique to lever: python. [DocsGPT](https://app.docsgpt.cloud/) reports 18k GitHub stars, 2.1k forks, and 87 open issues, last pushed Jul 10, 2026. [lever](https://arxiv.org/abs/2302.08468) has 90 stars, 8 forks, and 2 open issues, last pushed Jul 5, 2023. Figures are from public GitHub metadata via [DocsGPT's repository](https://github.com/arc53/DocsGPT) and [lever's repository](https://github.com/niansong1996/lever). | | [DocsGPT](/tools/arc53-docsgpt.md) | [lever](/tools/niansong1996-lever.md) | | --- | --- | --- | | Tagline | Private AI platform for agents, assistants and enterprise search. | Code for paper "LEVER: Learning to Verifiy Language-to-Code Generation with Execution" (ICML'23) | | Stars | 17,978 | 90 | | Forks | 2,072 | 8 | | Open issues | 87 | 2 | | Language | Python | Python | | Adopt for | DocsGPT is a private AI platform tailored for building agents, conducting deep research, and enabling enterprise search capabilities. | - | | Persona | - | - | | Runtime | - | - | | License | MIT License - Permits free use for commercial or non-commercial purposes but requires you to include the license text if distributing source code. | MIT | | Categories | AI Agents, Data & Retrieval | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DocsGPT](/tools/arc53-docsgpt.md) | [lever](/tools/niansong1996-lever.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1102d | | Open issues (now) | 87 | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/arc53-docsgpt/trust.md) | [trust report](/tools/niansong1996-lever/trust.md) | ## Decision facts: DocsGPT - **Requirements:** DocsGPT is built using Python and PyTorch, requiring familiarity with these technologies. It supports a wide variety of models but may need customization based. - **Adopt for:** DocsGPT is a private AI platform tailored for building agents, conducting deep research, and enabling enterprise search capabilities. - **License detail:** MIT License - Permits free use for commercial or non-commercial purposes but requires you to include the license text if distributing source code. ## Choose when ### Choose DocsGPT if… - Requirements: DocsGPT is built using Python and PyTorch, requiring familiarity with these technologies. It supports a wide variety of models but may need customization based.. - Tags unique to DocsGPT: agent-builder, agents, ai, chatgpt. - Also covers AI Agents. - When you need to build custom AI agents with built-in agent builder capability ### Choose lever if… - Tags unique to lever: python. - Leaner open-issue backlog (2). ## When NOT to use DocsGPT - If your project relies on open-source tools that are not compatible with the specific ecosystem of DocsGPT - When you specifically require real-time collaboration features directly integrated into the tool, as DocsGPT focuses more on agent building and research capabilities rather than live collaborative AI - For projects where a significant emphasis is placed on user-facing search interfaces, as DocsGPT's strength lies more in backend integration and deep research functionalities ## When NOT to use lever - Last GitHub push was 1103 days ago (dormant maintenance, Jul 5, 2023). Validate activity before betting a new project on lever. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ## Common questions ### What is the difference between DocsGPT and lever? DocsGPT: Private AI platform for agents, assistants and enterprise search.. lever: Code for paper "LEVER: Learning to Verifiy Language-to-Code Generation with Execution" (ICML'23). See the comparison table for live GitHub stats and shared categories. ### When should I choose DocsGPT over lever? Choose DocsGPT over lever when Requirements: DocsGPT is built using Python and PyTorch, requiring familiarity with these technologies. It supports a wide variety of models but may need customization based.; Tags unique to DocsGPT: agent-builder, agents, ai, chatgpt; Also covers AI Agents; When you need to build custom AI agents with built-in agent builder capability. ### When should I choose lever over DocsGPT? Choose lever over DocsGPT when Tags unique to lever: python; Leaner open-issue backlog (2). ### When should I avoid DocsGPT? If your project relies on open-source tools that are not compatible with the specific ecosystem of DocsGPT When you specifically require real-time collaboration features directly integrated into the tool, as DocsGPT focuses more on agent building and research capabilities rather than live collaborative AI For projects where a significant emphasis is placed on user-facing search interfaces, as DocsGPT's strength lies more in backend integration and deep research functionalities ### When should I avoid lever? Last GitHub push was 1103 days ago (dormant maintenance, Jul 5, 2023). Validate activity before betting a new project on lever. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ### Is DocsGPT or lever more popular on GitHub? DocsGPT has more GitHub stars (17,978 vs 90). Stars measure visibility, not whether either tool fits your constraints. ### Are DocsGPT and lever open source? Yes - both are open-source projects on GitHub (DocsGPT: MIT, lever: MIT). ### Where can I find alternatives to DocsGPT or lever? GraphCanon lists graph-backed alternatives at [DocsGPT alternatives](/tools/arc53-docsgpt/alternatives) and [lever alternatives](/tools/niansong1996-lever/alternatives) ([DocsGPT markdown twin](/tools/arc53-docsgpt/alternatives.md), [lever markdown twin](/tools/niansong1996-lever/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/arc53-docsgpt-vs-niansong1996-lever.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DocsGPT or lever? DocsGPT: Very active. lever: Dormant. 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 DocsGPT and lever? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DocsGPT trust report](/tools/arc53-docsgpt/trust); [lever trust report](/tools/niansong1996-lever/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arc53-docsgpt`](/api/graphcanon/graph?tool=arc53-docsgpt) - 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/_