--- title: "awesome-ai-apps vs awesome-ai-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arindam200-awesome-ai-apps-vs-rohitg00-awesome-ai-apps" tools: ["arindam200-awesome-ai-apps", "rohitg00-awesome-ai-apps"] --- # awesome-ai-apps vs awesome-ai-apps *GraphCanon updated Aug 26, 2026* ## Verdict Pick awesome-ai-apps if awesome-ai-apps is a curated list of projects focusing on AI applications and innovations such as RAG technologies, AI agents, and workflows, emphasizing large language models using Python; pick awesome-ai-apps if awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. [awesome-ai-apps](https://dub.sh/nebius) reports 13k GitHub stars, 1.8k forks, and 65 open issues, last pushed Aug 19, 2026. [awesome-ai-apps](https://agenstskills.com) has 817 stars, 174 forks, and 27 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [awesome-ai-apps's repository](https://github.com/Arindam200/awesome-ai-apps) and [awesome-ai-apps's repository](https://github.com/rohitg00/awesome-ai-apps). | | [awesome-ai-apps](/tools/arindam200-awesome-ai-apps.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Tagline | A curated list of AI applications showcasing RAG, agents, and workflows. | A curated collection of AI Agents and LLM Apps with various tech stacks | | Stars | 13,494 | 817 | | Forks | 1,760 | 174 | | Open issues | 65 | 27 | | Language | Python | HTML | | Adopt for | awesome-ai-apps is a curated list of projects focusing on AI applications and innovations such as RAG technologies, AI agents, and workflows, emphasizing large language models using Python. | awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. | | Persona | - | - | | Runtime | - | - | | License | MIT License ensures easy integration into both open source and proprietary projects without restrictions. | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-ai-apps](/tools/arindam200-awesome-ai-apps.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 6d | 182d | | Open issues (now) | 65 | 27 | | Stars delta | +226 (30d) | Unknown | | Open issues delta | -24 (30d) | Unknown | | Full report | [trust report](/tools/arindam200-awesome-ai-apps/trust.md) | [trust report](/tools/rohitg00-awesome-ai-apps/trust.md) | ## Decision facts: awesome-ai-apps - **Pricing:** freemium - As an open-source project under the MIT License, awesome-ai-apps is free to use. There are no paid plans beyond potential third-party service integrations or support contracts. - **Requirements:** Requires understanding of Python and familiarity with large language models and RAG technologies to benefit fully from the projects listed. - **Adopt for:** awesome-ai-apps is a curated list of projects focusing on AI applications and innovations such as RAG technologies, AI agents, and workflows, emphasizing large language models using Python. - **License detail:** MIT License ensures easy integration into both open source and proprietary projects without restrictions. ## Decision facts: awesome-ai-apps - **Adopt for:** awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. ## Choose when ### Choose awesome-ai-apps if… - awesome-ai-apps is primarily Python; awesome-ai-apps is HTML. - License: awesome-ai-apps is MIT, awesome-ai-apps is Apache-2.0. - Pricing: As an open-source project under the MIT License, awesome-ai-apps is free to use. There are no paid plans beyond potential third-party service integrations or support contracts.. - Requirements: Requires understanding of Python and familiarity with large language models and RAG technologies to benefit fully from the projects listed.. - Tags unique to awesome-ai-apps: hacktoberfest, mcp. - Use awesome-ai-apps when looking to explore or implement Retrieval-Augmented Generation (RAG) in Python projects focused on enhancing search-based question answering. ### Choose awesome-ai-apps if… - awesome-ai-apps is primarily HTML; awesome-ai-apps is Python. - License: awesome-ai-apps is Apache-2.0, awesome-ai-apps is MIT. - Tags unique to awesome-ai-apps: apps, automation, framework, genai. - For exploring real-world implementations of AI agents across different technologies ## When NOT to use awesome-ai-apps - Avoid awesome-ai-apps if your project requires non-Python support, as all the included applications are built using Python. - Do not use this repository if your focus is on backend-only AI services that do not involve RAG technologies or AI agents. ## When NOT to use awesome-ai-apps - When seeking detailed implementation steps specific to one technology stack - In scenarios demanding a deep dive into proprietary or less publicly-known application codes ## Common questions ### What is the difference between awesome-ai-apps and awesome-ai-apps? awesome-ai-apps: A curated list of AI applications showcasing RAG, agents, and workflows.. awesome-ai-apps: A curated collection of AI Agents and LLM Apps with various tech stacks. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-ai-apps over awesome-ai-apps? Choose awesome-ai-apps over awesome-ai-apps when awesome-ai-apps is primarily Python; awesome-ai-apps is HTML; License: awesome-ai-apps is MIT, awesome-ai-apps is Apache-2.0; Pricing: As an open-source project under the MIT License, awesome-ai-apps is free to use. There are no paid plans beyond potential third-party service integrations or support contracts.; Requirements: Requires understanding of Python and familiarity with large language models and RAG technologies to benefit fully from the projects listed.; Tags unique to awesome-ai-apps: hacktoberfest, mcp; Use awesome-ai-apps when looking to explore or implement Retrieval-Augmented Generation (RAG) in Python projects focused on enhancing search-based question answering. ### When should I choose awesome-ai-apps over awesome-ai-apps? Choose awesome-ai-apps over awesome-ai-apps when awesome-ai-apps is primarily HTML; awesome-ai-apps is Python; License: awesome-ai-apps is Apache-2.0, awesome-ai-apps is MIT; Tags unique to awesome-ai-apps: apps, automation, framework, genai; For exploring real-world implementations of AI agents across different technologies. ### When should I avoid awesome-ai-apps? Avoid awesome-ai-apps if your project requires non-Python support, as all the included applications are built using Python. Do not use this repository if your focus is on backend-only AI services that do not involve RAG technologies or AI agents. ### When should I avoid awesome-ai-apps? When seeking detailed implementation steps specific to one technology stack In scenarios demanding a deep dive into proprietary or less publicly-known application codes ### Is awesome-ai-apps or awesome-ai-apps more popular on GitHub? awesome-ai-apps has more GitHub stars (13,494 vs 817). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-ai-apps and awesome-ai-apps open source? Yes - both are open-source projects on GitHub (awesome-ai-apps: MIT, awesome-ai-apps: Apache-2.0). ### Where can I find alternatives to awesome-ai-apps or awesome-ai-apps? GraphCanon lists graph-backed alternatives at [awesome-ai-apps alternatives](/tools/arindam200-awesome-ai-apps/alternatives) and [awesome-ai-apps alternatives](/tools/rohitg00-awesome-ai-apps/alternatives) ([awesome-ai-apps markdown twin](/tools/arindam200-awesome-ai-apps/alternatives.md), [awesome-ai-apps markdown twin](/tools/rohitg00-awesome-ai-apps/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/arindam200-awesome-ai-apps-vs-rohitg00-awesome-ai-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-ai-apps or awesome-ai-apps? awesome-ai-apps: Very active. awesome-ai-apps: 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 awesome-ai-apps and awesome-ai-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-ai-apps trust report](/tools/arindam200-awesome-ai-apps/trust); [awesome-ai-apps trust report](/tools/rohitg00-awesome-ai-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arindam200-awesome-ai-apps`](/api/graphcanon/graph?tool=arindam200-awesome-ai-apps) - 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/_