--- title: "raga-llm-hub vs ai-engineering-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/raga-ai-hub-raga-llm-hub-vs-rohitg00-ai-engineering-from-scratch" tools: ["raga-ai-hub-raga-llm-hub", "rohitg00-ai-engineering-from-scratch"] --- # raga-llm-hub vs ai-engineering-from-scratch *GraphCanon updated Jul 11, 2026* ## Verdict Pick raga-llm-hub when license: raga-llm-hub is Other, ai-engineering-from-scratch is MIT; pick ai-engineering-from-scratch when license: ai-engineering-from-scratch is MIT, raga-llm-hub is Other. [raga-llm-hub](https://www.raga.ai/llms) reports 114 GitHub stars, 14 forks, and 2 open issues, last pushed Sep 9, 2024. [ai-engineering-from-scratch](https://aiengineeringfromscratch.com) has 38k stars, 6.3k forks, and 96 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [raga-llm-hub's repository](https://github.com/raga-ai-hub/raga-llm-hub) and [ai-engineering-from-scratch's repository](https://github.com/rohitg00/ai-engineering-from-scratch). | | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Tagline | Framework for LLM evaluation, guardrails and security | Learn it. Build it. Ship it for others. | | Stars | 114 | 37,922 | | Forks | 14 | 6,329 | | Open issues | 2 | 96 | | Language | Python | Python | | Adopt for | - | Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | LLM Frameworks, Evaluation & Observability | LLM Frameworks, AI Agents, Computer Vision, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 670d | 15d | | Open issues (now) | 2 | 96 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/raga-ai-hub-raga-llm-hub/trust.md) | [trust report](/tools/rohitg00-ai-engineering-from-scratch/trust.md) | ## Decision facts: ai-engineering-from-scratch - **Pricing:** freemium - The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up - **Adopt for:** Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. ## Choose when ### Choose raga-llm-hub if… - License: raga-llm-hub is Other, ai-engineering-from-scratch is MIT. - Tags unique to raga-llm-hub: llmops, python, guardrails, llm-security. - Also covers Evaluation & Observability. ### Choose ai-engineering-from-scratch if… - License: ai-engineering-from-scratch is MIT, raga-llm-hub is Other. - Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up. - Tags unique to ai-engineering-from-scratch: deep-learning, ai-engineering, agents, llm. - Also covers AI Agents, Computer Vision, Developer Tools. - When you want to start with foundational knowledge and learn the intricacies behind AI systems. ## When NOT to use raga-llm-hub - Last GitHub push was 670 days ago (dormant maintenance, Sep 9, 2024). Validate activity before betting a new project on raga-llm-hub. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## When NOT to use ai-engineering-from-scratch - If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. - When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ## Common questions ### What is the difference between raga-llm-hub and ai-engineering-from-scratch? raga-llm-hub: Framework for LLM evaluation, guardrails and security. ai-engineering-from-scratch: Learn it. Build it. Ship it for others.. See the comparison table for live GitHub stats and shared categories. ### When should I choose raga-llm-hub over ai-engineering-from-scratch? Choose raga-llm-hub over ai-engineering-from-scratch when License: raga-llm-hub is Other, ai-engineering-from-scratch is MIT; Tags unique to raga-llm-hub: llmops, python, guardrails, llm-security; Also covers Evaluation & Observability. ### When should I choose ai-engineering-from-scratch over raga-llm-hub? Choose ai-engineering-from-scratch over raga-llm-hub when License: ai-engineering-from-scratch is MIT, raga-llm-hub is Other; Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up; Tags unique to ai-engineering-from-scratch: deep-learning, ai-engineering, agents, llm; Also covers AI Agents, Computer Vision, Developer Tools; When you want to start with foundational knowledge and learn the intricacies behind AI systems. ### When should I avoid raga-llm-hub? Last GitHub push was 670 days ago (dormant maintenance, Sep 9, 2024). Validate activity before betting a new project on raga-llm-hub. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### When should I avoid ai-engineering-from-scratch? If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ### Is raga-llm-hub or ai-engineering-from-scratch more popular on GitHub? ai-engineering-from-scratch has more GitHub stars (37,922 vs 114). Stars measure visibility, not whether either tool fits your constraints. ### Are raga-llm-hub and ai-engineering-from-scratch open source? Yes - both are open-source projects on GitHub (raga-llm-hub: Other, ai-engineering-from-scratch: MIT). ### Where can I find alternatives to raga-llm-hub or ai-engineering-from-scratch? GraphCanon lists graph-backed alternatives at [raga-llm-hub alternatives](/tools/raga-ai-hub-raga-llm-hub/alternatives) and [ai-engineering-from-scratch alternatives](/tools/rohitg00-ai-engineering-from-scratch/alternatives) ([raga-llm-hub markdown twin](/tools/raga-ai-hub-raga-llm-hub/alternatives.md), [ai-engineering-from-scratch markdown twin](/tools/rohitg00-ai-engineering-from-scratch/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/raga-ai-hub-raga-llm-hub-vs-rohitg00-ai-engineering-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, raga-llm-hub or ai-engineering-from-scratch? raga-llm-hub: Dormant. ai-engineering-from-scratch: 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 raga-llm-hub and ai-engineering-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [raga-llm-hub trust report](/tools/raga-ai-hub-raga-llm-hub/trust); [ai-engineering-from-scratch trust report](/tools/rohitg00-ai-engineering-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=raga-ai-hub-raga-llm-hub`](/api/graphcanon/graph?tool=raga-ai-hub-raga-llm-hub) - 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/_