--- title: "raga-llm-hub vs awesome-LLM-resources" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/raga-ai-hub-raga-llm-hub-vs-wangrongsheng-awesome-llm-resources" tools: ["raga-ai-hub-raga-llm-hub", "wangrongsheng-awesome-llm-resources"] --- # raga-llm-hub vs awesome-LLM-resources *GraphCanon updated Aug 17, 2026* ## Verdict Pick raga-llm-hub if raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models; pick awesome-LLM-resources if awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a. [raga-llm-hub](https://www.raga.ai/llms) reports 114 GitHub stars, 14 forks, and 2 open issues, last pushed Sep 9, 2024. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 8.8k stars, 950 forks, and 23 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [raga-llm-hub's repository](https://github.com/raga-ai-hub/raga-llm-hub) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources). | | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Tagline | Framework for LLM evaluation, guardrails and security | Summary of the world's best LLM resources. | | Stars | 114 | 8,845 | | Forks | 14 | 950 | | Open issues | 2 | 23 | | Language | Python | - | | Adopt for | Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. | awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a | | Persona | - | - | | Runtime | - | - | | License | The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. | Apache-2.0 | | Categories | Evaluation & Observability | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 687d | 2d | | Open issues (now) | 2 | 23 | | Stars delta | Unknown | +142 (30d) | | Open issues delta | Unknown | -13 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/raga-ai-hub-raga-llm-hub/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | ## Decision facts: raga-llm-hub - **Pricing:** unknown - Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use. - **Requirements:** Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements. - **Adopt for:** Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. - **License detail:** The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. ## Decision facts: awesome-LLM-resources - **Adopt for:** awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a ## Choose when ### Choose raga-llm-hub if… - License: raga-llm-hub is Other, awesome-LLM-resources is Apache-2.0. - Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.. - Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.. - Tags unique to raga-llm-hub: guardrails, llm security, llm-evaluation, llmops. - When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment. ### Choose awesome-LLM-resources if… - License: awesome-LLM-resources is Apache-2.0, raga-llm-hub is Other. - Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models. - Also covers AI Agents, Developer Tools, Inference & Serving, LLM Frameworks, Model Training. - - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ## When NOT to use raga-llm-hub - If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. - Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects. ## When NOT to use awesome-LLM-resources - - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ## Common questions ### What is the difference between raga-llm-hub and awesome-LLM-resources? raga-llm-hub: Framework for LLM evaluation, guardrails and security. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories. ### When should I choose raga-llm-hub over awesome-LLM-resources? Choose raga-llm-hub over awesome-LLM-resources when License: raga-llm-hub is Other, awesome-LLM-resources is Apache-2.0; Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.; Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.; Tags unique to raga-llm-hub: guardrails, llm security, llm-evaluation, llmops; When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment. ### When should I choose awesome-LLM-resources over raga-llm-hub? Choose awesome-LLM-resources over raga-llm-hub when License: awesome-LLM-resources is Apache-2.0, raga-llm-hub is Other; Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Developer Tools, Inference & Serving, LLM Frameworks, Model Training; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ### When should I avoid raga-llm-hub? If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects. ### When should I avoid awesome-LLM-resources? - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ### Is raga-llm-hub or awesome-LLM-resources more popular on GitHub? awesome-LLM-resources has more GitHub stars (8,845 vs 114). Stars measure visibility, not whether either tool fits your constraints. ### Are raga-llm-hub and awesome-LLM-resources open source? Yes - both are open-source projects on GitHub (raga-llm-hub: Other, awesome-LLM-resources: Apache-2.0). ### Where can I find alternatives to raga-llm-hub or awesome-LLM-resources? GraphCanon lists graph-backed alternatives at [raga-llm-hub alternatives](/tools/raga-ai-hub-raga-llm-hub/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([raga-llm-hub markdown twin](/tools/raga-ai-hub-raga-llm-hub/alternatives.md), [awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/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-wangrongsheng-awesome-llm-resources.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 awesome-LLM-resources? raga-llm-hub: Dormant. awesome-LLM-resources: 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 raga-llm-hub and awesome-LLM-resources? 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); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/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/_