--- title: "HippoRAG vs llm-applications" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/osu-nlp-group-hipporag-vs-ray-project-llm-applications" tools: ["osu-nlp-group-hipporag", "ray-project-llm-applications"] --- # HippoRAG vs llm-applications *GraphCanon updated Aug 24, 2026* ## Verdict Pick HippoRAG if hippoRAG is a RAG framework that leverages Knowledge Graphs and Personalized PageRank for improved information retrieval from external documents; pick llm-applications if the llm-applications repository offers focused guidance on deploying RAG-based LLM apps in production environments with an emphasis on using Ray. [HippoRAG](https://arxiv.org/abs/2405.14831) reports 3.9k GitHub stars, 416 forks, and 7 open issues, last pushed Jul 29, 2026. [llm-applications](https://github.com/ray-project/llm-applications) has 1.9k stars, 256 forks, and 13 open issues, last pushed Aug 15, 2026. Figures are from public GitHub metadata via [HippoRAG's repository](https://github.com/OSU-NLP-Group/HippoRAG) and [llm-applications's repository](https://github.com/ray-project/llm-applications). | | [HippoRAG](/tools/osu-nlp-group-hipporag.md) | [llm-applications](/tools/ray-project-llm-applications.md) | | --- | --- | --- | | Tagline | HippoRAG is a RAG framework enabling LLMs to continuously integrate knowledge from external documents. | Comprehensive guide to building RAG-based LLM applications for production | | Stars | 3,902 | 1,855 | | Forks | 416 | 256 | | Open issues | 7 | 13 | | Language | Python | Jupyter Notebook | | Adopt for | HippoRAG is a RAG framework that leverages Knowledge Graphs and Personalized PageRank for improved information retrieval from external documents. | The llm-applications repository offers focused guidance on deploying RAG-based LLM apps in production environments with an emphasis on using Ray. | | Persona | - | - | | Runtime | - | - | | License | MIT | CC-BY-4.0 | | Categories | LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [HippoRAG](/tools/osu-nlp-group-hipporag.md) | [llm-applications](/tools/ray-project-llm-applications.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 3d | 8d | | Open issues (now) | 7 | 13 | | Stars delta | Unknown | -2 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/osu-nlp-group-hipporag/trust.md) | [trust report](/tools/ray-project-llm-applications/trust.md) | ## Shared compatibility - **OpenAI API**: [HippoRAG](/tools/osu-nlp-group-hipporag.md) - OpenAI API; [llm-applications](/tools/ray-project-llm-applications.md) - OpenAI API - **Python**: [HippoRAG](/tools/osu-nlp-group-hipporag.md) - Python runtime; [llm-applications](/tools/ray-project-llm-applications.md) - Python runtime ## Decision facts: HippoRAG - **Adopt for:** HippoRAG is a RAG framework that leverages Knowledge Graphs and Personalized PageRank for improved information retrieval from external documents. ## Decision facts: llm-applications - **Adopt for:** The llm-applications repository offers focused guidance on deploying RAG-based LLM apps in production environments with an emphasis on using Ray. ## Choose when ### Choose HippoRAG if… - HippoRAG is primarily Python; llm-applications is Jupyter Notebook. - License: HippoRAG is MIT, llm-applications is CC-BY-4.0. - Tags unique to HippoRAG: knowledge graphs, knowledge integration, language-models, personalized pagerank. - Also covers Model Training. - When integrating human-like long-term memory capabilities into LLM models to handle vast amounts of external knowledge ### Choose llm-applications if… - llm-applications is primarily Jupyter Notebook; HippoRAG is Python. - License: llm-applications is CC-BY-4.0, HippoRAG is MIT. - Tags unique to llm-applications: anyscale, fine-tuning, llama2, machin-learning. - Also covers Inference & Serving. - You require a detailed guide specifically tailored to the development and deployment of RAG-based applications, leveraging Ray for performance and scalability. ## When NOT to use HippoRAG - If your application does not require continuous integration of external documents or personalized information retrieval - For simpler applications where standard RAG frameworks without KG Personalized PageRank suffice for performance requirements ## When NOT to use llm-applications - If you are looking for a more generalized approach to LLM application development that does not specifically cater to RAG-based designs and Ray optimizations. - When your project workflow is incompatible with or cannot support Jupyter Notebook dependencies and the resources assume. ## Common questions ### What is the difference between HippoRAG and llm-applications? HippoRAG: HippoRAG is a RAG framework enabling LLMs to continuously integrate knowledge from external documents.. llm-applications: Comprehensive guide to building RAG-based LLM applications for production. See the comparison table for live GitHub stats and shared categories. ### When should I choose HippoRAG over llm-applications? Choose HippoRAG over llm-applications when HippoRAG is primarily Python; llm-applications is Jupyter Notebook; License: HippoRAG is MIT, llm-applications is CC-BY-4.0; Tags unique to HippoRAG: knowledge graphs, knowledge integration, language-models, personalized pagerank; Also covers Model Training; When integrating human-like long-term memory capabilities into LLM models to handle vast amounts of external knowledge. ### When should I choose llm-applications over HippoRAG? Choose llm-applications over HippoRAG when llm-applications is primarily Jupyter Notebook; HippoRAG is Python; License: llm-applications is CC-BY-4.0, HippoRAG is MIT; Tags unique to llm-applications: anyscale, fine-tuning, llama2, machin-learning; Also covers Inference & Serving; You require a detailed guide specifically tailored to the development and deployment of RAG-based applications, leveraging Ray for performance and scalability. ### When should I avoid HippoRAG? If your application does not require continuous integration of external documents or personalized information retrieval For simpler applications where standard RAG frameworks without KG Personalized PageRank suffice for performance requirements ### When should I avoid llm-applications? If you are looking for a more generalized approach to LLM application development that does not specifically cater to RAG-based designs and Ray optimizations. When your project workflow is incompatible with or cannot support Jupyter Notebook dependencies and the resources assume. ### Is HippoRAG or llm-applications more popular on GitHub? HippoRAG has more GitHub stars (3,902 vs 1,855). Stars measure visibility, not whether either tool fits your constraints. ### Are HippoRAG and llm-applications open source? Yes - both are open-source projects on GitHub (HippoRAG: MIT, llm-applications: CC-BY-4.0). ### Where can I find alternatives to HippoRAG or llm-applications? GraphCanon lists graph-backed alternatives at [HippoRAG alternatives](/tools/osu-nlp-group-hipporag/alternatives) and [llm-applications alternatives](/tools/ray-project-llm-applications/alternatives) ([HippoRAG markdown twin](/tools/osu-nlp-group-hipporag/alternatives.md), [llm-applications markdown twin](/tools/ray-project-llm-applications/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/osu-nlp-group-hipporag-vs-ray-project-llm-applications.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, HippoRAG or llm-applications? HippoRAG: Very active. llm-applications: 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 HippoRAG and llm-applications? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [HippoRAG trust report](/tools/osu-nlp-group-hipporag/trust); [llm-applications trust report](/tools/ray-project-llm-applications/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=osu-nlp-group-hipporag`](/api/graphcanon/graph?tool=osu-nlp-group-hipporag) - 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/_