--- title: "RAGLight vs HippoRAG" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bessouat40-raglight-vs-osu-nlp-group-hipporag" tools: ["bessouat40-raglight", "osu-nlp-group-hipporag"] --- # RAGLight vs HippoRAG *GraphCanon updated Sep 20, 2026* ## Verdict Pick RAGLight if rAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP; pick HippoRAG if hippoRAG is a RAG framework that integrates knowledge from external documents into LLMs, inspired by human long-term memory, and supports personalized page rank and knowledge graphs. [RAGLight](https://raglight.mintlify.app/) reports 673 GitHub stars, 102 forks, and 22 open issues, last pushed Sep 2, 2026. [HippoRAG](https://arxiv.org/abs/2405.14831) has 4.0k stars, 428 forks, and 9 open issues, last pushed Sep 3, 2026. Figures are from public GitHub metadata via [RAGLight's repository](https://github.com/Bessouat40/RAGLight) and [HippoRAG's repository](https://github.com/OSU-NLP-Group/HippoRAG). | | [RAGLight](/tools/bessouat40-raglight.md) | [HippoRAG](/tools/osu-nlp-group-hipporag.md) | | --- | --- | --- | | Tagline | A modular framework for Retrieval-Augmented Generation that supports integration with various LLMs and external tools. | A RAG framework enabling LLMs to integrate knowledge from external documents | | Stars | 673 | 4,012 | | Forks | 102 | 428 | | Open issues | 22 | 9 | | Language | Python | Python | | Adopt for | RAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP. | HippoRAG is a RAG framework that integrates knowledge from external documents into LLMs, inspired by human long-term memory, and supports personalized page rank and knowledge graphs. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Data & Retrieval | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [RAGLight](/tools/bessouat40-raglight.md) | [HippoRAG](/tools/osu-nlp-group-hipporag.md) | | --- | --- | --- | | Days since push | 17d | 14d | | Open issues (now) | 22 | 9 | | Stars delta | +3 (30d) | +110 (30d) | | Open issues delta | +10 (30d) | +2 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/bessouat40-raglight/trust.md) | [trust report](/tools/osu-nlp-group-hipporag/trust.md) | ## Decision facts: RAGLight - **Adopt for:** RAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP. ## Decision facts: HippoRAG - **Requirements:** Ensure you have Python 3.10 installed.; Set environment variables such as `CUDA_VISIBLE_DEVICES`, `HF_HOME`, and `OPENAI_API_KEY` as needed.; Install HippoRAG using Conda or `uv` for a project-local environment. - **Adopt for:** HippoRAG is a RAG framework that integrates knowledge from external documents into LLMs, inspired by human long-term memory, and supports personalized page rank and knowledge graphs. ## Choose when ### Choose RAGLight if… - Tags unique to RAGLight: agentic-ai, data-science, framework, huggingface. - Also covers AI Agents. - When you require seamless integration with various Language Models (LLMs) like Hugging Face or OpenAI models, making RAGLight a suitable choice for diverse model environments. ### Choose HippoRAG if… - Requirements: Ensure you have Python 3.10 installed.; Set environment variables such as `CUDA_VISIBLE_DEVICES`, `HF_HOME`, and `OPENAI_API_KEY` as needed.; Install HippoRAG using Conda or `uv` for a project-local environment.. - Tags unique to HippoRAG: external documents, knowledge graphs, knowledge integration, llms. - Also covers LLM Frameworks. - When you need a framework that integrates knowledge from external documents into LLMs in a manner inspired by human long-term memory. ## When NOT to use RAGLight - Avoid using RAGLight if your workflow strictly demands proprietary integration methods that are not supported by its modular framework structure. - If the project focuses on a specific LLM without the need for flexibility or interchangeability, the overhead of configuring diverse integrations in RAGLight might be unnecessary. ## When NOT to use HippoRAG - If your project does not require the integration of knowledge from external documents into LLMs in a manner inspired by human long-term memory. - When personalized page rank and knowledge graphs are not necessary for your project's knowledge retrieval and integration needs. - If you are not using Python 3.10 or do not wish to manage a project-local environment with Conda or `uv`. ## Common questions ### What is the difference between RAGLight and HippoRAG? RAGLight: A modular framework for Retrieval-Augmented Generation that supports integration with various LLMs and external tools.. HippoRAG: A RAG framework enabling LLMs to integrate knowledge from external documents. See the comparison table for live GitHub stats and shared categories. ### When should I choose RAGLight over HippoRAG? Choose RAGLight over HippoRAG when Tags unique to RAGLight: agentic-ai, data-science, framework, huggingface; Also covers AI Agents; When you require seamless integration with various Language Models (LLMs) like Hugging Face or OpenAI models, making RAGLight a suitable choice for diverse model environments. ### When should I choose HippoRAG over RAGLight? Choose HippoRAG over RAGLight when Requirements: Ensure you have Python 3.10 installed.; Set environment variables such as `CUDA_VISIBLE_DEVICES`, `HF_HOME`, and `OPENAI_API_KEY` as needed.; Install HippoRAG using Conda or `uv` for a project-local environment.; Tags unique to HippoRAG: external documents, knowledge graphs, knowledge integration, llms; Also covers LLM Frameworks; When you need a framework that integrates knowledge from external documents into LLMs in a manner inspired by human long-term memory. ### When should I avoid RAGLight? Avoid using RAGLight if your workflow strictly demands proprietary integration methods that are not supported by its modular framework structure. If the project focuses on a specific LLM without the need for flexibility or interchangeability, the overhead of configuring diverse integrations in RAGLight might be unnecessary. ### When should I avoid HippoRAG? If your project does not require the integration of knowledge from external documents into LLMs in a manner inspired by human long-term memory. When personalized page rank and knowledge graphs are not necessary for your project's knowledge retrieval and integration needs. If you are not using Python 3.10 or do not wish to manage a project-local environment with Conda or `uv`. ### Is RAGLight or HippoRAG more popular on GitHub? HippoRAG has more GitHub stars (4,012 vs 673). Stars measure visibility, not whether either tool fits your constraints. ### Are RAGLight and HippoRAG open source? Yes - both are open-source projects on GitHub (RAGLight: MIT, HippoRAG: MIT). ### Where can I find alternatives to RAGLight or HippoRAG? GraphCanon lists graph-backed alternatives at [RAGLight alternatives](/tools/bessouat40-raglight/alternatives) and [HippoRAG alternatives](/tools/osu-nlp-group-hipporag/alternatives) ([RAGLight markdown twin](/tools/bessouat40-raglight/alternatives.md), [HippoRAG markdown twin](/tools/osu-nlp-group-hipporag/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/bessouat40-raglight-vs-osu-nlp-group-hipporag.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, RAGLight or HippoRAG? RAGLight: Active. HippoRAG: 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 RAGLight and HippoRAG? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [RAGLight trust report](/tools/bessouat40-raglight/trust); [HippoRAG trust report](/tools/osu-nlp-group-hipporag/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bessouat40-raglight`](/api/graphcanon/graph?tool=bessouat40-raglight) - 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/_