--- title: "Lumos vs RAGLight" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/andrewnguonly-lumos-vs-bessouat40-raglight" tools: ["andrewnguonly-lumos", "bessouat40-raglight"] --- # Lumos vs RAGLight *GraphCanon updated Aug 22, 2026* ## Verdict Pick Lumos if lumos is a RAG LLM co-pilot that operates within Chrome and leverages local language models to support web browsing with automation; pick RAGLight if rAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP. [Lumos](https://github.com/andrewnguonly/Lumos) reports 1.5k GitHub stars, 112 forks, and 24 open issues, last pushed Jan 26, 2025. [RAGLight](https://raglight.mintlify.app/) has 670 stars, 101 forks, and 12 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [Lumos's repository](https://github.com/andrewnguonly/Lumos) and [RAGLight's repository](https://github.com/Bessouat40/RAGLight). | | [Lumos](/tools/andrewnguonly-lumos.md) | [RAGLight](/tools/bessouat40-raglight.md) | | --- | --- | --- | | Tagline | A RAG LLM co-pilot for browsing the web | A modular framework for Retrieval-Augmented Generation that supports integration with various LLMs and external tools. | | Stars | 1,516 | 670 | | Forks | 112 | 101 | | Open issues | 24 | 12 | | Language | TypeScript | Python | | Adopt for | Lumos is a RAG LLM co-pilot that operates within Chrome and leverages local language models to support web browsing with automation. | RAGLight emerges as an adaptable framework for Retrieval-Augmented Generation, offering integration flexibility with multiple LLMs and external tools through MCP. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Data & Retrieval, LLM Frameworks | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Lumos](/tools/andrewnguonly-lumos.md) | [RAGLight](/tools/bessouat40-raglight.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 564d | 57d | | Open issues (now) | 24 | 12 | | Stars delta | +1 (30d) | 0 (30d) | | Full report | [trust report](/tools/andrewnguonly-lumos/trust.md) | [trust report](/tools/bessouat40-raglight/trust.md) | ## Decision facts: Lumos - **Requirements:** Ensure that your environment supports Docker to run the Ollama server as required for Lumos operation.; Your development workflow should be prepared to integrate a Chrome extension, considering you need to load unpacked extensions into Chrome. - **Adopt for:** Lumos is a RAG LLM co-pilot that operates within Chrome and leverages local language models to support web browsing with automation. - **License detail:** MIT ## 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. ## Choose when ### Choose Lumos if… - Lumos is primarily TypeScript; RAGLight is Python. - Requirements: Ensure that your environment supports Docker to run the Ollama server as required for Lumos operation.; Your development workflow should be prepared to integrate a Chrome extension, considering you need to load unpacked extensions into Chrome.. - Tags unique to Lumos: chrome-extension, langchain, langchain-js, llm. - Also covers LLM Frameworks. - Use Lumos when your task involves heavy web navigation and requires interaction with the latest local machine learning models directly from a browser. ### Choose RAGLight if… - RAGLight is primarily Python; Lumos is TypeScript. - 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 NOT to use Lumos - Avoid using Lumos when your primary task does not involve browsing the web or requires a standalone application interface that does not need browser augmentation. - Do not use this tool if you are looking for support in languages other than TypeScript, as it is specifically built around this language. ## 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. ## Common questions ### What is the difference between Lumos and RAGLight? Lumos: A RAG LLM co-pilot for browsing the web. RAGLight: A modular framework for Retrieval-Augmented Generation that supports integration with various LLMs and external tools.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Lumos over RAGLight? Choose Lumos over RAGLight when Lumos is primarily TypeScript; RAGLight is Python; Requirements: Ensure that your environment supports Docker to run the Ollama server as required for Lumos operation.; Your development workflow should be prepared to integrate a Chrome extension, considering you need to load unpacked extensions into Chrome.; Tags unique to Lumos: chrome-extension, langchain, langchain-js, llm; Also covers LLM Frameworks; Use Lumos when your task involves heavy web navigation and requires interaction with the latest local machine learning models directly from a browser. ### When should I choose RAGLight over Lumos? Choose RAGLight over Lumos when RAGLight is primarily Python; Lumos is TypeScript; 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 avoid Lumos? Avoid using Lumos when your primary task does not involve browsing the web or requires a standalone application interface that does not need browser augmentation. Do not use this tool if you are looking for support in languages other than TypeScript, as it is specifically built around this language. ### 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. ### Is Lumos or RAGLight more popular on GitHub? Lumos has more GitHub stars (1,516 vs 670). Stars measure visibility, not whether either tool fits your constraints. ### Are Lumos and RAGLight open source? Yes - both are open-source projects on GitHub (Lumos: MIT, RAGLight: MIT). ### Where can I find alternatives to Lumos or RAGLight? GraphCanon lists graph-backed alternatives at [Lumos alternatives](/tools/andrewnguonly-lumos/alternatives) and [RAGLight alternatives](/tools/bessouat40-raglight/alternatives) ([Lumos markdown twin](/tools/andrewnguonly-lumos/alternatives.md), [RAGLight markdown twin](/tools/bessouat40-raglight/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/andrewnguonly-lumos-vs-bessouat40-raglight.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Lumos or RAGLight? Lumos: Dormant. RAGLight: Steady. 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 Lumos and RAGLight? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Lumos trust report](/tools/andrewnguonly-lumos/trust); [RAGLight trust report](/tools/bessouat40-raglight/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=andrewnguonly-lumos`](/api/graphcanon/graph?tool=andrewnguonly-lumos) - 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/_