--- title: "ragflow vs JARVIS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/infiniflow-ragflow-vs-likhithsai2580-jarvis" tools: ["infiniflow-ragflow", "likhithsai2580-jarvis"] --- # ragflow vs JARVIS *GraphCanon updated Sep 20, 2026* ## Verdict Pick ragflow if rAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license; pick JARVIS if jARVIS is a Python-based AI assistant offering multifunctional capabilities including voice interaction and visual interfaces. [ragflow](https://ragflow.io) reports 91k GitHub stars, 11k forks, and 1.4k open issues, last pushed Sep 18, 2026. [JARVIS](https://github.com/Likhithsai2580/JARVIS) has 147 stars, 64 forks, and 2 open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [ragflow's repository](https://github.com/infiniflow/ragflow) and [JARVIS's repository](https://github.com/Likhithsai2580/JARVIS). | | [ragflow](/tools/infiniflow-ragflow.md) | [JARVIS](/tools/likhithsai2580-jarvis.md) | | --- | --- | --- | | Tagline | Retrieval-Augmented Generation (RAG) engine with agent capabilities | A versatile AI assistant that integrates various functionalities | | Stars | 90,923 | 147 | | Forks | 10,767 | 64 | | Open issues | 1,440 | 2 | | Language | Go | Python | | Adopt for | RAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license. | JARVIS is a Python-based AI assistant offering multifunctional capabilities including voice interaction and visual interfaces. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ragflow](/tools/infiniflow-ragflow.md) | [JARVIS](/tools/likhithsai2580-jarvis.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 51d | | Open issues (now) | 1.4k | 2 | | Stars delta | +4.4k (30d) | +4 (30d) | | Open issues delta | -553 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/infiniflow-ragflow/trust.md) | [trust report](/tools/likhithsai2580-jarvis/trust.md) | ## Decision facts: ragflow - **Adopt for:** RAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license. ## Decision facts: JARVIS - **Adopt for:** JARVIS is a Python-based AI assistant offering multifunctional capabilities including voice interaction and visual interfaces. ## Choose when ### Choose ragflow if… - ragflow is primarily Go; JARVIS is Python. - License: ragflow is Apache-2.0, JARVIS is MIT. - Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search. - ragflow ships Docker support for self-hosted deployment. - When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management. ### Choose JARVIS if… - JARVIS is primarily Python; ragflow is Go. - License: JARVIS is MIT, ragflow is Apache-2.0. - Tags unique to JARVIS: agent, agents, assistant, g4f. - Also covers Speech & Audio. - Use JARVIS if you require an offline-capable AI assistant with local LLM support, enhancing privacy and reducing reliance on cloud services. ## When NOT to use ragflow - If your project does not require integration with external LLM and embedding services, as RAGFlow relies on these services. - If you are looking for a lightweight solution, as RAGFlow's Docker image is approximately 2 GB in size. - When you prefer tools that do not require building a Docker image, as RAGFlow's setup involves creating a Docker image. ## When NOT to use JARVIS - Avoid using JARVIS if you need a solution that strictly operates in an online environment; it is better suited for scenarios where both offline and online modes are acceptable. - Do not use JARVIS if your project requires highly specialized functionality that the multifunctional design of JARVIS cannot support with its current integrations. ## Common questions ### What is the difference between ragflow and JARVIS? ragflow: Retrieval-Augmented Generation (RAG) engine with agent capabilities. JARVIS: A versatile AI assistant that integrates various functionalities. See the comparison table for live GitHub stats and shared categories. ### When should I choose ragflow over JARVIS? Choose ragflow over JARVIS when ragflow is primarily Go; JARVIS is Python; License: ragflow is Apache-2.0, JARVIS is MIT; Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search; ragflow ships Docker support for self-hosted deployment; When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management. ### When should I choose JARVIS over ragflow? Choose JARVIS over ragflow when JARVIS is primarily Python; ragflow is Go; License: JARVIS is MIT, ragflow is Apache-2.0; Tags unique to JARVIS: agent, agents, assistant, g4f; Also covers Speech & Audio; Use JARVIS if you require an offline-capable AI assistant with local LLM support, enhancing privacy and reducing reliance on cloud services. ### When should I avoid ragflow? If your project does not require integration with external LLM and embedding services, as RAGFlow relies on these services. If you are looking for a lightweight solution, as RAGFlow's Docker image is approximately 2 GB in size. When you prefer tools that do not require building a Docker image, as RAGFlow's setup involves creating a Docker image. ### When should I avoid JARVIS? Avoid using JARVIS if you need a solution that strictly operates in an online environment; it is better suited for scenarios where both offline and online modes are acceptable. Do not use JARVIS if your project requires highly specialized functionality that the multifunctional design of JARVIS cannot support with its current integrations. ### Is ragflow or JARVIS more popular on GitHub? ragflow has more GitHub stars (90,923 vs 147). Stars measure visibility, not whether either tool fits your constraints. ### Are ragflow and JARVIS open source? Yes - both are open-source projects on GitHub (ragflow: Apache-2.0, JARVIS: MIT). ### Where can I find alternatives to ragflow or JARVIS? GraphCanon lists graph-backed alternatives at [ragflow alternatives](/tools/infiniflow-ragflow/alternatives) and [JARVIS alternatives](/tools/likhithsai2580-jarvis/alternatives) ([ragflow markdown twin](/tools/infiniflow-ragflow/alternatives.md), [JARVIS markdown twin](/tools/likhithsai2580-jarvis/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/infiniflow-ragflow-vs-likhithsai2580-jarvis.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ragflow or JARVIS? ragflow: Very active. JARVIS: 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 ragflow and JARVIS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ragflow trust report](/tools/infiniflow-ragflow/trust); [JARVIS trust report](/tools/likhithsai2580-jarvis/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=infiniflow-ragflow`](/api/graphcanon/graph?tool=infiniflow-ragflow) - 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/_