GStars
    infiniflow

    infiniflow/ragflow

    #90 this week

    RAGFlow is an agent-native database: a Retrieval-Augmented Generation (RAG) engine that grew into context infrastructure.

    llm
    agent-harness
    agent-native-database
    agentic-ai
    agentic-retrieval
    agentic-search
    Go
    Apache-2.0
    94.0K stars
    11.3K forks
    361 GitHub watchers
    Updated Nov 11, 2026
    View on GitHub

    Build with Backblaze B2

    SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.

    Explore Backblaze Labs

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    Ranks #5 among LLM repositories ranked this week, and #7 over the last 30 days; #90 of 163 repositories with measured growth this week (top 55%).

    This week's +526 stars is in line with its 30-day pace of about +450 per week.

    4 releases in the last 90 days, the latest 344 days ago, with 452 contributors on GitHub.

    Peaked at #14 in the weekly ranking the week of Oct 12, its best in the past year.

    Use Cases & Benefits

    • Implements a Retrieval-Augmented Generation engine combining RAG with Agent capabilities to enhance context for large language models.
    • Delivers a streamlined, configurable RAG workflow with deep document understanding and multi-format data compatibility for high-fidelity AI systems.
    • Use for building enterprise-grade AI systems that require precise knowledge extraction from complex, unstructured documents.
    • Use for integrating multi-modal data sources including images and scanned documents into LLM-powered applications.
    • Use for developing AI agents that perform advanced reasoning by combining internet search, code execution, and cross-language queries.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged context engine and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.

    Try our demo at https://demo.ragflow.io.

    Excerpt from the infiniflow/ragflow README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 14: +418Aug 15: +194Aug 16: +53Aug 17: +81Aug 18: +87Aug 19: +67Aug 20: +92Aug 27: +84Aug 28: +127Aug 29: +59Aug 30: +70Aug 31: +40Sep 1: +138Sep 2: +78Sep 3: +78Sep 4: +61Sep 5: +41Sep 6: +41Sep 7: +77Sep 8: +88Sep 9: +84Sep 10: +70Sep 11: +42Sep 22: +21Oct 10: +45Oct 11: +23Oct 29: +54Oct 30: +90Oct 31: +106Nov 1: +44Nov 2: +36Nov 3: +70Nov 4: +75Nov 5: +56Nov 6: +132Nov 7: +69Nov 8: +30Nov 9: +48Nov 10: +116Nov 11: +75

    +6,042 stars over 90 days across 47 snapshot days; best day +418 on Aug 14.

    Forks

    11.3K+950

    Open issues

    1.3K-611

    Compared with peers in LLM

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

    View category →
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    infiniflow/ragflow94.0K+52675344 days ago
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