zylon-ai

    zylon-ai/private-gpt

    Complete API layer for private AI applications on local models: RAG, skills, tools, MCP, text-to-sql, and more. Works with any OpenAI-compatible inference server.

    llm
    ai
    ai-tools
    on-premise
    Python
    Apache-2.0
    57.6K stars
    7.6K forks
    57.6K GitHub watchers
    Updated Nov 4, 2026
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    Where it stands

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

    No releases in the last 90 days; the most recent was 138 days ago, with 109 contributors on GitHub.

    Gained 16% more stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Provides a complete API layer for building private AI applications using local models with retrieval augmented generation and OpenAI-compatible inference.
    • Ensures full data privacy by operating entirely offline with no data leaving the local execution environment.
    • Use for developing secure, on-premise AI chatbots that answer questions based on private document collections.
    • Use for implementing custom retrieval and embedding pipelines for sensitive data in healthcare or legal domains.
    • Use for integrating private text-to-SQL and AI skill tools into enterprise applications without exposing data externally.

    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

    PrivateGPT is a production-ready AI project that allows you to ask questions about your documents using the power of Large Language Models (LLMs), even in scenarios without an Internet connection. 100% private, no data leaves your execution environment at any point.

    The project provides an API offering all the primitives required to build private, context-aware AI applications. It follows and extends the OpenAI API standard, and supports both normal and streaming responses.

    The API is divided into two logical blocks:

    High-level API, which abstracts all the complexity of a RAG (Retrieval Augmented Generation) pipeline implementation:

    splitting, metadata extraction, embedding generation and storage.

    abstracting the retrieval of context, the prompt engineering and the response generation.

    Low-level API, which allows advanced users to implement their own complex pipelines:

    In addition to this, a working Gradio UI client is provided to test the API, together with a set of useful tools such as bulk model download script, ingestion script, documents folder watch, etc.

    Generative AI is a game changer for our society, but adoption in companies of all sizes and data-sensitive domains like healthcare or legal is limited by a clear concern: privacy. Not being able to ensure that your data is fully under your control when using third-party AI tools is a risk those industries cannot take.

    Excerpt from the zylon-ai/private-gpt 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

    Forks

    7.6K+18

    Open issues

    20+18

    Compared with peers in LLM

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

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