README.md

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    What is Milvus

    As an open source vector similarity search engine, Milvus is easy-to-use, highly reliable, scalable, robust, and blazing fast. Adopted by over 100 organizations and institutions worldwide, Milvus empowers applications in a variety of fields, including image processing, computer vision, natural language processing, voice recognition, recommender systems, drug discovery, and more.

    The following is Milvus architecture:

    arch For more detailed introduction of Milvus and its architecture, see Milvus overview. See Milvus release notes to keep up-to-date with its releases and updates.

    Milvus is an LF AI Foundation incubation project.

    Get started

    Install Milvus

    See Milvus install guide to install Milvus using Docker. To install Milvus from source code, see build from source.

    Try example programs

    Try an example program with Milvus using Python, Java, Go, or C++ example code.

    Supported clients

    Application scenarios

    You can use Milvus to build intelligent systems in a variety of AI application scenarios. See Milvus Scenarios for live demos. You can also see Milvus Bootcamp for detailed solutions and application scenarios.

    Benchmark

    See our test reports for more information about performance benchmarking of different indexes in Milvus.

    Roadmap

    To learn what's coming up soon in Milvus, read our Roadmap.

    It is a Work in Progress, and is subject to reasonable adjustments when necessary. And we greatly appreciate any comments/requirements/suggestions regarding Milvus' roadmap.👏

    Contribution guidelines

    Contributions are welcomed and greatly appreciated. Please read our contribution guidelines for detailed contribution workflow. This project adheres to the code of conduct of Milvus. You must abide by this code in order to participate.

    We use GitHub issues to track issues and bugs. For general questions and public discussions, please join our community.

    Join us for Hacktoberfest

    Hacktoberfestlogo

    :octocat: Happy Hacktober! Let’s do something great one Pull Request at a time! In the whole October you can contribute to the open source project and get some cool T-shirts/swags. Milvus community is happy to join and celebrate open source by preparing our own swags for you to claim.

    💡 What is Hacktoberfest

    Hacktoberfest is a month-long celebration of open source software in partnership with Github. Learn more: Hacktoberfest

    How to participate

    • Hacktoberfest is open to everyone in our global community. Whether you’re an experienced contributor or looking for projects to contribute to for the first time, you’re welcome to participate.
    • Pull requests can be made in any GitHub-hosted repositories/projects. As long as the project is public and GitHub-hosted, your pull requests will count toward your participation.
    • You can sign up anytime between October 1 and October 31. Just be sure to sign up on the official Hacktoberfest website for your pull requests to count.

    ️ Participation rule

    To get the swags you must make four pull requests (PRs) between October 1–31 in any time zone, any repo is welcome but we encourage you to look for issues tagged with Hacktoberfest. If a maintainer reports your pull request as spam, it will not be counted toward your participation in Hacktoberfest. If a maintainer reports behavior that’s not in line with the project’s code of conduct, you will be ineligible to participate.

    🎁 Milvus swags and how to claim them

    • At least 2 PRs (max 30 swags).
    • Swags include: Milvus T-shirt, stickers and USB cable.
    • You will get a form when you file a PR.

    Join our community

    :heart:To connect with other users and contributors, welcome to join our Slack channel.

    See our community repository to learn more about our governance and access more community resources.

    Resources

    License

    Apache License 2.0

    项目简介

    A cloud-native vector database, storage for next generation AI applications

    🚀 Github 镜像仓库 🚀

    源项目地址

    https://github.com/milvus-io/milvus

    发行版本 100

    milvus-2.3.0

    全部发行版

    贡献者 68

    全部贡献者

    开发语言

    • Go 66.9 %
    • Python 17.7 %
    • C++ 12.2 %
    • Shell 1.5 %
    • Groovy 0.9 %