[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-4262":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":16,"forks30d":16,"starsTrendScore":19,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":10,"pushedAt":10,"updatedAt":38,"readmeContent":39,"aiSummary":40,"trendingCount":16,"starSnapshotCount":16,"syncStatus":41,"lastSyncTime":42,"discoverSource":43},4262,"vespa","vespa-engine\u002Fvespa","vespa-engine","The AI search platform","https:\u002F\u002Fvespa.ai",null,"Java",6958,718,163,220,0,15,49,7,39.57,"Apache License 2.0",false,"master",[25,26,27,28,29,30,31,32,33,34,35,36,37,5],"ai","big-data","java","machine-learning","rag","search","search-engine","server","serving-recommendation","tensor","vector","vector-database","vector-search","2026-06-12 02:01:01","\u003C!-- Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -->\n\n\u003Cpicture>\n  \u003Csource media=\"(prefers-color-scheme: dark)\" srcset=\"https:\u002F\u002Fassets.vespa.ai\u002Flogos\u002FVespa-logo-green-RGB.svg\">\n  \u003Csource media=\"(prefers-color-scheme: light)\" srcset=\"https:\u002F\u002Fassets.vespa.ai\u002Flogos\u002FVespa-logo-dark-RGB.svg\">\n  \u003Cimg alt=\"#Vespa\" width=\"200\" src=\"https:\u002F\u002Fassets.vespa.ai\u002Flogos\u002FVespa-logo-dark-RGB.svg\" style=\"margin-bottom: 25px;\">\n\u003C\u002Fpicture>\n\u003Cbr\u002F>\u003Cbr\u002F>\n\n[![Build status](https:\u002F\u002Fbadge.buildkite.com\u002F34f7cb35b91da4f929794c5fd7aa722fc15ca0224ad240270b.svg)](https:\u002F\u002Fbuildkite.com\u002Fvespaai\u002Fvespa-engine-vespa)\n![GitHub License](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fvespa-engine\u002Fvespa)\n![Maven metadata URL](https:\u002F\u002Fimg.shields.io\u002Fmaven-metadata\u002Fv?metadataUrl=https%3A%2F%2Frepo1.maven.org%2Fmaven2%2Fcom%2Fyahoo%2Fvespa%2Fparent%2Fmaven-metadata.xml)\n\n\n\nSearch, make inferences in and organize vectors, tensors, text and structured data, at serving time and any scale.\n\nThis repository contains all the code required to build and run all of Vespa yourself,\nand where you can see all development as it happens.\nAll the content in this repository is licensed under the Apache 2.0 license.\n\nA new release of Vespa is made from this repository's master branch every morning CET Monday through Thursday.\n\n- Home page: [https:\u002F\u002Fvespa.ai](https:\u002F\u002Fvespa.ai)\n- Documentation: [https:\u002F\u002Fdocs.vespa.ai](https:\u002F\u002Fdocs.vespa.ai)\n- Continuous build: [https:\u002F\u002Ffactory.vespa.ai](https:\u002F\u002Ffactory.vespa.ai)\n- Run applications in the cloud for free: [vespa.ai\u002Ffree-trial](https:\u002F\u002Fvespa.ai\u002Ffree-trial\u002F)\n\n## Table of contents\n\n- [Background](#background)\n- [Install](#install)\n- [Usage](#usage)\n- [Contribute](#contribute)\n- [Building](#building)\n- [License](#license)\n\n## Background\n\nUse cases such as search, recommendation and personalization need to select a subset of data in a large corpus,\nevaluate machine-learned models over the selected data, organize and aggregate it and return it, typically in less\nthan 100 milliseconds, all while the data corpus is continuously changing.\n\nThis is hard to do, especially with large data sets that need to be distributed over multiple nodes and evaluated in\nparallel. Vespa is a platform that performs these operations for you with high availability and performance.\nIt has been in development for many years and is used on several large internet services and apps which serve\nhundreds of thousands of queries from Vespa per second.\n\n## Install\n\nDeploy your Vespa applications to the cloud service: [console.vespa-cloud.com](https:\u002F\u002Fconsole.vespa-cloud.com\u002F),\nor run your own Vespa instance: [https:\u002F\u002Fdocs.vespa.ai\u002Fen\u002Fgetting-started.html](https:\u002F\u002Fdocs.vespa.ai\u002Fen\u002Fgetting-started.html)\n\n## Usage\n\n- The application created in the getting started guides linked above is fully functional and production-ready, but you may want to [add more nodes](https:\u002F\u002Fdocs.vespa.ai\u002Fen\u002Fmultinode-systems.html) for redundancy.\n- See [developing applications](https:\u002F\u002Fdocs.vespa.ai\u002Fen\u002Fdeveloper-guide.html) on adding your own Java components to your Vespa application.\n- [Vespa APIs](https:\u002F\u002Fdocs.vespa.ai\u002Fen\u002Fapi.html) is useful to understand how to interface with Vespa\n- Explore the [sample applications](https:\u002F\u002Fgithub.com\u002Fvespa-engine\u002Fsample-apps\u002Ftree\u002Fmaster)\n- Follow the [Vespa Blog](https:\u002F\u002Fblog.vespa.ai\u002F) for feature updates \u002F use cases\n- Join the [Vespa Slack community](https:\u002F\u002Fslack.vespa.ai\u002F) to ask questions and share feedback\n\nFull documentation is at [https:\u002F\u002Fdocs.vespa.ai](https:\u002F\u002Fdocs.vespa.ai).\n\n## Contribute\n\nWe welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) to learn how to contribute.\n\nIf you want to contribute to the documentation, see\n[https:\u002F\u002Fgithub.com\u002Fvespa-engine\u002Fdocumentation](https:\u002F\u002Fgithub.com\u002Fvespa-engine\u002Fdocumentation)\n\n## Building\n\nYou do not need to build Vespa to use it, but if you want to contribute you need to be able to build the code.\nThis section explains how to build and test Vespa. To understand where to make changes, see [Code-map.md](Code-map.md).\nSome suggested improvements with pointers to code are in [TODO.md](TODO.md).\n\n### Development environment\n\nC++ and Java building is supported on AlmaLinux 8.\nThe Java source can also be built on any platform having Java 17 and Maven 3.8+ installed.\nUse the following guide to set up a complete development environment using Docker\nfor building Vespa, running unit tests and running system tests:\n[Vespa development on AlmaLinux 8](https:\u002F\u002Fgithub.com\u002Fvespa-engine\u002Fdocker-image-dev#vespa-development-on-almalinux-8).\n\n#### Java environment for Mac\n1. Install [JDK17](https:\u002F\u002Fopenjdk.org\u002Fprojects\u002Fjdk\u002F17\u002F), \n   [Maven Version Manager](https:\u002F\u002Fbitbucket.org\u002Fmjensen\u002Fmvnvm\u002Fsrc\u002Fmaster\u002F) and [jEnv](https:\u002F\u002Fwww.jenv.be)\n   through [Homebrew](https:\u002F\u002Fbrew.sh\u002F).\n```sh\nbrew install jenv mvnvm openjdk@17\n```\n\n2. For the system Java wrappers to find this JDK, symlink it with\n```sh\nsudo ln -sfn \u002Fopt\u002Fhomebrew\u002Fopt\u002Fopenjdk@17\u002Flibexec\u002Fopenjdk.jdk \u002FLibrary\u002FJava\u002FJavaVirtualMachines\u002Fopenjdk-17.jdk\n```\n\n3. Follow \"Configure your shell\" in https:\u002F\u002Fwww.jenv.be. Configuration is shell specific. For `zsh` use the below commands:\n```sh\necho 'export PATH=\"$HOME\u002F.jenv\u002Fbin:$PATH\"' >> ~\u002F.zshrc\necho 'eval \"$(jenv init -)\"' >> ~\u002F.zshrc\neval \"$(jenv init -)\"\njenv enable-plugin export\nexec $SHELL -l\n```\n\n4. Add JDK17 to jEnv\n```sh\njenv add $(\u002Fusr\u002Flibexec\u002Fjava_home -v 17)\n```\n\n5. Verify configuration with Maven by executing below command in the root of the source code.\n   Output should refer to the JDK and Maven version specified in the [.java-version](.java-version) and [mvnvm.properties](mvnvm.properties).\n```sh\nmvn -v\n```\n\n### Build Java modules\n\n    export MAVEN_OPTS=\"-Xms128m -Xmx1024m\"\n    .\u002Fbootstrap.sh java\n    mvn install --threads 1C\n\nUse this if you only need to build the Java modules, otherwise follow the complete development guide above.\n\n### Run tests for shell scripts (on Mac)\nShell scripts are tested with [BATS](https:\u002F\u002Fbats-core.readthedocs.io\u002Fen\u002Fstable\u002F).\nTo run the tests locally, install the testing framework and its plugins.:\n```bash\nbrew install node\nsudo npm install -g bats bats-assert bats-support bats-mock\n```\nExport the `BATS_PLUGIN_PATH` environment variable to point to the global npm modules directory, which contains the BATS plugins:\n```bash\nexport BATS_PLUGIN_PATH=\"$(npm root -g)\"\n```\nThen run all tests with the following command (from the root of the repository):\n```bash\nbats -r .\n```\nTo run a specific test, use:\n```bash\nbats test_dir\u002Ftest_name.bats\n```\nTests can also be run in IntelliJ IDEA with the [BashSupport Pro](https:\u002F\u002Fplugins.jetbrains.com\u002Fplugin\u002F13841-bashsupport-pro)\nplugin. Ensure the `BATS_PLUGIN_PATH` environment variable is exported before launching the IDE\nto avoid setting it in each run configuration.\n\n## License\n\nCode licensed under the Apache 2.0 license. See [LICENSE](LICENSE) for terms.\n","Vespa 是一个用于在线处理大规模数据和AI任务的平台。它支持向量、张量、文本及结构化数据的搜索、推理与组织，能够在服务时以任何规模实时响应。Vespa 的核心技术特点包括高效的数据检索能力、强大的机器学习模型评估功能以及对不断变化的大数据集的良好支持。该平台适用于需要快速响应且能够处理大量并发查询的应用场景，如搜索引擎、推荐系统和个人化服务等。Vespa 采用Java开发，并遵循Apache License 2.0开源许可协议。",2,"2026-06-11 02:59:17","top_language"]