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等多种索引，从内存到磁盘可伸缩。除向量检索外还内置关键词全文检索，可把向量相似度、全文检索和结构化过滤融合在同一条查询里。\u003C\u002Fp>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>项目\u003C\u002Fth>\n\u003Cth>内容\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Fthead>\n\u003Ctbody>\u003Ctr>\n\u003Ctd>语言\u003C\u002Ftd>\n\u003Ctd>C++（Python \u002F Node.js \u002F Go \u002F Rust \u002F Dart SDK）\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>平台\u003C\u002Ftd>\n\u003Ctd>Linux、macOS、Windows，另有 Android \u002F iOS SDK\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>索引\u003C\u002Ftd>\n\u003Ctd>HNSW、DiskANN、IVF-RaBitQ 等\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>许可\u003C\u002Ftd>\n\u003Ctd>Apache-2.0\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\u003C\u002Ftable>\n\u003Cblockquote>\n\u003Cp>嵌入即用的向量检索：纯本地、无服务、无配置。\u003C\u002Fp>\n\u003C\u002Fblockquote>\n\u003Ch2 id=\"主要功能\">主要功能\u003C\u002Fh2>\u003Cul>\n\u003Cli>\u003Cstrong>毫秒级大规模检索\u003C\u002Fstrong>：面向数十亿向量优化，搜索延迟毫秒级\u003C\u002Fli>\n\u003Cli>\u003Cstrong>稠密与稀疏向量\u003C\u002Fstrong>：支持稠密、稀疏嵌入与多向量查询，索引类型从内存到磁盘可伸缩\u003C\u002Fli>\n\u003Cli>\u003Cstrong>全文检索\u003C\u002Fstrong>：原生关键词全文搜索，可用自然语言或结构化表达式查询字符串字段\u003C\u002Fli>\n\u003Cli>\u003Cstrong>混合查询\u003C\u002Fstrong>：向量相似度、全文检索、结构化过滤在一条查询中融合，结果更精准\u003C\u002Fli>\n\u003Cli>\u003Cstrong>持久化保障\u003C\u002Fstrong>：预写日志（WAL）保证进程崩溃或断电后数据不丢\u003C\u002Fli>\n\u003Cli>\u003Cstrong>并发读取\u003C\u002Fstrong>：多进程可同时读同一集合，写入单进程独占\u003C\u002Fli>\n\u003Cli>\u003Cstrong>随处运行\u003C\u002Fstrong>：作为进程内库，笔记本、服务器、CLI 工具甚至边缘设备都能跑\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"适用人群\">适用人群\u003C\u002Fh2>\u003Cul>\n\u003Cli>构建 RAG 与语义搜索的开发者\u003C\u002Fli>\n\u003Cli>LLM 应用与 Agent 记忆系统开发者\u003C\u002Fli>\n\u003Cli>需要本地嵌入式检索的工程师\u003C\u002Fli>\n\u003Cli>推荐系统与相似度搜索开发者\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"快速上手\">快速上手\u003C\u002Fh2>\u003Col>\n\u003Cli>安装 Python SDK：\u003Ccode>pip install zvec\u003C\u002Fcode>（需 64 位 Python 3.10-3.14）\u003C\u002Fli>\n\u003Cli>定义 schema 并创建集合，插入文档\u003C\u002Fli>\n\u003Cli>用向量执行相似度查询：\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Cdiv class=\"code-block\">\u003Cpre>\u003Ccode class=\"hljs language-python\">import zvec\n\nschema = zvec.CollectionSchema(\n    name='example',\n    vectors=zvec.VectorSchema('embedding', zvec.DataType.VECTOR_FP32, 4),\n)\ncollection = zvec.create_and_open(path='.\u002Fzvec_example', schema=schema)\ncollection.insert([\n    zvec.Doc(id='doc_1', vectors={'embedding': [0.1, 0.2, 0.3, 0.4]}),\n])\nresults = collection.query(\n    zvec.Query(field_name='embedding', vector=[0.4, 0.3, 0.3, 0.1]),\n    topk=10,\n)\u003C\u002Fcode>\u003C\u002Fpre>\u003C\u002Fdiv>\u003Col start=\"4\">\n\u003Cli>其他语言 SDK：Node.js 用 \u003Ccode>npm install @zvec\u002Fzvec\u003C\u002Fcode>，Go \u002F Rust \u002F Dart 参见官方文档\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Ch2 id=\"核心优势\">核心优势\u003C\u002Fh2>\u003Cul>\n\u003Cli>\u003Cstrong>零运维\u003C\u002Fstrong>：无服务、无配置，库直接嵌入应用随代码部署\u003C\u002Fli>\n\u003Cli>\u003Cstrong>生产级验证\u003C\u002Fstrong>：在阿里巴巴内部大规模场景长期使用\u003C\u002Fli>\n\u003Cli>\u003Cstrong>索引可伸缩\u003C\u002Fstrong>：从内存 HNSW 到磁盘 DiskANN，按数据规模选型\u003C\u002Fli>\n\u003Cli>\u003Cstrong>多语言生态\u003C\u002Fstrong>：Python、Node.js、Go、Rust、Dart\u002FFlutter 官方 SDK 全覆盖\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"系统要求\">系统要求\u003C\u002Fh2>\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>项目\u003C\u002Fth>\n\u003Cth>要求\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Fthead>\n\u003Ctbody>\u003Ctr>\n\u003Ctd>操作系统\u003C\u002Ftd>\n\u003Ctd>Linux（glibc\u002Fmusl）、macOS、Windows\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>支持架构\u003C\u002Ftd>\n\u003Ctd>x86_64、ARM64\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Python\u003C\u002Ftd>\n\u003Ctd>3.10 ~ 3.14（64 位）\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\u003C\u002Ftable>\n\u003Ch2 id=\"注意事项\">注意事项\u003C\u002Fh2>\u003Cul>\n\u003Cli>\u003Cstrong>写入单进程独占\u003C\u002Fstrong>：多进程并发只针对读，同一集合的写操作需单进程持有\u003C\u002Fli>\n\u003Cli>\u003Cstrong>源码构建\u003C\u002Fstrong>：本仓库为 C++ 核心，应用层一般通过各语言 SDK 使用，自行编译参见官方构建指南\u003C\u002Fli>\n\u003C\u002Ful>\n",1793248524008]