Milvus 3.0 新增 StructArray，一个实体可存多个向量，视频搜索、文档检索更精准。
Milvus 3.0 发布 StructArray 功能，允许在单个实体内存储多个元素。每个元素可包含向量和元数据，支持视频片段、多图像产品文档等场景。新功能提供元素级搜索和 EmbeddingList 搜索，适用于 ColBERT、ColPali 和智能体记忆等应用。
One entity doesn’t always mean one vector. A video has clips. A product has multiple images. A docu...
One entity doesn’t always mean one vector. A video has clips. A product has multiple images. A document has passages. Compressing them into a single embedding can hide the exact details users need. 𝗠𝗶𝗹𝘃𝘂𝘀 𝟯.𝟬 𝗦𝘁𝗿𝘂𝗰𝘁𝗔𝗿𝗿𝗮𝘆 lets you store those elements inside the parent entity, with a vector and metadata for each one. 𝗛𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝗶𝘁: 1. Create an ARRAY<STRUCT> field for the clips, images, or passages. 2. Add vector and scalar subfields such as embedding, caption, and confidence. 3. Use element-level search to find a specific element and return its parent ID plus offset. 4. Use EmbeddingList search when both the query and entity contain multiple vectors. 5. Apply MATCH_* or element_filter to ensure vector and metadata conditions match the same element. Useful for video search, multi-image product search, document retrieval, ColBERT, ColPali, and agent memory. See the sc milvus.io/blog/milvus-3-… les: https://t.co/bXZuMAsX6Q 💬 0 🔄 0 ❤️ 0 👀 71 ⚡