运行MongoDB Vector Search 查询

Overview

In this guide, you can learn how to use the MongoDB Vector Search feature in the Node.js driver.

You can use MongoDB Vector Search to perform a vector search on your data stored in Atlas. Vector search allows you to query your data based on semantic meaning rather than just keyword matches, which helps you retrieve more relevant search results. It enables your AI-powered applications to support use cases such as semantic search, hybrid search, and generative search, including Retrieval-Augmented Generation (RAG).

To learn more about MongoDB Vector Search, see the MongoDB Vector Search guides in the MongoDB Atlas documentation.

重要

功能兼容性

要了解哪些版本的 MongoDB Atlas 支持此功能，请参阅 MongoDB Atlas 文档中的限制。

执行向量搜索

To use this feature, you must create a vector search index and index your vector embeddings. To learn about how to programmatically create a vector search index, see the MongoDB Search and MongoDB Vector Search Indexes section in the Indexes guide. To learn more about vector embeddings, see How to Create Vector Embeddings in the Atlas documentation.

在您创建向量嵌入的向量搜索索引后，您可以在管道阶段引用此索引，如下例所示。

样本数据

本页上的示例展示了如何构建一个聚合管道，使用$vectorSearch阶段对sample_mflix.embedded_movies集合执行向量搜索，位于Atlas样本数据集中。

要学习；了解如何创建免费的MongoDB Atlas 群集并加载示例数据集，请参阅Atlas入门指南。

向量搜索示例

您可以使用聚合管道中的$vectorSearch 阶段执行向量搜索查询。要在集合上执行向量搜索，首先必须有一个包含向量嵌入的字段的集合，以及覆盖该字段的向量搜索索引。

在以下示例中，聚合管道在集合中每个文档的 plot 字段中搜索与术语“time travel”在语义上相关的文本。$vectorSearch 管道中的 queryVector 字段是您查询的向量表示。

const { MongoClient } = require("mongodb");
// Replace with the connection string to your Atlas cluster to connect
const uri = "<connection-string>";
const client = new MongoClient(uri);
async function run() {
    try {
        await client.connect();
        // Sets the namespace
        const database = client.db("sample_mflix");
        const coll = database.collection("embedded_movies");
        // Defines the pipeline
        const agg = [
            {
              '$vectorSearch': {
                'index': 'vector_index',
                'path': 'plot_embedding',
                'queryVector': Binary.fromFloat32Array(Float32Array.from([
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                ])),
                'numCandidates': 150,
                'limit': 10
              }
            }, {
              '$project': {
                '_id': 0,
                'plot': 1,
                'title': 1,
                'score': {
                  '$meta': 'vectorSearchScore'
                }
              }
            }
          ];
        // Runs pipeline
        const result = coll.aggregate(agg);
        // Prints results
        for await (const doc of result) {
            console.log(doc);
        }
    }   finally {
            await client.close();
    }
}
run().catch(console.dir);

{
   plot: 'A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.',
   title: 'Thrill Seekers',
   score: 0.9259490966796875
}
{
   plot: 'At the age of 21, Tim discovers he can travel in time and change what happens and has happened in his own life. His decision to make his world a better place by getting a girlfriend turns out not to be as easy as you might think.',
   title: 'About Time',
   score: 0.9253997802734375
}
{
   plot: 'An officer for a security agency that regulates time travel, must fend for his life against a shady politician who has a tie to his past.',
   title: 'Timecop',
   score: 0.922332763671875
}
{
   plot: "After using his mother's newly built time machine, Dolf gets stuck
   involuntary in the year 1212. He ends up in a children's crusade where he confronts
   his new friends with modern techniques...",
   title: 'Crusade in Jeans',
   score: 0.92205810546875
}
{
   plot: 'Hoping to alter the events of the past, a 19th century inventor instead travels 800,000 years into the future, where he finds humankind divided into two warring races.',
   title: 'The Time Machine',
   score: 0.921875
}
{
   plot: 'A time-travel experiment in which a robot probe is sent from the year 2073 to the year 1973 goes terribly wrong thrusting one of the project scientists, a man named Nicholas Sinclair into a...',
   title: 'A.P.E.X.',
   score: 0.9202728271484375
}
{
   plot: "Agent J travels in time to M.I.B.'s early days in 1969 to stop an alien from assassinating his friend Agent K and changing history.",
   title: 'Men in Black 3',
   score: 0.9198150634765625
}
{
   plot: 'Bound by a shared destiny, a teen bursting with scientific curiosity and a former boy-genius inventor embark on a mission to unearth the secrets of a place somewhere in time and space that exists in their collective memory.',
   title: 'Tomorrowland',
   score: 0.91961669921875
}
{
   plot: 'A romantic drama about a Chicago librarian with a gene that causes him to involuntarily time travel, and the complications it creates for his marriage.',
   title: "The Time Traveler's Wife",
   score: 0.9174346923828125
}
{
   plot: 'With the help of his uncle, a man travels to the future to try and bring his girlfriend back to life.',
   title: 'Love Story 2050',
   score: 0.9165191650390625
}

此查询使用 $vectorSearch 阶段：

执行近似最近邻 (ANN) 向量搜索
在 plot_embedding 字段中搜索指定的术语
通过使用 numCandidates 选项，将搜索中使用的最近邻数设置为 150。
使用 limit 选项从查询中返回最多 10 个文档

它使用 $project 阶段：

在结果中仅包含电影 plot 和 title 字段
添加 score 字段，显示每个结果与搜索词的相关性