Atlas Vector Search 快速入门

在此页面上

创建向量搜索索引

运行向量搜索查询
学习总结
后续步骤

本快速入门介绍了如何将包含矢量嵌入的样本文档加载到 Atlas 集群或本地 Atlas 部署中，在这些嵌入上创建 Atlas Vector Search 索引，然后执行语义搜索以返回与查询相似的文档。

所需时间：15 分钟

创建向量搜索索引

在本部分中，您将在加载到 Atlas 集群或本地计算机上托管的部署中的样本数据上创建 Atlas Vector Search 索引：

设置 Atlas 集群。

创建免费的 Atlas 帐户或登录现有帐户。
如果您还没有 Atlas 集群，请创建一个免费的 M 0集群。要了解有关创建 Atlas 集群的更多信息，请参阅创建集群。
注意
如果您使用的是现有集群，则必须对 Atlas 项目拥有 Project Data Access Admin或更高访问权限。
如果您创建新集群，则默认拥有必要的权限。
每个项目只能创建一个M0免费集群。
在左侧边栏中，单击Atlas Search 。从 Select data source菜单中选择您的集群，然后单击Go to Atlas Search 。
如果您尚未将示例数据集加载到集群，请单击Load a Sample Dataset 。在 Load Sample Dataset（加载样本数据集）对话框中，单击Load Sample Dataset （确认）进行确认。
如果已加载示例数据集，请检查sample_mflix数据库是否包含embedded_movies集合。如果没有，请删除示例数据库并重新加载示例数据集。
加载样本数据集可能需要几分钟时间才能完成。

创建 Vector Search 索引。

样本数据加载完成后，单击Create Search Index 。
在Atlas Vector Search部分下，选择JSON Editor并单击Next 。
在Database and Collection部分中，展开sample_mflix数据库并选择embedded_movies集合。
此集合中的每个文档都包含有关电影的信息，包括以字符串形式表示的电影情节摘要，该字符串也已转换为向量并存储为嵌入文档的plot_embedding 字段中。
在 Index Name 字段中指定 vector_index。

将以下向量搜索索引定义复制并粘贴到 JSON 编辑器中。

1 {
2   "fields": [{
3     "type": "vector",
4     "path": "plot_embedding",
5     "numDimensions": 1536,
6     "similarity": "dotProduct"
7   }]
8 }

该索引定义：

将plot_embedding字段索引为vector类型。该字段包含表示电影情节摘要的向量嵌入。
指定1536向量维度。
使用dotProduct相似度来衡量相似度。

单击 Next（连接）。
单击 Create Search Index（连接）。
构建索引大约需要一分钟时间。向量索引构建完成后， Status列显示为Active 。

安装依赖项。

安装Atlas CLI和MongoDB Database Tools。
如果您使用 Homebrew ，您可以在终端中运行以下命令：
```
brew install mongodb-atlas-cli
brew tap mongodb/brew && brew install mongodb-database-tools
```
安装 Docker。
- 对于 MacOS 或 Windows，请安装 Docker Desktop v4 。31 +。
- 对于 Linux，请安装 Docker Engine v27 。0 +。

有关详细说明，请参阅先决条件。

设置本地 Atlas 部署。

如果您没有 Atlas 帐户，请在终端中运行atlas setup或创建一个新帐户。
在终端中，运行atlas auth login以使用 Atlas 登录档案进行身份验证。要了解更多信息，请参阅从 Atlas CLI 连接。
运行atlas deployments setup并按照提示创建本地部署。当提示连接到部署时，选择skip 。
有关详细说明，请参阅创建本地 Atlas 部署。

加载示例数据。

在终端中运行以下命令以下载示例数据：
```
curl  https://atlas-education.s3.amazonaws.com/sampledata.archive -o sampledata.archive
```
运行以下命令，将数据加载到部署中，并将<port-number>替换为托管部署的端口：
```
mongorestore --archive=sampledata.archive --port=<port-number>
```

创建 Vector Search 索引。

创建一个文件，名为： vector-index.json

将以下索引定义复制并粘贴到 JSON文件中。

{
  "database": "sample_mflix",
  "collectionName": "embedded_movies",
  "type": "vectorSearch",
  "name": "vector_index",
    "fields": [
      {
        "type": "vector",
        "path": "plot_embedding",
        "numDimensions": 1536,
        "similarity": "dotProduct"
      }
    ]
}

该索引定义：

将plot_embedding字段索引为vector类型。该字段包含表示电影情节摘要的向量嵌入。
指定1536向量维度。
使用dotProduct相似度来衡量相似度。

保存文件，然后在终端中运行以下命令，将<path-to-file>替换为您创建的vector-index.json文件的路径。
```
atlas deployments search indexes create --file <path-to-file>
```

运行向量搜索查询

在本部分中，您将对索引嵌入运行样本向量搜索查询。

➤ 要设置用于运行本节中示例的客户端，请使用本页面右侧导航窗格中的选择语言下拉菜单。

单击“ Collections ”（集合）标签页，查看“Data Explorer”（数据浏览器）。

转到集合的Aggregation 标签页。

展开数据库列表下的sample_mflix ，然后从该数据库的collection列表中选择embedded_movies 。
单击sample_mflix.embedded_movies集合的Aggregation标签页。

构建并运行向量搜索查询。

在聚合管道窗格中，单击</> Text开关启用管道编辑的文本模式。
将以下示例查询复制并粘贴到文本编辑器中。
此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

1 [
2   {
3     "$vectorSearch": {
4       "index": "vector_index",
5       "path": "plot_embedding",
6       "queryVector": 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10   },
11   {
12     "$project": {
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14       "plot": 1,
15       "title": 1,
16       "score": { $meta: "vectorSearchScore" }
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1 {
2     "score": 0.9332506656646729,
3     "plot": "A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.",
4     "title": "Thrill Seekers"
5 }
6 {
7     "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.",
8     "title": "About Time",
9     "score": 0.9312690496444702
10 }
11 {
12     "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.",
13     "title": "The Time Machine",
14     "score": 0.929530143737793
15 }
16 {
17     "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...",
18     "title": "Crusade in Jeans",
19     "score": 0.9290417432785034
20 }
21 {
22     "title": "Timecop",
23     "score": 0.9283161759376526,
24     "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."
25 }
26 {
27     "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...",
28     "title": "A.P.E.X.",
29     "score": 0.9266218543052673
30 }
31 {
32     "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.",
33     "title": "Men in Black 3",
34     "score": 0.9258455038070679
35 }
36 {
37     "score": 0.9240515828132629,
38     "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.",
39     "title": "Tomorrowland"
40 }
41 {
42     "plot": "With the help of his uncle, a man travels to the future to try and bring his girlfriend back to life.",
43     "title": "Love Story 2050",
44     "score": 0.923175573348999
45 }
46 {
47     "plot": "A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...",
48     "title": "The Portal",
49     "score": 0.9228089451789856
50 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

Pipeline Output窗格会显示查询结果。

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

下载并安装`mongosh` 。

连接到中的集群或本地部署。`mongosh`

在终端窗口中打开mongosh并连接到您的 Atlas 集群。有关连接的详细说明，请参阅通过 mongosh 连接。

在终端窗口中，运行atlas deployments connect并按照提示通过mongosh连接到本地 Atlas 部署。有关连接的详细说明，请参阅管理本地 Atlas 部署。

切换到`sample_mflix` 数据库。

use sample_mflix

switched to db sample_mflix

构建并运行向量搜索查询。

将以下示例查询复制并粘贴到终端，然后使用mongosh运行。由于向量嵌入中的字符数量，当您粘贴查询时， mongosh可能会略有延迟。
此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

1 db.embedded_movies.aggregate([
2   {
3     "$vectorSearch": {
4       "index": "vector_index",
5       "path": "plot_embedding",
6       "queryVector": 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8       "limit": 10
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10   },
11   {
12     "$project": {
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16       "score": { $meta: "vectorSearchScore" }
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1 [
2   {
3     plot: 'A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.',
4     title: 'Thrill Seekers',
5     score: 0.9332506656646729
6   },
7   {
8     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.',
9     title: 'About Time',
10     score: 0.9312690496444702
11   },
12   {
13     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.',
14     title: 'The Time Machine',
15     score: 0.929530143737793
16   },
17   {
18     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...",
19     title: 'Crusade in Jeans',
20     score: 0.9290417432785034
21   },
22   {
23     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.',
24     title: 'Timecop',
25     score: 0.9283161759376526
26   },
27   {
28     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...',
29     title: 'A.P.E.X.',
30     score: 0.9266218543052673
31   },
32   {
33     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.",
34     title: 'Men in Black 3',
35     score: 0.9258455038070679
36   },
37   {
38     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.',
39     title: 'Tomorrowland',
40     score: 0.9240515828132629
41   },
42   {
43     plot: 'With the help of his uncle, a man travels to the future to try and bring his girlfriend back to life.',
44     title: 'Love Story 2050',
45     score: 0.923175573348999
46   },
47   {
48     plot: 'A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...',
49     title: 'The Portal',
50     score: 0.9228089451789856
51   }
52 ]

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

安装 MongoDB C 驱动程序。

有关详细的安装说明，请参阅MongoDB C 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建一个名为atlas-vector-search-quick-start.c的文件，并将以下示例查询复制并粘贴到该文件中：

1 #include <bson/bson.h>
2 #include <mongoc/mongoc.h>
3 #include <stdio.h>
4 
5 int main(void) {
6   
7     mongoc_client_t *client;
8     mongoc_collection_t *collection;
9     mongoc_cursor_t *cursor;
10     bson_array_builder_t *builder;
11     bson_t *pipeline;
12     bson_t query_vector;
13     bson_error_t error;
14     const bson_t *doc;
15     char *str;
16     
17     int arrSize = 1536; // This collection has a vector array of 1536 dimensions; depending on your vector embedding model, this mary vary
18     double embeddings[] = 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19 
20     // Initialize the MongoDB C Driver
21     mongoc_init();
22 
23     // Connect to your Atlas collection
24     client =  mongoc_client_new("<connection-string>");
25     collection = mongoc_client_get_collection (client, "sample_mflix", "embedded_movies");
26 
27     // Build query vector array
28     builder = bson_array_builder_new();
29     
30     for(int i = 0; i < arrSize; i++){
31         bson_array_builder_append_double(builder, embeddings[i]);
32     }
33 
34     bson_array_builder_build(builder, &query_vector);
35     bson_array_builder_destroy(builder);
36 
37     // Create aggregation pipeline for Vector Search
38     pipeline = BCON_NEW(
39         "pipeline",
40         "[",
41             "{",
42                 "$vectorSearch", "{", 
43                     "index", "vector_index", 
44                     "path", "plot_embedding", 
45                     "queryVector", BCON_ARRAY(&query_vector),
46                     "numCandidates", BCON_INT32(150), 
47                     "limit", BCON_INT32(10), 
48                 "}", 
49             "}",
50             "{",
51                 "$project", "{", 
52                     "title", BCON_BOOL(true),
53                     "plot", BCON_BOOL(true),
54                     "_id", BCON_BOOL(false),
55                     "score", "{",
56                         "$meta", "vectorSearchScore",
57                     "}",
58                 "}",
59             "}",
60         "]"
61     );
62 
63     // Run query
64     cursor = mongoc_collection_aggregate(collection, MONGOC_QUERY_NONE, pipeline, NULL, NULL );
65   
66     // Print results
67     while (mongoc_cursor_next (cursor, &doc)) {
68         str = bson_as_canonical_extended_json (doc, NULL);
69         printf ("%s\n", str);
70         bson_free (str);
71     }
72 
73     // Cleanup
74     bson_destroy(pipeline);
75     mongoc_cursor_destroy(cursor);
76     mongoc_collection_destroy(collection);
77     mongoc_client_destroy(client);
78     mongoc_cleanup();
79 
80     return 0;
81 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

为您的项目配置 CMake。

在项目目录中，创建一个名为CMakeLists.txt的文件并将以下代码复制到该文件中。

cmake_minimum_required(VERSION 3.30)
project(atlas-vector-search-quick-start)
# Specify the minimum version you require.
find_package (mongoc-1.0 1.27.6 REQUIRED)
add_executable(atlas-vector-search-quick-start
  atlas-vector-search-quick-start.c
)
# The "atlas-vector-search-quick-start.c" sample program is shared among four tests.
target_link_libraries (atlas-vector-search-quick-start PRIVATE mongo::mongoc_shared)

在项目文件夹中创建一个名为build的目录。
```
mkdir build
```
进入build目录并运行cmake命令以创建 Makefile。
```
cd build
cmake ../
```

运行您的查询。

从build目录中，编译并运行atlas-vector-search-quick-start.c文件。

cmake --build .
./atlas-vector-search-quick-start

1 { "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" : { "$numberDouble" : "0.78926712274551391602" } }
2 { "plot" : "At the age of 21, Tim discovers he can travel in time and change what happens and has happened in his own life. His decision to make his world a better place by getting a girlfriend turns out not to be as easy as you might think.", "title" : "About Time", "score" : { "$numberDouble" : "0.78436046838760375977" } }
3 { "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" : { "$numberDouble" : "0.78010666370391845703" } }
4 { "plot" : "After using his mother's newly built time machine, Dolf gets stuck involuntary in the year 1212. He ends up in a children's crusade where he confronts his new friends with modern techniques...", "title" : "Crusade in Jeans", "score" : { "$numberDouble" : "0.77891707420349121094" } }
5 { "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" : { "$numberDouble" : "0.77716124057769775391" } }
6 { "plot" : "A time-travel experiment in which a robot probe is sent from the year 2073 to the year 1973 goes terribly wrong thrusting one of the project scientists, a man named Nicholas Sinclair into a...", "title" : "A.P.E.X.", "score" : { "$numberDouble" : "0.77308857440948486328" } }
7 { "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" : { "$numberDouble" : "0.77123808860778808594" } }
8 { "plot" : "Bound by a shared destiny, a teen bursting with scientific curiosity and a former boy-genius inventor embark on a mission to unearth the secrets of a place somewhere in time and space that exists in their collective memory.", "title" : "Tomorrowland", "score" : { "$numberDouble" : "0.76699239015579223633" } }
9 { "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" : { "$numberDouble" : "0.76493728160858154297" } }
10 { "plot" : "A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...", "title" : "The Portal", "score" : { "$numberDouble" : "0.76407861709594726562" } }

将 MongoDB C++ 驱动程序添加到您的项目中。

安装 C++ 驱动程序。有关详细的安装说明，请参阅MongoDB C++ 驱动程序文档。

创建一个名为query-quick-start的新目录。

mkdir query-quick-start

进入目录，创建CMakeLists.txt文件。

cd query-quick-start
touch CMakeLists.txt

将以下行复制并粘贴到CMakeLists.txt文件中：

cmake_minimum_required(VERSION 3.30)
project(query_quick_start)
set(CMAKE_CXX_STANDARD 17)
find_package(mongocxx REQUIRED)
find_package(bsoncxx REQUIRED)
add_executable(query_quick_start
  atlas_vector_search_quick_start.cpp
)
target_link_libraries(query_quick_start PRIVATE mongo::mongocxx_shared)
target_link_libraries(query_quick_start PRIVATE mongo::bsoncxx_shared)

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建名为atlas_vector_search_quick_start.cpp的文件。

将以下示例查询复制并粘贴到 atlas_vector_search_quick_start.cpp 文件中：

1 #include <bsoncxx/builder/basic/document.hpp>
2 #include <bsoncxx/builder/list.hpp>
3 #include <bsoncxx/json.hpp>
4 #include <mongocxx/client.hpp>
5 #include <mongocxx/instance.hpp>
6 #include <mongocxx/uri.hpp>
7 
8 using bsoncxx::builder::basic::kvp;
9 using bsoncxx::builder::basic::make_document;
10 
11 int main() {
12   try {
13     mongocxx::instance inst{};
14 
15     // Replace the placeholder with your Atlas connection string
16     const auto uri = mongocxx::uri{"<connection-string>"};
17 
18     // Connect to your Atlas cluster
19     auto client = mongocxx::client{uri};
20     auto db = client["sample_mflix"];
21     auto collection = db["embedded_movies"];
22 
23     // Define vector embeddings to search
24     auto vectors = bsoncxx::builder::list{
25       -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 0.007650814, 0.003458861, -0.0031223053, -0.01932697, -0.033615597, 0.00745088, 0.006321252, -0.0038154104, 0.014555207, 0.027697546, -0.02828402, 0.0066711367, 0.0077107945, 0.01794076, 0.011349596, -0.0052715978, 0.014755142, -0.019753495, -0.011156326, 0.011202978, 0.022126047, 0.00846388, 0.030549942, -0.0041386373, 0.018847128, -0.00033655585, 0.024925126, -0.003555496, -0.019300312, 0.010749794, 0.0075308536, -0.018287312, -0.016567878, -0.012869096, -0.015528221, 0.0078107617, -0.011156326, 0.013522214, -0.020646535, -0.01211601, 0.055928253, 0.011596181, -0.017247654, 0.0005939711, -0.026977783, -0.003942035, -0.009583511, -0.0055248477, -0.028737204, 0.023179034, 0.003995351, 0.0219661, -0.008470545, 0.023392297, 0.010469886, -0.015874773, 0.007890735, -0.009690142, -0.00024970944, 0.012775794, 0.0114762215, 0.013422247, 0.010429899, -0.03686786, -0.006717788, -0.027484283, 0.011556195, -0.036068123, -0.013915418, -0.0016327957, 0.0151016945, -0.020473259, 0.004671795, -0.012555866, 0.0209531, 0.01982014, 0.024485271, 0.0105431955, -0.005178295, 0.033162415, -0.013795458, 0.007150979, 0.010243294, 0.005644808, 0.017260984, -0.0045618312, 0.0024725192, 0.004305249, -0.008197301, 0.0014203656, 0.0018460588, 0.005015015, -0.011142998, 0.01439526, 0.022965772, 0.02552493, 0.007757446, -0.0019726837, 0.009503538, -0.032042783, 0.008403899, -0.04609149, 0.013808787, 0.011749465, 0.036388017, 0.016314628, 0.021939443, -0.0250051, -0.017354285, -0.012962398, 0.00006107364, 0.019113706, 0.03081652, -0.018114036, -0.0084572155, 0.009643491, -0.0034721901, 0.0072642746, -0.0090636825, 0.01642126, 0.013428912, 0.027724205, 0.0071243206, -0.6858542, -0.031029783, -0.014595194, -0.011449563, 0.017514233, 0.01743426, 0.009950057, 0.0029706885, -0.015714826, -0.001806072, 0.011856096, 0.026444625, -0.0010663156, -0.006474535, 0.0016161345, -0.020313311, 0.0148351155, -0.0018393943, 0.0057347785, 0.018300641, -0.018647194, 0.03345565, -0.008070676, 0.0071443142, 0.014301958, 0.0044818576, 0.003838736, -0.007350913, -0.024525259, -0.001142124, -0.018620536, 0.017247654, 0.007037683, 0.010236629, 0.06046009, 0.0138887605, -0.012122675, 0.037694257, 0.0055081863, 0.042492677, 0.00021784494, -0.011656162, 0.010276617, 0.022325981, 0.005984696, -0.009496873, 0.013382261, -0.0010563189, 0.0026507939, -0.041639622, 0.008637156, 0.026471283, -0.008403899, 0.024858482, -0.00066686375, -0.0016252982, 0.027590916, 0.0051449724, 0.0058647357, -0.008743787, -0.014968405, 0.027724205, -0.011596181, 0.0047650975, -0.015381602, 0.0043718936, 0.002159289, 0.035908177, -0.008243952, -0.030443309, 0.027564257, 0.042625964, -0.0033688906, 0.01843393, 0.019087048, 0.024578573, 0.03268257, -0.015608194, -0.014128681, -0.0033538956, -0.0028757197, -0.004121976, -0.032389335, 0.0034322033, 0.058807302, 0.010943064, -0.030523283, 0.008903735, 0.017500903, 0.00871713, -0.0029406983, 0.013995391, -0.03132302, -0.019660193, -0.00770413, -0.0038853872, 0.0015894766, -0.0015294964, -0.006251275, -0.021099718, -0.010256623, -0.008863748, 0.028550599, 0.02020668, -0.0012962399, -0.003415542, -0.0022509254, 0.0119360695, 0.027590916, -0.046971202, -0.0015194997, -0.022405956, 0.0016677842, -0.00018535563, -0.015421589, -0.031802863, 0.03814744, 0.0065411795, 0.016567878, -0.015621523, 0.022899127, -0.011076353, 0.02841731, -0.002679118, -0.002342562, 0.015341615, 0.01804739, -0.020566562, -0.012989056, -0.002990682, 0.01643459, 0.00042527664, 0.008243952, -0.013715484, -0.004835075, -0.009803439, 0.03129636, -0.021432944, 0.0012087687, -0.015741484, -0.0052016205, 0.00080890034, -0.01755422, 0.004811749, -0.017967418, -0.026684547, -0.014128681, 0.0041386373, -0.013742141, -0.010056688, -0.013268964, -0.0110630235, -0.028337335, 0.015981404, -0.00997005, -0.02424535, -0.013968734, -0.028310679, -0.027750863, -0.020699851, 0.02235264, 0.001057985, 0.00081639783, -0.0099367285, 0.013522214, -0.012016043, -0.00086471526, 0.013568865, 0.0019376953, -0.019020405, 0.017460918, -0.023045745, 0.008503866, 0.0064678704, -0.011509543, 0.018727167, -0.003372223, -0.0028690554, -0.0027024434, -0.011902748, -0.012182655, -0.015714826, -0.0098634185, 0.00593138, 0.018753825, 0.0010146659, 0.013029044, 0.0003521757, -0.017620865, 0.04102649, 0.00552818, 0.024485271, -0.009630162, -0.015608194, 0.0006718621, -0.0008418062, 0.012395918, 0.0057980907, 0.016221326, 0.010616505, 0.004838407, -0.012402583, 0.019900113, -0.0034521967, 0.000247002, -0.03153628, 0.0011038032, -0.020819811, 0.016234655, -0.00330058, -0.0032289368, 0.00078973995, -0.021952773, -0.022459272, 0.03118973, 0.03673457, -0.021472929, 0.0072109587, -0.015075036, 0.004855068, -0.0008151483, 0.0069643734, 0.010023367, -0.010276617, -0.023019087, 0.0068244194, -0.0012520878, -0.0015086699, 0.022046074, -0.034148756, -0.0022192693, 0.002427534, -0.0027124402, 0.0060346797, 0.015461575, 0.0137554705, 0.009230294, -0.009583511, 0.032629255, 0.015994733, -0.019167023, -0.009203636, 0.03393549, -0.017274313, -0.012042701, -0.0009930064, 0.026777849, -0.013582194, -0.0027590916, -0.017594207, -0.026804507, -0.0014236979, -0.022032745, 0.0091236625, -0.0042419364, -0.00858384, -0.0033905501, -0.020739838, 0.016821127, 0.022539245, 0.015381602, 0.015141681, 0.028817179, -0.019726837, -0.0051283115, -0.011489551, -0.013208984, -0.0047017853, -0.0072309524, 0.01767418, 0.0025658219, -0.010323267, 0.012609182, -0.028097415, 0.026871152, -0.010276617, 0.021912785, 0.0022542577, 0.005124979, -0.0019710176, 0.004518512, -0.040360045, 0.010969722, -0.0031539614, -0.020366628, -0.025778178, -0.0110030435, -0.016221326, 0.0036587953, 0.016207997, 0.003007343, -0.0032555948, 0.0044052163, -0.022046074, -0.0008822095, -0.009363583, 0.028230704, -0.024538586, 0.0029840174, 0.0016044717, -0.014181997, 0.031349678, -0.014381931, -0.027750863, 0.02613806, 0.0004136138, -0.005748107, -0.01868718, -0.0010138329, 0.0054348772, 0.010703143, -0.003682121, 0.0030856507, -0.004275259, -0.010403241, 0.021113047, -0.022685863, -0.023032416, 0.031429652, 0.001792743, -0.005644808, -0.011842767, -0.04078657, -0.0026874484, 0.06915057, -0.00056939584, -0.013995391, 0.010703143, -0.013728813, -0.022939114, -0.015261642, -0.022485929, 0.016807798, 0.007964044, 0.0144219175, 0.016821127, 0.0076241563, 0.005461535, -0.013248971, 0.015301628, 0.0085171955, -0.004318578, 0.011136333, -0.0059047225, -0.010249958, -0.018207338, 0.024645219, 0.021752838, 0.0007614159, -0.013648839, 0.01111634, -0.010503208, -0.0038487327, -0.008203966, -0.00397869, 0.0029740208, 0.008530525, 0.005261601, 0.01642126, -0.0038753906, -0.013222313, 0.026537929, 0.024671877, -0.043505676, 0.014195326, 0.024778508, 0.0056914594, -0.025951454, 0.017620865, -0.0021359634, 0.008643821, 0.021299653, 0.0041686273, -0.009017031, 0.04044002, 0.024378639, -0.027777521, -0.014208655, 0.0028623908, 0.042119466, 0.005801423, -0.028124074, -0.03129636, 0.022139376, -0.022179363, -0.04067994, 0.013688826, 0.013328944, 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26     };
27 
28     // Define the pipeline with vectorSearch query options
29     mongocxx::pipeline stages;
30 
31     stages
32         .append_stage(make_document(
33             kvp("$vectorSearch",
34                 make_document(kvp("index", "vector_index"),
35                               kvp("path", "plot_embedding"),
36                               kvp("queryVector", vectors),
37                               kvp("numCandidates", 150), kvp("limit", 10)))))
38         .project(make_document(
39             kvp("_id", 0), kvp("plot", 1), kvp("title", 1),
40             kvp("score", make_document(kvp("$meta", "vectorSearchScore")))));
41 
42     auto cursor = collection.aggregate(stages);
43 
44     for (auto&& doc : cursor) {
45       std::cout << bsoncxx::to_json(doc) << std::endl;
46     }
47   } catch (const std::exception& e) {
48     std::cout << "Exception: " << e.what() << std::endl;
49   }
50   return 0;
51 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

编译并运行查询。

创建并进入/build目录：
```
mkdir build && cd build
```
准备项目。
```
cmake ../
```
构建应用。
```
cmake --build .
```

执行应用以运行查询。

./query_quick_start

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

为查询设置并初始化 .NET/C# 项目。

创建一个名为query-quick-start的新目录，并使用 dotnet new 命令初始化项目。
```
mkdir query-quick-start
cd query-quick-start
dotnet new console
```
将 .NET/C# 驱动程序作为依赖项添加到项目中。
```
dotnet add package MongoDB.Driver
```

有关更详细的安装说明，请参阅MongoDB C# 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

编辑Program.cs文件。

将以下示例查询复制并粘贴到 Program.cs 文件中：

1 using MongoDB.Bson;
2 using MongoDB.Bson.Serialization.Attributes;
3 using MongoDB.Bson.Serialization.Conventions;
4 using MongoDB.Driver;
5 
6 public class vectorSearchBasicQuery 
7 {
8   // define connection to your Atlas cluster
9   private const string MongoConnectionString = "<connection-string>";
10 
11   public static void Main(string[] args){
12     var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };
13     ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);
14 
15     // connect to your Atlas cluster
16     var mongoClient = new MongoClient(MongoConnectionString);
17 
18     // define namespace
19     var moviesDatabase = mongoClient.GetDatabase("sample_mflix");
20     var moviesCollection = moviesDatabase.GetCollection<EmbeddedMovie>("embedded_movies");
21 
22     // define vector embeddings to search
23     var vector = new[] 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24     var options = new VectorSearchOptions<EmbeddedMovie>() {
25         IndexName = "vector_index",
26         NumberOfCandidates = 150
27     };
28 
29     // run query
30     var results = moviesCollection.Aggregate()
31                 .VectorSearch(movie => movie.Embedding, vector, 10, options)
32                 .Project(Builders<EmbeddedMovie>.Projection
33                   .Include(movie => movie.Title)
34                   .Include(movie => movie.Plot)
35                   .Exclude(movie => movie.Id)
36                   .MetaVectorSearchScore(movie => movie.Score))
37                 .ToList();
38 
39     // print results
40     foreach (var movie in results)
41       {
42         Console.WriteLine(movie.ToJson());
43       }
44   }
45 }
46 
47 [BsonIgnoreExtraElements]
48 public class EmbeddedMovie
49 {
50     [BsonIgnoreIfDefault]
51     public string Title { get; set; }
52     public string Plot { get; set; }
53     [BsonElement("plot_embedding")]
54     public double[] Embedding { get; set; }
55     public double Score { get; set; }
56 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

编译并运行Program.cs文件。

dotnet run query-quick-start.csproj

1 { "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" : 0.9332506656646729 }
2 { "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" : 0.9312690496444702 }
3 { "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" : 0.929530143737793 }
4 { "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" : 0.9290417432785034 }
5 { "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" : 0.9283161759376526 }
6 { "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" : 0.9266218543052673 }
7 { "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" : 0.9258455038070679 }
8 { "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" : 0.9240515828132629 }
9 { "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" : 0.923175573348999 }
10 { "plot" : "A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...", "title" : "The Portal", "score" : 0.9228089451789856 }

将 MongoDB Go 驱动程序添加到您的项目中。

运行以下命令：

初始化 Go 模块：

mkdir go-vector-quickstart && cd go-vector-quickstart
go mod init go-vector-quickstart

添加 MongoDB Go 作为依赖项：

go get go.mongodb.org/mongo-driver/mongo

有关更详细的安装说明，请参阅MongoDB Go 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建名为atlas_vector_search_quick_start.go的文件。

将以下示例查询复制并粘贴到 atlas_vector_search_quick_start.go 文件中：

1 package main
2 
3 import (
4   "context"
5   "encoding/json"
6   "fmt"
7   "log"
8 
9   "go.mongodb.org/mongo-driver/bson"
10   "go.mongodb.org/mongo-driver/mongo"
11   "go.mongodb.org/mongo-driver/mongo/options"
12 )
13 
14 func main() {
15 
16   ctx := context.TODO()
17 
18   // Replace the placeholder with your Atlas connection string
19   const uri = "<connection-string>"
20 
21   // Connect to your Atlas cluster
22   clientOptions := options.Client().ApplyURI(uri)
23   client, err := mongo.Connect(ctx, clientOptions)
24   if err != nil {
25     log.Fatal(err)
26   }
27   defer client.Disconnect(ctx)
28 
29   // Set the namespace
30   coll := client.Database("sample_mflix").Collection("embedded_movies")
31 
32   // Define the pipeline with $vectorSearch query options
33   queryVectorValues := []float64{
34     -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 0.007650814, 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0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136,
35   }
36 
37   pipeline := mongo.Pipeline{
38     bson.D{
39       {"$vectorSearch", bson.D{
40         {"queryVector", queryVectorValues},
41         {"index", "vector_index"},
42         {"path", "plot_embedding"},
43         {"numCandidates", 150},
44         {"limit", 10},
45       }},
46     },
47     bson.D{
48       {"$project", bson.D{
49         {"_id", 0},
50         {"plot", 1},
51         {"title", 1},
52         {"score", bson.D{
53           {"$meta", "vectorSearchScore"},
54         }},
55       }},
56     },
57   }
58 
59   // Run the pipeline
60   cursor, err := coll.Aggregate(ctx, pipeline)
61   if err != nil {
62     log.Fatalf("Failed to run aggregation: %v", err)
63   }
64   defer cursor.Close(ctx)
65 
66   // Print results
67   for cursor.Next(ctx) {
68     var doc bson.M
69     if err := cursor.Decode(&doc); err != nil {
70       log.Fatalf("Failed to decode document: %v", err)
71     }
72     jsonDoc, err := json.Marshal(doc)
73     if err != nil {
74       log.Fatalf("Failed to marshal document to JSON: %v", err)
75     }
76     fmt.Println(string(jsonDoc))
77   }
78 
79   if err := cursor.Err(); err != nil {
80     log.Fatalf("Cursor error: %v", err)
81   }
82 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

运行以下命令来查询您的集合：

go run atlas_vector_search_quick_start.go

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

确保您的`CLASSPATH` 包含以下库。

`junit`	4.11 或更高版本
`mongodb-driver-sync`	4.3.0 或更高版本
`slf4j-log4j12`	1.7.30 或更高版本

有关更详细的安装说明，请参阅MongoDB Java 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建名为BasicQuery.java的文件。

将以下示例查询复制并粘贴到 BasicQuery.java 文件中：

1 import static com.mongodb.client.model.Aggregates.*;
2 import static com.mongodb.client.model.Projections.*;
3 import static com.mongodb.client.model.search.SearchPath.fieldPath;
4 import static java.util.Arrays.asList;
5 import com.mongodb.client.MongoClient;
6 import com.mongodb.client.MongoClients;
7 import com.mongodb.client.MongoCollection;
8 import com.mongodb.client.MongoDatabase;
9 import java.util.List;
10 import com.mongodb.client.model.search.FieldSearchPath;
11 import org.bson.Document;
12 import org.bson.conversions.Bson;
13 
14 public class BasicQuery {
15   public static void main( String[] args ) {
16     // specify connection
17     String uri = "<connection-string>";
18 
19     // establish connection and set namespace
20     try (MongoClient mongoClient = MongoClients.create(uri)) {
21       MongoDatabase database = mongoClient.getDatabase("sample_mflix");
22       MongoCollection<Document> collection = database.getCollection("embedded_movies");
23       
24   	  // define $vectorSearch query options 
25 	    List<Double> queryVector = (asList(-0.0016261312d, -0.028070757d, -0.011342932d, -0.012775794d, -0.0027440966d, 0.008683807d, -0.02575152d, -0.02020668d, -0.010283281d, -0.0041719596d, 0.021392956d, 0.028657231d, -0.006634482d, 0.007490867d, 0.018593878d, 0.0038187427d, 0.029590257d, -0.01451522d, 0.016061379d, 0.00008528442d, -0.008943722d, 0.01627464d, 0.024311995d, -0.025911469d, 0.00022596726d, -0.008863748d, 0.008823762d, -0.034921836d, 0.007910728d, -0.01515501d, 0.035801545d, -0.0035688248d, -0.020299982d, -0.03145631d, -0.032256044d, -0.028763862d, -0.0071576433d, -0.012769129d, 0.012322609d, -0.006621153d, 0.010583182d, 0.024085402d, -0.001623632d, 0.007864078d, -0.021406285d, 0.002554159d, 0.012229307d, -0.011762793d, 0.0051682983d, 0.0048484034d, 0.018087378d, 0.024325324d, -0.037694257d, -0.026537929d, -0.008803768d, -0.017767483d, -0.012642504d, -0.0062712682d, 0.0009771782d, -0.010409906d, 0.017754154d, -0.004671795d, -0.030469967d, 0.008477209d, -0.005218282d, -0.0058480743d, -0.020153364d, -0.0032805866d, 0.004248601d, 0.0051449724d, 0.006791097d, 0.007650814d, 0.003458861d, -0.0031223053d, -0.01932697d, -0.033615597d, 0.00745088d, 0.006321252d, -0.0038154104d, 0.014555207d, 0.027697546d, -0.02828402d, 0.0066711367d, 0.0077107945d, 0.01794076d, 0.011349596d, -0.0052715978d, 0.014755142d, -0.019753495d, -0.011156326d, 0.011202978d, 0.022126047d, 0.00846388d, 0.030549942d, -0.0041386373d, 0.018847128d, -0.00033655585d, 0.024925126d, -0.003555496d, -0.019300312d, 0.010749794d, 0.0075308536d, -0.018287312d, -0.016567878d, -0.012869096d, -0.015528221d, 0.0078107617d, -0.011156326d, 0.013522214d, -0.020646535d, -0.01211601d, 0.055928253d, 0.011596181d, -0.017247654d, 0.0005939711d, -0.026977783d, -0.003942035d, -0.009583511d, -0.0055248477d, -0.028737204d, 0.023179034d, 0.003995351d, 0.0219661d, -0.008470545d, 0.023392297d, 0.010469886d, -0.015874773d, 0.007890735d, -0.009690142d, -0.00024970944d, 0.012775794d, 0.0114762215d, 0.013422247d, 0.010429899d, -0.03686786d, -0.006717788d, -0.027484283d, 0.011556195d, -0.036068123d, -0.013915418d, -0.0016327957d, 0.0151016945d, -0.020473259d, 0.004671795d, -0.012555866d, 0.0209531d, 0.01982014d, 0.024485271d, 0.0105431955d, -0.005178295d, 0.033162415d, -0.013795458d, 0.007150979d, 0.010243294d, 0.005644808d, 0.017260984d, -0.0045618312d, 0.0024725192d, 0.004305249d, -0.008197301d, 0.0014203656d, 0.0018460588d, 0.005015015d, -0.011142998d, 0.01439526d, 0.022965772d, 0.02552493d, 0.007757446d, -0.0019726837d, 0.009503538d, -0.032042783d, 0.008403899d, -0.04609149d, 0.013808787d, 0.011749465d, 0.036388017d, 0.016314628d, 0.021939443d, -0.0250051d, -0.017354285d, -0.012962398d, 0.00006107364d, 0.019113706d, 0.03081652d, -0.018114036d, -0.0084572155d, 0.009643491d, -0.0034721901d, 0.0072642746d, -0.0090636825d, 0.01642126d, 0.013428912d, 0.027724205d, 0.0071243206d, -0.6858542d, -0.031029783d, -0.014595194d, -0.011449563d, 0.017514233d, 0.01743426d, 0.009950057d, 0.0029706885d, -0.015714826d, -0.001806072d, 0.011856096d, 0.026444625d, -0.0010663156d, -0.006474535d, 0.0016161345d, -0.020313311d, 0.0148351155d, -0.0018393943d, 0.0057347785d, 0.018300641d, -0.018647194d, 0.03345565d, -0.008070676d, 0.0071443142d, 0.014301958d, 0.0044818576d, 0.003838736d, -0.007350913d, -0.024525259d, -0.001142124d, -0.018620536d, 0.017247654d, 0.007037683d, 0.010236629d, 0.06046009d, 0.0138887605d, -0.012122675d, 0.037694257d, 0.0055081863d, 0.042492677d, 0.00021784494d, -0.011656162d, 0.010276617d, 0.022325981d, 0.005984696d, -0.009496873d, 0.013382261d, -0.0010563189d, 0.0026507939d, -0.041639622d, 0.008637156d, 0.026471283d, -0.008403899d, 0.024858482d, -0.00066686375d, -0.0016252982d, 0.027590916d, 0.0051449724d, 0.0058647357d, -0.008743787d, -0.014968405d, 0.027724205d, -0.011596181d, 0.0047650975d, -0.015381602d, 0.0043718936d, 0.002159289d, 0.035908177d, -0.008243952d, -0.030443309d, 0.027564257d, 0.042625964d, -0.0033688906d, 0.01843393d, 0.019087048d, 0.024578573d, 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0.004811749d, -0.017967418d, -0.026684547d, -0.014128681d, 0.0041386373d, -0.013742141d, -0.010056688d, -0.013268964d, -0.0110630235d, -0.028337335d, 0.015981404d, -0.00997005d, -0.02424535d, -0.013968734d, -0.028310679d, -0.027750863d, -0.020699851d, 0.02235264d, 0.001057985d, 0.00081639783d, -0.0099367285d, 0.013522214d, -0.012016043d, -0.00086471526d, 0.013568865d, 0.0019376953d, -0.019020405d, 0.017460918d, -0.023045745d, 0.008503866d, 0.0064678704d, -0.011509543d, 0.018727167d, -0.003372223d, -0.0028690554d, -0.0027024434d, -0.011902748d, -0.012182655d, -0.015714826d, -0.0098634185d, 0.00593138d, 0.018753825d, 0.0010146659d, 0.013029044d, 0.0003521757d, -0.017620865d, 0.04102649d, 0.00552818d, 0.024485271d, -0.009630162d, -0.015608194d, 0.0006718621d, -0.0008418062d, 0.012395918d, 0.0057980907d, 0.016221326d, 0.010616505d, 0.004838407d, -0.012402583d, 0.019900113d, -0.0034521967d, 0.000247002d, -0.03153628d, 0.0011038032d, -0.020819811d, 0.016234655d, -0.00330058d, -0.0032289368d, 0.00078973995d, -0.021952773d, -0.022459272d, 0.03118973d, 0.03673457d, -0.021472929d, 0.0072109587d, -0.015075036d, 0.004855068d, -0.0008151483d, 0.0069643734d, 0.010023367d, -0.010276617d, -0.023019087d, 0.0068244194d, -0.0012520878d, -0.0015086699d, 0.022046074d, -0.034148756d, -0.0022192693d, 0.002427534d, -0.0027124402d, 0.0060346797d, 0.015461575d, 0.0137554705d, 0.009230294d, -0.009583511d, 0.032629255d, 0.015994733d, -0.019167023d, -0.009203636d, 0.03393549d, -0.017274313d, -0.012042701d, -0.0009930064d, 0.026777849d, -0.013582194d, -0.0027590916d, -0.017594207d, -0.026804507d, -0.0014236979d, -0.022032745d, 0.0091236625d, -0.0042419364d, -0.00858384d, -0.0033905501d, -0.020739838d, 0.016821127d, 0.022539245d, 0.015381602d, 0.015141681d, 0.028817179d, -0.019726837d, -0.0051283115d, -0.011489551d, -0.013208984d, -0.0047017853d, -0.0072309524d, 0.01767418d, 0.0025658219d, -0.010323267d, 0.012609182d, -0.028097415d, 0.026871152d, -0.010276617d, 0.021912785d, 0.0022542577d, 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-0.018207338d, 0.024645219d, 0.021752838d, 0.0007614159d, -0.013648839d, 0.01111634d, -0.010503208d, -0.0038487327d, -0.008203966d, -0.00397869d, 0.0029740208d, 0.008530525d, 0.005261601d, 0.01642126d, -0.0038753906d, -0.013222313d, 0.026537929d, 0.024671877d, -0.043505676d, 0.014195326d, 0.024778508d, 0.0056914594d, -0.025951454d, 0.017620865d, -0.0021359634d, 0.008643821d, 0.021299653d, 0.0041686273d, -0.009017031d, 0.04044002d, 0.024378639d, -0.027777521d, -0.014208655d, 0.0028623908d, 0.042119466d, 0.005801423d, -0.028124074d, -0.03129636d, 0.022139376d, -0.022179363d, -0.04067994d, 0.013688826d, 0.013328944d, 0.0046184794d, -0.02828402d, -0.0063412455d, -0.0046184794d, -0.011756129d, -0.010383247d, -0.0018543894d, -0.0018593877d, -0.00052024535d, 0.004815081d, 0.014781799d, 0.018007403d, 0.01306903d, -0.020433271d, 0.009043689d, 0.033189073d, -0.006844413d, -0.019766824d, -0.018767154d, 0.00533491d, -0.0024575242d, 0.018727167d, 0.0058080875d, -0.013835444d, 0.0040719924d, 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26 	    String indexName = "vector_index";
27 	    FieldSearchPath fieldSearchPath = fieldPath("plot_embedding");
28 	    int numCandidates = 150;
29       int limit = 10;
30       
31       // define pipeline 
32       List<Bson> pipeline = asList(
33           vectorSearch(
34            fieldSearchPath,
35            queryVector,
36            indexName,
37            numCandidates,
38            limit),
39           project(
40            fields(exclude("_id"), include("title"), include("plot"), 
41            metaVectorSearchScore("score"))));
42       
43 	    // run query and print results
44       collection.aggregate(pipeline)
45         .forEach(doc -> System.out.println(doc.toJson()));	
46     }
47   }
48 }

注意

要在 Maven 环境中运行示例代码，请将以下代码添加到文件中的 import 语句上方。

package com.mongodb.drivers;

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

编译并运行BasicQuery.java文件：

javac BasicQuery.java
java BasicQuery

1 {"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": 0.9332506656646729}
2 {"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": 0.9312690496444702}
3 {"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": 0.929530143737793}
4 {"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", "vectorSearchScore": 0.9290417432785034}
5 {"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": 0.9283161759376526}
6 {"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.", "vectorSearchScore": 0.9266218543052673}
7 {"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": 0.9258455038070679}
8 {"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": 0.9240515828132629}
9 {"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", "vectorSearchScore": 0.7649372816085815}
10 {"plot": "A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...", "title": "The Portal", "score": 0.9228089451789856}

安装 MongoDB Kotlin 协程驱动程序。

有关在项目中将驱动程序添加为依赖项的说明，请参阅MongoDB Kotlin 协程驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建一个名为 atlasVectorSearchQuery.kt 的文件。

将以下示例查询复制并粘贴到 atlasVectorSearchQuery.kt 文件中：

1 import com.mongodb.client.model.Aggregates
2 import com.mongodb.client.model.Projections
3 import com.mongodb.client.model.search.SearchPath.fieldPath
4 import com.mongodb.kotlin.client.coroutine.MongoClient
5 import kotlinx.coroutines.flow.count
6 import org.bson.Document
7 
8 data class Movie(val title: String, val plot: String, val score: Double?)
9 
10 suspend fun main() {
11 
12     // Replace the placeholder with your Atlas connection string
13     val uri = "<connection-string>"
14     val client = MongoClient.create(uri)
15 
16     try {
17         // Connect to your Atlas cluster
18         val database = client.getDatabase("sample_mflix")
19         val collection = database.getCollection<Movie>("embedded_movies")
20 
21         // Define the pipeline with $vectorSearch query options
22         val queryVector = listOf(
23             -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 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0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136,
24             )
25         val path = fieldPath("plot_embedding")
26         val index = "vector_index"
27         val numCandidates = 150L
28         val limit = 10L
29 
30         val pipeline = listOf(
31             Aggregates.vectorSearch(path, queryVector, index, numCandidates, limit),
32             Aggregates.project(
33                 Projections.fields(
34                     Projections.excludeId(),
35                     Projections.include(Movie::plot.name),
36                     Projections.include(Movie::title.name),
37                     Projections.metaVectorSearchScore(Movie::score.name)
38                 )
39             )
40         )
41 
42         // Run the pipeline
43         val resultsFlow = collection.aggregate<Document>(pipeline)
44 
45         // Print results
46         val resultCount = resultsFlow.count()
47         if (resultCount > 0) {
48             resultsFlow.collect { result ->
49                 println(result.toJson())
50             }
51         } else {
52             println("No results found.")
53         }
54     } catch (e: Exception) {
55         println("Error occurred: ${e.message}")
56     } finally {
57         client.close()
58     }
59 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

在 IDE 中运行atlasVectorSearchQuery.kt文件。输出应类似于以下内容：

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

安装 MongoDB Kotlin Sync 驱动程序。

有关在项目中将驱动程序添加为依赖项的说明，请参阅MongoDB Kotlin Sync 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建一个名为 atlasVectorSearchQuery.kt 的文件。

将以下示例查询复制并粘贴到 atlasVectorSearchQuery.kt 文件中：

1 import com.mongodb.client.model.Aggregates
2 import com.mongodb.client.model.Projections
3 import com.mongodb.client.model.search.SearchPath.fieldPath
4 import com.mongodb.kotlin.client.MongoClient
5 import org.bson.Document
6 
7 data class Movie(val title: String, val plot: String, val score: Double?)
8 
9 fun main() {
10 
11     // Replace the placeholder with your Atlas connection string
12     val uri = "<connection-string>"
13     val client = MongoClient.create(uri)
14 
15     try {
16         // Connect to your Atlas cluster
17         val database = client.getDatabase("sample_mflix")
18         val collection = database.getCollection<Movie>("embedded_movies")
19 
20         // Define the pipeline with $vectorSearch query options
21         val queryVector = listOf(
22             -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 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0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136,
23             )
24         val path = fieldPath("plot_embedding")
25         val index = "vector_index"
26         val numCandidates = 150L
27         val limit = 10L
28 
29         val pipeline = listOf(
30             Aggregates.vectorSearch(path, queryVector, index, numCandidates, limit),
31             Aggregates.project(
32                 Projections.fields(
33                     Projections.excludeId(),
34                     Projections.include(Movie::plot.name),
35                     Projections.include(Movie::title.name),
36                     Projections.metaVectorSearchScore(Movie::score.name)
37                 )
38             )
39         )
40 
41         // Run the pipeline
42         val results = collection.aggregate<Document>(pipeline).toList()
43 
44         // Print results
45         if (results.isNotEmpty()) {
46             results.forEach { result ->
47                 println(result.toJson()).toString()
48             }
49         } else {
50             println("No results found.")
51         }
52     } catch (e: Exception) {
53         println("Error occurred: ${e.message}")
54     } finally {
55         client.close()
56     }
57 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

在 IDE 中运行atlasVectorSearchQuery.kt文件。输出应类似于以下内容：

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

安装 MongoDB Node.js 驱动程序。

运行以下命令之一：

npm install mongodb

yarn add mongodb

有关更详细的安装说明，请参阅MongoDB Node.js 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建名为atlas-vector-search-quick-start.js的文件。

将以下示例查询复制并粘贴到 atlas-vector-search-quick-start.js 文件中：

1 const { MongoClient } = require("mongodb");
2 
3 // connect to your Atlas cluster
4 const uri = "<connection-string>";
5 
6 const client = new MongoClient(uri);
7 
8 async function run() {
9     try {
10         await client.connect();
11 
12         // set namespace
13         const database = client.db("sample_mflix");
14         const coll = database.collection("embedded_movies");
15 
16         // define pipeline
17         const agg = [
18             {
19               '$vectorSearch': {
20                 'index': 'vector_index',
21                 'path': 'plot_embedding',
22                 'queryVector': [
23                   -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 0.007650814, 0.003458861, -0.0031223053, -0.01932697, -0.033615597, 0.00745088, 0.006321252, -0.0038154104, 0.014555207, 0.027697546, -0.02828402, 0.0066711367, 0.0077107945, 0.01794076, 0.011349596, -0.0052715978, 0.014755142, -0.019753495, -0.011156326, 0.011202978, 0.022126047, 0.00846388, 0.030549942, -0.0041386373, 0.018847128, -0.00033655585, 0.024925126, -0.003555496, -0.019300312, 0.010749794, 0.0075308536, -0.018287312, -0.016567878, -0.012869096, -0.015528221, 0.0078107617, -0.011156326, 0.013522214, -0.020646535, -0.01211601, 0.055928253, 0.011596181, -0.017247654, 0.0005939711, -0.026977783, -0.003942035, -0.009583511, -0.0055248477, -0.028737204, 0.023179034, 0.003995351, 0.0219661, -0.008470545, 0.023392297, 0.010469886, -0.015874773, 0.007890735, -0.009690142, -0.00024970944, 0.012775794, 0.0114762215, 0.013422247, 0.010429899, -0.03686786, -0.006717788, -0.027484283, 0.011556195, -0.036068123, -0.013915418, -0.0016327957, 0.0151016945, -0.020473259, 0.004671795, 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24                 ],
25                 'numCandidates': 150,
26                 'limit': 10
27               }
28             }, {
29               '$project': {
30                 '_id': 0,
31                 'plot': 1,
32                 'title': 1,
33                 'score': {
34                   '$meta': 'vectorSearchScore'
35                 }
36               }
37             }
38           ];
39         // run pipeline
40         const result = coll.aggregate(agg);
41 
42         // print results
43         await result.forEach((doc) => console.dir(JSON.stringify(doc)));
44     } finally {
45         await client.close();
46     }
47 }
48 run().catch(console.dir);

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

运行以下命令来查询您的集合：

node atlas-vector-search-quick-start.js

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

安装 MongoDB PHP 驱动程序。

有关详细的安装说明，请参阅MongoDB PHP 库文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建一个名为 atlas_vector_search_quick_start.php 的文件。

将以下示例查询复制并粘贴到 atlas_vector_search_quick_start.php 文件中：

1 <?php
2 
3 require 'vendor/autoload.php';
4 
5 // Replace the placeholder with your Atlas connection string
6 $uri = '<connection-string>';
7 
8 try {
9 
10     // Connect to your Atlas cluster
11     $client = new MongoDB\Client($uri);
12 
13     // Set the namespace
14     $database = $client->selectDatabase('sample_mflix');
15     $collection = $database->selectCollection('embedded_movies');
16 
17     // Define the pipeline with $vectorSearch query options
18     $pipeline = [
19         [
20             '$vectorSearch' => [
21                 'queryVector' => [
22                     -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 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0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136
23                 ],
24                 'index' => 'vector_index',
25                 'path' => 'plot_embedding',
26                 'numCandidates' => 150,
27                 'limit' => 10
28             ]
29         ],
30         [
31             '$project' => [
32                 '_id' => 0,
33                 'plot' => 1,
34                 'title' => 1,
35                 'score' => [
36                     '$meta' => 'vectorSearchScore'
37                 ]
38             ]
39         ]
40     ];
41 
42     // Run the pipeline
43     $result = $collection->aggregate($pipeline);
44 
45     // Print results
46     foreach ($result as $document) {
47         echo json_encode($document) . "\n";
48     }
49 
50 } catch (MongoDB\Driver\Exception\Exception $e) {
51     echo "Error: " . $e->getMessage() . "\n";
52 }

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

运行以下命令来查询您的集合：

php atlas_vector_search_quick_start.php

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

安装`pymongo` ，即适用于 MongoDB 的 Python 驱动程序。

运行以下命令：

pip install pymongo

有关更详细的安装说明，请参阅MongoDB Python 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建一个名为 atlas-vector-search-quick-start.py 的文件。

将以下示例查询复制并粘贴到 atlas-vector-search-quick-start.py 文件中：

1 import pymongo
2 import datetime
3 
4 # connect to your Atlas cluster
5 client = pymongo.MongoClient("<connection-string>")
6 
7 # define pipeline
8 pipeline = [
9   {
10     '$vectorSearch': {
11       'index': 'vector_index', 
12       'path': 'plot_embedding', 
13       'queryVector': [-0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 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14       'numCandidates': 150, 
15       'limit': 10
16     }
17   }, {
18     '$project': {
19       '_id': 0, 
20       'plot': 1, 
21       'title': 1, 
22       'score': {
23         '$meta': 'vectorSearchScore'
24       }
25     }
26   }
27 ]
28 
29 # run pipeline
30 result = client["sample_mflix"]["embedded_movies"].aggregate(pipeline)
31 
32 # print results
33 for i in result:
34     print(i)
35

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

运行以下命令来查询您的集合：

python atlas-vector-search-quick-start.py

1 {'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': 0.9332506656646729}
2 {'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': 0.9312690496444702}
3 {'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': 0.929530143737793}
4 {'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': 0.9290417432785034}
5 {'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': 0.9283161759376526}
6 {'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': 0.9266218543052673}
7 {'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': 0.9258455038070679}
8 {'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': 0.9240515828132629}
9 {'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': 0.923175573348999}
10 {'plot': 'A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...', 'title': 'The Portal', 'score': 0.9228089451789856}

安装 MongoDB Ruby 驱动程序。

如果您还没有项目的Gemfile ，请运行以下命令生成一个：
```
bundle init
```
将mongo gem 添加到Gemfile中：
Gemfile
```
gem "mongo"
```
运行以下命令以安装依赖项：
```
bundle install
```

这将安装最新版本的 Ruby 驱动程序。有关备用安装说明和版本兼容性，请参阅MongoDB Ruby 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

创建名为atlas_vector_search_quick_start.rb的文件。

将以下示例查询复制并粘贴到 atlas_vector_search_quick_start.rb 文件中：

1 require 'mongo'
2 require 'json'
3 
4 # Replace the placeholder with your Atlas connection string
5 uri = "<connection-string>"
6 
7 begin
8   # Connect to the MongoDB client
9   client = Mongo::Client.new(uri, database: 'sample_mflix')
10 
11   # Set the namespace
12   db = client.database
13   collection = db[:embedded_movies]
14 
15   # Define the pipeline with $vectorSearch query options
16   pipeline = [
17     {
18       '$vectorSearch' => {
19         'queryVector' => [ -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 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-0.0255116, 0.017220996, 0.004358565, -0.00934359, 0.0099967085, 0.011162991, 0.03092315, -0.021046404, -0.015514892, 0.0011946067, -0.01816735, 0.010876419, -0.10124666, -0.03550831, 0.0056348112, 0.013942076, 0.005951374, 0.020419942, -0.006857742, -0.020873128, -0.021259667, 0.0137554705, 0.0057880944, -0.029163731, -0.018767154, -0.021392956, 0.030896494, -0.005494857, -0.0027307675, -0.006801094, -0.014821786, 0.021392956, -0.0018110704, -0.0018843795, -0.012362596, -0.0072176233, -0.017194338, -0.018713837, -0.024272008, 0.03801415, 0.00015880188, 0.0044951867, -0.028630573, -0.0014070367, -0.00916365, -0.026537929, -0.009576847, -0.013995391, -0.0077107945, 0.0050016865, 0.00578143, -0.04467862, 0.008363913, 0.010136662, -0.0006268769, -0.006591163, 0.015341615, -0.027377652, -0.00093136, 0.029243704, -0.020886457, -0.01041657, -0.02424535, 0.005291591, -0.02980352, -0.009190307, 0.019460259, -0.0041286405, 0.004801752, 0.0011787785, -0.001257086, -0.011216307, -0.013395589, 0.00088137644, -0.0051616337, 0.03876057, -0.0033455652, 0.00075850025, -0.006951045, -0.0062112883, 0.018140694, -0.006351242, -0.008263946, 0.018154023, -0.012189319, 0.0075508473, -0.044358727, -0.0040153447, 0.0093302615, -0.010636497, 0.032789204, -0.005264933, -0.014235313, -0.018393943, 0.007297597, -0.016114693, 0.015021721, 0.020033404, 0.0137688, 0.0011046362, 0.010616505, -0.0039453674, 0.012109346, 0.021099718, -0.0072842683, -0.019153694, -0.003768759, 0.039320387, -0.006747778, -0.0016852784, 0.018154023, 0.0010963057, -0.015035049, -0.021033075, -0.04345236, 0.017287642, 0.016341286, -0.008610498, 0.00236922, 0.009290274, 0.028950468, -0.014475234, -0.0035654926, 0.015434918, -0.03372223, 0.004501851, -0.012929076, -0.008483873, -0.0044685286, -0.0102233, 0.01615468, 0.0022792495, 0.010876419, -0.0059647025, 0.01895376, -0.0069976957, -0.0042952523, 0.017207667, -0.00036133936, 0.0085905045, 0.008084005, 0.03129636, -0.016994404, -0.014915089, 0.020100048, -0.012009379, 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0.02071318, -0.03156294, -0.030869836, -0.006324584, 0.013795458, -0.00047151142, 0.016874444, 0.00947688, 0.00985009, -0.029883493, 0.024205362, -0.013522214, -0.015075036, -0.030603256, 0.029270362, 0.010503208, 0.021539574, 0.01743426, -0.023898797, 0.022019416, -0.0068777353, 0.027857494, -0.021259667, 0.0025758184, 0.006197959, 0.006447877, -0.00025200035, -0.004941706, -0.021246338, -0.005504854, -0.008390571, -0.0097301295, 0.027244363, -0.04446536, 0.05216949, 0.010243294, -0.016008062, 0.0122493, -0.0199401, 0.009077012, 0.019753495, 0.006431216, -0.037960835, -0.027377652, 0.016381273, -0.0038620618, 0.022512587, -0.010996379, -0.0015211658, -0.0102233, 0.007071005, 0.008230623, -0.009490209, -0.010083347, 0.024431955, 0.002427534, 0.02828402, 0.0035721571, -0.022192692, -0.011882754, 0.010056688, 0.0011904413, -0.01426197, -0.017500903, -0.00010985966, 0.005591492, -0.0077707744, -0.012049366, 0.011869425, 0.00858384, -0.024698535, -0.030283362, 0.020140035, 0.011949399, -0.013968734, 0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136 ],
20         'index' => 'vector_index',
21         'path' => 'plot_embedding',
22         'numCandidates' => 150,
23         'limit' => 10
24       }
25     },
26     {
27       '$project' => {
28         '_id' => 0,
29         'plot' => 1,
30         'title' => 1,
31         'score' => { '$meta' => 'vectorSearchScore' }
32       }
33     }
34   ]
35 
36   # Run the pipeline
37   results = collection.aggregate(pipeline)
38 
39   # Print results
40   results.each do |document|
41     puts JSON(document)
42   end
43 
44 rescue Mongo::Error::NoServerAvailable => e
45   puts "Failed to connect to MongoDB: #{e.message}"
46 
47 rescue Mongo::Error::OperationFailure => e
48   puts "Failed to run aggregation: #{e.message}"
49 
50 rescue Mongo::Error => e
51   puts "A MongoDB error occurred: #{e.message}"
52 
53 rescue StandardError => e
54   puts "A general error occurred: #{e.message}"
55 
56 ensure
57   client&.close
58   puts "MongoDB client closed."
59 end

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

运行以下命令来查询您的集合：

bundle exec ruby atlas_vector_search_quick_start.rb

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

安装适用于 MongoDB 的 Rust 驱动程序。

有关更详细的安装说明，请参阅MongoDB Rust 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

在项目的main.rs文件中，粘贴以下代码：

#![recursion_limit = "2560"]
use mongodb::{ 
    bson::{Document, doc},
    Client
};
use futures::TryStreamExt;
#[tokio::main]
async fn main() -> mongodb::error::Result<()> {
    // Replace the placeholder with your Atlas connection string
    let client = Client::with_uri_str("<connection-string>").await?;
    
    let pipeline  = vec! [
        doc! {
            "$vectorSearch": doc! {
            "queryVector": [ -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 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            ],
            "path": "plot_embedding",
            "numCandidates": 150,
            "index": "vector_index",
            "limit": 10
        }
        },
        doc! {
            "$project": doc! {
                "_id": 0,
                "plot": 1,
                "title": 1,
                "score": doc! { "$meta": "vectorSearchScore"
                }
            }
        }
    ];
    let coll = client.database("sample_mflix").collection::<Document>("embedded_movies");
    let mut results = coll.aggregate(pipeline).await?;
    while let Some(result) = results.try_next().await? {
        println!("{}", result);
    }
    Ok(())
}

#![recursion_limit = "2560"]
use mongodb::{ 
    bson::{Document, doc},
    sync::Client
};
fn main() -> mongodb::error::Result<()> {
    // Replace the placeholder with your Atlas connection string
    let client = Client::with_uri_str("<connection-string>")?;
    let pipeline  = vec! [
        doc! {
            "$vectorSearch": doc! {
            "queryVector": [ -0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 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-0.006684466, 0.01306903, 0.00015765642, -0.00530492, 0.0005277429, 0.015421589, 0.015528221, 0.032202728, -0.003485519, -0.0014286962, 0.033908837, 0.001367883, 0.010509873, 0.025271678, -0.020993087, 0.019846799, 0.006897729, -0.010216636, -0.00725761, 0.01818068, -0.028443968, -0.011242964, -0.014435247, -0.013688826, 0.006101324, -0.0022509254, 0.013848773, -0.0019077052, 0.017181009, 0.03422873, 0.005324913, -0.0035188415, 0.014128681, -0.004898387, 0.005038341, 0.0012320944, -0.005561502, -0.017847456, 0.0008538855, -0.0047884234, 0.011849431, 0.015421589, -0.013942076, 0.0029790192, -0.013702155, 0.0001199605, -0.024431955, 0.019926772, 0.022179363, -0.016487904, -0.03964028, 0.0050849924, 0.017487574, 0.022792496, 0.0012504216, 0.004048667, -0.00997005, 0.0076041627, -0.014328616, -0.020259995, 0.0005598157, -0.010469886, 0.0016852784, 0.01716768, -0.008990373, -0.001987679, 0.026417969, 0.023792166, 0.0046917885, -0.0071909656, -0.00032051947, -0.023259008, -0.009170313, 0.02071318, -0.03156294, -0.030869836, -0.006324584, 0.013795458, -0.00047151142, 0.016874444, 0.00947688, 0.00985009, -0.029883493, 0.024205362, -0.013522214, -0.015075036, -0.030603256, 0.029270362, 0.010503208, 0.021539574, 0.01743426, -0.023898797, 0.022019416, -0.0068777353, 0.027857494, -0.021259667, 0.0025758184, 0.006197959, 0.006447877, -0.00025200035, -0.004941706, -0.021246338, -0.005504854, -0.008390571, -0.0097301295, 0.027244363, -0.04446536, 0.05216949, 0.010243294, -0.016008062, 0.0122493, -0.0199401, 0.009077012, 0.019753495, 0.006431216, -0.037960835, -0.027377652, 0.016381273, -0.0038620618, 0.022512587, -0.010996379, -0.0015211658, -0.0102233, 0.007071005, 0.008230623, -0.009490209, -0.010083347, 0.024431955, 0.002427534, 0.02828402, 0.0035721571, -0.022192692, -0.011882754, 0.010056688, 0.0011904413, -0.01426197, -0.017500903, -0.00010985966, 0.005591492, -0.0077707744, -0.012049366, 0.011869425, 0.00858384, -0.024698535, -0.030283362, 0.020140035, 0.011949399, -0.013968734, 0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136
            ],
            "path": "plot_embedding",
            "numCandidates": 150,
            "index": "vector_index",
            "limit": 10
        }
        },
        doc! {
            "$project": doc! {
                "_id": 0,
                "plot": 1,
                "title": 1,
                "score": doc! { "$meta": "vectorSearchScore"
                }
            }
        }
    ];
    let coll = client.database("sample_mflix").collection::<Document>("embedded_movies");
    let mut cursor = coll.aggregate(pipeline).run()?;
    while cursor.advance()? {
        println!("{}", cursor.deserialize_current()?);
    }
    Ok(())
}

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

运行以下命令来查询您的集合：

cargo run

1 {'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': 0.9332506656646729}
2 {'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': 0.9312690496444702}
3 {'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': 0.929530143737793}
4 {'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': 0.9290417432785034}
5 {'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': 0.9283161759376526}
6 {'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': 0.9266218543052673}
7 {'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': 0.9258455038070679}
8 {'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': 0.9240515828132629}
9 {'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': 0.923175573348999}
10 {'plot': 'A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...', 'title': 'The Portal', 'score': 0.9228089451789856}

安装 MongoDB Scala 驱动程序。

有关基于您的环境和所使用的 Scala 版本的安装说明，请参阅MongoDB Scala 驱动程序文档。

构建向量搜索查询。

此查询搜索plot字段中包含与术语“时间旅行”语义相关的文本的文档。

使用您常用的工具创建一个新的 Scala 项目。在本快速入门中，我们使用quick-start sbt 创建一个名为的项目。
```
sbt new scala/hello-world.g8
```
出现提示时，将应用程序命名为quick-start 。

打开Main.scala文件并将内容替换为以下向量搜索查询：

import org.mongodb.scala._
import org.mongodb.scala.model._
import org.mongodb.scala.model.Aggregates._
import org.mongodb.scala.model.Projections._
import org.mongodb.scala.model.search.SearchPath.fieldPath
object Main extends App {
    val mongoClient: MongoClient = MongoClient("<connection-string>")
    val database: MongoDatabase = mongoClient.getDatabase("sample_mflix")
    val collection: MongoCollection[Document] = database.getCollection("embedded_movies")
    collection.aggregate(Seq(
        Aggregates.vectorSearch(fieldPath("plot_embedding"),
            List(-0.0016261312, -0.028070757, -0.011342932, -0.012775794, -0.0027440966, 0.008683807, -0.02575152, -0.02020668, -0.010283281, -0.0041719596, 0.021392956, 0.028657231, -0.006634482, 0.007490867, 0.018593878, 0.0038187427, 0.029590257, -0.01451522, 0.016061379, 0.00008528442, -0.008943722, 0.01627464, 0.024311995, -0.025911469, 0.00022596726, -0.008863748, 0.008823762, -0.034921836, 0.007910728, -0.01515501, 0.035801545, -0.0035688248, -0.020299982, -0.03145631, -0.032256044, -0.028763862, -0.0071576433, -0.012769129, 0.012322609, -0.006621153, 0.010583182, 0.024085402, -0.001623632, 0.007864078, -0.021406285, 0.002554159, 0.012229307, -0.011762793, 0.0051682983, 0.0048484034, 0.018087378, 0.024325324, -0.037694257, -0.026537929, -0.008803768, -0.017767483, -0.012642504, -0.0062712682, 0.0009771782, -0.010409906, 0.017754154, -0.004671795, -0.030469967, 0.008477209, -0.005218282, -0.0058480743, -0.020153364, -0.0032805866, 0.004248601, 0.0051449724, 0.006791097, 0.007650814, 0.003458861, -0.0031223053, -0.01932697, -0.033615597, 0.00745088, 0.006321252, -0.0038154104, 0.014555207, 0.027697546, -0.02828402, 0.0066711367, 0.0077107945, 0.01794076, 0.011349596, -0.0052715978, 0.014755142, -0.019753495, -0.011156326, 0.011202978, 0.022126047, 0.00846388, 0.030549942, -0.0041386373, 0.018847128, -0.00033655585, 0.024925126, -0.003555496, -0.019300312, 0.010749794, 0.0075308536, -0.018287312, -0.016567878, -0.012869096, -0.015528221, 0.0078107617, -0.011156326, 0.013522214, -0.020646535, -0.01211601, 0.055928253, 0.011596181, -0.017247654, 0.0005939711, -0.026977783, -0.003942035, -0.009583511, -0.0055248477, -0.028737204, 0.023179034, 0.003995351, 0.0219661, -0.008470545, 0.023392297, 0.010469886, -0.015874773, 0.007890735, -0.009690142, -0.00024970944, 0.012775794, 0.0114762215, 0.013422247, 0.010429899, -0.03686786, -0.006717788, -0.027484283, 0.011556195, -0.036068123, -0.013915418, -0.0016327957, 0.0151016945, -0.020473259, 0.004671795, 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-0.0015294964, -0.006251275, -0.021099718, -0.010256623, -0.008863748, 0.028550599, 0.02020668, -0.0012962399, -0.003415542, -0.0022509254, 0.0119360695, 0.027590916, -0.046971202, -0.0015194997, -0.022405956, 0.0016677842, -0.00018535563, -0.015421589, -0.031802863, 0.03814744, 0.0065411795, 0.016567878, -0.015621523, 0.022899127, -0.011076353, 0.02841731, -0.002679118, -0.002342562, 0.015341615, 0.01804739, -0.020566562, -0.012989056, -0.002990682, 0.01643459, 0.00042527664, 0.008243952, -0.013715484, -0.004835075, -0.009803439, 0.03129636, -0.021432944, 0.0012087687, -0.015741484, -0.0052016205, 0.00080890034, -0.01755422, 0.004811749, -0.017967418, -0.026684547, -0.014128681, 0.0041386373, -0.013742141, -0.010056688, -0.013268964, -0.0110630235, -0.028337335, 0.015981404, -0.00997005, -0.02424535, -0.013968734, -0.028310679, -0.027750863, -0.020699851, 0.02235264, 0.001057985, 0.00081639783, -0.0099367285, 0.013522214, -0.012016043, -0.00086471526, 0.013568865, 0.0019376953, 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0.042732596, -0.011649498, -0.011982721, -0.016967745, -0.0060913274, -0.007130985, -0.013109017, -0.009710136),
        "vector_index",
        150,
        10
        ),
        Aggregates.project(
        Projections.fields(
            Projections.excludeId(),
            Projections.include("plot"),
            Projections.include("title"),
            Projections.meta(
            "score", "vectorSearchScore"
            )
        )
    )
  )).foreach { doc => println(doc.toBsonDocument()) }
}

此查询使用$vectorSearch阶段执行以下操作：

在sample_mflix.embedded_moves集合的plot_embedding字段中，将搜索词的向量嵌入与电影情节的向量嵌入进行比较。
最多考虑150个最相似的电影情节，并返回前10结果。

它使用$project阶段执行以下操作：

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

要了解有关该管道阶段的更多信息，请参阅运行向量搜索查询。

指定`<connection-string>` 。

将<connection-string>替换为 Atlas 集群或本地部署的连接字符串。
连接字符串应使用以下格式：
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
确保连接字符串包含数据库用户的档案。要了解有关查找连接字符串的更多信息，请参阅通过驱动程序连接。
连接字符串应使用以下格式：
mongodb://localhost:<port-number>/?directConnection=true
保存文件。

运行您的查询。

Scala 可以在多种工具和环境中运行。在此示例中，我们通过使用sbt命令启动 sbt 服务器，然后键入~run来运行新的 Scala 项目。

sbt:quick-start> ~run

1 '{"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":0.9332506656646729}'
2 '{"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":0.9312690496444702}'
3 '{"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":0.929530143737793}'
4 '{"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":0.9290417432785034}';
5 '{"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":0.9283161759376526}'
6 '{"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":0.9266218543052673}'
7 '{"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":0.9258455038070679}'
8 '{"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":0.9240515828132629}'
9 '{"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":0.923175573348999}'
10 '{"plot":"A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...","title":"The Portal","score":0.9228089451789856}'

学习总结

本快速入门重点介绍从 Atlas 集群检索包含与所提供查询在语义上相关的文本的文档。但是，您可以在嵌入上创建向量搜索索引，以表示您可能写入 Atlas 集群的任何类型的数据，例如图像或视频。

样本数据

本快速入门使用包含电影详细信息的sample_mflix.embedded_movies集合。在集合的每个文档中， plot_embedding字段包含一个向量嵌入，表示plot字段中的字符串。有关集合中文档模式的更多信息，请参阅样本 Mflix 数据集。

通过将源数据及其相应的向量嵌入存储在同一文档中，您可以利用这两个字段进行复杂查询或混合搜索。您甚至可以将从不同嵌入模型生成的向量嵌入存储在同一文档中，以简化针对特定用例测试不同向量嵌入模型的性能的工作流程。

向量嵌入

sample_mflix.embedded_movies集合和示例查询中的向量嵌入是使用 OpenAI text-embedding-ada-002嵌入模型创建的。您选择的嵌入模型决定了您在向量搜索索引中使用的向量维度和向量相似度函数。您可以使用任何喜欢的嵌入模型，并且值得尝试不同的模型，因为根据具体使用案例，不同模型的准确性可能有所不同。

要了解如何创建自己数据的向量嵌入，请参阅如何创建向量嵌入。

向量索引定义

索引是一种数据结构，它保存集合文档中的数据子集，可提高特定查询的数据库性能。向量搜索索引指向包含向量嵌入的字段，包括向量的维度以及用于衡量查询向量与数据库中存储的向量之间相似度的函数。

由于本快速入门中使用的text-embedding-ada-002嵌入模型会将数据转换为具有1536维度的向量嵌入并支持cosine函数，因此该向量搜索索引指定了相同的向量维度数和相似度函数。

向量搜索查询

您在本快速入门中运行的查询是一个聚合管道，其中$vectorSearch阶段执行近似最近邻 (ANN)搜索，然后是细化结果的$project阶段。要查看向量搜索查询的所有选项，包括使用精确最近邻 (ENN)或如何使用filter选项缩小向量搜索范围，请参阅运行向量搜索查询。

后续步骤

要创建自己的数据的嵌入并将其加载到 Atlas，请参阅创建嵌入。
要在生成式 AI 和RAG应用程序中利用 Atlas Vector Search，请参阅将矢量搜索与 AI 技术集成。
要使用 Atlas Vector Search 构建可投入生产的 AI 聊天机器人，请参阅 MongoDB 聊天机器人框架。
要了解如何在无需 API 密钥或信用的情况下实施 RAG ，请参阅使用 Atlas Vector Search 构建本地 RAG 实施。

后退

Atlas Vector Search

来年

如何创建向量嵌入

1	{
2	"fields": [{
3	"type": "vector",
4	"path": "plot_embedding",
5	"numDimensions": 1536,
6	"similarity": "dotProduct"
7	}]
8	}

1	[
2	{
3	"$vectorSearch": {
4	"index": "vector_index",
5	"path": "plot_embedding",
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1	{
2	"score": 0.9332506656646729,
3	"plot": "A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.",
4	"title": "Thrill Seekers"
5	}
6	{
7	"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.",
8	"title": "About Time",
9	"score": 0.9312690496444702
10	}
11	{
12	"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.",
13	"title": "The Time Machine",
14	"score": 0.929530143737793
15	}
16	{
17	"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...",
18	"title": "Crusade in Jeans",
19	"score": 0.9290417432785034
20	}
21	{
22	"title": "Timecop",
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24	"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."
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26	{
27	"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...",
28	"title": "A.P.E.X.",
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32	"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.",
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38	"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.",
39	"title": "Tomorrowland"
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41	{
42	"plot": "With the help of his uncle, a man travels to the future to try and bring his girlfriend back to life.",
43	"title": "Love Story 2050",
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46	{
47	"plot": "A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...",
48	"title": "The Portal",
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11	{
12	"$project": {
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1	[
2	{
3	plot: 'A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.',
4	title: 'Thrill Seekers',
5	score: 0.9332506656646729
6	},
7	{
8	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.',
9	title: 'About Time',
10	score: 0.9312690496444702
11	},
12	{
13	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.',
14	title: 'The Time Machine',
15	score: 0.929530143737793
16	},
17	{
18	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...",
19	title: 'Crusade in Jeans',
20	score: 0.9290417432785034
21	},
22	{
23	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.',
24	title: 'Timecop',
25	score: 0.9283161759376526
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27	{
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29	title: 'A.P.E.X.',
30	score: 0.9266218543052673
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32	{
33	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.",
34	title: 'Men in Black 3',
35	score: 0.9258455038070679
36	},
37	{
38	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.',
39	title: 'Tomorrowland',
40	score: 0.9240515828132629
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42	{
43	plot: 'With the help of his uncle, a man travels to the future to try and bring his girlfriend back to life.',
44	title: 'Love Story 2050',
45	score: 0.923175573348999
46	},
47	{
48	plot: 'A dimension-traveling wizard gets stuck in the 21st century because cell-phone radiation interferes with his magic. With his home world on the brink of war, he seeks help from a jaded ...',
49	title: 'The Portal',
50	score: 0.9228089451789856
51	}
52	]

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7	{'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': 0.9258455038070679}
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创建向量搜索索引

设置 Atlas 集群。

注意

创建 Vector Search 索引。

安装依赖项。

设置本地 Atlas 部署。

加载示例数据。

创建 Vector Search 索引。

运行向量搜索查询

单击“ Collections ”（集合）标签页，查看“Data Explorer”（数据浏览器）。

转到集合的Aggregation 标签页。

构建并运行向量搜索查询。

下载并安装mongosh 。

连接到 中的集群或本地部署。mongosh

切换到sample_mflix 数据库。

构建并运行向量搜索查询。

安装 MongoDB C 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

为您的项目配置 CMake。

运行您的查询。

将 MongoDB C++ 驱动程序添加到您的项目中。

构建向量搜索查询。

指定<connection-string> 。

编译并运行查询。

为查询设置并初始化 .NET/C# 项目。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

将 MongoDB Go 驱动程序添加到您的项目中。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

确保您的CLASSPATH 包含以下库。

构建向量搜索查询。

注意

指定<connection-string> 。

运行您的查询。

安装 MongoDB Kotlin 协程驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装 MongoDB Kotlin Sync 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装 MongoDB Node.js 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装 MongoDB PHP 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装pymongo ，即适用于 MongoDB 的 Python 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装 MongoDB Ruby 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装适用于 MongoDB 的 Rust 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

安装 MongoDB Scala 驱动程序。

构建向量搜索查询。

指定<connection-string> 。

运行您的查询。

学习总结

样本数据

向量嵌入

向量索引定义

向量搜索查询

后续步骤

下载并安装`mongosh` 。

连接到中的集群或本地部署。`mongosh`

切换到`sample_mflix` 数据库。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。

确保您的`CLASSPATH` 包含以下库。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。

安装`pymongo` ，即适用于 MongoDB 的 Python 驱动程序。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。

指定`<connection-string>` 。