README

A PHP client for Milvus 2.5.x.

Installation

composer require mathsgod/milvus-client-php

Quick Start

Initialize Client

use Milvus\Client;

$client = new Client(
    "http://localhost:19530", // Milvus server URI
    "username",               // Optional: username
    "password",               // Optional: password
    "default",                // Optional: database name
    "token"                   // Optional: JWT token
);

Example: Create Collection with Various Field Types and Search

$client = new Milvus\Client();

$client->createCollection(
    collection_name: "testing",
    schema: $client->createSchema()
        ->addField("id", Milvus\DataType::INT64, is_primary: true)
        ->addField("array", Milvus\DataType::ARRAY, element_type: Milvus\DataType::INT64, max_capacity: 10)
        ->addField("vector", Milvus\DataType::FLOAT_VECTOR, dim: 5)
        ->addField("text", Milvus\DataType::VARCHAR, max_length: 1000, nullable: true)
        ->addField("metadata", Milvus\DataType::JSON, nullable: true),
    index_params: $client->prepareIndexParams()
        ->addIndex(
            field_name: "vector",
            index_name: "my_index",
            index_type: Milvus\IndexType::AUTOINDEX,
            metric_type: Milvus\MetricType::COSINE
        ),
);

// Insert data
$client->insert(
    collection_name: "testing",
    data: [
        [
            "id" => 1,
            "array" => [1, 2, 3],
            "vector" => [0.1, 0.2, 0.3, 0.4, 0.5],
            "text" => "Hello World",
            "metadata" => ["key1" => "value1", "key2" => "value2"]
        ],
        [
            "id" => 2,
            "array" => [4, 5, 6],
            "vector" => [0.6, 0.7, 0.8, 0.9, 1.0],
            "text" => null,
            "metadata" => null
        ]
    ]
);

print_R($client->search(
    collection_name: "testing",
    data: [[0.1, 0.2, 0.3, 0.4, 0.5]],
    anns_field: "vector",
    limit: 3,
    output_fields: ["id", "vector", "text", "metadata"],
));

Example Search Result

Array
(
    [0] => Array
        (
            [distance] => 0.99999994
            [id] => 1
            [metadata] => {"key1":"value1","key2":"value2"}
            [text] => Hello World
            [vector] => Array
                (
                    [0] => 0.1
                    [1] => 0.2
                    [2] => 0.3
                    [3] => 0.4
                    [4] => 0.5
                )

        )

    [1] => Array
        (
            [distance] => 0.96495044
            [id] => 2
            [metadata] =>
            [text] =>
            [vector] => Array
                (
                    [0] => 0.6
                    [1] => 0.7
                    [2] => 0.8
                    [3] => 0.9
                    [4] => 1
                )

        )

)

Full-Text Search Example

$client = new Milvus\Client();

$client->dropCollection("testing2");

// Full-Text Search

$client->createCollection(
    collection_name: "testing2",
    schema: $client->createSchema()
        ->addField("id", Milvus\DataType::INT64, is_primary: true)
        ->addField("text_sparse", Milvus\DataType::SPARSE_FLOAT_VECTOR)
        ->addField("document", Milvus\DataType::VARCHAR, max_length: 1000, enable_analyzer: true, enable_match: true)
        ->addFunction(
            name: "bm25",
            function_type: Milvus\FunctionType::BM25,
            input_field_names: ["document"],
            output_field_names: ["text_sparse"]
        ),
    index_params: $client->prepareIndexParams()
        ->addIndex(
            field_name: "text_sparse",
            index_name: "text_sparse_index",
            index_type: Milvus\IndexType::SPARSE_INVERTED_INDEX,
            metric_type: Milvus\MetricType::BM25
        ),
);

// Insert data
$client->insert(
    collection_name: "testing2",
    data: [
        [
            "id" => 1,
            "document" => "This is a sample document for testing.",
        ],
        [
            "id" => 2,
            "document" => "Another document for testing purposes.",
        ],
        [
            "id" => 3,
            "document" => "Milvus is a vector database designed for scalable similarity search.",
        ],
        [
            "id" => 4,
            "document" => "Full-text search enables users to find relevant documents quickly.",
        ],
        [
            "id" => 5,
            "document" => "This document contains information about PHP and Milvus integration.",
        ],
        [
            "id" => 6,
            "document" => "Testing the search functionality with various sample documents.",
        ],
        [
            "id" => 7,
            "document" => "Another example document to increase the dataset size.",
        ],
        [
            "id" => 8,
            "document" => "Sample data helps in validating the search and indexing features.",
        ]
    ]
);

print_r($client->search(
    collection_name: "testing2",
    data: ['sample'],
    anns_field: "text_sparse",
    limit: 5
));

Hybrid Search Example

$client = new Milvus\Client();

$client->dropCollection("testing");

// Hybrid Search
$client->createCollection(
    collection_name: "testing",
    schema: $client->createSchema()
        ->addField("id", Milvus\DataType::INT64, is_primary: true)
        ->addField("vector", Milvus\DataType::FLOAT_VECTOR, dim: 5)
        ->addField("document", Milvus\DataType::VARCHAR, max_length: 1000, enable_analyzer: true, enable_match: true)
        ->addField("text_sparse", Milvus\DataType::SPARSE_FLOAT_VECTOR)
        ->addFunction(
            name: "bm25",
            function_type: Milvus\FunctionType::BM25,
            input_field_names: ["document"],
            output_field_names: ["text_sparse"]
        ),
    index_params: $client->prepareIndexParams()
        ->addIndex(
            field_name: "vector",
            index_name: "my_index",
            index_type: Milvus\IndexType::AUTOINDEX,
            metric_type: Milvus\MetricType::COSINE
        )->addIndex(
            field_name: "text_sparse",
            index_name: "text_sparse_index",
            index_type: Milvus\IndexType::SPARSE_INVERTED_INDEX,
            metric_type: Milvus\MetricType::BM25
        ),
);

// Insert data
$client->insert(
    collection_name: "testing",
    data: [
        [
            "id" => 1,
            "vector" => [0.1, 0.2, 0.3, 0.4, 0.5],
            "document" => "This is a sample document for testing.",
        ],
        [
            "id" => 2,
            "vector" => [0.6, 0.7, 0.8, 0.9, 1.0],
            "document" => "Another document for testing purposes.",
        ],
        [
            "id" => 3,
            "vector" => [0.1, 0.2, 0.3, 0.4, 0.5],
            "document" => "Milvus is a vector database designed for scalable similarity search.",
        ],
        [
            "id" => 4,
            "vector" => [0.6, 0.7, 0.8, 0.9, 1.0],
            "document" => "Full-text search enables users to find relevant documents quickly.",
        ],
    ]
);

$query = "sample document";

print_r($client->hybridSearch(
    collection_name: "testing",
    search: [
        new HybridSearchRequest(
            data: [[0.1, 0.2, 0.3, 0.4, 0.5]], // embedding vector of the query
            anns_field: "vector",
            limit: 10,
            param: ["nprobe" => 10] // search parameters
        ),
        new HybridSearchRequest(
            data: [$query], // query string
            anns_field: "text_sparse",
            limit: 10,
            param: ["drop_ratio_search" => 0.2]
        )
    ],
    ranker: new WeightedRanker([0.5, 0.5]),
    output_fields: ["id", "document"]
));

Database Operations

Create Database

$client->createDatabase("my_db");

Switch Database

$client->usingDatabase("my_db");

List All Databases

$dbs = $client->listDatabases();

Describe Database

$info = $client->describeDatabase("my_db");

Drop Database

$client->dropDatabase("my_db");

Collection Operations

Create Collection

$client->createCollection(
    collection_name: "test_collection",
    schema: $client->createSchema()
        ->addField("id", Milvus\DataType::INT64, is_primary: true)
        ->addField("array", Milvus\DataType::ARRAY, element_type: Milvus\DataType::INT64, max_capacity: 10)
        ->addField("vector", Milvus\DataType::FLOAT_VECTOR, dim: 5)
        ->addField("text", Milvus\DataType::VARCHAR, max_length: 1000, nullable: true)
        ->addField("metadata", Milvus\DataType::JSON, nullable: true),
    index_params: $client->prepareIndexParams()
        ->addIndex(
            field_name: "vector",
            index_name: "my_index",
            index_type: Milvus\IndexType::AUTOINDEX,
            metric_type: Milvus\MetricType::COSINE
        ),
);

List All Collections

$collections = $client->listCollections();

Describe Collection

$desc = $client->describeCollection("test_collection");

Drop Collection

$client->dropCollection("test_collection");

Load/Release Collection

$client->loadCollection("test_collection");
$client->releaseCollection("test_collection");

Rename Collection

$client->renameCollection("old_name", "new_name");

Vector Data Operations

Insert Data

$entities = [
    ["id" => 1, "vector" => [1.0, 2.0, 3.0, 4.0, 5.0]],
    ["id" => 2, "vector" => [2.0, 2.0, 3.0, 4.0, 5.0]],
];
$client->insert("test_collection", $entities);

Upsert Data

$client->upsert("test_collection", $entities);

Query Data

$result = $client->query("test_collection", "id in [1,2]");

Delete Data

$client->delete("test_collection", "id in [1]");

Vector Search

$result = $client->search(
    collection_name: "test_collection",
    data: [[1.0, 2.0, 3.0, 4.0, 5.0]],
    anns_field: "vector",
    limit: 10,
    output_fields: ["id", "vector"]
);

Index Operations

Create Index

$indexParams = $client->prepareIndexParams();
$indexParams->addIndex(
    field_name: "vector",
    index_name: "my_index",
    index_type: Milvus\IndexType::AUTOINDEX,
    metric_type: Milvus\MetricType::COSINE
);
$client->createIndex("test_collection", $indexParams);

List Indexes

$indexes = $client->listIndexes("test_collection");

Users & Privileges

List Users

$users = $client->listUsers();

Create User

$client->createUser("test_user", "password");

Describe User

$userInfo = $client->describeUser("test_user");

Drop User

$client->dropUser("test_user");

Update Password

$client->updatePassword("test_user", "old_password", "new_password");

Roles & Privileges

List Roles

$roles = $client->listRoles();

Create Role

$client->createRole("admin");

Describe Role

$roleInfo = $client->describeRole("admin");

Drop Role

$client->dropRole("admin");

Grant Privilege to Role

$client->grantPrivilege("admin", "Collection", "Insert", "test_collection");

Advanced

Hybrid Search

$result = $client->hybridSearch(
    collection_name: "test_collection",
    search: [
        new HybridSearchRequest(
            data: [[0.1, 0.2, 0.3, 0.4, 0.5]],
            anns_field: "vector",
            limit: 10,
            param: []
        ),
    ],
    ranker: new Milvus\RRFRanker(10),
    output_fields: ["id", "vector"]
);

mathsgod / milvus-client-php

Maintainers

Details

README

Installation

Quick Start

Initialize Client

Example: Create Collection with Various Field Types and Search

Example Search Result

Full-Text Search Example

Hybrid Search Example

Database Operations

Create Database

Switch Database

List All Databases

Describe Database

Drop Database

Collection Operations

Create Collection

List All Collections

Describe Collection

Drop Collection

Load/Release Collection

Rename Collection

Vector Data Operations

Insert Data

Upsert Data

Query Data

Delete Data

Vector Search

Index Operations

Create Index

List Indexes

Users & Privileges

List Users

Create User

Describe User

Drop User

Update Password

Roles & Privileges

List Roles

Create Role

Describe Role

Drop Role

Grant Privilege to Role

Advanced

Hybrid Search

Reference