The Ballerina Milvus vector store module provides a comprehensive API for integrating with Milvus vector database, enabling efficient storage, retrieval, and management of high-dimensional vectors. This module implements the Ballerina AI VectorStore interface and supports multiple vector search algorithms including dense, sparse, and hybrid vector search modes.

To utilize the Milvus connector, you must have access to a running Milvus instance. You can use one of the following methods for that.

1. Make sure Docker is installed on your system.

2. Use the following command to start a Milvus standalone instance in docker

# Download the installation script
$ curl -sfL https://raw.githubusercontent.com/milvus-io/milvus/master/scripts/standalone_embed.sh -o standalone_embed.sh

#Start the Docker container
$ bash standalone_embed.sh start

For detailed installation instructions, refer to the official Milvus documentation.

• Linux/macOS: Run Milvus in Docker
• Windows: Run Milvus in Docker on Windows

Zilliz Cloud provides a fully managed Milvus service. Follow these steps to set up your cloud instance:

1. Sign up to Zilliz Cloud: Visit Zilliz Cloud and create an account.

   

2. Set up your account: Complete the account setup process with your details.

   

3. Create a new cluster: From the welcome page, select "Create Cluster" to start setting up your Milvus instance.

   

4. Configure cluster details: Provide the necessary configuration details for your cluster, including cluster name, cloud provider, and region.

   

5. Download credentials: Once your cluster is created, download the authentication credentials and connection details.

   

6. Generate API Key: Navigate to the API Keys section in your cluster dashboard and generate an API key for authentication.

import ballerina/ai;
import ballerinax/ai.milvus;

ai:VectorStore vectorStore = check new milvus:VectorStore(
    serviceUrl = "add-milvus-service-url",
    apiKey = "add-api-key",
    config = {
        collectionName: "add-collection-name"
    }
);

ai:Error? result = vectorStore.add(
    [
        {
            id: "1",
            embedding: [1.0, 2.0, 3.0],
            chunk: {
                'type: "text", 
                content: "This is a chunk"
            }
        }
    ]
);

ai:VectorMatch[]|ai:Error matches = vectorStore.query({
    embedding: [1.1, 2.1, 3.1],
    filters: {
        // optional metadata filters
    }
});

The Ballerina Milvus vector store module provides practical examples illustrating usage in various scenarios. Explore these examples.

1. Movie recommendation system This example shows how to use Milvus vector store APIs to implement a movie recommendation system that stores movie embeddings and queries them to find similar movies based on vector similarity and metadata filtering.

Issues and Projects tabs are disabled for this repository as this is part of the Ballerina Library. To report bugs, request new features, start new discussions, view project boards, etc., go to the Ballerina Library parent repository. This repository only contains the source code for the module.

1. Download and install Java SE Development Kit (JDK) version 21 (from one of the following locations).

   • Oracle

   • OpenJDK

     Note: Set the JAVA_HOME environment variable to the path name of the directory into which you installed JDK.

2. Generate a GitHub access token with read package permissions, then set the following env variables:

   export packageUser=<Your GitHub Username>
   export packagePAT=<GitHub Personal Access Token>

Execute the commands below to build from the source.

1. To build the package:

   ./gradlew clean build

2. To run the tests:

   ./gradlew clean test

3. To run a group of tests

   ./gradlew clean test -Pgroups=<test_group_names>

4. To build the without the tests:

   ./gradlew clean build -x test

5. To debug the package with a remote debugger:

   ./gradlew clean build -Pdebug=<port>

6. To debug with Ballerina language:

   ./gradlew clean build -PbalJavaDebug=<port>

7. Publish the generated artifacts to the local Ballerina central repository:

   ./gradlew clean build -PpublishToLocalCentral=true

8. Publish the generated artifacts to the Ballerina central repository:

   ./gradlew clean build -PpublishToCentral=true

As an open-source project, Ballerina welcomes contributions from the community.

For more information, go to the contribution guidelines.

All the contributors are encouraged to read the Ballerina Code of Conduct.