VectorStore

Last update:

May 18, 2026

Description

Initializes a new Vector Store Client instance. This function acts as the factory for connecting to various vector store providers (such as InMemory, Milvus, Pinecone, Chroma, and Qdrant). It handles connection configuration, authentication, and default collection settings.

Syntax

VectorStore(struct configuration)

History

New in ColdFusion 2025.0.08

Parameters

Name	Type	Required	Description
configuration	Struct	Yes	A structure containing connection and collection configuration details.

Configuration struct details

The configuration structure supports the following keys. Applicability may vary by provider (Milvus, Pinecone, Qdrant, Chroma).

Milvus

Key	Type	Default	Description	Required
url	string		Milvus service endpoint	Yes
dimension	number		Vector dimension	Yes
collectionName	string	default	Name of the collection	No
databaseName	string	default	Database name	No
metricType	string	COSINE	Similarity metric	No
indexType	string	HNSW	Index type used for vector search	No
apiKey	string		API key for authentication	No
username	string		Username for authentication	No
password	string		Password for authentication	No

connectionSettings	Struct			No
The keys are specified below:
callTimeout	duration	60s	RPC call timeout	No
connectionTimeout	duration	20s	Connection timeout	No
keepAlive	boolean	true	Enable keep-alive	No
keepAliveTime	duration	30s	Keep-alive interval	No
keepAliveTimeout	duration	5s	Keep-alive timeout	No
idleTimeout	duration	600s	Idle timeout	No
deadline	duration	180s	Overall deadline	No

retrySettings	Struct			No
The keys are specified below:
maxRetries	number	10	Maximum retries	No
retryOnRateLimit	boolean	true	Retry on rate limit	No
initialBackoff	duration	500ms	Initial backoff	No
maxBackoff	duration	3s	Maximum backoff	No
backoffMultiplier	number	3	Backoff multiplier	No

Pinecone

Key	Type	Default	Description	Required
apiKey	string		API key	Yes
indexName	string		Index name	Yes
namespace	string	default	Namespace	No

podConfig	Struct
The keys are specified below:
dimension	number		Vector dimension	Conditional
environment	string		Deployment environment	Conditional
podType	string		Pod type	Conditional

serverlessConfig	Struct
The keys are specified below:
dimension	number		Vector dimension	Yes
cloud	string		Cloud provider	Conditional
region	string		Cloud region	Conditional
deletionProtection	boolean		Deletion protection	No

IMPORTANT: Either podConfig or serverlessConfig is required, and all fields in their respective sections are required.

Qdrant

Key	Type	Default	Description	Required
url	string		Service endpoint	Yes
dimension	number		Vector dimension	Yes
collectionName	string	default	Collection name	No
apiKey	string		API key	No
metricType	string	COSINE	Similarity metric	No

connectionSettings	Struct			No
The keys are specified below:
callTimeout	duration	60s	RPC call timeout	No
connectionTimeout	duration	20s	Connection timeout	No
keepAlive	boolean	true	Enable keep-alive	No
keepAliveTime	duration	30s	Keep-alive interval	No
keepAliveTimeout	duration	5s	Keep-alive timeout	No
idleTimeout	duration	600s	Idle timeout	No

retrySettings	Struct			No
The keys are specified below:
maxRetries	number	10	Maximum retries	No
initialBackoff	duration	500ms	Initial backoff	No
maxBackoff	duration	3000ms	Maximum backoff	No
backoffMultiplier	number	3	Backoff multiplier	No

Chroma

Key	Type	Default	Description	Required
url	string		Service endpoint	Yes
collectionName	string	default	Collection name	No
databaseName	string	default	Database name	No
tenantName	string	default	Tenant name	No
callTimeout	duration	60s	Request timeout	No

Returns

A VectorStoreClient object used to perform data and collection operations.

Usage

Use this function to establish the connection before performing any CRUD or search operations. If an embeddingModel is provided in the configuration, the client will automatically handle text-to-vector conversion.

Example

<cfscript>

    try {

        vectorstoreclient = vectorStore({

            "provider": "milvus",

            "url": "http://your-milvus-host:19530",

            "databaseName": "default",

            "collectionName": "cf_docs",

            "dimension": 768,

            "metricType": "COSINE",

            "indexType": "HNSW",

            "apiKey": "",

            "embeddingModel": {

                "provider": "ollama",

                "modelName": "nomic-embed-text:latest",

                "baseUrl": "http://localhost:11434",

                "dimension": 768

            }

        });

        writeDump(vectorstoreclient.add({

            "text": "ColdFusion is a rapid application development platform.",

            "metadata": { "product": "coldfusion", "year": 2025 }

        }));

        writeDump(vectorstoreclient.search({

            "text": "rapid application development",

            "minScore": 0.25,

            "topK": 5,

            "filter": { "year": 2025 }

        }));

    } 

    catch (any e) {

        writeDump(e);

    }

</cfscript>

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