Types

VectorItem

Represents a single vector with its associated data.

type VectorItem struct {
    Id       string                 `json:"id"`                // Unique identifier
    Vector   []float32              `json:"vector,omitempty"`  // Vector data
    Contents NullableContents       `json:"contents,omitempty"` // Optional text content  
    Metadata map[string]interface{} `json:"metadata,omitempty"` // Optional metadata
}

Fields

Field	Type	Description
`Id`	`string`	Unique identifier for the vector (required)
`Vector`	`[]float32`	The vector data as float32 slice
`Contents`	`NullableContents`	Optional text content associated with the vector
`Metadata`	`map[string]interface{}`	Optional key-value pairs for filtering and retrieval

CreateIndexParams

Parameters for creating a new encrypted vector index.

type CreateIndexParams struct {
    IndexName      string     `json:"index_name"`            // Unique identifier for the index
    IndexKey       []byte     `json:"index_key"`             // 32-byte encryption key
    IndexConfig    IndexModel `json:"index_config,omitempty"` // Index configuration
    Metric         *string    `json:"metric,omitempty"`       // Distance metric
    EmbeddingModel *string    `json:"embedding_model,omitempty"` // Associated embedding model
}

Fields

Field	Type	Required	Description
`IndexName`	`string`	Yes	Unique identifier for the index
`IndexKey`	`[]byte`	Yes	32-byte encryption key (use GenerateKey() to create)
`IndexConfig`	`IndexModel`	No	Index configuration (IVF, IVFFlat, or IVFPQ)
`Metric`	`*string`	No	Distance metric (“euclidean”, “cosine”)
`EmbeddingModel`	`*string`	No	Name of embedding model to associate

Index Configuration Types

IndexModel Interface

All index configuration types implement this interface.

type IndexModel interface {
    ToIndexConfig() *internal.IndexConfig
}

IVF Configuration

Create an IVF (Inverted File) index configuration.

func IndexIVF(dimension int32) *indexIVF

IVFFlat Configuration

Create an IVFFlat (Inverted File Flat) index configuration for higher accuracy.

func IndexIVFFlat(dimension int32) *indexIVFFlat

IVFPQ Configuration

Create an IVFPQ (Inverted File with Product Quantization) index configuration for memory efficiency.

func IndexIVFPQ(dimension int32, pqDim int32, pqBits int32) *indexIVFPQ

Parameters

Parameter	Type	Description
`dimension`	`int32`	The dimensionality of vectors that will be stored
`pqDim`	`int32`	Product quantization dimension (typically dimension/8 or dimension/16)
`pqBits`	`int32`	Bits per PQ code (typically 8, higher = more accurate but larger)

Response Types

QueryResponse

Response from similarity search operations.

type QueryResponse = internal.QueryResponse

Contains search results with similar vectors and their metadata.

QueryResultItem

A single result from a similarity search query.

type QueryResultItem = internal.QueryResultItem

Represents one matching vector with its similarity score and metadata.

GetResponse

Response from Get operations containing retrieved vectors.

type GetResponse = internal.GetResponseModel

ListIDsResponse

Response from ListIDs operations.

type ListIDsResponse = internal.ListIDsResponse

Contains the list of vector IDs in the index.

TrainParams

Parameters for training an encrypted vector index.

type TrainParams struct {
    BatchSize  *int32   `json:"batch_size,omitempty"`  // Number of vectors per training batch
    MaxIters   *int32   `json:"max_iters,omitempty"`   // Maximum training iterations  
    Tolerance  *float64 `json:"tolerance,omitempty"`   // Convergence tolerance
    MaxMemory  *int32   `json:"max_memory,omitempty"`  // Maximum memory usage in MB
    NLists     *int32   `json:"n_lists,omitempty"`     // Number of IVF clusters
}

Fields

Field	Type	Description
`BatchSize`	`*int32`	Number of vectors processed per training batch (default: 2048)
`MaxIters`	`*int32`	Maximum training iterations (default: 100)
`Tolerance`	`*float64`	Convergence tolerance for training (default: 1e-6)
`MaxMemory`	`*int32`	Maximum memory usage in MB, 0 = no limit (default: 0)
`NLists`	`*int32`	Number of IVF clusters, 0 = auto-determine (default: 0)

Introduction

Client

Encrypted Index

Types & Helpers

VectorItem

Fields

CreateIndexParams

Fields

Index Configuration Types

IndexModel Interface

IVF Configuration

IVFFlat Configuration

IVFPQ Configuration

Parameters

Response Types

QueryResponse

QueryResultItem

GetResponse

ListIDsResponse

TrainParams

Fields

​VectorItem

​Fields

​CreateIndexParams

​Fields

​Index Configuration Types

​IndexModel Interface

​IVF Configuration

​IVFFlat Configuration

​IVFPQ Configuration

​Parameters

​Response Types

​QueryResponse

​QueryResultItem

​GetResponse

​ListIDsResponse

​TrainParams

​Fields

VectorItem

Fields

CreateIndexParams

Fields

Index Configuration Types

IndexModel Interface

IVF Configuration

IVFFlat Configuration

IVFPQ Configuration

Parameters

Response Types

QueryResponse

QueryResultItem

GetResponse

ListIDsResponse

TrainParams

Fields