index

type CombineStrategy string

type FlatIndex struct {
	// contains filtered or unexported fields
}

type HNSW struct {
	// Parameters
	M              int     // Max number of bi-directional links per node
	MaxM           int     // Max number of links for layer 0
	EfConstruction int     // Size of dynamic candidate list
	ML             float64 // Level assignment probability
	Seed           int64   // Random seed

	// Index data
	Nodes      map[string]*HNSWNode
	EntryPoint string

	// Distance function
	DistFunc func(a, b []float32) float32

	// Quantization
	Quantizer Quantizer
	// contains filtered or unexported fields
}

type HNSWAdapter struct {
	*HNSW
	// contains filtered or unexported fields
}

type HNSWNode struct {
	ID        string
	Vector    []float32
	Quantized []byte // Quantized vector data (optional)
	Level     int
	Neighbors [][]string // Neighbors at each level
	Deleted   bool
}

type HybridIndex struct {
	// contains filtered or unexported fields
}

type IVFAdapter struct {
	*IVFIndex
}

type IVFIndex struct {
	NCentroids int         // Number of cluster centroids
	Dimension  int         // Vector dimension
	Centroids  [][]float32 // Cluster centroids
	Invlists   [][]int     // Inverted lists (vector IDs per cluster)
	Vectors    [][]float32 // Original vectors (optional, for reranking)
	IDs        []string    // Vector IDs
	Trained    bool
	NProbe     int // Number of clusters to search
	// contains filtered or unexported fields
}

type IndexType string

type LSHConfig struct {
	NumTables    int   // Number of hash tables (more = better recall, more memory)
	NumHashFuncs int   // Number of hash functions per table (more = more selective)
	Dimension    int   // Vector dimension
	Seed         int64 // Random seed for reproducibility
}

type LSHIndex struct {
	// contains filtered or unexported fields
}

type LSHSearchResult struct {
	ID       string
	Distance float32
}

type MultiIndex struct {
	// contains filtered or unexported fields
}

type MultiIndexConfig struct {
	// Primary index for fast approximate search
	PrimaryIndex IndexType

	// Secondary indices for refinement
	SecondaryIndices []IndexType

	// Strategy for combining results
	CombineStrategy CombineStrategy

	// Reranking configuration
	RerankTopK int

	// Parallel search
	Parallel bool
}

type Quantizer interface {
	Encode(vec []float32) ([]byte, error)
	Decode(encoded []byte) ([]float32, error)
}

type VectorIndex interface {
	Insert(id string, vector []float32) error
	Search(query []float32, k int) ([]string, []float32)
	Delete(id string) error
	Size() int
}