Struct VectorIndex 

pub struct VectorIndex { /* private fields */ }

Vector index for semantic search

Implementations

impl VectorIndex

pub fn new() -> Self

Create a new vector index

pub fn with_parallel_processing(parallel_processor: ParallelProcessor) -> Self

Create a new vector index with parallel processing support

pub fn add_vector(&mut self, id: String, embedding: Vec<f32>) -> Result<()>

Add a vector to the index

pub fn build_index(&mut self) -> Result<()>

Build the index from all added vectors

pub fn search( &self, query_embedding: &[f32], top_k: usize, ) -> Result<Vec<(String, f32)>>

Search for similar vectors

pub fn len(&self) -> usize

Get the number of vectors in the index

pub fn is_empty(&self) -> bool

Check if the index is empty

pub fn dimension(&self) -> Option<usize>

Get embedding dimension (assuming all embeddings have the same dimension)

pub fn remove_vector(&mut self, id: &str) -> Result<()>

Remove a vector from the index

pub fn get_ids(&self) -> Vec<String>

Get all vector IDs

pub fn contains(&self, id: &str) -> bool

Check if a vector exists

pub fn get_embedding(&self, id: &str) -> Option<&Vec<f32>>

Get embedding by ID

pub fn batch_add_vectors( &mut self, vectors: Vec<(String, Vec<f32>)>, ) -> Result<()>

Batch add multiple vectors in parallel with proper synchronization

pub fn batch_search( &self, queries: &[Vec<f32>], top_k: usize, ) -> Result<Vec<Vec<(String, f32)>>>

Batch search for multiple queries in parallel

pub fn compute_all_similarities(&self) -> HashMap<(String, String), f32>

Parallel similarity computation between all vectors with optimized chunking

pub fn find_similar( &self, query_embedding: &[f32], threshold: f32, ) -> Result<Vec<(String, f32)>>

Find vectors within a similarity threshold

pub fn statistics(&self) -> VectorIndexStatistics

Calculate statistics about the index

Trait Implementations

impl Default for VectorIndex

fn default() -> Self

Returns the “default value” for a type.