Struct InMemoryVectorStore 

pub struct InMemoryVectorStore { /* private fields */ }

Linear-scan in-memory vector store.

Implementations

impl InMemoryVectorStore

pub fn new(embedder: Arc<dyn Embeddings>) -> Self

New empty store with the given embedder and Cosine distance.

pub fn with_distance(embedder: Arc<dyn Embeddings>, distance: Distance) -> Self

New empty store with explicit distance.

pub fn distance(&self) -> Distance

Currently configured distance metric.

Trait Implementations

impl VectorStore for InMemoryVectorStore

fn add_texts<'life0, 'async_trait>( &'life0 mut self, texts: Vec<String>, metadata: Option<Vec<HashMap<String, Value>>>, ) -> Pin<Box<dyn Future<Output = Result<Vec<String>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Add documents (text + optional metadata). The store is responsible for embedding them. Returns the IDs assigned.

fn add_vectors<'life0, 'async_trait>( &'life0 mut self, vectors: Vec<Vec<f32>>, texts: Vec<String>, metadata: Option<Vec<HashMap<String, Value>>>, ) -> Pin<Box<dyn Future<Output = Result<Vec<String>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Add pre-embedded vectors directly. Useful when the caller has already paid the embedding cost.

fn similarity_search<'life0, 'life1, 'async_trait>( &'life0 self, query: &'life1 str, k: usize, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Similarity search: embed the query, return top-k matches.

fn similarity_search_by_vector<'life0, 'async_trait>( &'life0 self, query_vector: Vec<f32>, k: usize, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Similarity search by pre-computed query vector.

fn delete<'life0, 'async_trait>( &'life0 mut self, ids: Vec<String>, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

Delete documents by ID. IDs not found are silently ignored.

fn len(&self) -> usize

Number of documents currently stored.

fn similarity_search_with_filter<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, query: &'life1 str, k: usize, filter: &'life2 Filter, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Similarity search with a metadata filter.

fn is_empty(&self) -> bool

True if no documents are stored.