Struct InMemoryVectorStore 

pub struct InMemoryVectorStore { /* private fields */ }

In-memory vector store

Implementations

impl InMemoryVectorStore

pub fn new() -> InMemoryVectorStore

Creates a new in-memory vector store

Trait Implementations

impl Default for InMemoryVectorStore

fn default() -> InMemoryVectorStore

Returns the “default value” for a type.

impl VectorStore for InMemoryVectorStore

fn add_documents<'life0, 'async_trait>( &'life0 self, documents: Vec<Document>, embeddings: Vec<Vec<f32>>, ) -> Pin<Box<dyn Future<Output = Result<Vec<String>, VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, InMemoryVectorStore: 'async_trait,

Adds documents.

fn similarity_search<'life0, 'life1, 'async_trait>( &'life0 self, query_embedding: &'life1 [f32], k: usize, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>, VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, InMemoryVectorStore: 'async_trait,

Searches similar documents.

fn similarity_search_with_min_score<'life0, 'life1, 'async_trait>( &'life0 self, query_embedding: &'life1 [f32], k: usize, min_score: Option<f32>, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>, VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, InMemoryVectorStore: 'async_trait,

Similarity search with a minimum score threshold.

fn similarity_search_with_filter<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, query_embedding: &'life1 [f32], k: usize, filter: Option<&'life2 MetadataFilter>, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>, VectorStoreError>> + Send + 'async_trait>>

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

Similarity search with metadata filtering.

fn get_document<'life0, 'life1, 'async_trait>( &'life0 self, id: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Option<Document>, VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, InMemoryVectorStore: 'async_trait,

Gets document by ID.

fn get_embedding<'life0, 'life1, 'async_trait>( &'life0 self, id: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Option<Vec<f32>>, VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, InMemoryVectorStore: 'async_trait,

Gets document embedding by ID.

fn delete_document<'life0, 'life1, 'async_trait>( &'life0 self, id: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, InMemoryVectorStore: 'async_trait,

Deletes document.

fn count<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = usize> + Send + 'async_trait>>

where 'life0: 'async_trait, InMemoryVectorStore: 'async_trait,

Returns document count.

fn clear<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + 'async_trait>>

where 'life0: 'async_trait, InMemoryVectorStore: 'async_trait,

Clears store.

fn embed_query(&self) -> Option<&dyn Embeddings>

Returns this vector store’s built-in text embedder, if any.

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

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

Text similarity search: vectorizes query with the embedder returned by embed_query, then searches.