Struct InMemoryVectorStore 

pub struct InMemoryVectorStore { /* private fields */ }

An in-memory vector store using cosine similarity for search.

Collections are stored as nested HashMaps: collection name → chunk ID → chunk. All operations are async-safe via tokio::sync::RwLock.

Example

use adk_rag::{InMemoryVectorStore, VectorStore};

let store = InMemoryVectorStore::new();
store.create_collection("docs", 384).await?;

Implementations

impl InMemoryVectorStore

pub fn new() -> Self

Create a new empty in-memory vector store.

Trait Implementations

impl Debug for InMemoryVectorStore

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for InMemoryVectorStore

fn default() -> InMemoryVectorStore

Returns the “default value” for a type.

impl VectorStore for InMemoryVectorStore

fn create_collection<'life0, 'life1, 'async_trait>( &'life0 self, name: &'life1 str, _dimensions: usize, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

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

Create a named collection. No-op if it already exists.

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

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

Delete a named collection and all its data.

fn upsert<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, collection: &'life1 str, chunks: &'life2 [Chunk], ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

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

Upsert chunks into a collection. Chunks must have embeddings set.

fn delete<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, collection: &'life1 str, ids: &'life2 [&'life3 str], ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait,

Delete chunks by their IDs from a collection.

fn search<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, collection: &'life1 str, embedding: &'life2 [f32], top_k: usize, ) -> Pin<Box<dyn Future<Output = Result<Vec<SearchResult>>> + Send + 'async_trait>>

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

Search for the top_k most similar chunks to the given embedding.