Struct VectorizeVectorStore 

pub struct VectorizeVectorStore<M> { /* private fields */ }

A vector store backed by Cloudflare Vectorize.

This struct implements VectorStoreIndex to provide vector similarity search using Cloudflare’s globally distributed Vectorize service.

Implementations

impl<M> VectorizeVectorStore<M>

pub fn new( model: M, account_id: impl Into<String>, index_name: impl Into<String>, api_token: impl Into<String>, ) -> Self

Creates a new Vectorize vector store.

Arguments

• model - The embedding model to use for query embedding
• account_id - Cloudflare account ID
• index_name - Name of the Vectorize index
• api_token - Cloudflare API token with Vectorize read permissions

Trait Implementations

impl<M: Clone> Clone for VectorizeVectorStore<M>

fn clone(&self) -> VectorizeVectorStore<M>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<M: Debug> Debug for VectorizeVectorStore<M>

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

Formats the value using the given formatter.

impl<M> InsertDocuments for VectorizeVectorStore<M>

where M: EmbeddingModel + Sync + Send,

async fn insert_documents<Doc: Serialize + Embed + Send>( &self, documents: Vec<(Doc, OneOrMany<Embedding>)>, ) -> Result<(), VectorStoreError>

impl<M> VectorStoreIndex for VectorizeVectorStore<M>

where M: EmbeddingModel + Sync + Send,

type Filter = VectorizeFilter

The filter type for this backend.

async fn top_n<T: for<'a> Deserialize<'a> + Send>( &self, req: VectorSearchRequest<Self::Filter>, ) -> Result<Vec<(f64, String, T)>, VectorStoreError>

Returns the top N most similar documents as (score, id, document) tuples.

async fn top_n_ids( &self, req: VectorSearchRequest<Self::Filter>, ) -> Result<Vec<(f64, String)>, VectorStoreError>

Returns the top N most similar document IDs as (score, id) tuples.