Struct S3VectorsVectorStore 

pub struct S3VectorsVectorStore<M> { /* private fields */ }

Implementations

impl<M> S3VectorsVectorStore<M>

where M: EmbeddingModel,

pub fn new( embedding_model: M, client: Client, bucket_name: &str, index_name: &str, ) -> Self

pub fn bucket_name(&self) -> &str

pub fn set_bucket_name(&mut self, bucket_name: &str)

pub fn index_name(&self) -> &str

pub fn set_index_name(&mut self, index_name: &str)

pub fn client(&self) -> &Client

Trait Implementations

impl<M> InsertDocuments for S3VectorsVectorStore<M>

where M: EmbeddingModel,

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

Insert documents into the vector store.

impl<M> VectorStoreIndex for S3VectorsVectorStore<M>

where M: EmbeddingModel,

type Filter = S3SearchFilter

async fn top_n<T: for<'a> Deserialize<'a> + Send>( &self, req: VectorSearchRequest<S3SearchFilter>, ) -> Result<Vec<(f64, String, T)>, VectorStoreError>

Get the top n documents based on the distance to the given query. The result is a list of tuples of the form (score, id, document)

async fn top_n_ids( &self, req: VectorSearchRequest<S3SearchFilter>, ) -> Result<Vec<(f64, String)>, VectorStoreError>

Same as top_n but returns the document ids only.