Struct rig::vector_store::NoIndex

pub struct NoIndex;

Trait Implementations

impl VectorStoreIndex for NoIndex

async fn top_n_from_query( &self, _query: &str, _n: usize, ) -> Result<Vec<(f64, DocumentEmbeddings)>, VectorStoreError>

Get the top n documents based on the distance to the given embedding. The distance is calculated as the cosine distance between the prompt and the document embedding. The result is a list of tuples with the distance and the document.

async fn top_n_from_embedding( &self, _prompt_embedding: &Embedding, _n: usize, ) -> Result<Vec<(f64, DocumentEmbeddings)>, VectorStoreError>

Get the top n documents based on the distance to the given embedding. The distance is calculated as the cosine distance between the prompt and the document embedding. The result is a list of tuples with the distance and the document.

fn top_n_documents_from_query<T: for<'a> Deserialize<'a>>( &self, query: &str, n: usize, ) -> impl Future<Output = Result<Vec<(f64, T)>, VectorStoreError>> + Send

Same as top_n_from_query but returns the documents without its embeddings. The documents are deserialized into the given type.

fn top_n_ids_from_query( &self, query: &str, n: usize, ) -> impl Future<Output = Result<Vec<(f64, String)>, VectorStoreError>> + Send

Same as top_n_from_query but returns the document ids only.

fn top_n_documents_from_embedding<T: for<'a> Deserialize<'a>>( &self, prompt_embedding: &Embedding, n: usize, ) -> impl Future<Output = Result<Vec<(f64, T)>, VectorStoreError>> + Send

Same as top_n_from_embedding but returns the documents without its embeddings. The documents are deserialized into the given type.

fn top_n_ids_from_embedding( &self, prompt_embedding: &Embedding, n: usize, ) -> impl Future<Output = Result<Vec<(f64, String)>, VectorStoreError>> + Send

Same as top_n_from_embedding but returns the document ids only.