Struct InMemoryVectorStore 

pub struct InMemoryVectorStore { /* private fields */ }

内存向量存储

Implementations

impl InMemoryVectorStore

pub fn new() -> InMemoryVectorStore

创建新的内存向量存储

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,

带最低分数阈值的相似度检索。

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>

返回该向量存储自带的文本嵌入器(若有)。

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,

文本相似度检索:用 embed_query 返回的嵌入器把 query 向量化后再检索。