Trait SemanticCache 

pub trait SemanticCache: Cache {
    // Required methods
    fn find_similar_by_embedding<'life0, 'life1, 'async_trait>(
        &'life0 self,
        query_embedding: &'life1 [f32],
        threshold: f32,
    ) -> Pin<Box<dyn Future<Output = Result<Option<(CacheEntry, f32)>, CacheError>> + Send + 'async_trait>>
       where Self: 'async_trait,
             'life0: 'async_trait,
             'life1: 'async_trait;
    fn store_with_embedding<'life0, 'life1, 'life2, 'life3, 'async_trait>(
        &'life0 self,
        query: &'life1 str,
        context: &'life2 str,
        response: &'life3 str,
        function_calls: Vec<String>,
        embedding: Vec<f32>,
    ) -> Pin<Box<dyn Future<Output = Result<(), CacheError>> + Send + 'async_trait>>
       where Self: 'async_trait,
             'life0: 'async_trait,
             'life1: 'async_trait,
             'life2: 'async_trait,
             'life3: 'async_trait;
}

Trait for semantic cache with similarity matching

Unlike regular caching, semantic caching finds similar queries based on embedding vectors rather than exact string matches.

Required Methods

fn find_similar_by_embedding<'life0, 'life1, 'async_trait>( &'life0 self, query_embedding: &'life1 [f32], threshold: f32, ) -> Pin<Box<dyn Future<Output = Result<Option<(CacheEntry, f32)>, CacheError>> + Send + 'async_trait>>

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

Find similar entries based on embedding similarity

Takes a pre-computed embedding vector and finds cached entries with embeddings above the similarity threshold.

Returns the best matching entry and its similarity score (0.0 to 1.0).

fn store_with_embedding<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, query: &'life1 str, context: &'life2 str, response: &'life3 str, function_calls: Vec<String>, embedding: Vec<f32>, ) -> Pin<Box<dyn Future<Output = Result<(), CacheError>> + Send + 'async_trait>>

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

Store with embedding for semantic matching

Stores the response along with its embedding vector for future similarity searches.

Implementors

impl SemanticCache for SemanticMemoryCache