Struct EmbeddingModel 

pub struct EmbeddingModel { /* private fields */ }

Embedding model for generating semantic embeddings

Implementations

impl EmbeddingModel

pub async fn new(config: EmbeddingConfig) -> Result<Self>

Create new embedding model with real Candle inference

pub fn encode(&mut self, text: &str) -> Result<Embedding>

Generate embedding for a single text using TRUE BERT neural network inference

pub fn encode_batch(&mut self, texts: &[String]) -> Result<Vec<Embedding>>

Generate embeddings for multiple texts

pub fn encode_batch_parallel( &mut self, texts: &[String], ) -> Result<(Vec<Embedding>, Vec<String>)>

Generate embeddings for multiple texts with parallel processing and error recovery

pub fn encode_batch_with_retry( &mut self, texts: &[String], max_retries: usize, retry_delay_ms: u64, ) -> Result<(Vec<Embedding>, Vec<String>, usize)>

Batch encoding with retry logic and graceful error handling

pub fn clear_cache(&mut self)

Clear the embedding cache

pub fn cache_size(&self) -> usize

Get cache size

pub fn config(&self) -> &EmbeddingConfig

Get model configuration

pub fn has_tokenizer(&self) -> bool

Check if real tokenizer is loaded

pub fn dimension(&self) -> usize

Get embedding dimension

pub fn health_check(&self) -> EmbeddingHealth

Get embedding model health status

pub fn clear_cache_selective(&mut self, keep_recent: Option<usize>)

Clear cache with optional size limit

pub fn cache_stats(&self) -> CacheStats

Get cache statistics