Struct SentenceTransformerGenerator 

pub struct SentenceTransformerGenerator { /* private fields */ }

Transformer-based embedding generator supporting multiple models

Implementations

impl SentenceTransformerGenerator

pub fn new(config: EmbeddingConfig) -> Self

pub fn with_model_type( config: EmbeddingConfig, model_type: TransformerModelType, ) -> Self

pub fn roberta(config: EmbeddingConfig) -> Self

Create a new RoBERTa model generator

pub fn distilbert(config: EmbeddingConfig) -> Self

Create a new DistilBERT model generator

pub fn multilingual_bert(config: EmbeddingConfig) -> Self

Create a new multilingual BERT model generator

pub fn model_type(&self) -> &TransformerModelType

Get the current model type

pub fn model_details(&self) -> ModelDetails

Get detailed information about the current model

pub fn supports_language(&self, language_code: &str) -> bool

Check if the model supports a specific language

pub fn estimate_inference_time(&self, text_length: usize) -> u64

Get the estimated inference time for a given text length

pub fn model_size_mb(&self) -> usize

Get the memory footprint of the model in MB

pub fn efficiency_rating(&self) -> f32

Get efficiency rating (higher is better/faster)

Trait Implementations

impl AsAny for SentenceTransformerGenerator

fn as_any(&self) -> &dyn Any

fn as_any_mut(&mut self) -> &mut dyn Any

impl EmbeddingGenerator for SentenceTransformerGenerator

fn generate(&self, content: &EmbeddableContent) -> Result<Vector>

Generate embedding for content

fn dimensions(&self) -> usize

Get the embedding dimensions

fn config(&self) -> &EmbeddingConfig

Get the model configuration

fn generate_batch(&self, contents: &[EmbeddableContent]) -> Result<Vec<Vector>>

Generate embeddings for multiple contents in batch