Struct InstrumentedSparseEmbeddingModel 

pub struct InstrumentedSparseEmbeddingModel {
    pub inner: Arc<dyn SparseEmbeddingModel>,
    pub alias: String,
    pub provider_id: String,
    pub timeout: Option<Duration>,
    pub retry: Option<RetryConfig>,
}

Wrapper around a SparseEmbeddingModel adding timeout / retry / metrics.

Fields

inner: Arc<dyn SparseEmbeddingModel>

alias: String

provider_id: String

timeout: Option<Duration>

retry: Option<RetryConfig>

Trait Implementations

impl ModelInfo for InstrumentedSparseEmbeddingModel

fn model_id(&self) -> &str

The underlying model identifier (e.g. a HuggingFace repo ID or API model name).

fn active_execution_providers(&self) -> Vec<String>

Names of the ONNX Runtime execution providers requested for the underlying session, in priority order. Empty for remote and non-ONNX models.

impl SparseEmbeddingModel for InstrumentedSparseEmbeddingModel

fn embed<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, texts: &'life1 [&'life2 str], ) -> Pin<Box<dyn Future<Output = Result<SparseEmbedResult>> + Send + 'async_trait>>

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

Embed a batch of text strings into learned-sparse vectors.

fn vocab_size(&self) -> u32

The size of the term space the produced term_ids index into.

fn warmup<'life0, 'async_trait>( &'life0 self, ) -> Pin<Box<dyn Future<Output = Result<()>> + Send + 'async_trait>>

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

Optional warmup hook (e.g. load weights into memory on first access). The default is a no-op.