Struct LocalEmbeddingProvider 

pub struct LocalEmbeddingProvider { /* private fields */ }

Local embedding provider using sentence transformers

Runs embedding models locally using candle-transformers or similar. Provides offline embedding generation with no external dependencies.

Models Supported

• sentence-transformers/all-MiniLM-L6-v2 (384 dims, default)
• sentence-transformers/all-mpnet-base-v2 (768 dims, higher quality)
• sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 (384 dims, multilingual)

Example

use do_memory_core::embeddings::{EmbeddingProvider, LocalEmbeddingProvider, LocalConfig};

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let config = LocalConfig::new(
        "sentence-transformers/all-MiniLM-L6-v2",
        384
    );
    let provider = LocalEmbeddingProvider::new(config).await?;

    let embedding = provider.embed_text("Hello world").await?;
    println!("Generated embedding with {} dimensions", embedding.len());
    Ok(())
}

Implementations

impl LocalEmbeddingProvider

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

Create a new local embedding provider

Arguments

• config - Model configuration specifying which model to use

Returns

Configured local embedding provider

pub async fn is_loaded(&self) -> bool

Check if model is loaded

pub fn model_info(&self) -> Value

Get model information

Trait Implementations

impl EmbeddingProvider for LocalEmbeddingProvider

fn embed_text<'life0, 'life1, 'async_trait>( &'life0 self, text: &'life1 str, ) -> Pin<Box<dyn Future<Output = Result<Vec<f32>>> + Send + 'async_trait>>

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

Generate embedding for a single text

fn embed_batch<'life0, 'life1, 'async_trait>( &'life0 self, texts: &'life1 [String], ) -> Pin<Box<dyn Future<Output = Result<Vec<Vec<f32>>>> + Send + 'async_trait>>

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

Generate embeddings for multiple texts in batch

fn embedding_dimension(&self) -> usize

Get the embedding dimension for this provider

fn model_name(&self) -> &str

Get the model name/identifier

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

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

Check if the provider is available/configured

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

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

Warm up the provider (load models, test connections, etc.)

fn metadata(&self) -> Value

Get provider-specific metadata

fn similarity<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, text1: &'life1 str, text2: &'life2 str, ) -> Pin<Box<dyn Future<Output = Result<f32>> + Send + 'async_trait>>

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

Calculate semantic similarity between two texts