Get Sim N

Performs a similarity search in a vector store, retrieving the top-N most similar embeddings to a given query vector. This operation is the core of the AI client’s retrieval capability, enabling semantic search, recommendation, and nearest-neighbor lookups.

Source Code Example

Click to expand

use ahnlich_client_rs::ai::AiClient;
use ahnlich_client_rs::error::AhnlichError;
use ahnlich_types::ai::preprocess::PreprocessAction;
use ahnlich_types::ai::query::GetSimN;
use ahnlich_types::algorithm::algorithms::Algorithm;
use ahnlich_types::keyval::StoreInput;
use ahnlich_types::keyval::store_input::Value;
use std::collections::HashMap;


#[tokio::main]
async fn main() -> Result<(), AhnlichError> {
    // Connect to AI server
    let addr = "127.0.0.1:1370";
    let client = AiClient::new(addr.to_string()).await?;


    // Prepare the search input
    let search_input = StoreInput {
        value: Some(Value::RawString("example query".into())),
    };


    // Construct GetSimN parameters
    let params = GetSimN {
        store: "Main0".to_string(),
        search_input: Some(search_input),
        closest_n: 3, // number of similar entries to retrieve
        algorithm: Algorithm::CosineSimilarity as i32,
        execution_provider: None,
        preprocess_action: PreprocessAction::NoPreprocessing as i32,
        condition: None,
        model_params: HashMap::new(),
    };


    // Run the GetSimN command
    let res = client.get_sim_n(params, None).await?;
    println!("GetSimN result: {:?}", res);


    Ok(())
}

Parameters

• params: GetSimN — The query input, including the target vector and configuration such as the number of neighbors (N) to return and optional filters.

  • model_params: HashMap<String, String> — Optional runtime parameters for the AI model. For face detection models (Buffalo_L, SFace+YuNet), supports "confidence_threshold" to control minimum detection confidence. Pass an empty HashMap to use model defaults. See Model Parameters for details.

• tracing_id: Option<String> — Optional trace parent ID for distributed observability across services.

Returns

• Ok(GetSimNResult) — Contains the ranked list of the top-N closest embeddings along with their similarity scores and associated metadata.

• Err(AhnlichError) — Returned when the query fails, parameters are invalid, or the service encounters an error.

Behavior (explains the code, brief)

• Wraps the GetSimN query in a tonic::Request.

• Adds trace propagation metadata if provided.

• Sends the request to the AI service’s get_sim_n RPC method.

• Waits for the response and unwraps the result.

• Returns a GetSimNResult with the similarity matches.