Set

Schema

This request accepts an optional schema field. When it is omitted, the server uses the public schema. Set schema to target a store in another schema.

Inserts or updates embeddings and their associated metadata into a vector store managed by the AI service. This operation is central to populating a store with new data or refreshing existing entries to keep the dataset consistent and relevant for similarity search.

Source Code Example

Click to expand

Rust

use ahnlich_client_rs::ai::AiClient;
use ahnlich_client_rs::error::AhnlichError;
use ahnlich_types::ai::preprocess::PreprocessAction;
use ahnlich_types::ai::query::Set;
use ahnlich_types::keyval::{AiStoreEntry, StoreInput, StoreValue};
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 data for Set
    let set_params = Set {
        store: "Main0".to_string(),
        schema: Some("analytics".to_string()),
        execution_provider: None,
        preprocess_action: PreprocessAction::NoPreprocessing as i32,
        inputs: vec![
            AiStoreEntry {
                key: Some(StoreInput { value: Some(Value::RawString("Adidas Yeezy".into())) }),
                value: Some(StoreValue { value: HashMap::new() }),
            },
            AiStoreEntry {
                key: Some(StoreInput { value: Some(Value::RawString("Nike Air Jordans".into())) }),
                value: Some(StoreValue { value: HashMap::new() }),
            },
        ],
        model_params: HashMap::new(),
    };


    // Run the set command
    let res = client.set(set_params, None).await?;
    println!("Inserted entries: {:?}", res.upsert);


    Ok(())
}

Parameters

• params: Set — The embeddings and metadata to be stored, including the store key and value. If a key already exists, this call updates the associated record.
  • 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.

Returns

• Ok(SetResult) — Contains the outcome of the insertion or update (e.g., confirmation of success, affected keys).

• Err(AhnlichError) — If the operation fails due to invalid input, conflicts, or server-side errors.

Behavior (explains the code, brief)

• Prepares the Set request payload inside a tonic::Request.

• Adds tracing context if provided.

• Sends the request via the AI client’s set RPC method.

• Waits for the response and extracts the typed result.

• Returns a SetResult indicating success or failure.