Rust

The Ahnlich Rust client library is a Rust crate that allows you to interact with Ahnlich DB and Ahnlich AI.

---

id: client-rust

title: Rust SDK (🦀)

sidebar_label: Rust

description: Official Rust client library to integrate with Ahnlich DB (exact vector search) and AI (semantic embeddings) services.

---

🦀 Ahnlich Rust SDK

The official Rust client to interface with ahnlich‑db (exact similarity search) and ahnlich‑ai (semantic similarity) over gRPC.

See full API docs and examples at docs.rs – ahnlich_client_rs

oaicite:0

🚀 Connecting to DB / AI Services

Both services expect:

• ahnlich-db should be accessible (default: 127.0.0.1:1369)
• ahnlich-ai should be separately reachable (default: 127.0.0.1:1370 or as configured)

The SDK supports optional W3C trace context via an Option<String> trace_id in all calls.

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let tracing_id: Option<String> = None;

    // ✔️ DB client:
    let db_client = ahnlich_client_rs::db::DbClient::new("127.0.0.1:1369".to_string()).await?;
    db_client.ping(tracing_id.clone()).await?;

    // ✔️ AI client:
    let ai_client = ahnlich_client_rs::ai::AIClient::new("127.0.0.1:1369".to_string()).await?;
    ai_client.ping(tracing_id.clone()).await?;

    Ok(())
}

🧠 Best Practices Always match vector/query dimension to the store’s declared dimension (e.g. 128 or 768).

Use DbClient::pipeline() or AIClient::pipeline() if you require ordered batched operations with predictable response order.

Metadata predicates are fast and flexible filtering tools—even if predicates aren't pre-indexed.

AI Stores automatically handle embedding; no need to compute embeddings manually for raw input.

Installation

Installation and Usage

Reference

Reference