Crate ahnlich_client_rs

Ahnlich Rust Client

A Rust client for communicating with Ahnlich’s DB and AI services over gRPC.

Overview

This crate provides clients for interacting with both the vector database (DB) and AI services in Ahnlich. It supports building pipelines for batching multiple requests in order and receiving their responses in sequence.

Internally, connections are managed via gRPC multiplexing—no external pooling is needed.

Clients

This crate exposes two primary client modules:

• db — for interacting with the vector database.
• ai — for interacting with the AI service.

Both clients provide direct methods and pipeline builders for batching commands.

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Example: DB Client

use ahnlich_client_rs::db::DbClient;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let db_client = DbClient::new("127.0.0.1:1369".to_string()).await?;
    let tracing_id: Option<String> = None;

    db_client.ping(tracing_id).await?;
    Ok(())
}

Example: AI Client

use ahnlich_client_rs::ai::AIClient;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let ai_client = AIClient::new("127.0.0.1:1369".to_string()).await?;
    let tracing_id: Option<String> = None;

    ai_client.ping(tracing_id).await?;
    Ok(())
}

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Pipelines

Pipelines enable multiple ordered operations to be issued in a batch. This ensures the operations are executed in sequence and allows for consistent read-after-write semantics.

Example: DB Pipeline

use ahnlich_client_rs::db::DbClient;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let db_client = DbClient::new("127.0.0.1:1369".to_string()).await?;
    let tracing_id: Option<String> = None;
    let mut pipeline = db_client.pipeline(tracing_id);

    pipeline.list_clients();
    pipeline.list_stores();
    let responses = pipeline.exec().await?;

    Ok(())
}

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Types & Utilities

This crate re-exports common parameter and result types via the prelude module. You can use it to simplify imports:

use ahnlich_client_rs::prelude::*;

For full type definitions and request builders, refer to the ahnlich_types crate.

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Testing

Example tests can be found in the repository to demonstrate usage, including:

• Creating stores
• Setting and getting values
• Listing clients and stores
• Predicate-based querying

These tests validate the behavior of both DB and AI pipelines in real scenarios, including with image inputs and structured metadata.

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Distributed Tracing

The client supports W3C Trace Context via optional traceparent headers. You can pass an Option<String> as tracing_id to propagate context across services.

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Modules

ai

db

error

prelude