Crate arc_vector_rust

The ArcVector Vector Database client

This library uses GRPC to connect to the ArcVector server and allows you to access most if not all features. If you find a missing feature, please open an issue.

If you use this library, you’ll likely want to import the usual types and functions:

#[allow(unused_import)]
use arc_vector_rust::prelude::*;

To work with a ArcVector database, you’ll first need to connect by creating a ArcVectorClient:

let mut config = ArcVectorClientConfig::from_url(url);
config.api_key = std::env::var("ARC_VECTOR_API_KEY").ok();
ArcVectorClient::new(Some(config))

ArcVector works with Collections of Points. To add vector data, you first create a collection:

use arc_vector_rust::arc_vector::{VectorParams, VectorsConfig};
use arc_vector_rust::arc_vector::vectors_config::Config;
let response = arc_vector_client
    .create_collection(&CreateCollection {
        collection_name: "my_collection".into(),
        vectors_config: Some(VectorsConfig {
            config: Some(Config::Params(VectorParams {
                size: 512,
                distance: Distance::Cosine as i32,
                ..Default::default()
            })),
        }),
        ..Default::default()
    })
    .await?;

The most interesting parts are the collection_name and the vectors_config.size (the length of vectors to store) and distance (which is the Distance measure to gauge similarity for the nearest neighbors search).

Now we have a collection, we can insert (or rather upsert) points. Points have an id, one or more vectors and a payload. We can usually do that in bulk, but for this example, we’ll add a single point:

let point = PointStruct {
    id: Some(PointId::from(42)), // unique u64 or String
    vectors: Some(vec![0.0_f32; 512].into()),
    payload: std::collections::HashMap::from([
        ("great".into(), Value::from(true)),
        ("level".into(), Value::from(9000)),
        ("text".into(), Value::from("Hi ArcVector!")),
        ("list".into(), Value::from(vec![1.234, 0.815])),
    ]),
};

let response = arc_vector_client
    .upsert_points("my_collection", vec![point], None)
    .await?;

Finally, we can retrieve points in various ways, the canonical one being a plain similarity search:

let response = arc_vector_client
    .search_points(&SearchPoints {
        collection_name: "my_collection".to_string(),
        vector: vec![0.0_f32; 512],
        limit: 4,
        with_payload: Some(true.into()),
        ..Default::default()
    })
    .await?;

You can also add a filters: Some(filters) field to the SearchPoints argument to filter the result. See the Filter documentation for details.

Modules

arc_vector

client

error

filters

prelude

serde