feature request: add seperate function for full-text-search for filters

Qdrant Rust client

The Qdrant - High-Performance Vector Search at Scale - client for Rust.

Documentation:

Qdrant documentation: https://qdrant.tech/documentation/
Crate documentation: https://docs.rs/qdrant-client

Installation

cargo add qdrant-client

Package is available in crates.io

Examples

A list of example snippets can be found here

More examples can be found in the examples folder

Dependencies

The client uses gRPC via the Tonic library.

To change anything in the protocol buffer definitions, you need the protoc Protocol Buffers compiler, along with Protocol Buffers resource files.

Refer to the Tonic installation guide for more details.

Usage

Run Qdrant with enabled gRPC interface:

# With env variable
docker run -p 6333:6333 -p 6334:6334 \
    -e QDRANT__SERVICE__GRPC_PORT="6334" \
    qdrant/qdrant

Or by updating the configuration file:

service:
  grpc_port: 6334

Making requests

Add necessary dependencies:

cargo add qdrant-client anyhow tonic tokio serde-json --features tokio/rt-multi-thread

Add search example from examples/search.rs to your src/main.rs:

use qdrant_client::qdrant::{
    Condition, CreateCollectionBuilder, Distance, Filter, PointStruct, ScalarQuantizationBuilder,
    SearchParamsBuilder, SearchPointsBuilder, UpsertPointsBuilder, VectorParamsBuilder,
};
use qdrant_client::{Payload, Qdrant, QdrantError};

#[tokio::main]
async fn main() -> Result<(), QdrantError> {
    // Example of top level client
    // You may also use tonic-generated client from `src/qdrant.rs`
    let client = Qdrant::from_url("http://localhost:6334").build()?;

    let collections_list = client.list_collections().await?;
    dbg!(collections_list);
    // collections_list = {
    //   "collections": [
    //     {
    //       "name": "test"
    //     }
    //   ]
    // }

    let collection_name = "test";
    client.delete_collection(collection_name).await?;

    client
        .create_collection(
            CreateCollectionBuilder::new(collection_name)
                .vectors_config(VectorParamsBuilder::new(10, Distance::Cosine))
                .quantization_config(ScalarQuantizationBuilder::default()),
        )
        .await?;

    let collection_info = client.collection_info(collection_name).await?;
    dbg!(collection_info);

    let payload: Payload = serde_json::json!(
        {
            "foo": "Bar",
            "bar": 12,
            "baz": {
                "qux": "quux"
            }
        }
    )
    .try_into()
    .unwrap();

    let points = vec![PointStruct::new(0, vec![12.; 10], payload)];
    client
        .upsert_points(UpsertPointsBuilder::new(collection_name, points))
        .await?;

    let search_result = client
        .search_points(
            SearchPointsBuilder::new(collection_name, [11.; 10], 10)
                .filter(Filter::all([Condition::matches("bar", 12)]))
                .with_payload(true)
                .params(SearchParamsBuilder::default().exact(true)),
        )
        .await?;
    dbg!(&search_result);
    // search_result = [
    //   {
    //     "id": 0,
    //     "version": 0,
    //     "score": 1.0000001,
    //     "payload": {
    //       "bar": 12,
    //       "baz": {
    //         "qux": "quux"
    //       },
    //       "foo": "Bar"
    //     }
    //   }
    // ]

    let found_point = search_result.result.into_iter().next().unwrap();
    let mut payload = found_point.payload;
    let baz_payload = payload.remove("baz").unwrap().into_json();
    println!("baz: {}", baz_payload);
    // baz: {"qux":"quux"}

    Ok(())
}

Or run the example from this project directly:

cargo run --example search

Qdrant Cloud

Qdrant Cloud is a managed service for Qdrant.

The client needs to be configured properly to access the service.

make sure to use the correct port (6334)
make sure to pass your API KEY

use qdrant_client::Qdrant;

let client = Qdrant::from_url("http://xxxxxxxxxx.eu-central.aws.cloud.qdrant.io:6334")
    // Use an environment variable for the API KEY for example
    .api_key(std::env::var("QDRANT_API_KEY"))
    .build()?;

	pub struct Range {
	#[prost(double, optional, tag = "1")]
	pub lt: ::core::option::Option<f64>,
	#[prost(double, optional, tag = "2")]
	pub gt: ::core::option::Option<f64>,
	#[prost(double, optional, tag = "3")]
	pub gte: ::core::option::Option<f64>,
	#[prost(double, optional, tag = "4")]
	pub lte: ::core::option::Option<f64>,
	}

	#[allow(clippy::derive_partial_eq_without_eq)]
	#[derive(Clone, PartialEq, ::prost::Message)]
	pub struct Vector {
	#[prost(float, repeated, tag = "1")]
	pub data: ::prost::alloc::vec::Vec<f32>,
	}

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