Struct QdrantDriver 

pub struct QdrantDriver { /* private fields */ }

High-performance gRPC driver for Qdrant.

Uses gRPC/HTTP2 with zero-copy protobuf encoding:

• Encodes protobuf directly with pre-computed headers
• Reuses buffers to minimize allocations
• Uses memcpy for vector data (no per-element loop)

Example

use qail_qdrant::QdrantDriver;
use qail_core::prelude::*;

let driver = QdrantDriver::connect("localhost", 6334).await?;

let results = driver.search(
    "products",
    &embedding,
    10,
    Some(0.5),
).await?;

Implementations

impl QdrantDriver

pub async fn connect(host: &str, port: u16) -> QdrantResult<Self>

Connect to Qdrant gRPC endpoint (default port 6334).

pub async fn connect_addr(addr: &str) -> QdrantResult<Self>

Connect with address string.

pub async fn search( &mut self, collection: &str, vector: &[f32], limit: u64, score_threshold: Option<f32>, ) -> QdrantResult<Vec<ScoredPoint>>

Vector similarity search with zero-copy encoding.

Arguments

• collection - Collection name
• vector - Query vector
• limit - Max results
• score_threshold - Optional minimum score

Performance

Vector is encoded via memcpy (no per-element serialization).

pub async fn search_batch( &mut self, collection: &str, vectors: &[Vec<f32>], limit: u64, score_threshold: Option<f32>, ) -> QdrantResult<Vec<Vec<ScoredPoint>>>

Search multiple vectors concurrently using HTTP/2 pipelining.

This sends all requests concurrently over a single h2 connection, achieving 2-3x speedup compared to sequential searches.

Example

let vectors = vec![vec1, vec2, vec3];
let results = driver.search_batch("products", &vectors, 10, None).await?;

pub async fn search_ast(&mut self, cmd: &Qail) -> QdrantResult<Vec<ScoredPoint>>

Search using QAIL AST.

Extracts vector, collection, limit from the Qail command.

pub async fn upsert( &mut self, collection: &str, points: &[Point], wait: bool, ) -> QdrantResult<()>

Upsert points with zero-copy encoding.

pub async fn create_collection( &mut self, collection_name: &str, vector_size: u64, distance: Distance, on_disk: bool, ) -> QdrantResult<()>

Create a collection with specific vector parameters.

pub async fn delete_collection( &mut self, collection_name: &str, ) -> QdrantResult<()>

Delete a collection.

pub async fn delete_points( &mut self, collection_name: &str, point_ids: &[u64], ) -> QdrantResult<()>

Delete points by ID from a collection.