Qdrant.Client 1.19.0

Qdrant .NET SDK

📥 Installation

dotnet add package Qdrant.Client

📖 Documentation

Usage examples are available throughout the Qdrant documentation.

🔌 Getting started

Creating a client

A client can be instantiated with

var client = new QdrantClient("localhost");

which creates a client that will connect to Qdrant on http://localhost:6334.

Internally, the high level client uses a low level gRPC client to interact with Qdrant. Additional constructor overloads provide more control over how the gRPC client is configured. The following example configures a client to use TLS, validating the certificate using its thumbprint, and also configures API key authentication:

var channel = QdrantChannel.ForAddress("https://localhost:6334", new ClientConfiguration
{
    ApiKey = "<api key>",
    CertificateThumbprint = "<certificate thumbprint>"
});
var grpcClient = new QdrantGrpcClient(channel);
var client = new QdrantClient(grpcClient);

var channel = GrpcChannel.ForAddress($"https://localhost:6334", new GrpcChannelOptions
{
  HttpHandler = new WinHttpHandler
  {
    ServerCertificateValidationCallback =
      CertificateValidation.Thumbprint("<certificate thumbprint>")
  }
});
var callInvoker = channel.Intercept(metadata =>
{
  metadata.Add("api-key", "<api key>");
  return metadata;
});

var grpcClient = new QdrantGrpcClient(callInvoker);
var client = new QdrantClient(grpcClient);

User-Agent

When a channel is created via QdrantChannel.ForAddress (which both QdrantClient("localhost") and the ClientConfiguration overloads use), the client adds a qdrant-dotnet/<version> token to the request User-Agent alongside the gRPC library token, e.g.:

grpc-dotnet/2.71.0 (.NET 8.0.4; CLR 8.0.4; net8.0; linux; x64) qdrant-dotnet/1.19.0

This lets server-side tooling attribute traffic to the .NET client and its version. On .NET Framework, where the underlying channel handler must be configured manually, the token is not added automatically.

Working with collections

Once a client has been created, create a new collection

await client.CreateCollectionAsync("my_collection", 
    new VectorParams { Size = 100, Distance = Distance.Cosine });

Insert vectors into a collection

// generate some vectors
var random = new Random();
var points = Enumerable.Range(1, 100).Select(i => new PointStruct
{
  Id = (ulong)i,
  Vectors = Enumerable.Range(1, 100).Select(_ => (float)random.NextDouble()).ToArray(),
  Payload = 
  { 
    ["color"] = "red", 
    ["rand_number"] = i % 10 
  }
}).ToList();

var updateResult = await client.UpsertAsync("my_collection", points);

Search for similar vectors

var queryVector = Enumerable.Range(1, 100).Select(_ => (float)random.NextDouble()).ToArray();

// return the 5 closest points
var points = await client.SearchAsync(
  "my_collection",
  queryVector,
  limit: 5);

Search for similar vectors with filtering condition

// static import Conditions to easily build filtering
using static Qdrant.Client.Grpc.Conditions;

// return the 5 closest points where rand_number >= 3
var points = await _client.SearchAsync(
  "my_collection",
  queryVector,
  filter: Range("rand_number", new Range { Gte = 3 }),
  limit: 5);