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);

Important

IMPORTANT NOTICE for .NET Framework

.NET Framework has limited supported for gRPC over HTTP/2, but it can be enabled by

Configuring qdrant to use TLS, and you must use HTTPS, so you will need to set up server certificate validation
Referencing System.Net.Http.WinHttpHandler 6.0.1 or later, and configuring WinHttpHandler as the inner handler for GrpcChannelOptions

The following example configures a client for .NET Framework to use TLS, validating the certificate using its thumbprint, and also configures API key authentication:

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);

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