Typesense-dotnet

.net client for Typesense.

You can get the NuGet package here.

Feel free to make issues or create pull requests if you find any bugs or there are missing features.

Setup

Setup in service collection so it can be dependency injected. The AddTypesenseClient can be found in the Typesense.Setup namespace. Remember to change the settings to match your Typesense service. Right now you can specify multiple nodes, but the implementation has not been completed yet, so if you want to use this for multiple nodes, then put a load balancer in front of your services and point the settings to your load balancer.

var provider = new ServiceCollection()
    .AddTypesenseClient(config =>
    {
        config.ApiKey = "mysecretapikey";
        config.Nodes = new List<Node>
        {
            new Node("localhost", "8108", "http")
        };
    }).BuildServiceProvider();

After that you can get it from the provider instance or dependency inject it.

var typesenseClient = provider.GetService<ITypesenseClient>();

Create collection

When you create the collection, you can specify each field with name, type and if it should be a facet, an optional or an indexed field.

var schema = new Schema(
    "Addresses",
    new List<Field>
    {
        new Field("id", FieldType.Int32, false),
        new Field("houseNumber", FieldType.Int32, false),
        new Field("accessAddress", FieldType.String, false, true),
        new Field("metadataNotes", FieldType.String, false, true, false),
    },
    "houseNumber");

var createCollectionResult = await typesenseClient.CreateCollection(schema);

The example uses camelCase by default for field names, but you override this on the document you want to insert. Below is an example using snake_case.

public class Address
{
    [JsonPropertyName("id")]
    public string Id { get; set; }
    [JsonPropertyName("house_number")]
    public int HouseNumber { get; set; }
    [JsonPropertyName("access_address")]
    public string AccessAddress { get; set; }
    [JsonPropertyName("metadata_notes")]
    public string MetadataNotes { get; set; }
}

Update collection

Update existing collection.

var updateSchema = new UpdateSchema(new List<UpdateSchemaField>
{
    // Example deleting existing field.
    new UpdateSchemaField("metadataNotes", drop: true),
    // Example adding a new field.
    new UpdateSchemaField("city", FieldType.String, facet: false, optional: true)
});

var updateCollectionResponse = await typesenseClient.UpdateCollection("Addresses", updateSchema);

Index document

var address = new Address
{
    Id = 1,
    HouseNumber = 2,
    AccessAddress = "Smedgade 25B"
};

var createDocumentResult = await typesenseClient.CreateDocument<Address>("Addresses", address);

Upsert document

var address = new Address
{
    Id = 1,
    HouseNumber = 2,
    AccessAddress = "Smedgade 25B"
};

var upsertResult = await typesenseClient.UpsertDocument<Address>("Addresses", address);

Search document in collection

var query = new SearchParameters("Smed", "accessAddress");
var searchResult = await typesenseClient.Search<Address>("Addresses", query);

Search grouped

var query = new GroupedSearchParameters("Stark", "company_name", "country");
var response = await _client.SearchGrouped<Company>("companies", query);

Multi search documents

Multi search goes from one query to four, if you need more than that please open an issue and I'll implement more.

Example of using a single query in multi-search.

var query = new MultiSearchParameters("companies", "Stark", "company_name");

var response = await _client.MultiSearch<Company>(queryOne);

Example of using a two queries in multi-search.

var queryOne = new MultiSearchParameters("companies", "Stark", "company_name");
var queryTwo = new MultiSearchParameters("employees", "Kenny", "person_name");

var (r1, r2) = await _client.MultiSearch<Company, Employee>(queryOne, queryTwo);

Example of using a three queries in multi-search (you get the pattern currently it goes up to four.).

var queryOne = new MultiSearchParameters("companies", "Stark", "company_name");
var queryTwo = new MultiSearchParameters("employees", "Kenny", "person_name");
var queryThree = new MultiSearchParameters("companies", "Awesome Corp.", "company_name");

var (r1, r2, r3) = await _client.MultiSearch<Company, Employee, Company>(queryOne, queryTwo, queryThree);

Vector search

Typesense supports the ability to add embeddings generated by your Machine Learning models to each document, and then doing a nearest-neighbor search on them. This lets you build features like similarity search, recommendations, semantic search, visual search, etc. Here is an example of how to create a vector schema, a vector document, and perform a multi search using a vector as a query parameter.

const string COLLECTION_NAME = "address_vector_search";

var schema = new Schema(
    COLLECTION_NAME,
    new List<Field>
    {
        new Field("vec", FieldType.FloatArray, 4)
    });

_ = await _client.CreateCollection(schema);

await _client.CreateDocument(
    COLLECTION_NAME,
    new AddressVectorSearch()
    {
        Id = "0",
        Vec = new float[] { 0.04F, 0.234F, 0.113F, 0.001F }
    });

var query = new MultiSearchParameters(COLLECTION_NAME, "*")
{
    // vec:([0.96826, 0.94, 0.39557, 0.306488], k:100)
    VectorQuery = new(
        vector: new float[] { 0.96826F, 0.94F, 0.39557F, 0.306488F },
        k: 100)
};

var response = await _client.MultiSearch<AddressVectorSearch>(query);

Retrieve a document on id

var retrievedDocument = await typesenseClient.RetrieveDocument<Address>("Addresses", "1");

Update document on id

var address = new Address
{
    Id = 1,
    HouseNumber = 2,
    AccessAddress = "Smedgade 25B"
};

var updateDocumentResult = await typesenseClient.UpdateDocument<Address>("Addresses", "1", address);

Delete document on id

var deleteResult = await typesenseClient.DeleteDocument<Address>("Addresses", "1");

Update documents using filter

var updateResult = await typesenseClient.UpdateDocuments("Addresses", "houseNumber:=2", { "accessAddress": "Smedgade 25C" });

Delete documents using filter

var deleteResult = await typesenseClient.DeleteDocuments("Addresses", "houseNumber:>=3", 100);

Drop a collection on name

var deleteCollectionResult = await typesenseClient.DeleteCollection("Addresses");

Import documents

The default batch size is 40. The default ImportType is Create. You can pick between three different import types Create, Upsert, Update. The returned values are a list of ImportResponse that contains a success code, error and the failed document as a string representation.

var importDocumentResults = await typesenseClient.ImportDocuments<Address>("Addresses", addresses, 40, ImportType.Create);

Export documents

var addresses = await typesenseClient.ExportDocuments<Address>("Addresses");

Api keys

Create key

ExpiresAt is optional. Value is optional.

var apiKey = new Key(
    "Example key one",
    new[] { "*" },
    new[] { "*" });

var createdKey = await typesenseClient.CreateKey(apiKey);

Retrieve key

var retrievedKey = await typesenseClient.RetrieveKey(0);

List keys

var keys = await typesenseClient.ListKeys();

Delete key

var deletedKey = await typesenseClient.DeleteKey(0);

Generate Scoped Search key

var scopedSearchKey = typesenseClient.GenerateScopedSearchKey("MainOrParentAPIKey", "{\"filter_by\":\"accessible_to_user_ids:2\"}");

Curation

While Typesense makes it really easy and intuitive to deliver great search results, sometimes you might want to promote certain documents over others. Or, you might want to exclude certain documents from a query's result set.

Using overrides, you can include or exclude specific documents for a given query.

Upsert

var searchOverride = new SearchOverride(new List<Include> { new Include("2", 1) }, new Rule("Sul", "exact"));
var upsertSearchOverrideResponse = await typesenseClient.UpsertSearchOverride("Addresses", "addresses-override", searchOverride);

List all overrides

var listSearchOverrides = await typesenseClient.ListSearchOverrides("Addresses");

Retrieve overrides

var retrieveSearchOverride = await typesenseClient.RetrieveSearchOverride("Addresses", "addresses-override");

Delete override

var deletedSearchOverrideResult = await typesenseClient.DeleteSearchOverride("Addresses", "addresses-override");

Collection alias

An alias is a virtual collection name that points to a real collection. Read more here.

Upsert collection alias

var upsertCollectionAlias = await typesenseClient.UpsertCollectionAlias("Address_Alias", new CollectionAlias("Addresses"));

List all collection aliases

var listCollectionAliases = await typesenseClient.ListCollectionAliases();

Retrieve collection alias

var retrieveCollectionAlias = await typesenseClient.RetrieveCollectionAlias("Address_Alias");

Delete collection alias

var deleteCollectionAlias = await typesenseClient.DeleteCollectionAlias("Addresses_Alias");

Synonyms

The synonyms feature allows you to define search terms that should be considered equivalent. For eg: when you define a synonym for sneaker as shoe, searching for sneaker will now return all records with the word shoe in them, in addition to records with the word sneaker. Read more here.

Upsert synonym

var upsertSynonym = await typesenseClient.UpsertSynonym("Addresses", "Address_Synonym", new SynonymSchema(new List<string> { "Sultan", "Soltan", "Softan" }));

Retrieve a synonym

var retrieveSynonym = await typesenseClient.RetrieveSynonym("Addresses", "Address_Synonym");

List all synonyms

var listSynonyms = await typesenseClient.ListSynonyms("Addresses");

Delete synonym

var deleteSynonym = await typesenseClient.DeleteSynonym("Addresses", "Address_Synonym");

Metrics

Get current RAM, CPU, Disk & Network usage metrics.

var metrics = await typesenseClient.RetrieveMetrics();

Stats

Get stats about API endpoints.

var stats = await typesenseClient.RetrieveStats();

Health