How to add a vectorizer for a search index in C#

Question

Hiya

I'm currently working on a project that indexes a certain amount of data. This goes flawlessly when I create the index, with vectors, inside the portal.
Whenever I create such index with a C# program, it succeeds, but without the vectorizer. There isn't also any info on how/where you add a Vectorizer inside the new index with that code.

Thanks in advance!

EDIT: I found the answer myself, but for some reason i can't accept my own answer. See the answer posted by me to find the solution.

My code:

//Initialisation of new index
var indexName = _srchClient.IndexName;
var vectorSearchConfigName = "vectorconfig-" + _options.ProjectName;
var vectorSearchProfileName = "vectorprofile-" + _options.ProjectName;
//var semanticConfigName = "semanticconfig-" + _options.ProjectName;
var index = new SearchIndex(indexName)
{
    VectorSearch = new()
    {
        Algorithms =
        {
            new HnswAlgorithmConfiguration(vectorSearchConfigName)
        },
        Profiles =
        {
            new VectorSearchProfile(vectorSearchProfileName, vectorSearchConfigName)
        }
    },
    Fields =
    {
        new SimpleField("id", SearchFieldDataType.String) { IsKey = true },
        new SearchableField("content") { AnalyzerName = LexicalAnalyzerName.StandardLucene },
        new SimpleField("sourcePage", SearchFieldDataType.String) {IsFacetable = true},
        new SimpleField("sourceFile", SearchFieldDataType.String) {IsFacetable = true},
        new SearchField("embedding", SearchFieldDataType.Collection(SearchFieldDataType.Single))
        {
            VectorSearchDimensions = 1536,
            IsSearchable = true,
            VectorSearchProfileName = vectorSearchProfileName
        }
    },
    //When using free tier, this can't be used!
    //SemanticSearch = new()
    //{
    //    Configurations =
    //    {
    //        new SemanticConfiguration(semanticConfigName, new()
    //        {
    //            ContentFields =
    //            {
    //                new SemanticField("content")
    //            }
    //        })
    //    }
    //}
};
// Create a new search index
await _srchIndexClient.CreateIndexAsync(index);   

Answer 1

Hi again Thibault Verlinde

Thats awesome finding the solution, so let me paste your solution below as you cant accept your own answer, accept the answer and this helps the other community members who face the same problem. Thanks very much for the contrubution.

This is the updated code:

//Initialisation of new index
var indexName = _srchClient.IndexName;
var vectorSearchConfigName = "vectorconfig-" + _options.ProjectName;
var vectorSearchProfileName = "vectorprofile-" + _options.ProjectName;
var vectorizerName = "vectorizer-" + _options.ProjectName;
//var semanticConfigName = "semanticconfig-" + _options.ProjectName;
var index = new SearchIndex(indexName)
{
    VectorSearch = new()
    {
        Algorithms =
        {
            new HnswAlgorithmConfiguration(vectorSearchConfigName)
        },
        Profiles =
        {
            new VectorSearchProfile(vectorSearchProfileName, vectorSearchConfigName)
            {
                Vectorizer = vectorizerName
            }
        },
        Vectorizers =
        {
            new AzureOpenAIVectorizer(vectorizerName)
            {
                AzureOpenAIParameters = new AzureOpenAIParameters()
                {
                    ResourceUri = new Uri(_options.OAIEndpoint),
                    ApiKey = _options.OAIKey,
                    DeploymentId = _embeddingConfigs.EmbeddingModel
                }
            }
        }
    },
    Fields =
    {
        new SimpleField("id", SearchFieldDataType.String) { IsKey = true },
        new SearchableField("content") { AnalyzerName = LexicalAnalyzerName.StandardLucene },
        new SimpleField("sourcePage", SearchFieldDataType.String) {IsFacetable = true},
        new SimpleField("sourceFile", SearchFieldDataType.String) {IsFacetable = true},
        new SearchField("embedding", SearchFieldDataType.Collection(SearchFieldDataType.Single))
        {
            VectorSearchDimensions = _embeddingConfigs.VectorSearchDimensions,
            IsSearchable = true,
            VectorSearchProfileName = vectorSearchProfileName
        }
    },
    //When using free tier, this can't be used!
    //SemanticSearch = new()
    //{
    //    Configurations =
    //    {
    //        new SemanticConfiguration(semanticConfigName, new()
    //        {
    //            ContentFields =
    //            {
    //                new SemanticField("content")
    //            }
    //        })
    //    }
    //}
};

Answer 2

Hey there Thibault Verlinde

Thats a good question thanks for using QandA platform

So i guess you need to define and configure the vectorizer within the SearchIndex object before creating the index.

Lemme modify your code to include a vectorizer, below

var indexName = _srchClient.IndexName;
var vectorSearchConfigName = "vectorconfig-" + _options.ProjectName;
var vectorSearchProfileName = "vectorprofile-" + _options.ProjectName;

var vectorizer = new SearchIndexVectorizer
{
    Name = vectorSearchConfigName,
    Source = "/document/content", // Specify the source field for vectorization
    Tokenizer = new LexicalTokenizer(LexicalTokenizerName.StandardLucene),
    OdataType = "#Microsoft.Azure.Search.StandardAnalyzer"
};
var index = new SearchIndex(indexName)
{
    VectorSearch = new()
    {
        Algorithms =
        {
            new HnswAlgorithmConfiguration(vectorSearchConfigName)
        },
        Profiles =
        {
            new VectorSearchProfile(vectorSearchProfileName, vectorSearchConfigName)
        }
    },
    Fields =
    {
        new SimpleField("id", SearchFieldDataType.String) { IsKey = true },
        new SearchableField("content") { AnalyzerName = LexicalAnalyzerName.StandardLucene },
        new SimpleField("sourcePage", SearchFieldDataType.String) {IsFacetable = true},
        new SimpleField("sourceFile", SearchFieldDataType.String) {IsFacetable = true},
        new SearchField("embedding", SearchFieldDataType.Collection(SearchFieldDataType.Single))
        {
            VectorSearchDimensions = 1536,
            IsSearchable = true,
            VectorSearchProfileName = vectorSearchProfileName
        }
    },
    Vectorizers = { vectorizer } // Add the vectorizer to the index
};
// Now ccreate a new search index
await _srchIndexClient.CreateIndexAsync(index);

If this helps kindly accept the answer thanks much.