Azure Search Documents Dotnet

using Azure.Identity;using Azure.Search.Documents;
// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>var credential = new DefaultAzureCredential(    DefaultAzureCredential.DefaultEnvironmentVariableName);// Or use a specific credential directly in production:// See https://learn.microsoft.com/dotnet/api/overview/azure/identity-readme?view=azure-dotnet#credential-classes// var credential = new ManagedIdentityCredential();var client = new SearchClient(    new Uri(Environment.GetEnvironmentVariable("SEARCH_ENDPOINT")),    Environment.GetEnvironmentVariable("SEARCH_INDEX_NAME"),    credential);

using Azure;using Azure.Search.Documents;
var credential = new AzureKeyCredential(    Environment.GetEnvironmentVariable("SEARCH_API_KEY"));var client = new SearchClient(    new Uri(Environment.GetEnvironmentVariable("SEARCH_ENDPOINT")),    Environment.GetEnvironmentVariable("SEARCH_INDEX_NAME"),    credential);

using Azure.Search.Documents.Indexes;using Azure.Search.Documents.Indexes.Models;
// Define model with attributespublic class Hotel{    [SimpleField(IsKey = true, IsFilterable = true)]    public string HotelId { get; set; }
    [SearchableField(IsSortable = true)]    public string HotelName { get; set; }
    [SearchableField(AnalyzerName = LexicalAnalyzerName.EnLucene)]    public string Description { get; set; }
    [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]    public double? Rating { get; set; }
    [VectorSearchField(VectorSearchDimensions = 1536, VectorSearchProfileName = "vector-profile")]    public ReadOnlyMemory<float>? DescriptionVector { get; set; }}
// Create indexvar indexClient = new SearchIndexClient(endpoint, credential);var fieldBuilder = new FieldBuilder();var fields = fieldBuilder.Build(typeof(Hotel));
var index = new SearchIndex("hotels"){    Fields = fields,    VectorSearch = new VectorSearch    {        Profiles = { new VectorSearchProfile("vector-profile", "hnsw-algo") },        Algorithms = { new HnswAlgorithmConfiguration("hnsw-algo") }    }};
await indexClient.CreateOrUpdateIndexAsync(index);

var index = new SearchIndex("hotels"){    Fields =    {        new SimpleField("hotelId", SearchFieldDataType.String) { IsKey = true, IsFilterable = true },        new SearchableField("hotelName") { IsSortable = true },        new SearchableField("description") { AnalyzerName = LexicalAnalyzerName.EnLucene },        new SimpleField("rating", SearchFieldDataType.Double) { IsFilterable = true, IsSortable = true },        new SearchField("descriptionVector", SearchFieldDataType.Collection(SearchFieldDataType.Single))        {            VectorSearchDimensions = 1536,            VectorSearchProfileName = "vector-profile"        }    }};

var searchClient = new SearchClient(endpoint, indexName, credential);
// Upload (add new)var hotels = new[] { new Hotel { HotelId = "1", HotelName = "Hotel A" } };await searchClient.UploadDocumentsAsync(hotels);
// Merge (update existing)await searchClient.MergeDocumentsAsync(hotels);
// Merge or Upload (upsert)await searchClient.MergeOrUploadDocumentsAsync(hotels);
// Deleteawait searchClient.DeleteDocumentsAsync("hotelId", new[] { "1", "2" });
// Batch operationsvar batch = IndexDocumentsBatch.Create(    IndexDocumentsAction.Upload(hotel1),    IndexDocumentsAction.Merge(hotel2),    IndexDocumentsAction.Delete(hotel3));await searchClient.IndexDocumentsAsync(batch);

var options = new SearchOptions{    Filter = "rating ge 4",    OrderBy = { "rating desc" },    Select = { "hotelId", "hotelName", "rating" },    Size = 10,    Skip = 0,    IncludeTotalCount = true};
SearchResults<Hotel> results = await searchClient.SearchAsync<Hotel>("luxury", options);
Console.WriteLine($"Total: {results.TotalCount}");await foreach (SearchResult<Hotel> result in results.GetResultsAsync()){    Console.WriteLine($"{result.Document.HotelName} (Score: {result.Score})");}

var options = new SearchOptions{    Facets = { "rating,count:5", "category" }};
var results = await searchClient.SearchAsync<Hotel>("*", options);
foreach (var facet in results.Value.Facets["rating"]){    Console.WriteLine($"Rating {facet.Value}: {facet.Count}");}

// Autocompletevar autocompleteOptions = new AutocompleteOptions { Mode = AutocompleteMode.OneTermWithContext };var autocomplete = await searchClient.AutocompleteAsync("lux", "suggester-name", autocompleteOptions);
// Suggestionsvar suggestOptions = new SuggestOptions { UseFuzzyMatching = true };var suggestions = await searchClient.SuggestAsync<Hotel>("lux", "suggester-name", suggestOptions);

using Azure.Search.Documents.Models;
// Pure vector searchvar vectorQuery = new VectorizedQuery(embedding){    KNearestNeighborsCount = 5,    Fields = { "descriptionVector" }};
var options = new SearchOptions{    VectorSearch = new VectorSearchOptions    {        Queries = { vectorQuery }    }};
var results = await searchClient.SearchAsync<Hotel>(null, options);

var options = new SearchOptions{    QueryType = SearchQueryType.Semantic,    SemanticSearch = new SemanticSearchOptions    {        SemanticConfigurationName = "my-semantic-config",        QueryCaption = new QueryCaption(QueryCaptionType.Extractive),        QueryAnswer = new QueryAnswer(QueryAnswerType.Extractive)    }};
var results = await searchClient.SearchAsync<Hotel>("best hotel for families", options);
// Access semantic answersforeach (var answer in results.Value.SemanticSearch.Answers){    Console.WriteLine($"Answer: {answer.Text} (Score: {answer.Score})");}
// Access captionsawait foreach (var result in results.Value.GetResultsAsync()){    var caption = result.SemanticSearch?.Captions?.FirstOrDefault();    Console.WriteLine($"Caption: {caption?.Text}");}

var vectorQuery = new VectorizedQuery(embedding){    KNearestNeighborsCount = 5,    Fields = { "descriptionVector" }};
var options = new SearchOptions{    QueryType = SearchQueryType.Semantic,    SemanticSearch = new SemanticSearchOptions    {        SemanticConfigurationName = "my-semantic-config"    },    VectorSearch = new VectorSearchOptions    {        Queries = { vectorQuery }    }};
// Combines keyword search, vector search, and semantic rankingvar results = await searchClient.SearchAsync<Hotel>("luxury beachfront", options);

using Azure;
try{    var results = await searchClient.SearchAsync<Hotel>("query");}catch (RequestFailedException ex) when (ex.Status == 404){    Console.WriteLine("Index not found");}catch (RequestFailedException ex){    Console.WriteLine($"Search error: {ex.Status} - {ex.ErrorCode}: {ex.Message}");}