azure-search-documents-dotnet

作者原文

Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET", "SearchClient", "SearchIndexClient", "vector search C#", "semantic search .NET", "hybrid search", "Azure.Search.Documents".

SkillPi 解读

能完成的任务

azure-search-documents-dotnet

适合谁

按原作者介绍判断适用范围。

输入和输出

以完整原文为准，云端传输需由使用者确认。

软件、账号及付费要求

本包是 azure-search-documents-dotnet 的 Microsoft Azure SDK 文档与示例，不含已验证的可执行安装程序。使用示例前核对 SDK 包名、版本、Azure 租户/订阅和实际终结点，仅授予本任务所需的最小权限；不把管理员凭据或真实机密写进示例、日志或提交。示例连接的云服务可能接收所选文本、文档、音频、消息、日志或其他输入并产生费用；确认数据范围、脱敏及费用后再连接。创建、更新、删除资源、密钥/权限变更或发送消息须由用户逐项确认，在测试资源上验证，避免生产数据覆盖与不可逆操作。文档中的占位终结点和样例输入必须替换并核对；网站仅核对固定源版本、完整附件和静态/病毒库证据，未运行 SDK、验证外部服务兼容性或授权任何云访问。

限制与区别

原作者介绍原样保留，中文为对应翻译。文档示例未经本站运行；版本、兼容性和效果为作者陈述。

实测状态

未测试

安全评级与访问范围

caution · 静态证据核验，不代表运行安全保证。

本包是 azure-search-documents-dotnet 的 Microsoft Azure SDK 文档与示例，不含已验证的可执行安装程序。使用示例前核对 SDK 包名、版本、Azure 租户/订阅和实际终结点，仅授予本任务所需的最小权限；不把管理员凭据或真实机密写进示例、日志或提交。示例连接的云服务可能接收所选文本、文档、音频、消息、日志或其他输入并产生费用；确认数据范围、脱敏及费用后再连接。创建、更新、删除资源、密钥/权限变更或发送消息须由用户逐项确认，在测试资源上验证，避免生产数据覆盖与不可逆操作。文档中的占位终结点和样例输入必须替换并核对；网站仅核对固定源版本、完整附件和静态/病毒库证据，未运行 SDK、验证外部服务兼容性或授权任何云访问。

使用前请由宿主核对并授权实际文件读写、外部服务和联网目的地；本站的核验不会授予任何运行权限。

原始 SKILL.md

---
name: azure-search-documents-dotnet
description: |
  Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET", "SearchClient", "SearchIndexClient", "vector search C#", "semantic search .NET", "hybrid search", "Azure.Search.Documents".
license: MIT
metadata:
  author: Microsoft
  version: "1.0.0"
  package: Azure.Search.Documents
---

# Azure.Search.Documents (.NET)

Build search applications with full-text, vector, semantic, and hybrid search capabilities.

## Installation

```bash
dotnet add package Azure.Search.Documents
dotnet add package Azure.Identity
```

**Current Versions**: Stable v11.7.0, Preview v11.8.0-beta.1

## Environment Variables

```bash
SEARCH_ENDPOINT=https://<search-service>.search.windows.net  # Required: search service endpoint
SEARCH_INDEX_NAME=<index-name>  # Required: search index name
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production
SEARCH_API_KEY=<api-key>  # Only required for AzureKeyCredential auth
```

## Authentication

**Microsoft Entra Token Credential**:
```csharp
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);
```

**API Key**:
```csharp
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);
```

## Client Selection

| Client | Purpose |
|--------|---------|
| `SearchClient` | Query indexes, upload/update/delete documents |
| `SearchIndexClient` | Create/manage indexes, synonym maps |
| `SearchIndexerClient` | Manage indexers, skillsets, data sources |

## Index Creation

### Using FieldBuilder (Recommended)

```csharp
using Azure.Search.Documents.Indexes;
using Azure.Search.Documents.Indexes.Models;

// Define model with attributes
public 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 index
var 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);
```

### Manual Field Definition

```csharp
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"
        }
    }
};
```

## Document Operations

```csharp
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);

// Delete
await searchClient.DeleteDocumentsAsync("hotelId", new[] { "1", "2" });

// Batch operations
var batch = IndexDocumentsBatch.Create(
    IndexDocumentsAction.Upload(hotel1),
    IndexDocumentsAction.Merge(hotel2),
    IndexDocumentsAction.Delete(hotel3));
await searchClient.IndexDocumentsAsync(batch);
```

## Search Patterns

### Basic Search

```csharp
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})");
}
```

### Faceted Search

```csharp
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}");
}
```

### Autocomplete and Suggestions

```csharp
// Autocomplete
var autocompleteOptions = new AutocompleteOptions { Mode = AutocompleteMode.OneTermWithContext };
var autocomplete = await searchClient.AutocompleteAsync("lux", "suggester-name", autocompleteOptions);

// Suggestions
var suggestOptions = new SuggestOptions { UseFuzzyMatching = true };
var suggestions = await searchClient.SuggestAsync<Hotel>("lux", "suggester-name", suggestOptions);
```

## Vector Search

See [references/vector-search.md](references/vector-search.md) for detailed patterns.

```csharp
using Azure.Search.Documents.Models;

// Pure vector search
var 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);
```

## Semantic Search

See [references/semantic-search.md](references/semantic-search.md) for detailed patterns.

```csharp
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 answers
foreach (var answer in results.Value.SemanticSearch.Answers)
{
    Console.WriteLine($"Answer: {answer.Text} (Score: {answer.Score})");
}

// Access captions
await foreach (var result in results.Value.GetResultsAsync())
{
    var caption = result.SemanticSearch?.Captions?.FirstOrDefault();
    Console.WriteLine($"Caption: {caption?.Text}");
}
```

## Hybrid Search (Vector + Keyword + Semantic)

```csharp
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 ranking
var results = await searchClient.SearchAsync<Hotel>("luxury beachfront", options);
```

## Field Attributes Reference

| Attribute | Purpose |
|-----------|---------|
| `SimpleField` | Non-searchable field (filters, sorting, facets) |
| `SearchableField` | Full-text searchable field |
| `VectorSearchField` | Vector embedding field |
| `IsKey = true` | Document key (required, one per index) |
| `IsFilterable = true` | Enable $filter expressions |
| `IsSortable = true` | Enable $orderby |
| `IsFacetable = true` | Enable faceted navigation |
| `IsHidden = true` | Exclude from results |
| `AnalyzerName` | Specify text analyzer |

## Error Handling

```csharp
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}");
}
```

## Best Practices

1. **Use `DefaultAzureCredential`** over API keys for production
2. **Use `FieldBuilder`** with model attributes for type-safe index definitions
3. **Use `CreateOrUpdateIndexAsync`** for idempotent index creation
4. **Batch document operations** for better throughput
5. **Use `Select`** to return only needed fields
6. **Configure semantic search** for natural language queries
7. **Combine vector + keyword + semantic** for best relevance

## Reference Files

| File | Contents |
|------|----------|
| [references/vector-search.md](references/vector-search.md) | Vector search, hybrid search, vectorizers |
| [references/semantic-search.md](references/semantic-search.md) | Semantic ranking, captions, answers |

版权与许可声明

    MIT License

    Copyright (c) Microsoft Corporation.

    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE