azure-ai-document-intelligence-dotnet

$npx mdskill add microsoft/skills/azure-ai-document-intelligence-dotnet

Extract text, tables, and structured data from documents using Azure AI.

  • Process invoices, receipts, and ID documents automatically.
  • Depends on Azure Document Intelligence endpoint and API key.
  • Uses prebuilt and custom models to analyze document content.
  • Returns extracted data as structured output for further processing.

SKILL.md

.github/skills/azure-ai-document-intelligence-dotnetView on GitHub ↗
---
name: azure-ai-document-intelligence-dotnet
description: |
  Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".
license: MIT
metadata:
  author: Microsoft
  version: "1.0.0"
  package: Azure.AI.DocumentIntelligence
---

# Azure.AI.DocumentIntelligence (.NET)

Extract text, tables, and structured data from documents using prebuilt and custom models.

## Installation

```bash
dotnet add package Azure.AI.DocumentIntelligence
dotnet add package Azure.Identity
```

**Current Version**: v1.0.0 (GA)

## Environment Variables

```bash
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource-name>.cognitiveservices.azure.com/  # Required: Document Intelligence endpoint
DOCUMENT_INTELLIGENCE_API_KEY=<your-api-key>  # Only required for AzureKeyCredential auth
BLOB_CONTAINER_SAS_URL=https://<storage>.blob.core.windows.net/<container>?<sas-token>  # Optional: blob container SAS URL for training data
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production
```

## Authentication

### Microsoft Entra Token Credential

```csharp
using Azure.Identity;
using Azure.AI.DocumentIntelligence;

string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
// 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 DocumentIntelligenceClient(new Uri(endpoint), credential);
```

> **Note**: Entra ID requires a **custom subdomain** (e.g., `https://<resource-name>.cognitiveservices.azure.com/`), not a regional endpoint.

### API Key

```csharp
string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
string apiKey = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_API_KEY");
var client = new DocumentIntelligenceClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
```

## Client Types

| Client | Purpose |
|--------|---------|
| `DocumentIntelligenceClient` | Analyze documents, classify documents |
| `DocumentIntelligenceAdministrationClient` | Build/manage custom models and classifiers |

## Prebuilt Models

| Model ID | Description |
|----------|-------------|
| `prebuilt-read` | Extract text, languages, handwriting |
| `prebuilt-layout` | Extract text, tables, selection marks, structure |
| `prebuilt-invoice` | Extract invoice fields (vendor, items, totals) |
| `prebuilt-receipt` | Extract receipt fields (merchant, items, total) |
| `prebuilt-idDocument` | Extract ID document fields (name, DOB, address) |
| `prebuilt-businessCard` | Extract business card fields |
| `prebuilt-tax.us.w2` | Extract W-2 tax form fields |
| `prebuilt-healthInsuranceCard.us` | Extract health insurance card fields |

## Core Workflows

### 1. Analyze Invoice

```csharp
using Azure.AI.DocumentIntelligence;

Uri invoiceUri = new Uri("https://example.com/invoice.pdf");

Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-invoice", 
    invoiceUri);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    if (document.Fields.TryGetValue("VendorName", out DocumentField vendorNameField)
        && vendorNameField.FieldType == DocumentFieldType.String)
    {
        string vendorName = vendorNameField.ValueString;
        Console.WriteLine($"Vendor Name: '{vendorName}', confidence: {vendorNameField.Confidence}");
    }

    if (document.Fields.TryGetValue("InvoiceTotal", out DocumentField invoiceTotalField)
        && invoiceTotalField.FieldType == DocumentFieldType.Currency)
    {
        CurrencyValue invoiceTotal = invoiceTotalField.ValueCurrency;
        Console.WriteLine($"Invoice Total: '{invoiceTotal.CurrencySymbol}{invoiceTotal.Amount}'");
    }
    
    // Extract line items
    if (document.Fields.TryGetValue("Items", out DocumentField itemsField)
        && itemsField.FieldType == DocumentFieldType.List)
    {
        foreach (DocumentField item in itemsField.ValueList)
        {
            var itemFields = item.ValueDictionary;
            if (itemFields.TryGetValue("Description", out DocumentField descField))
                Console.WriteLine($"  Item: {descField.ValueString}");
        }
    }
}
```

### 2. Extract Layout (Text, Tables, Structure)

```csharp
Uri fileUri = new Uri("https://example.com/document.pdf");

Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-layout", 
    fileUri);

AnalyzeResult result = operation.Value;

// Extract text by page
foreach (DocumentPage page in result.Pages)
{
    Console.WriteLine($"Page {page.PageNumber}: {page.Lines.Count} lines, {page.Words.Count} words");
    
    foreach (DocumentLine line in page.Lines)
    {
        Console.WriteLine($"  Line: '{line.Content}'");
    }
}

// Extract tables
foreach (DocumentTable table in result.Tables)
{
    Console.WriteLine($"Table: {table.RowCount} rows x {table.ColumnCount} columns");
    foreach (DocumentTableCell cell in table.Cells)
    {
        Console.WriteLine($"  Cell ({cell.RowIndex}, {cell.ColumnIndex}): {cell.Content}");
    }
}
```

### 3. Analyze Receipt

```csharp
Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-receipt", 
    receiptUri);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    if (document.Fields.TryGetValue("MerchantName", out DocumentField merchantField))
        Console.WriteLine($"Merchant: {merchantField.ValueString}");
        
    if (document.Fields.TryGetValue("Total", out DocumentField totalField))
        Console.WriteLine($"Total: {totalField.ValueCurrency.Amount}");
        
    if (document.Fields.TryGetValue("TransactionDate", out DocumentField dateField))
        Console.WriteLine($"Date: {dateField.ValueDate}");
}
```

### 4. Build Custom Model

```csharp
var adminClient = new DocumentIntelligenceAdministrationClient(
    new Uri(endpoint), 
    new AzureKeyCredential(apiKey));

string modelId = "my-custom-model";
Uri blobContainerUri = new Uri("<blob-container-sas-url>");

var blobSource = new BlobContentSource(blobContainerUri);
var options = new BuildDocumentModelOptions(modelId, DocumentBuildMode.Template, blobSource);

Operation<DocumentModelDetails> operation = await adminClient.BuildDocumentModelAsync(
    WaitUntil.Completed, 
    options);

DocumentModelDetails model = operation.Value;

Console.WriteLine($"Model ID: {model.ModelId}");
Console.WriteLine($"Created: {model.CreatedOn}");

foreach (var docType in model.DocumentTypes)
{
    Console.WriteLine($"Document type: {docType.Key}");
    foreach (var field in docType.Value.FieldSchema)
    {
        Console.WriteLine($"  Field: {field.Key}, Confidence: {docType.Value.FieldConfidence[field.Key]}");
    }
}
```

### 5. Build Document Classifier

```csharp
string classifierId = "my-classifier";
Uri blobContainerUri = new Uri("<blob-container-sas-url>");

var sourceA = new BlobContentSource(blobContainerUri) { Prefix = "TypeA/train" };
var sourceB = new BlobContentSource(blobContainerUri) { Prefix = "TypeB/train" };

var docTypes = new Dictionary<string, ClassifierDocumentTypeDetails>()
{
    { "TypeA", new ClassifierDocumentTypeDetails(sourceA) },
    { "TypeB", new ClassifierDocumentTypeDetails(sourceB) }
};

var options = new BuildClassifierOptions(classifierId, docTypes);

Operation<DocumentClassifierDetails> operation = await adminClient.BuildClassifierAsync(
    WaitUntil.Completed, 
    options);

DocumentClassifierDetails classifier = operation.Value;
Console.WriteLine($"Classifier ID: {classifier.ClassifierId}");
```

### 6. Classify Document

```csharp
string classifierId = "my-classifier";
Uri documentUri = new Uri("https://example.com/document.pdf");

var options = new ClassifyDocumentOptions(classifierId, documentUri);

Operation<AnalyzeResult> operation = await client.ClassifyDocumentAsync(
    WaitUntil.Completed, 
    options);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    Console.WriteLine($"Document type: {document.DocumentType}, confidence: {document.Confidence}");
}
```

### 7. Manage Models

```csharp
// Get resource details
DocumentIntelligenceResourceDetails resourceDetails = await adminClient.GetResourceDetailsAsync();
Console.WriteLine($"Custom models: {resourceDetails.CustomDocumentModels.Count}/{resourceDetails.CustomDocumentModels.Limit}");

// Get specific model
DocumentModelDetails model = await adminClient.GetModelAsync("my-model-id");
Console.WriteLine($"Model: {model.ModelId}, Created: {model.CreatedOn}");

// List models
await foreach (DocumentModelDetails modelItem in adminClient.GetModelsAsync())
{
    Console.WriteLine($"Model: {modelItem.ModelId}");
}

// Delete model
await adminClient.DeleteModelAsync("my-model-id");
```

## Key Types Reference

| Type | Description |
|------|-------------|
| `DocumentIntelligenceClient` | Main client for analysis |
| `DocumentIntelligenceAdministrationClient` | Model management |
| `AnalyzeResult` | Result of document analysis |
| `AnalyzedDocument` | Single document within result |
| `DocumentField` | Extracted field with value and confidence |
| `DocumentFieldType` | String, Date, Number, Currency, etc. |
| `DocumentPage` | Page info (lines, words, selection marks) |
| `DocumentTable` | Extracted table with cells |
| `DocumentModelDetails` | Custom model metadata |
| `BlobContentSource` | Training data source |

## Build Modes

| Mode | Use Case |
|------|----------|
| `DocumentBuildMode.Template` | Fixed layout documents (forms) |
| `DocumentBuildMode.Neural` | Variable layout documents |

## Best Practices

1. **Use DefaultAzureCredential** for production
2. **Reuse client instances** — clients are thread-safe
3. **Handle long-running operations** — Use `WaitUntil.Completed` for simplicity
4. **Check field confidence** — Always verify `Confidence` property
5. **Use appropriate model** — Prebuilt for common docs, custom for specialized
6. **Use custom subdomain** — Required for Entra ID authentication

## Error Handling

```csharp
using Azure;

try
{
    var operation = await client.AnalyzeDocumentAsync(
        WaitUntil.Completed, 
        "prebuilt-invoice", 
        documentUri);
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Error: {ex.Status} - {ex.Message}");
}
```

## Related SDKs

| SDK | Purpose | Install |
|-----|---------|---------|
| `Azure.AI.DocumentIntelligence` | Document analysis (this SDK) | `dotnet add package Azure.AI.DocumentIntelligence` |
| `Azure.AI.FormRecognizer` | Legacy SDK (deprecated) | Use DocumentIntelligence instead |

## Reference Links

| Resource | URL |
|----------|-----|
| NuGet Package | https://www.nuget.org/packages/Azure.AI.DocumentIntelligence |
| API Reference | https://learn.microsoft.com/dotnet/api/azure.ai.documentintelligence |
| GitHub Samples | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/documentintelligence/Azure.AI.DocumentIntelligence/samples |
| Document Intelligence Studio | https://documentintelligence.ai.azure.com/ |
| Prebuilt Models | https://aka.ms/azsdk/formrecognizer/models |

More from microsoft/skills

SkillDescription
agent-framework-azure-ai-pyBuild Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
airunway-aks-setupSet up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".
appinsights-instrumentationGuidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
applicationinsights-web-tsInstrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.
azure-aiUse for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-ai-agents-persistent-dotnet|
azure-ai-agents-persistent-java|
azure-ai-anomalydetector-javaBuild anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
azure-ai-contentsafety-javaBuild content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
azure-ai-contentsafety-py|