home / skills / sickn33 / antigravity-awesome-skills / azure-ai-formrecognizer-java

azure-ai-formrecognizer-java skill

/skills/azure-ai-formrecognizer-java

This skill helps you build Java document analysis apps using Azure Document Intelligence to extract text, tables, and key-value data from receipts, invoices,

npx playbooks add skill sickn33/antigravity-awesome-skills --skill azure-ai-formrecognizer-java

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
10.0 KB
---
name: azure-ai-formrecognizer-java
description: Build document analysis applications with Azure Document Intelligence (Form Recognizer) SDK for Java. Use when extracting text, tables, key-value pairs from documents, receipts, invoices, or building custom document models.
package: com.azure:azure-ai-formrecognizer
---

# Azure Document Intelligence (Form Recognizer) SDK for Java

Build document analysis applications using the Azure AI Document Intelligence SDK for Java.

## Installation

```xml
<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-formrecognizer</artifactId>
    <version>4.2.0-beta.1</version>
</dependency>
```

## Client Creation

### DocumentAnalysisClient

```java
import com.azure.ai.formrecognizer.documentanalysis.DocumentAnalysisClient;
import com.azure.ai.formrecognizer.documentanalysis.DocumentAnalysisClientBuilder;
import com.azure.core.credential.AzureKeyCredential;

DocumentAnalysisClient client = new DocumentAnalysisClientBuilder()
    .credential(new AzureKeyCredential("{key}"))
    .endpoint("{endpoint}")
    .buildClient();
```

### DocumentModelAdministrationClient

```java
import com.azure.ai.formrecognizer.documentanalysis.administration.DocumentModelAdministrationClient;
import com.azure.ai.formrecognizer.documentanalysis.administration.DocumentModelAdministrationClientBuilder;

DocumentModelAdministrationClient adminClient = new DocumentModelAdministrationClientBuilder()
    .credential(new AzureKeyCredential("{key}"))
    .endpoint("{endpoint}")
    .buildClient();
```

### With DefaultAzureCredential

```java
import com.azure.identity.DefaultAzureCredentialBuilder;

DocumentAnalysisClient client = new DocumentAnalysisClientBuilder()
    .endpoint("{endpoint}")
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildClient();
```

## Prebuilt Models

| Model ID | Purpose |
|----------|---------|
| `prebuilt-layout` | Extract text, tables, selection marks |
| `prebuilt-document` | General document with key-value pairs |
| `prebuilt-receipt` | Receipt data extraction |
| `prebuilt-invoice` | Invoice field extraction |
| `prebuilt-businessCard` | Business card parsing |
| `prebuilt-idDocument` | ID document (passport, license) |
| `prebuilt-tax.us.w2` | US W2 tax forms |

## Core Patterns

### Extract Layout

```java
import com.azure.ai.formrecognizer.documentanalysis.models.*;
import com.azure.core.util.BinaryData;
import com.azure.core.util.polling.SyncPoller;
import java.io.File;

File document = new File("document.pdf");
BinaryData documentData = BinaryData.fromFile(document.toPath());

SyncPoller<OperationResult, AnalyzeResult> poller = 
    client.beginAnalyzeDocument("prebuilt-layout", documentData);

AnalyzeResult result = poller.getFinalResult();

// Process pages
for (DocumentPage page : result.getPages()) {
    System.out.printf("Page %d: %.2f x %.2f %s%n",
        page.getPageNumber(),
        page.getWidth(),
        page.getHeight(),
        page.getUnit());
    
    // Lines
    for (DocumentLine line : page.getLines()) {
        System.out.println("Line: " + line.getContent());
    }
    
    // Selection marks (checkboxes)
    for (DocumentSelectionMark mark : page.getSelectionMarks()) {
        System.out.printf("Checkbox: %s (confidence: %.2f)%n",
            mark.getSelectionMarkState(),
            mark.getConfidence());
    }
}

// Tables
for (DocumentTable table : result.getTables()) {
    System.out.printf("Table: %d rows x %d columns%n",
        table.getRowCount(),
        table.getColumnCount());
    
    for (DocumentTableCell cell : table.getCells()) {
        System.out.printf("Cell[%d,%d]: %s%n",
            cell.getRowIndex(),
            cell.getColumnIndex(),
            cell.getContent());
    }
}
```

### Analyze from URL

```java
String documentUrl = "https://example.com/invoice.pdf";

SyncPoller<OperationResult, AnalyzeResult> poller = 
    client.beginAnalyzeDocumentFromUrl("prebuilt-invoice", documentUrl);

AnalyzeResult result = poller.getFinalResult();
```

### Analyze Receipt

```java
SyncPoller<OperationResult, AnalyzeResult> poller = 
    client.beginAnalyzeDocumentFromUrl("prebuilt-receipt", receiptUrl);

AnalyzeResult result = poller.getFinalResult();

for (AnalyzedDocument doc : result.getDocuments()) {
    Map<String, DocumentField> fields = doc.getFields();
    
    DocumentField merchantName = fields.get("MerchantName");
    if (merchantName != null && merchantName.getType() == DocumentFieldType.STRING) {
        System.out.printf("Merchant: %s (confidence: %.2f)%n",
            merchantName.getValueAsString(),
            merchantName.getConfidence());
    }
    
    DocumentField transactionDate = fields.get("TransactionDate");
    if (transactionDate != null && transactionDate.getType() == DocumentFieldType.DATE) {
        System.out.printf("Date: %s%n", transactionDate.getValueAsDate());
    }
    
    DocumentField items = fields.get("Items");
    if (items != null && items.getType() == DocumentFieldType.LIST) {
        for (DocumentField item : items.getValueAsList()) {
            Map<String, DocumentField> itemFields = item.getValueAsMap();
            System.out.printf("Item: %s, Price: %.2f%n",
                itemFields.get("Name").getValueAsString(),
                itemFields.get("Price").getValueAsDouble());
        }
    }
}
```

### General Document Analysis

```java
SyncPoller<OperationResult, AnalyzeResult> poller = 
    client.beginAnalyzeDocumentFromUrl("prebuilt-document", documentUrl);

AnalyzeResult result = poller.getFinalResult();

// Key-value pairs
for (DocumentKeyValuePair kvp : result.getKeyValuePairs()) {
    System.out.printf("Key: %s => Value: %s%n",
        kvp.getKey().getContent(),
        kvp.getValue() != null ? kvp.getValue().getContent() : "null");
}
```

## Custom Models

### Build Custom Model

```java
import com.azure.ai.formrecognizer.documentanalysis.administration.models.*;

String blobContainerUrl = "{SAS_URL_of_training_data}";
String prefix = "training-docs/";

SyncPoller<OperationResult, DocumentModelDetails> poller = adminClient.beginBuildDocumentModel(
    blobContainerUrl,
    DocumentModelBuildMode.TEMPLATE,
    prefix,
    new BuildDocumentModelOptions()
        .setModelId("my-custom-model")
        .setDescription("Custom invoice model"),
    Context.NONE);

DocumentModelDetails model = poller.getFinalResult();

System.out.println("Model ID: " + model.getModelId());
System.out.println("Created: " + model.getCreatedOn());

model.getDocumentTypes().forEach((docType, details) -> {
    System.out.println("Document type: " + docType);
    details.getFieldSchema().forEach((field, schema) -> {
        System.out.printf("  Field: %s (%s)%n", field, schema.getType());
    });
});
```

### Analyze with Custom Model

```java
SyncPoller<OperationResult, AnalyzeResult> poller = 
    client.beginAnalyzeDocumentFromUrl("my-custom-model", documentUrl);

AnalyzeResult result = poller.getFinalResult();

for (AnalyzedDocument doc : result.getDocuments()) {
    System.out.printf("Document type: %s (confidence: %.2f)%n",
        doc.getDocType(),
        doc.getConfidence());
    
    doc.getFields().forEach((name, field) -> {
        System.out.printf("Field '%s': %s (confidence: %.2f)%n",
            name,
            field.getContent(),
            field.getConfidence());
    });
}
```

### Compose Models

```java
List<String> modelIds = Arrays.asList("model-1", "model-2", "model-3");

SyncPoller<OperationResult, DocumentModelDetails> poller = 
    adminClient.beginComposeDocumentModel(
        modelIds,
        new ComposeDocumentModelOptions()
            .setModelId("composed-model")
            .setDescription("Composed from multiple models"));

DocumentModelDetails composedModel = poller.getFinalResult();
```

### Manage Models

```java
// List models
PagedIterable<DocumentModelSummary> models = adminClient.listDocumentModels();
for (DocumentModelSummary summary : models) {
    System.out.printf("Model: %s, Created: %s%n",
        summary.getModelId(),
        summary.getCreatedOn());
}

// Get model details
DocumentModelDetails model = adminClient.getDocumentModel("model-id");

// Delete model
adminClient.deleteDocumentModel("model-id");

// Check resource limits
ResourceDetails resources = adminClient.getResourceDetails();
System.out.printf("Models: %d / %d%n",
    resources.getCustomDocumentModelCount(),
    resources.getCustomDocumentModelLimit());
```

## Document Classification

### Build Classifier

```java
Map<String, ClassifierDocumentTypeDetails> docTypes = new HashMap<>();
docTypes.put("invoice", new ClassifierDocumentTypeDetails()
    .setAzureBlobSource(new AzureBlobContentSource(containerUrl).setPrefix("invoices/")));
docTypes.put("receipt", new ClassifierDocumentTypeDetails()
    .setAzureBlobSource(new AzureBlobContentSource(containerUrl).setPrefix("receipts/")));

SyncPoller<OperationResult, DocumentClassifierDetails> poller = 
    adminClient.beginBuildDocumentClassifier(docTypes,
        new BuildDocumentClassifierOptions().setClassifierId("my-classifier"));

DocumentClassifierDetails classifier = poller.getFinalResult();
```

### Classify Document

```java
SyncPoller<OperationResult, AnalyzeResult> poller = 
    client.beginClassifyDocumentFromUrl("my-classifier", documentUrl, Context.NONE);

AnalyzeResult result = poller.getFinalResult();

for (AnalyzedDocument doc : result.getDocuments()) {
    System.out.printf("Classified as: %s (confidence: %.2f)%n",
        doc.getDocType(),
        doc.getConfidence());
}
```

## Error Handling

```java
import com.azure.core.exception.HttpResponseException;

try {
    client.beginAnalyzeDocumentFromUrl("prebuilt-receipt", "invalid-url");
} catch (HttpResponseException e) {
    System.out.println("Status: " + e.getResponse().getStatusCode());
    System.out.println("Error: " + e.getMessage());
}
```

## Environment Variables

```bash
FORM_RECOGNIZER_ENDPOINT=https://<resource>.cognitiveservices.azure.com/
FORM_RECOGNIZER_KEY=<your-api-key>
```

## Trigger Phrases

- "document intelligence Java"
- "form recognizer SDK"
- "extract text from PDF"
- "OCR document Java"
- "analyze invoice receipt"
- "custom document model"
- "document classification"

Overview

This skill provides a concise, production-ready guide to using Azure Document Intelligence (Form Recognizer) SDK for Java. It explains client setup, prebuilt models, core analysis patterns, custom model training and management. It helps teams extract text, tables, key-value pairs, receipts, invoices, IDs, and classify documents programmatically.

How this skill works

The skill shows how to create DocumentAnalysisClient and DocumentModelAdministrationClient with API keys or DefaultAzureCredential, then call synchronous pollers to analyze local files or URLs. It covers prebuilt models (layout, receipt, invoice, ID, etc.), parsing results (pages, lines, tables, fields), and extracting structured fields with confidence scores. It also documents building, composing, listing, and deleting custom models and classifiers through the administration client.

When to use it

  • Extract structured data from PDFs, images, receipts, invoices, business cards, and ID documents.
  • Automate ingestion pipelines that convert documents into searchable, structured records.
  • Train and deploy custom models for organization-specific document layouts and fields.
  • Classify mixed document batches into types (invoice, receipt, contract) before downstream processing.
  • Validate OCR output and confidence scores for compliance or auditing workflows.

Best practices

  • Use DefaultAzureCredential in production for managed identity authentication when running in Azure.
  • Choose prebuilt models for common document types to speed development; use custom models when accuracy requires domain-specific fields.
  • Send documents as BinaryData for local files or use URL analysis for cloud-stored assets to optimize bandwidth and latency.
  • Check DocumentField confidence values and selection marks to filter or flag low-confidence extractions.
  • Manage model lifecycle: version, compose, and delete unused models; monitor resource limits via adminClient.getResourceDetails().

Example use cases

  • Extract merchant, date, and line items from receipts and feed into accounting systems.
  • Parse invoices to automatically populate AP systems and trigger payment workflows.
  • Index multi-page contracts by extracting key clauses, tables, and signer details for search and review.
  • Classify incoming document batches and route them to specialized processors (invoices to AP, IDs to KYC).
  • Train a custom model for a proprietary form layout and use it to populate an internal database reliably.

FAQ

Which authentication methods are supported?

You can authenticate with AzureKeyCredential (API key) or DefaultAzureCredential for managed identities and developer flows.

When should I build a custom model versus using prebuilt models?

Start with prebuilt models for common document types; build custom models when documents have unique layouts or require extracting nonstandard fields at higher accuracy.