SKILLS/azure-ai-formrecognizer-java/SKILL.md
Build document analysis applications using the Azure AI Document Intelligence SDK for Java.
npx skillsauth add pinkpixel-dev/skills-collection-1 azure-ai-formrecognizer-javaInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Build document analysis applications using the Azure AI Document Intelligence SDK for Java.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-formrecognizer</artifactId>
<version>4.2.0-beta.1</version>
</dependency>
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();
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();
import com.azure.identity.DefaultAzureCredentialBuilder;
DocumentAnalysisClient client = new DocumentAnalysisClientBuilder()
.endpoint("{endpoint}")
.credential(new DefaultAzureCredentialBuilder().build())
.buildClient();
| 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 |
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());
}
}
String documentUrl = "https://example.com/invoice.pdf";
SyncPoller<OperationResult, AnalyzeResult> poller =
client.beginAnalyzeDocumentFromUrl("prebuilt-invoice", documentUrl);
AnalyzeResult result = poller.getFinalResult();
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());
}
}
}
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");
}
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());
});
});
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());
});
}
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();
// 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());
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();
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());
}
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());
}
FORM_RECOGNIZER_ENDPOINT=https://<resource>.cognitiveservices.azure.com/
FORM_RECOGNIZER_KEY=<your-api-key>
This skill is applicable to execute the workflow or actions described in the overview.
development
Build a systematic threat hunt hypothesis framework that transforms threat intelligence, attack patterns, and environmental data into testable hunting hypotheses.
development
Deploy MISP (Malware Information Sharing Platform) to aggregate, correlate, and distribute threat intelligence feeds from multiple sources for centralized IOC management and automated SIEM integration.
development
Build comprehensive threat actor profiles using open-source intelligence (OSINT) techniques to document adversary motivations, capabilities, infrastructure, and TTPs for proactive defense.
development
Builds a structured SOC incident response playbook for ransomware attacks covering detection, containment, eradication, and recovery phases with specific SIEM queries, isolation procedures, and decision trees. Use when SOC teams need formalized response procedures for ransomware incidents aligned to NIST SP 800-61 and MITRE ATT&CK ransomware techniques.