azure-ai-formrecognizer-java
oleh microsoft
Rebranding: Azure AI Form Recognizer kini menjadi Azure AI Document Intelligence. Proyek baru sebaiknya menggunakan com.azure:azure-ai-documentintelligence. Paket lawas azure-ai-formrecognizer hanya menargetkan versi API 2023-07-31. Lihat Panduan Migrasi.
npx skills add https://github.com/microsoft/skills --skill azure-ai-formrecognizer-javaAzure AI Document Intelligence SDK for Java
Rebranding: Azure AI Form Recognizer is now Azure AI Document Intelligence. New projects should use
com.azure:azure-ai-documentintelligence. The legacyazure-ai-formrecognizerpackage targets API version 2023-07-31 only. See Migration Guide.
Before Implementation
Search microsoft-docs MCP for current API patterns:
- Query:
"azure-ai-documentintelligence Java SDK" - Verify: Parameters match installed SDK version (latest GA: 1.0.7)
Installation
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-documentintelligence</artifactId>
<version>1.0.0</version>
</dependency>
<!-- For DefaultAzureCredential -->
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<version>1.14.2</version>
</dependency>
Environment Variables
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource>.cognitiveservices.azure.com/ # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
Authentication
DefaultAzureCredential (Recommended)
import com.azure.ai.documentintelligence.DocumentIntelligenceClient;
import com.azure.ai.documentintelligence.DocumentIntelligenceClientBuilder;
import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;
TokenCredential credential = new DefaultAzureCredentialBuilder()
.requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
.build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();
DocumentIntelligenceClient client = new DocumentIntelligenceClientBuilder()
.endpoint(System.getenv("DOCUMENT_INTELLIGENCE_ENDPOINT"))
.credential(credential)
.buildClient();
API Key
import com.azure.core.credential.AzureKeyCredential;
DocumentIntelligenceClient client = new DocumentIntelligenceClientBuilder()
.endpoint(System.getenv("DOCUMENT_INTELLIGENCE_ENDPOINT"))
.credential(new AzureKeyCredential(System.getenv("DOCUMENT_INTELLIGENCE_KEY")))
.buildClient();
Administration Client
import com.azure.ai.documentintelligence.DocumentIntelligenceAdministrationClient;
import com.azure.ai.documentintelligence.DocumentIntelligenceAdministrationClientBuilder;
import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;
TokenCredential credential = new DefaultAzureCredentialBuilder()
.requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
.build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();
DocumentIntelligenceAdministrationClient adminClient = new DocumentIntelligenceAdministrationClientBuilder()
.endpoint(System.getenv("DOCUMENT_INTELLIGENCE_ENDPOINT"))
.credential(credential)
.buildClient();
Async Client
import com.azure.ai.documentintelligence.DocumentIntelligenceAsyncClient;
import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;
TokenCredential credential = new DefaultAzureCredentialBuilder()
.requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
.build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();
DocumentIntelligenceAsyncClient asyncClient = new DocumentIntelligenceClientBuilder()
.endpoint(System.getenv("DOCUMENT_INTELLIGENCE_ENDPOINT"))
.credential(credential)
.buildAsyncClient();
Prebuilt Models
| Model ID | Purpose |
|---|---|
prebuilt-read | Extract text, lines, words, languages |
prebuilt-layout | Text, tables, selection marks, structure |
prebuilt-receipt | Receipt data extraction |
prebuilt-invoice | Invoice field extraction |
prebuilt-idDocument | ID documents (passport, license) |
prebuilt-tax.us.w2 | US W2 tax forms |
prebuilt-healthInsuranceCard.us | US health insurance cards |
prebuilt-contract | Contract field extraction |
Retired models:
prebuilt-businessCardandprebuilt-documentare retired in API version 2024-11-30. Use the legacyazure-ai-formrecognizerpackage for these.
Core Patterns
Analyze from File
import com.azure.ai.documentintelligence.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(), (int) document.length());
SyncPoller<AnalyzeOperationDetails, AnalyzeResult> poller =
client.beginAnalyzeDocument("prebuilt-layout",
new AnalyzeDocumentOptions(documentData));
AnalyzeResult result = poller.getFinalResult();
Analyze from URL
String documentUrl = "https://example.com/invoice.pdf";
SyncPoller<AnalyzeOperationDetails, AnalyzeResult> poller =
client.beginAnalyzeDocument("prebuilt-invoice",
new AnalyzeDocumentOptions(documentUrl));
AnalyzeResult result = poller.getFinalResult();
Extract Layout
AnalyzeResult result = poller.getFinalResult();
for (DocumentPage page : result.getPages()) {
System.out.printf("Page has width: %.2f and height: %.2f, measured with unit: %s%n",
page.getWidth(), page.getHeight(), page.getUnit());
// Lines
for (DocumentLine line : page.getLines()) {
System.out.printf("Line '%s' is within bounding box %s.%n",
line.getContent(), line.getPolygon());
}
// Selection marks
for (DocumentSelectionMark mark : page.getSelectionMarks()) {
System.out.printf("Selection mark is '%s' with confidence %.2f.%n",
mark.getState(), 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());
}
}
Extract Document Fields
SyncPoller<AnalyzeOperationDetails, AnalyzeResult> poller =
client.beginAnalyzeDocument("prebuilt-receipt",
new AnalyzeDocumentOptions(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.getValueString(), merchantName.getConfidence());
}
DocumentField transactionDate = fields.get("TransactionDate");
if (transactionDate != null && transactionDate.getType() == DocumentFieldType.DATE) {
System.out.printf("Date: %s%n", transactionDate.getValueDate());
}
}
Analyze with Options
SyncPoller<AnalyzeOperationDetails, AnalyzeResult> poller =
client.beginAnalyzeDocument("my-custom-model",
new AnalyzeDocumentOptions(documentUrl)
.setPages(Collections.singletonList("1-3"))
.setLocale("en-US")
.setDocumentAnalysisFeatures(Arrays.asList(DocumentAnalysisFeature.LANGUAGES))
.setOutputContentFormat(DocumentContentFormat.TEXT));
Custom Models
Build Custom Model
String blobContainerUrl = "{SAS_URL_of_training_data}";
SyncPoller<DocumentModelBuildOperationDetails, DocumentModelDetails> poller =
adminClient.beginBuildDocumentModel(
new BuildDocumentModelOptions("my-custom-model", DocumentBuildMode.TEMPLATE)
.setAzureBlobSource(new AzureBlobContentSource(blobContainerUrl)));
DocumentModelDetails model = poller.getFinalResult();
System.out.printf("Model ID: %s%n", model.getModelId());
System.out.printf("Created: %s%n", model.getCreatedOn());
model.getDocumentTypes().forEach((docType, details) -> {
details.getFieldSchema().forEach((field, schema) -> {
System.out.printf("Field: %s (%s)%n", field, schema.getType());
});
});
Manage Models
// Resource limits
DocumentIntelligenceResourceDetails resourceDetails = adminClient.getResourceDetails();
System.out.printf("Models: %d / %d%n",
resourceDetails.getCustomDocumentModels().getCount(),
resourceDetails.getCustomDocumentModels().getLimit());
// List models
PagedIterable<DocumentModelDetails> models = adminClient.listModels();
for (DocumentModelDetails model : models) {
System.out.printf("Model: %s, Created: %s%n",
model.getModelId(), model.getCreatedOn());
}
// Get model
DocumentModelDetails model = adminClient.getModel("model-id");
// Delete model
adminClient.deleteModel("model-id");
Document Classification
Build Classifier
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<DocumentClassifierBuildOperationDetails, DocumentClassifierDetails> poller =
adminClient.beginBuildClassifier(
new BuildDocumentClassifierOptions("my-classifier", docTypes));
DocumentClassifierDetails classifier = poller.getFinalResult();
Classify Document
SyncPoller<AnalyzeOperationDetails, AnalyzeResult> poller =
client.beginClassifyDocument("my-classifier",
new ClassifyDocumentOptions(documentUrl));
AnalyzeResult result = poller.getFinalResult();
for (AnalyzedDocument doc : result.getDocuments()) {
System.out.printf("Classified as: %s (confidence: %.2f)%n",
doc.getDocumentType(), doc.getConfidence());
}
Error Handling
import com.azure.core.exception.HttpResponseException;
try {
client.beginAnalyzeDocument("prebuilt-receipt",
new AnalyzeDocumentOptions("invalid-url"));
} catch (HttpResponseException e) {
System.out.printf("Status: %d, Error: %s%n",
e.getResponse().getStatusCode(), e.getMessage());
}
Migration from azure-ai-formrecognizer
| Old (formrecognizer v4.x) | New (documentintelligence v1.x) |
|---|---|
DocumentAnalysisClient | DocumentIntelligenceClient |
DocumentAnalysisClientBuilder | DocumentIntelligenceClientBuilder |
DocumentModelAdministrationClient | DocumentIntelligenceAdministrationClient |
beginAnalyzeDocumentFromUrl(modelId, url) | beginAnalyzeDocument(modelId, new AnalyzeDocumentOptions(url)) |
beginAnalyzeDocument(modelId, data) | beginAnalyzeDocument(modelId, new AnalyzeDocumentOptions(data)) |
SyncPoller<OperationResult, AnalyzeResult> | SyncPoller<AnalyzeOperationDetails, AnalyzeResult> |
field.getValueAsString() | field.getValueString() |
field.getValueAsDate() | field.getValueDate() |
field.getValueAsDouble() | field.getValueNumber() |
field.getValueAsList() | field.getValueList() |
field.getValueAsMap() | field.getValueObject() |
mark.getSelectionMarkState() | mark.getState() |
adminClient.beginBuildDocumentModel(url, mode, prefix, options, ctx) | adminClient.beginBuildDocumentModel(new BuildDocumentModelOptions(id, mode).setAzureBlobSource(...)) |
adminClient.getResourceDetails() → .getCustomDocumentModelCount() | adminClient.getResourceDetails() → .getCustomDocumentModels().getCount() |
FORM_RECOGNIZER_ENDPOINT | DOCUMENT_INTELLIGENCE_ENDPOINT |
Reference Files
| File | Contents |
|---|---|
| references/examples.md | Complete code examples for all scenarios |
Lebih banyak skill dari microsoft
oss-growth
microsoft
Persona peretas pertumbuhan OSS
official
microsoft-foundry
microsoft
Menyebarkan, mengevaluasi, dan mengelola agen Foundry secara menyeluruh: pembuatan Docker, push ACR, pembuatan agen yang dihosting/dengan prompt, memulai kontainer, evaluasi batch, evaluasi berkelanjutan, alur kerja pengoptimal prompt, agent.yaml, kurasi kumpulan data dari jejak. GUNAKAN UNTUK: menyebarkan agen ke Foundry, agen yang dihosting, membuat agen, memanggil agen, mengevaluasi agen, menjalankan evaluasi batch, evaluasi berkelanjutan, pemantauan berkelanjutan, status evaluasi berkelanjutan, mengoptimalkan prompt, meningkatkan prompt, pengoptimal prompt, mengoptimalkan instruksi agen, meningkatkan agen...
officialdevelopmentdevops
azure-ai
microsoft
Gunakan untuk Azure AI: Search, Speech, OpenAI, Document Intelligence. Membantu pencarian, pencarian vektor/hibrida, ucapan-ke-teks, teks-ke-ucapan, transkripsi, OCR. KAPAN: AI Search, pencarian kueri, pencarian vektor, pencarian hibrida, pencarian semantik, ucapan-ke-teks, teks-ke-ucapan, transkripsi, OCR, konversi teks ke ucapan.
officialdevelopmentapi
azure-deploy
microsoft
Jalankan deployment Azure untuk aplikasi yang SUDAH DISIAPKAN dan memiliki file .azure/deployment-plan.md serta infrastruktur yang sudah ada. JANGAN gunakan skill ini saat pengguna meminta untuk MEMBUAT aplikasi baru — gunakan azure-prepare sebagai gantinya. Skill ini menjalankan perintah azd up, azd deploy, terraform apply, dan az deployment dengan pemulihan kesalahan bawaan. Membutuhkan .azure/deployment-plan.md dari azure-prepare dan status tervalidasi dari azure-validate. KAPAN: "jalankan azd up", "jalankan azd deploy", "jalankan deployment",...
officialdevopsaws
azure-storage
microsoft
Layanan Azure Storage termasuk Blob Storage, File Shares, Queue Storage, Table Storage, dan Data Lake. Menjawab pertanyaan tentang tingkat akses penyimpanan (hot, cool, cold, archive), kapan menggunakan setiap tingkat, dan perbandingan tingkat. Menyediakan penyimpanan objek, berbagi file SMB, pengiriman pesan asinkron, NoSQL key-value, dan analitik big data. Termasuk manajemen siklus hidup. GUNAKAN UNTUK: blob storage, file shares, queue storage, table storage, data lake, unggah file, unduh blob, akun penyimpanan, tingkat akses,...
officialdevelopmentdatabase
azure-diagnostics
microsoft
Debug masalah produksi Azure menggunakan AppLens, Azure Monitor, resource health, dan triase aman. KAPAN: debug masalah produksi, troubleshoot app service, CPU tinggi app service, kegagalan deployment app service, troubleshoot container apps, troubleshoot functions, troubleshoot AKS, kubectl tidak bisa terhubung, kegagalan kube-system/CoreDNS, pod pending, crashloop, node tidak siap, kegagalan upgrade, analisis log, KQL, insights, kegagalan image pull, masalah cold start, kegagalan health probe,...
officialdevopsdevelopment
azure-prepare
microsoft
Siapkan aplikasi Azure untuk deployment (infra Bicep/Terraform, azure.yaml, Dockerfiles). Gunakan untuk membuat/memodernisasi atau membuat+men-deploy; bukan untuk migrasi lintas-cloud (gunakan azure-cloud-migrate). JANGAN GUNAKAN UNTUK: aplikasi copilot-sdk (gunakan azure-hosted-copilot-sdk). KAPAN: "membuat aplikasi", "membangun aplikasi web", "membuat API", "membuat API HTTP serverless", "membuat frontend", "membuat backend", "membangun layanan", "memodernisasi aplikasi", "memperbarui aplikasi", "menambahkan autentikasi", "menambahkan caching", "hosting di Azure", "membuat dan...
officialdevelopmentdevops
azure-validate
microsoft
Validasi pra-penyebaran untuk kesiapan Azure. Lakukan pemeriksaan mendalam pada konfigurasi, infrastruktur (Bicep atau Terraform), penetapan peran RBAC, izin identitas terkelola, dan prasyarat sebelum menyebarkan. KAPAN: validasi aplikasi saya, periksa kesiapan penyebaran, jalankan pemeriksaan awal, verifikasi konfigurasi, periksa apakah siap untuk menyebarkan, validasi azure.yaml, validasi Bicep, uji sebelum menyebarkan, pecahkan kesalahan penyebaran, validasi Azure Functions, validasi function app, validasi serverless...
officialdevopstesting