菜单
ALWAYS use this when the request matches Azure AI Formrecognizer Java: Build document analysis applications using the Azure AI Document Intelligence SDK for Java.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Anhvu1107/all-agent-skill --skill azure-ai-formrecognizer-java命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | azure-ai-formrecognizer-java |
| description | ALWAYS use this when the request matches Azure AI Formrecognizer Java: Build document analysis applications using the Azure AI Document Intelligence SDK for Java. |
Start with:
references/senior-master-standard.mdreferences/usage-routing.mdreferences/quality-checklist.mdThen load only the inherited docs, scripts, assets, or examples that match the user's actual task.
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 ()
.credential( ())
.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.