跳到正文
cccskills
免费在 GitHub 公开

azure-ai-formrecognizer-java

Build Java applications that extract text, tables, and fields from documents using Azure AI Document Intelligence. Covers ready-made models for invoices and receipts, custom model creation, document classification, authentication, and error handling.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

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

集成工具Azure
查看安装方法

适用场景

  • Extract text and tables from PDFs
  • Read invoice and receipt fields
  • Build models for custom document formats
  • Classify documents by type

包含的文件(1)

  • SKILL.md10.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Azure Document Intelligence (Form Recognizer) SDK for Java

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

Installation

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

Client Creation

DocumentAnalysisClient

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

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

import com.azure.identity.DefaultAzureCredentialBuilder;

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

Prebuilt Models

Model IDPurpose
prebuilt-layoutExtract text, tables, selection marks
prebuilt-documentGeneral document with key-value pairs
prebuilt-receiptReceipt data extraction
prebuilt-invoiceInvoice field extraction
prebuilt-businessCardBusiness card parsing
prebuilt-idDocumentID document (passport, license)
prebuilt-tax.us.w2US W2 tax forms

Core Patterns

Extract Layout

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

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

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

AnalyzeResult result = poller.getFinalResult();

Analyze Receipt

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

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

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

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

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

// 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

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

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

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

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"

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Assess a new or existing AI project by examining its code, goals, and constraints. Recommend skills confirmed to exist in the available registry, then outline tasks and implementation phases with dependencies, completion criteria, and checks.

中文简介正在准备中。当前显示英语简介。

  • Planning the first steps of a new AI project
  • Assessing technical issues in an existing project
  • Selecting relevant skills from an available registry
sickn33/agentic-awesome-skills4.8万2026年10月19日 更新

007

免费

Review code and infrastructure for security risks, map potential threats, and plan stronger defenses. The skill covers OWASP checks, attack and defense exercises, and incident response, with validation required for each environment.

中文简介正在准备中。当前显示英语简介。

  • Reviewing code and infrastructure security
  • Mapping threats with STRIDE or PASTA
  • Planning stronger security settings
sickn33/agentic-awesome-skills4.8万2026年10月19日 更新

Turn a repeatable task into an Andru.ia skill with clear inputs, outputs, examples, and limits. Draft SKILL.md, check the folder structure and required validations, and prepare a pull request describing the changes for review.

中文简介正在准备中。当前显示英语简介。

  • Creating a skill for a repeatable task
  • Improving an existing skill’s examples and limits
  • Validating skill files and preparing a pull request
sickn33/agentic-awesome-skills4.8万2026年10月19日 更新

Prepare an industry briefing once a project's sector is defined. It covers sector context, potentially applicable regulations, familiar interface patterns, technology choices, and risks, while separating verified evidence from hypotheses and questions requiring further review.

中文简介正在准备中。当前显示英语简介。

  • Researching industry requirements before product design
  • Checking regulations for a project's jurisdiction
  • Choosing interface patterns familiar to target users
sickn33/agentic-awesome-skills4.8万2026年10月19日 更新

Create presentation drafts from text, outlines, or documents through the 2slides API. Match a reference image's style, choose themes, add AI voice narration, and export slide images or audio for review and use.

中文简介正在准备中。当前显示英语简介。

  • Create a presentation from text or an outline
  • Summarize a document into slides
  • Match slide styling to a reference image
sickn33/agentic-awesome-skills4.8万2026年10月19日 更新

Plan a 360-degree or peer feedback process and create empty response templates from confirmed requirements. Produces consistent CSV, SQL, JSON Schema, or Notion property mappings while keeping visibility choices and scoring configuration separate.

中文简介正在准备中。当前显示英语简介。

  • Plan an anonymous peer feedback process
  • Create a CSV template for feedback responses
  • Align feedback fields across SQL and JSON Schema
sickn33/agentic-awesome-skills4.8万2026年10月19日 更新

查看 sickn33 的全部技能

报告此技能的问题