Azure Ai Formrecognizer Java
Azure Ai Formrecognizer Java is an data AI skill with a core value of Build document analysis applications with Azure Document Intelligence (Form Recognizer) SDK for Java. It
helps developers solve real-world problems in the data domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
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 buildi...
Quick Facts
mkdir -p ./skills/azure-ai-formrecognizer-java && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-ai-formrecognizer-java/SKILL.md -o ./skills/azure-ai-formrecognizer-java/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# 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 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
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, DocumentFi🎯 Best For
- Technical writers
- API documentation teams
- UI designers
- Product designers
- Claude users
💡 Use Cases
- Generating JSDoc/TSDoc comments
- Writing README files for new projects
- Generating component mockups
- Creating design system tokens
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Azure Ai Formrecognizer Java to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does it follow my documentation style?
Most documentation skills respect existing style. Provide a style guide or example in your prompt.
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
How do I install Azure Ai Formrecognizer Java?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-ai-formrecognizer-java/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Auto-generating without reviewing
AI documentation can contain inaccuracies. Always verify technical accuracy.
Skipping usability testing
AI-generated designs should be validated with real users before development.
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.