feat: Add Official Microsoft & Gemini Skills (845+ Total)
🚀 Impact Significantly expands the capabilities of **Antigravity Awesome Skills** by integrating official skill collections from **Microsoft** and **Google Gemini**. This update increases the total skill count to **845+**, making the library even more comprehensive for AI coding assistants. ✨ Key Changes 1. New Official Skills - **Microsoft Skills**: Added a massive collection of official skills from [microsoft/skills](https://github.com/microsoft/skills). - Includes Azure, .NET, Python, TypeScript, and Semantic Kernel skills. - Preserves the original directory structure under `skills/official/microsoft/`. - Includes plugin skills from the `.github/plugins` directory. - **Gemini Skills**: Added official Gemini API development skills under `skills/gemini-api-dev/`. 2. New Scripts & Tooling - **`scripts/sync_microsoft_skills.py`**: A robust synchronization script that: - Clones the official Microsoft repository. - Preserves the original directory heirarchy. - Handles symlinks and plugin locations. - Generates attribution metadata. - **`scripts/tests/inspect_microsoft_repo.py`**: Debug tool to inspect the remote repository structure. - **`scripts/tests/test_comprehensive_coverage.py`**: Verification script to ensure 100% of skills are captured during sync. 3. Core Improvements - **`scripts/generate_index.py`**: Enhanced frontmatter parsing to safely handle unquoted values containing `@` symbols and commas (fixing issues with some Microsoft skill descriptions). - **`package.json`**: Added `sync:microsoft` and `sync:all-official` scripts for easy maintenance. 4. Documentation - Updated `README.md` to reflect the new skill counts (845+) and added Microsoft/Gemini to the provider list. - Updated `CATALOG.md` and `skills_index.json` with the new skills. 🧪 Verification - Ran `scripts/tests/test_comprehensive_coverage.py` to verify all Microsoft skills are detected. - Validated `generate_index.py` fixes by successfully indexing the new skills.
This commit is contained in:
Ahmed Rehan
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skills/official/microsoft/java/foundry/formrecognizer/SKILL.md
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skills/official/microsoft/java/foundry/formrecognizer/SKILL.md
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---
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name: azure-ai-formrecognizer-java
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description: 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 building custom document models.
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package: com.azure:azure-ai-formrecognizer
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---
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# Azure Document Intelligence (Form Recognizer) SDK for Java
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Build document analysis applications using the Azure AI Document Intelligence SDK for Java.
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## Installation
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```xml
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<dependency>
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<groupId>com.azure</groupId>
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<artifactId>azure-ai-formrecognizer</artifactId>
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<version>4.2.0-beta.1</version>
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</dependency>
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```
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## Client Creation
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### DocumentAnalysisClient
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```java
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import com.azure.ai.formrecognizer.documentanalysis.DocumentAnalysisClient;
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import com.azure.ai.formrecognizer.documentanalysis.DocumentAnalysisClientBuilder;
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import com.azure.core.credential.AzureKeyCredential;
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DocumentAnalysisClient client = new DocumentAnalysisClientBuilder()
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.credential(new AzureKeyCredential("{key}"))
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.endpoint("{endpoint}")
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.buildClient();
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```
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### DocumentModelAdministrationClient
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```java
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import com.azure.ai.formrecognizer.documentanalysis.administration.DocumentModelAdministrationClient;
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import com.azure.ai.formrecognizer.documentanalysis.administration.DocumentModelAdministrationClientBuilder;
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DocumentModelAdministrationClient adminClient = new DocumentModelAdministrationClientBuilder()
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.credential(new AzureKeyCredential("{key}"))
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.endpoint("{endpoint}")
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.buildClient();
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```
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### With DefaultAzureCredential
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```java
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import com.azure.identity.DefaultAzureCredentialBuilder;
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DocumentAnalysisClient client = new DocumentAnalysisClientBuilder()
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.endpoint("{endpoint}")
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.credential(new DefaultAzureCredentialBuilder().build())
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.buildClient();
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```
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## Prebuilt Models
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| Model ID | Purpose |
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|----------|---------|
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| `prebuilt-layout` | Extract text, tables, selection marks |
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| `prebuilt-document` | General document with key-value pairs |
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| `prebuilt-receipt` | Receipt data extraction |
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| `prebuilt-invoice` | Invoice field extraction |
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| `prebuilt-businessCard` | Business card parsing |
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| `prebuilt-idDocument` | ID document (passport, license) |
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| `prebuilt-tax.us.w2` | US W2 tax forms |
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## Core Patterns
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### Extract Layout
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```java
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import com.azure.ai.formrecognizer.documentanalysis.models.*;
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import com.azure.core.util.BinaryData;
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import com.azure.core.util.polling.SyncPoller;
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import java.io.File;
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File document = new File("document.pdf");
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BinaryData documentData = BinaryData.fromFile(document.toPath());
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SyncPoller<OperationResult, AnalyzeResult> poller =
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client.beginAnalyzeDocument("prebuilt-layout", documentData);
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AnalyzeResult result = poller.getFinalResult();
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// Process pages
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for (DocumentPage page : result.getPages()) {
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System.out.printf("Page %d: %.2f x %.2f %s%n",
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page.getPageNumber(),
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page.getWidth(),
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page.getHeight(),
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page.getUnit());
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// Lines
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for (DocumentLine line : page.getLines()) {
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System.out.println("Line: " + line.getContent());
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}
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// Selection marks (checkboxes)
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for (DocumentSelectionMark mark : page.getSelectionMarks()) {
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System.out.printf("Checkbox: %s (confidence: %.2f)%n",
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mark.getSelectionMarkState(),
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mark.getConfidence());
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}
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}
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// Tables
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for (DocumentTable table : result.getTables()) {
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System.out.printf("Table: %d rows x %d columns%n",
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table.getRowCount(),
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table.getColumnCount());
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for (DocumentTableCell cell : table.getCells()) {
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System.out.printf("Cell[%d,%d]: %s%n",
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cell.getRowIndex(),
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cell.getColumnIndex(),
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cell.getContent());
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}
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}
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```
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### Analyze from URL
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```java
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String documentUrl = "https://example.com/invoice.pdf";
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SyncPoller<OperationResult, AnalyzeResult> poller =
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client.beginAnalyzeDocumentFromUrl("prebuilt-invoice", documentUrl);
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AnalyzeResult result = poller.getFinalResult();
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```
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### Analyze Receipt
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```java
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SyncPoller<OperationResult, AnalyzeResult> poller =
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client.beginAnalyzeDocumentFromUrl("prebuilt-receipt", receiptUrl);
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AnalyzeResult result = poller.getFinalResult();
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for (AnalyzedDocument doc : result.getDocuments()) {
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Map<String, DocumentField> fields = doc.getFields();
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DocumentField merchantName = fields.get("MerchantName");
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if (merchantName != null && merchantName.getType() == DocumentFieldType.STRING) {
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System.out.printf("Merchant: %s (confidence: %.2f)%n",
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merchantName.getValueAsString(),
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merchantName.getConfidence());
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}
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DocumentField transactionDate = fields.get("TransactionDate");
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if (transactionDate != null && transactionDate.getType() == DocumentFieldType.DATE) {
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System.out.printf("Date: %s%n", transactionDate.getValueAsDate());
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}
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DocumentField items = fields.get("Items");
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if (items != null && items.getType() == DocumentFieldType.LIST) {
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for (DocumentField item : items.getValueAsList()) {
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Map<String, DocumentField> itemFields = item.getValueAsMap();
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System.out.printf("Item: %s, Price: %.2f%n",
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itemFields.get("Name").getValueAsString(),
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itemFields.get("Price").getValueAsDouble());
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}
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}
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}
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```
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### General Document Analysis
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```java
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SyncPoller<OperationResult, AnalyzeResult> poller =
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client.beginAnalyzeDocumentFromUrl("prebuilt-document", documentUrl);
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AnalyzeResult result = poller.getFinalResult();
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// Key-value pairs
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for (DocumentKeyValuePair kvp : result.getKeyValuePairs()) {
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System.out.printf("Key: %s => Value: %s%n",
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kvp.getKey().getContent(),
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kvp.getValue() != null ? kvp.getValue().getContent() : "null");
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}
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```
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## Custom Models
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### Build Custom Model
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```java
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import com.azure.ai.formrecognizer.documentanalysis.administration.models.*;
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String blobContainerUrl = "{SAS_URL_of_training_data}";
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String prefix = "training-docs/";
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SyncPoller<OperationResult, DocumentModelDetails> poller = adminClient.beginBuildDocumentModel(
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blobContainerUrl,
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DocumentModelBuildMode.TEMPLATE,
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prefix,
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new BuildDocumentModelOptions()
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.setModelId("my-custom-model")
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.setDescription("Custom invoice model"),
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Context.NONE);
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DocumentModelDetails model = poller.getFinalResult();
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System.out.println("Model ID: " + model.getModelId());
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System.out.println("Created: " + model.getCreatedOn());
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model.getDocumentTypes().forEach((docType, details) -> {
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System.out.println("Document type: " + docType);
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details.getFieldSchema().forEach((field, schema) -> {
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System.out.printf(" Field: %s (%s)%n", field, schema.getType());
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});
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});
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```
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### Analyze with Custom Model
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```java
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SyncPoller<OperationResult, AnalyzeResult> poller =
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client.beginAnalyzeDocumentFromUrl("my-custom-model", documentUrl);
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AnalyzeResult result = poller.getFinalResult();
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for (AnalyzedDocument doc : result.getDocuments()) {
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System.out.printf("Document type: %s (confidence: %.2f)%n",
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doc.getDocType(),
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doc.getConfidence());
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doc.getFields().forEach((name, field) -> {
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System.out.printf("Field '%s': %s (confidence: %.2f)%n",
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name,
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field.getContent(),
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field.getConfidence());
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});
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}
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```
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### Compose Models
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```java
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List<String> modelIds = Arrays.asList("model-1", "model-2", "model-3");
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SyncPoller<OperationResult, DocumentModelDetails> poller =
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adminClient.beginComposeDocumentModel(
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modelIds,
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new ComposeDocumentModelOptions()
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.setModelId("composed-model")
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.setDescription("Composed from multiple models"));
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DocumentModelDetails composedModel = poller.getFinalResult();
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```
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### Manage Models
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```java
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// List models
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PagedIterable<DocumentModelSummary> models = adminClient.listDocumentModels();
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for (DocumentModelSummary summary : models) {
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System.out.printf("Model: %s, Created: %s%n",
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summary.getModelId(),
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summary.getCreatedOn());
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}
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// Get model details
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DocumentModelDetails model = adminClient.getDocumentModel("model-id");
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// Delete model
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adminClient.deleteDocumentModel("model-id");
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// Check resource limits
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ResourceDetails resources = adminClient.getResourceDetails();
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System.out.printf("Models: %d / %d%n",
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resources.getCustomDocumentModelCount(),
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resources.getCustomDocumentModelLimit());
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```
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## Document Classification
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### Build Classifier
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```java
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Map<String, ClassifierDocumentTypeDetails> docTypes = new HashMap<>();
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docTypes.put("invoice", new ClassifierDocumentTypeDetails()
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.setAzureBlobSource(new AzureBlobContentSource(containerUrl).setPrefix("invoices/")));
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docTypes.put("receipt", new ClassifierDocumentTypeDetails()
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.setAzureBlobSource(new AzureBlobContentSource(containerUrl).setPrefix("receipts/")));
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SyncPoller<OperationResult, DocumentClassifierDetails> poller =
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adminClient.beginBuildDocumentClassifier(docTypes,
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new BuildDocumentClassifierOptions().setClassifierId("my-classifier"));
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DocumentClassifierDetails classifier = poller.getFinalResult();
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```
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### Classify Document
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```java
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SyncPoller<OperationResult, AnalyzeResult> poller =
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client.beginClassifyDocumentFromUrl("my-classifier", documentUrl, Context.NONE);
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AnalyzeResult result = poller.getFinalResult();
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for (AnalyzedDocument doc : result.getDocuments()) {
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System.out.printf("Classified as: %s (confidence: %.2f)%n",
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doc.getDocType(),
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doc.getConfidence());
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}
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```
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## Error Handling
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```java
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import com.azure.core.exception.HttpResponseException;
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try {
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client.beginAnalyzeDocumentFromUrl("prebuilt-receipt", "invalid-url");
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} catch (HttpResponseException e) {
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System.out.println("Status: " + e.getResponse().getStatusCode());
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System.out.println("Error: " + e.getMessage());
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}
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```
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## Environment Variables
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```bash
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FORM_RECOGNIZER_ENDPOINT=https://<resource>.cognitiveservices.azure.com/
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FORM_RECOGNIZER_KEY=<your-api-key>
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```
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## Trigger Phrases
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- "document intelligence Java"
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- "form recognizer SDK"
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- "extract text from PDF"
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- "OCR document Java"
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- "analyze invoice receipt"
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- "custom document model"
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- "document classification"
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