/azure-ai

Azure Document Intelligence — TypeScript SDK Quick Reference

Condensed from azure-ai-document-intelligence-ts. Full patterns (custom models, classifiers, batch polling) in the azure-ai-document-intelligence-ts plugin skill if installed.

Install

npm install @azure-rest/ai-document-intelligence @azure/identity

Quick Start

Auth: DefaultAzureCredential is for local development. See auth-best-practices.md for production patterns.

import DocumentIntelligence, { isUnexpected, getLongRunningPoller, AnalyzeOperationOutput } from "@azure-rest/ai-document-intelligence";
const client = DocumentIntelligence(endpoint, new DefaultAzureCredential());

Non-Obvious Patterns

• REST client — DocumentIntelligence is a function, not a class
• Analyze path: client.path("/documentModels/{modelId}:analyze", "prebuilt-layout").post({...})
• Must use getLongRunningPoller(client, initialResponse) then poller.pollUntilDone()
• Local file: send as base64Source in body, not as binary stream
• Pagination: import { paginate } from "@azure-rest/ai-document-intelligence"

Best Practices

1. Use getLongRunningPoller() — document analysis is async, always poll
2. Check isUnexpected() — type guard for proper error handling
3. Choose the right model — prebuilt when possible, custom for specialized docs
4. Handle confidence scores — set thresholds for your use case
5. Use paginate() helper for listing models
6. Prefer neural mode for custom models over template