Azure AI Search — TypeScript SDK Quick Reference

Condensed from azure-search-documents-ts. Full patterns (semantic config, vector profiles, autocomplete) in the azure-search-documents-ts plugin skill if installed.

Install

npm install @azure/search-documents @azure/identity

Quick Start

import { SearchClient, SearchIndexClient, SearchIndexerClient } from "@azure/search-documents";
const searchClient = new SearchClient(endpoint, indexName, credential);

Non-Obvious Patterns

• Vector search uses vectorSearchOptions.queries array with kind: "vector"
• Semantic search requires queryType: "semantic" + semanticSearchOptions
• Batch ops: searchClient.indexDocuments({ actions: [{ upload: doc }, { delete: doc }] })

Best Practices

1. Use hybrid search — combine vector + text for best results
2. Enable semantic ranking — improves relevance for natural language queries
3. Batch document uploads — use uploadDocuments with arrays, not single docs
4. Use filters for security — implement document-level security with filters
5. Index incrementally — use mergeOrUploadDocuments for updates
6. Monitor query performance — use includeTotalCount: true sparingly in production