← ClaudeAtlas

azure-search-documents-tslisted

Build search applications using Azure AI Search SDK for JavaScript (@azure/search-documents). Use when creating/managing indexes, implementing vector/hybrid search, semantic ranking, or building agentic retrieval with knowledge bases.
aiskillstore/marketplace · ★ 329 · Data & Documents · score 82
Install: claude install-skill aiskillstore/marketplace
# Azure AI Search SDK for TypeScript Build search applications with vector, hybrid, and semantic search capabilities. ## Installation ```bash npm install @azure/search-documents @azure/identity ``` ## Environment Variables ```bash AZURE_SEARCH_ENDPOINT=https://<service-name>.search.windows.net AZURE_SEARCH_INDEX_NAME=my-index AZURE_SEARCH_ADMIN_KEY=<admin-key> # Optional if using Entra ID ``` ## Authentication ```typescript import { SearchClient, SearchIndexClient } from "@azure/search-documents"; import { DefaultAzureCredential } from "@azure/identity"; const endpoint = process.env.AZURE_SEARCH_ENDPOINT!; const indexName = process.env.AZURE_SEARCH_INDEX_NAME!; const credential = new DefaultAzureCredential(); // For searching const searchClient = new SearchClient(endpoint, indexName, credential); // For index management const indexClient = new SearchIndexClient(endpoint, credential); ``` ## Core Workflow ### Create Index with Vector Field ```typescript import { SearchIndex, SearchField, VectorSearch } from "@azure/search-documents"; const index: SearchIndex = { name: "products", fields: [ { name: "id", type: "Edm.String", key: true }, { name: "title", type: "Edm.String", searchable: true }, { name: "description", type: "Edm.String", searchable: true }, { name: "category", type: "Edm.String", filterable: true, facetable: true }, { name: "embedding", type: "Collection(Edm.Single)", searchable: true, vectorSearchDime