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azure-search-documents-ts

Build scalable search applications with the Azure AI Search SDK for JavaScript.

2.9k|323|Updated Jan 16, 2026
Search Tags:#azure#vector#semantic#knowledge-base#hybrid#search-sdk
One-click install
npx skills add https://github.com/microsoft/skills --skill azure-search-documents-ts-microsoft
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: azure-search-documents-ts
Source: https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-typescript/skills/azure-search-documents-ts
Command: npx skills add https://github.com/microsoft/skills --skill azure-search-documents-ts-microsoft

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Developers need a cohesive toolkit to create, manage, and scale search experiences in applications, including vector, hybrid, and semantic capabilities, without reinventing integration boilerplate.

Core Features & Use Cases

  • Vector search to retrieve semantically similar documents from a Knowledge Base
  • Hybrid search combining keyword and vector signals for richer results
  • Semantic ranking to improve relevance with natural language queries
  • Index management and configuration using the Azure SDK for JavaScript
  • Agent-based retrieval patterns to drive retrieval augmented generation and knowledge-base interactions
  • Guidance and samples for building search-powered experiences in frontend and server environments

Quick Start

Install the Azure AI Search SDK for JavaScript and scaffold a sample knowledge-base search app using the @azure/search-documents package

Frequently Asked Questions about azure-search-documents-ts

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement vector search in JavaScript using Azure AI Search?▼

Implement vector search in JavaScript by installing the @azure/search-documents package, configuring index fields for vectors, and querying the Azure AI Search SDK to retrieve semantically similar documents from your knowledge base.

What is hybrid search and how does it combine keyword and vector signals?▼

Hybrid search combines traditional keyword text matching with vector similarity scores to deliver richer, more relevant query results from an Azure AI Search index.

Can I use the Azure Search SDK with Azure OpenAI for retrieval augmented generation?▼

Yes, the Azure Search SDK integrates with Azure OpenAI or other vectorization backends to drive agent-based retrieval patterns and retrieval augmented generation from a knowledge base.

How do I configure and manage search indexes with the Azure JavaScript SDK?▼

Configure search indexes in JavaScript by defining index fields, vector dimensions, and semantic ranking profiles within the @azure/search-documents package to structure your searchable knowledge base.

Does semantic ranking improve natural language queries in Azure AI Search?▼

Semantic ranking improves natural language query relevance by evaluating the contextual meaning of search terms, ensuring results from the knowledge base match user intent more effectively.

Can I build frontend search experiences using the Azure AI Search JavaScript SDK?▼

Yes, the Azure AI Search JavaScript SDK provides patterns and samples for building scalable search-powered experiences across both frontend and server-side environments.

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