Quickstart: Vector search in Azure AI Search using JavaScript
This sample demonstrates the fundamentals of vector search, including creating a vector index, loading documents with embeddings, and running vector and hybrid queries.
What's in this sample
| File | Description |
|---|---|
package.json |
Project file that defines dependencies |
sample.env |
Environment variable template for configuration |
src/createIndex.js |
Creates a search index with vector field configurations |
src/deleteIndex.js |
Deletes an existing search index |
src/uploadDocuments.js |
Uploads documents with precomputed embeddings |
src/queryVector.js |
Precomputed sample query vector |
src/search*.js |
Runs vector, hybrid, and semantic hybrid queries |
Documentation
This sample accompanies Quickstart: Vector search using JavaScript. Follow the documentation for prerequisites, setup instructions, and detailed explanations.
Next step
You can learn more about Azure AI Search on the official documentation site.