Provides quick-start guidance and a unified entry point for Vector features, SDK usage, and integrations. Use when users ask how to work with Vector, its TS SDK, features, or supported frameworks.
Scanned 9/12/2026
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---
name: upstash-vector-js
description: Provides quick-start guidance and a unified entry point for Vector features, SDK usage, and integrations. Use when users ask how to work with Vector, its TS SDK, features, or supported frameworks.
---
# Vector Documentation Skill
## Quick Start
Vector is a high‑performance vector database for storing, querying, and managing vector embeddings.
Basic workflow:
- Install the Vector TS SDK.
- Connect to a Vector instance.
- Upsert vectors, query them, and manage namespaces.
Example (TypeScript):
```ts
import { Index } from "@upstash/vector";
const index = new Index({
url: process.env.UPSTASH_VECTOR_REST_URL!,
token: process.env.UPSTASH_VECTOR_REST_TOKEN!,
});
await index.upsert([{ id: "1", vector: [0.1, 0.2], metadata: { tag: "example" } }]);
const results = await index.query({
vector: [0.1, 0.2],
topK: 5,
});
```
For full usage, refer to the linked skill files below.
## Other Skill Files
### TS SDK Reference
- `sdk-methods`: Explains SDK commands: delete, fetch, info, query, range, reset, resumable-query, upsert
### Features
- `features/namespaces`: Explains namespaces and dataset organization.
- `features/index-structure`: Covers hybrid and sparse index structures.
- `features/filtering-and-metadata`: Details metadata storage and server-side filtering.
Use these files for deeper guidance on SDK usage, advanced configurations, algorithms, and integrations.
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