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upstash-vector-js

upstash-vector-js

github.com/upstashData & databases341.3k installsUpdated 2d ago
Repository

About upstash-vector-js

upstash-vector-js is a documentation skill for the Upstash Vector TypeScript SDK. It helps developers store, query, and manage vector embeddings, with references to SDK methods, index structures, namespaces, and filtering.

Key features

  1. 01Vector upsert and query guidance
  2. 02Index management methods
  3. 03Namespace-based dataset organization
  4. 04Hybrid and sparse index references
  5. 05Metadata storage and filtering

Use cases

  1. 01Adding embeddings to a vector index
  2. 02Querying vectors and filtering by metadata
  3. 03Organizing datasets with namespaces

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/upstash/skills --skill upstash-vector-js

After installing, type/upstash-vector-jsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

sdk-methods.md
features/
filtering-and-metadata.md
index-structure.md
namespaces.md

Details

From the project README

Vector Documentation Skill

Bundled docs and source

Before writing or debugging SDK code, check node_modules/@upstash/vector/docs/ for bundled docs and node_modules/@upstash/vector/src/ for readable TypeScript source. Read and search the relevant files when present; otherwise use the references in this 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):

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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