Quick Start
Get started with VectorsDB in under 5 minutes. Build your first AI agent memory system.
1
Install the SDK
Add VectorsDB to your project
npm install @aetherfy/vectorsdb2
Initialize the client
Get your API key from the dashboard
import { VectorsDB } from '@aetherfy/vectorsdb'
const client = new VectorsDB({
apiKey: process.env.VECTORSDB_API_KEY
})3
Create a collection
Set up a collection for your vectors
await client.createCollection('agent-memory', {
vector_size: 1536, // OpenAI ada-002 dimensions
distance: 'cosine'
})4
Insert vectors
Add vectors with metadata to your collection
await client.upsert('agent-memory', {
id: 'memory-001',
vector: embeddings, // Your vector embeddings
metadata: {
agent_id: 'assistant',
content: 'User prefers morning meetings',
timestamp: Date.now()
}
})5
Search vectors
Find similar vectors with filtering
const results = await client.search('agent-memory', {
vector: queryEmbedding,
limit: 5,
filter: { agent_id: 'assistant' }
})
console.log(results) // Returns in <100ms globally